Active-Optical Sensors Using Red NDVI Compared to Red Edge NDVI for Prediction of Corn Grain Yield in North Dakota, U.S.A.

Science.gov (United States)

Sharma, Lakesh K.; Bu, Honggang; Denton, Anne; Franzen, David W.

2015-01-01

Active-optical sensor readings from an N non-limiting area standard established within a farm field are used to predict yield in the standard. Lower yield predictions from sensor readings obtained from other parts of the field outside of the N non-limiting standard area indicate a need for supplemental N. Active-optical sensor algorithms for predicting corn (Zea mays, L.) yield to direct in-season nitrogen (N) fertilization in corn utilize red NDVI (normalized differential vegetative index). Use of red edge NDVI might improve corn yield prediction at later growth stages when corn leaves cover the inter-row space resulting in “saturation” of red NDVI readings. The purpose of this study was to determine whether the use of red edge NDVI in two active-optical sensors (GreenSeeker™ and Holland Scientific Crop Circle™) improved corn yield prediction. Nitrogen rate experiments were established at 15 sites in North Dakota (ND). Sensor readings were conducted at V6 and V12 corn. Red NDVI and red edge NDVI were similar in the relationship of readings with yield at V6. At V12, the red edge NDVI was superior to the red NDVI in most comparisons, indicating that it would be most useful in developing late-season N application algorithms. PMID:26540057

An Improved Method for Producing High Spatial-Resolution NDVI Time Series Datasets with Multi-Temporal MODIS NDVI Data and Landsat TM/ETM+ Images

OpenAIRE

Rao, Yuhan; Zhu, Xiaolin; Chen, Jin; Wang, Jianmin

2015-01-01

Due to technical limitations, it is impossible to have high resolution in both spatial and temporal dimensions for current NDVI datasets. Therefore, several methods are developed to produce high resolution (spatial and temporal) NDVI time-series datasets, which face some limitations including high computation loads and unreasonable assumptions. In this study, an unmixing-based method, NDVI Linear Mixing Growth Model (NDVI-LMGM), is proposed to achieve the goal of accurately and efficiently bl...

Minimizing Gaps of Daily Ndvi Map with Geostationary Satellite Remote Sensing Data

Science.gov (United States)

Lee, S.; Ryu, Y.; Jiang, C.

2015-12-01

Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI

Normalization of NDVI from Different Sensor System using MODIS Products as Reference

International Nuclear Information System (INIS)

Wenxia, Gan; Liangpei, Zhang; Wei, Gong; Huanfeng, Shen

2014-01-01

Medium Resolution NDVI(Normalized Difference Vegetation Index) from different sensor systems such as Landsat, SPOT, ASTER, CBERS and HJ-1A/1B satellites provide detailed spatial information for studies of ecosystems, vegetation biophysics, and land cover. Limitation of sensor designs, cloud contamination, and sensor failure highlighted the need to normalize and integrate NDVI from multiple sensor system in order to create a consistent, long-term NDVI data set. In this paper, we used a reference-based method for NDVI normalization. And present an application of this approach which covert Landsat ETM+ NDVI calculated by digital number (NDVI DN ) to NDVI calculated by surface reflectance (NDVI SR ) using MODIS products as reference, and different cluster was treated differently. Result shows that this approach can produce NDVI with highly agreement to NDVI calculated by surface reflectance from physical approaches based on 6S (Second Simulation of the satellite Signal in the Solar Spectrum). Although some variability exists, the cluster specified reference based approach shows considerable potential for NDVI normalization. Therefore, NDVI products in MODIS era from different sources can be combined for time-series analysis, biophysical parameter retrievals, and other downstream analysis

RGB-NDVI colour composites for visualizing forest change dynamics

Science.gov (United States)

Sader, S. A.; Winne, J. C.

1992-01-01

The study presents a simple and logical technique to display and quantify forest change using three dates of satellite imagery. The normalized difference vegetation index (NDVI) was computed for each date of imagery to define high and low vegetation biomass. Color composites were generated by combining each date of NDVI with either the red, green, or blue (RGB) image planes in an image display monitor. Harvest and regeneration areas were quantified by applying a modified parallelepiped classification creating an RGB-NDVI image with 27 classes that were grouped into nine major forest change categories. Aerial photographs and stand history maps are compared with the forest changes indicated by the RGB-NDVI image. The utility of the RGB-NDVI technique for supporting forest inventories and updating forest resource information systems are presented and discussed.

Comportamento do NDVI obtido por sensor ótico ativo em cereais Behavior of NDVI obtained from an active optical sensor in cereals

Directory of Open Access Journals (Sweden)

Fabrício Pinheiro Povh

2008-08-01

Full Text Available O objetivo deste trabalho foi avaliar, com um sensor ótico ativo, o comportamento do índice de vegetação por diferença normalizada (NDVI - "normalized difference vegetation index", nas culturas de trigo, triticale, cevada e milho. Cinco experimentos foram conduzidos no Paraná e São Paulo, com variação de classes de solo, doses e fontes de N, e variedades de trigo. As seguintes variáveis foram avaliadas: NDVI, teor de N foliar, matéria seca e produtividade das culturas. Análises de regressões foram realizadas entre as doses de N aplicadas e NDVI, teor de N foliar, matéria seca e produtividade. Análises de correlação entre as variáveis foram realizadas. O trigo, triticale e cevada apresentaram resposta às aplicações de doses crescentes de N, pelo aumento nas leituras do NDVI, no teor de N foliar e na produtividade. Medido pelo sensor ótico ativo utilizado, o NDVI apresenta alto potencial para manejo do N nas culturas do trigo, triticale e cevada, e baixo potencial para a cultura do milho. Há interferência das variedades de trigo nas leituras do sensor ótico ativo.The objective of this work was to evaluate the behavior of the normalized difference vegetation index (NDVI, with an active optical sensor, in wheat, triticale, barley and corn crops. Experiments were conducted in Paraná and São Paulo, comparing different soil classes, N rates and sources, and wheat varieties. The following variables were determined: NDVI, N foliar content, dry mass and crop yield. Regression analyses were performed between NDVI and applied N rates, N foliar content, dry mass and yield. Correlation analyses among the variables were performed. Wheat, triticale and barley crops showed response to increasing N rates by the increase in the NDVI readings, to N foliar content and to yield. Measured by the used active optical sensor the NDVI shows high potential for N management wheat, triticale and barley crops, and low potential for corn crops. There

NDVI to Detect Sugarcane Aphid Injury to Grain Sorghum.

Science.gov (United States)

Elliott, N C; Backoulou, G F; Brewer, M J; Giles, K L

2015-06-01

Multispectral remote sensing has potential to provide quick and inexpensive information on sugarcane aphid, Melanaphis sacchari (Zehntner), pest status in sorghum fields. We describe a study conducted to determine if injury caused by sugarcane aphid to sorghum plants in fields of grain sorghum could be detected using multispectral remote sensing from a fixed wing aircraft. A study was conducted in commercial grain sorghum fields in the Texas Gulf Coast region in June 2014. Twenty-six commercial grain sorghum fields were selected and rated for the level of injury to sorghum plants in the field caused by sugarcane aphid. Plant growth stage ranged from 5.0 (watery ripe) to 7.0 (hard dough) among fields; and plant injury rating from sugarcane aphid ranged from 1.0 (little or no injury) to 4.0 (>40% of plants displaying injury) among fields. The normalized differenced vegetation index (NDVI) is calculated from light reflectance in the red and near-infrared wavelength bands in multispectral imagery and is a common index of plant stress. High NDVI indicates low levels of stress and low NDVI indicates high stress. NDVI ranged from -0.07 to 0.26 among fields. The correlation between NDVI and plant injury rating was negative and significant, as was the correlation between NDVI and plant growth stage. The negative correlation of NDVI with injury rating indicated that plant stress increased with increasing plant injury. Reduced NDVI with increasing plant growth probably resulted from reduced photosynthetic activity in more mature plants. The correlation between plant injury rating and plant growth stage was positive and significant indicating that plant injury from sugarcane aphid increased as plants matured. The partial correlation of NDVI with plant injury rating was negative and significant indicating that NDVI decreased with increasing plant injury after adjusting for its association with plant growth stage. We demonstrated that remotely sensed imagery acquired from grain

Tendência das séries temporais de precipitação da região sul do Brasil

Directory of Open Access Journals (Sweden)

Adilson Pinheiro

2013-09-01

Full Text Available O objetivo deste trabalho é avaliar a presença de tendências nas séries temporais de precipitação no Sul do Brasil. Foram analisadas séries temporais diárias, mensais e anuais de 18 estações pluviométricas. As distribuições de probabilidade normal e de extremos tipo I foram empregadas para análise dos dados. Foi, ainda, aplicado o teste de tendência de Mann-Kendall na detecção de tendências ou de variabilidades climáticas. Os resultados mostram uma tendência positiva dos máximos diários anuais ao longo do tempo, assim como significativa elevação dos totais mensais e anuais na maioria das estações. O teste de tendência de Mann-Kendal mostra mudanças estatisticamente significativas, ao nível de 95%, em 16 das 18 estações pluviométricas analisadas.

The Impact of Soil Reflectance on the Quantification of the Green Vegetation Fraction from NDVI

Science.gov (United States)

Montandon, L. M.; Small, E. E.

2008-01-01

The green vegetation fraction (Fg) is an important climate and hydrologic model parameter. A common method to calculate Fg is to create a simple linear mixing rnodeP between two NDVI endmembers: bare soil NDVI (NDVI(sub o)) and full vegetation NDVI (NDVI(sub infinity)). Usually it is assumed that NDVI(sub o), is close to zero (NDVI(sub o) approx.-0.05) and is generally chosen from the lowest observed NDVI values. However, the mean soil NDVI computed from 2906 samples is much larger (NDVI=0.2) and is highly variable (standard deviation=O. 1). We show that the underestimation of NDVI(sub o) yields overestimations of Fg. The largest errors occur in grassland and shrubland areas. Using parameters for NDVI(sub o) and NDVI(sub infinity) derived from global scenes yields overestimations of Fg ((Delta) Fg*) that are larger than 0.2 for the majority of U.S. land cover types when pixel NDVI values are 0.2NDVI(sub pixel)NDVI values. When using conterminous U.S. scenes to derive NDV(sub o) and NDVI(sub infinity), the overestimation is less (0.10-0.17 for 0.2NDVI(sub pixel)NDVI cycle. We propose using global databases of NDVI(sub o) along with information on historical NDVI(sub pixel) values to compute a statistically most-likely estimate of Fg (Fg*). Using in situ measurements made at the Sevilleta LTER, we show that this approach yields better estimates of Fg than using global invariant NDVI(sub o) values estimated from whole scenes (Figure 2). At the two studied sites, the Fg estimate was adjusted by 52% at the grassland and 86% at the shrubland. More significant advances will require information on spatial distribution of soil reflectance.

Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe

Science.gov (United States)

Funk, Chris; Budde, Michael E.

2009-01-01

For thirty years, simple crop water balance models have been used by the early warning community to monitor agricultural drought. These models estimate and accumulate actual crop evapotranspiration, evaluating environmental conditions based on crop water requirements. Unlike seasonal rainfall totals, these models take into account the phenology of the crop, emphasizing conditions during the peak grain filling phase of crop growth. In this paper we describe an analogous metric of crop performance based on time series of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) imagery. A special temporal filter is used to screen for cloud contamination. Regional NDVI time series are then composited for cultivated areas, and adjusted temporally according to the timing of the rainy season. This adjustment standardizes the NDVI response vis-??-vis the expected phenological response of maize. A national time series index is then created by taking the cropped-area weighted average of the regional series. This national time series provides an effective summary of vegetation response in agricultural areas, and allows for the identification of NDVI green-up during grain filling. Onset-adjusted NDVI values following the grain filling period are well correlated with U.S. Department of Agriculture production figures, possess desirable linear characteristics, and perform better than more common indices such as maximum seasonal NDVI or seasonally averaged NDVI. Thus, just as appropriately calibrated crop water balance models can provide more information than seasonal rainfall totals, the appropriate agro-phenological filtering of NDVI can improve the utility and accuracy of space-based agricultural monitoring.

Deriving crop calendar using NDVI time-series

Science.gov (United States)

Patel, J. H.; Oza, M. P.

2014-11-01

Agricultural intensification is defined in terms as cropping intensity, which is the numbers of crops (single, double and triple) per year in a unit cropland area. Information about crop calendar (i.e. number of crops in a parcel of land and their planting & harvesting dates and date of peak vegetative stage) is essential for proper management of agriculture. Remote sensing sensors provide a regular, consistent and reliable measurement of vegetation response at various growth stages of crop. Therefore it is ideally suited for monitoring purpose. The spectral response of vegetation, as measured by the Normalized Difference Vegetation Index (NDVI) and its profiles, can provide a new dimension for describing vegetation growth cycle. The analysis based on values of NDVI at regular time interval provides useful information about various crop growth stages and performance of crop in a season. However, the NDVI data series has considerable amount of local fluctuation in time domain and needs to be smoothed so that dominant seasonal behavior is enhanced. Based on temporal analysis of smoothed NDVI series, it is possible to extract number of crop cycles per year and their crop calendar. In the present study, a methodology is developed to extract key elements of crop growth cycle (i.e. number of crops per year and their planting - peak - harvesting dates). This is illustrated by analysing MODIS-NDVI data series of one agricultural year (from June 2012 to May 2013) over Gujarat. Such an analysis is very useful for analysing dynamics of kharif and rabi crops.

Evaluating temporal consistency of long-term global NDVI datasets for trend analysis

DEFF Research Database (Denmark)

Tian, Feng; Fensholt, Rasmus; Verbesselt, Jan

2015-01-01

-sensor NDVI time series by analyzing the co-occurrence between breaks in the NDVI time series and sensor shifts from GIMMS3g (Global Inventory Modeling and Mapping Studies 3rd generation), VIP3 (Vegetation Index and Phenology version 3), LTDR4 (Long Term Data Record version 4) and SPOT-VGT (Système Pour l......, potentially introducing uncertainties in NDVI trend analysis. Platform/sensor change from VGT-1 to VGT-2 is found to cause a significant positive break in the SPOT-VGT NDVI time series. Potential artifacts exist in humid, dry-subhumid, semi-arid and hyper-arid regions of GIMMS3g NDVI, whereas no signs...

The precision of the NDVI derived from AVHRR observations

International Nuclear Information System (INIS)

Roderick, M.; Smith, R.; Cridland, S.

1996-01-01

Vegetation studies using NOAA-AVHRR data have tended to focus on the use of the normalized difference vegetation index (NDVI). This unitless index is computed using near-infrared and red reflectances, and thus has both an accuracy and precision. This article reports on a formal statistical framework for assessing the precision of the NDVI derived from NOAA-AVHRR observations. The framework is based on the “best possible” precision concept, which assumes that signal quantization is the only source of observational error. While the radiance resolution of a spectral observation is essentially fixed by the instrument characteristics, the reflectance resolution is the radiance resolution divided by the cosine of the solar zenith angle. Using typical solar zenith angles for AVHRR image acquisitions over Australia, ± 0.01 NDVI units is typically with “best possible” precision attainable in the NDVI, although this degrades significantly over dark targets, and at large solar zenith angles. Transforming the computed NDVI into a single byte for disk storage results in little or no loss of precision. The framework developed in this article can be adapted to estimate the “best possible” precision of other vegetation indices derived using data from other remote sensing satellites. (author)

Can temporal and spatial NDVI predict regional bird-species richness?

Directory of Open Access Journals (Sweden)

Sebastián Nieto

2015-01-01

Full Text Available Understanding the distribution of the species and its controls over biogeographic scales is still a major challenge in ecology. National Park Networks provide an opportunity to assess the relationship between ecosystem functioning and biodiversity in areas with low human impacts. We tested the productivity–biodiversity hypothesis which states that the number of species increases with the available energy, and the ​variability–biodiversity hypothesis which states that the number of species increases with the diversity of habitats. The available energy and habitat heterogeneity estimated by the normalized difference vegetation index (NDVI was shown as a good predictor of bird-species richness for a diverse set of biomes in previously published studies. However, there is not a universal relationship between NDVI and bird-species richness. Here we tested if the NDVI can predict bird species richness in areas with low human impact in Argentina. Using a dataset from the National Park Network of Argentina we found that the best predictor of bird species richness was the minimum value of NDVI per year which explained 75% of total variability. The inclusion of the spatial heterogeneity of NDVI improved the explanation power to 80%. Minimum NDVI was highly correlated with precipitation and winter temperature. Our analysis provides a tool for assessing bird-species richness at scales on which land-use planning practitioners make their decisions for Southern South America.

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

Science.gov (United States)

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

A Non-Stationary 1981–2012 AVHRR NDVI3g Time Series

Directory of Open Access Journals (Sweden)

Jorge E. Pinzon

2014-07-01

Full Text Available The NDVI3g time series is an improved 8-km normalized difference vegetation index (NDVI data set produced from Advanced Very High Resolution Radiometer (AVHRR instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of ± 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series

Science.gov (United States)

Pinzon, Jorge E.; Tucker, Compton J.

2014-01-01

The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

Changes in the NDVI of Boreal Forests over the period 1984 to 2003 measured using time series of Landsat TM/ETM+ surface reflectance and the GIMMS AVHRR NDVI record.

Science.gov (United States)

McMillan, A. M.; Rocha, A. V.; Goulden, M. L.

2006-12-01

There is a prevailing opinion that the boreal landscape is undergoing change as a result of warming temperatures leading to earlier springs, greater forest fire frequency and possibly CO2 fertilization. One widely- used line of evidence is the GIMMS AVHRR NDVI record. Several studies suggest increasing rates of photosynthesis in boreal forests from 1982 to 1991 (based on NDVI increases) while others suggest declining photosynthesis from 1996 to 2003. We suspect that a portion of these changes are due to the successional stage of the forests. We compiled a time-series of atmospherically-corrected Landsat TM/ETM+ images spanning the period 1984 to 2003 over the BOREAS Northern Study Area and compared spatial and temporal patterns of NDVI between the two records. The Landsat time series is higher resolution and, together with the Canadian Fire Service Large Fire Database, provides stand-age information. We then (1) analyzed the agreement between the Landsat and GIMMS AVHRR time series; (2) determined how the stage of forest succession affected NDVI; (3) assessed how the calculation method of annual averages of NDVI affects decadal-scale trends. The agreement between the Landsat and the AVHRR was reasonable although the depression of NDVI associated with the aerosols from the Pinatubo volcano was greater in the GIMMS time series. Pixels containing high proportions of stands burned within a decade of the observation period showed very high gains in NDVI while the more mature stands were constant. While NDVI appears to exhibit a large sensitivity to the presence of snow, the choice of a May to September averaging period for NDVI over a June to August averaging period did not affect the interannual patterns in NDVI at this location because the snow pack was seldom present in either of these periods. Knowledge of the spatial and temporal patterns of wild fire will prove useful in interpreting trends of remotely-sensed proxies of photosynthesis.

Using NDVI to measure precipitation in semi-arid landscapes

Science.gov (United States)

Birtwhistle, Amy N.; Laituri, Melinda; Bledsoe, Brian; Friedman, Jonathan M.

2016-01-01

Measuring precipitation in semi-arid landscapes is important for understanding the processes related to rainfall and run-off; however, measuring precipitation accurately can often be challenging especially within remote regions where precipitation instruments are scarce. Typically, rain-gauges are sparsely distributed and research comparing rain-gauge and RADAR precipitation estimates reveal that RADAR data are often misleading, especially for monsoon season convective storms. This study investigates an alternative way to map the spatial and temporal variation of precipitation inputs along ephemeral stream channels using Normalized Difference Vegetation Index (NDVI) derived from Landsat Thematic Mapper imagery. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG), a region covering 3,367 km2 of semiarid landscapes in southwestern Arizona, USA. The change in NDVI from a pre-to post-monsoon season image along ephemeral stream channels explained 73% of the variance in annual monsoonal precipitation totals from a nearby rain-gauge. In addition, large seasonal changes in NDVI along channels were useful in determining when and where flow events have occurred.

Evaluation of the Quality of NDVI3g Dataset against Collection 6 MODIS NDVI in Central Europe between 2000 and 2013

OpenAIRE

Anikó Kern; Hrvoje Marjanović; Zoltán Barcza

2016-01-01

Remote sensing provides invaluable insight into the dynamics of vegetation with global coverage and reasonable temporal resolution. Normalized Difference Vegetation Index (NDVI) is widely used to study vegetation greenness, production, phenology and the responses of ecosystems to climate fluctuations. The extended global NDVI3g dataset created by Global Inventory Modeling and Mapping Studies (GIMMS) has an exceptional 32 years temporal coverage. Due to the methodology that was used to create ...

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

Science.gov (United States)

Potter, C. S.

1997-01-01

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

Estimating agricultural yield gap in Africa using MODIS NDVI dataset

Science.gov (United States)

Luan, Y.; Zhu, W.; Luo, X.; Liu, J.; Cui, X.

2013-12-01

Global agriculture has undergone a period of rapid intensification characterized as 'Green Revolution', except for Africa, which is the region most affected by unreliable food access and undernourishment. Increasing crop production will be one of the most challenges and most effectual way to mitigate food insecurity there, as Africa's agricultural yield is on a much lower level comparing to global average. In this study we characterize cropland vegetation phenology in Africa based on MODIS NDVI time series between 2000 and 2012. Cumulated NDVI is a proxy for net primary productivity and used as an indicator for evaluating the potential yield gap in Africa. It is achieved via translating the gap between optimum attainable productivity level in each classification of cropping systems and actual productivity level by the relationship of cumulated NDVI and cereal-equivalent production. The results show most of cropland area in Africa have decreasing trend in cumulated NDVI, distributing in the Nile Delta, Eastern Africa and central of semi-arid to arid savanna area, except significant positive cumulated NDVI trends are mainly found between Senegal and Benin. Using cumulated NDVI and statistics of cereal equivalent production, we find remarkable potential yield gap at the Horn of East Africa (especially in Somalia), Northern Africa (Morocco, Algeria and Tunisia). Meanwhile, countries locating at the savanna area near Sahel desert and South Africa also show significant potential, though they already have a relatively high level of productivity. Our results can help provide policy recommendation for local government or NGO to tackle food security problems by identifying zones with high potential of yield improvement.

Detecting long-duration cloud contamination in hyper-temporal NDVI imagery

NARCIS (Netherlands)

Ali, A.; de Bie, C.A.J.M.; Skidmore, A.K.

2013-01-01

Cloud contamination impacts on the quality of hyper-temporal NDVI imagery and its subsequent interpretation. Short-duration cloud impacts are easily removed by using quality flags and an upper envelope filter, but long-duration cloud contamination of NDVI imagery remains. In this paper, an approach

NDVI indicated characteristics of vegetation cover change in China's metropolises over the last three decades.

Science.gov (United States)

Sun, Jinyu; Wang, Xuhui; Chen, Anping; Ma, Yuecun; Cui, Mengdi; Piao, Shilong

2011-08-01

How urban vegetation was influenced by three decades of intensive urbanization in China is of great interest but rarely studied. In this paper, we used satellite derived Normalized Difference Vegetation Index (NDVI) and socioeconomic data to evaluate effects of urbanization on vegetation cover in China's 117 metropolises over the last three decades. Our results suggest that current urbanization has caused deterioration of urban vegetation across most cities in China, particularly in East China. At the national scale, average urban area NDVI (NDVI(u)) significantly decreased during the last three decades (P NDVI(u) did not show statistically significant trend before 1990 but decrease remarkably after 1990 (P NDVI(u) turning point. The year when NDVI(u) started to decline significantly for Central China and East China was 1987 and 1990, respectively, while NDVI(u) in West China remained relatively constant until 1998. NDVI(u) changes in the Yangtze River Delta and the Pearl River Delta, two regions which has been undergoing the most rapid urbanization in China, also show different characteristics. The Pearl River Delta experienced a rapid decline in NDVI(u) from the early 1980s to the mid-1990s; while in the Yangtze River Delta, NDVI(u) did not decline significantly until the early 1990s. Such different patterns of NDVI(u) changes are closely linked with policy-oriented difference in urbanization dynamics of these regions, which highlights the importance of implementing a sustainable urban development policy.

A modified integrated NDVI for improving estimates of terrestrial net primary production

Science.gov (United States)

Running, Steven W.

1990-01-01

Logic is presented for a time-integrated NDVI that is modified by an AVHRR derived surface evaporation resistance factor sigma, and truncated by temperatures that cause plant dormancy, to improve environmental sensitivity. With this approach, NDVI observed during subfreezing temperatures is not integrated. Water stress-related impairment in plant activity is incorporated by reducing the effective NDVI at each integration with sigma, which is derived from the slope of the surface temperature to NDVI ratio for climatically similar zones of the scene. A comparison of surface resistance before and after an extended drought period for a 1200 sq km region of coniferous forest in Montana is presented.

A NDVI assisted remote sensing image adaptive scale segmentation method

Science.gov (United States)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Impact of Sensor Degradation on the MODIS NDVI Time Series

Science.gov (United States)

Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

2012-01-01

Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in MODIS NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.

Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

Science.gov (United States)

Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

2011-01-01

interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology

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Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel D.; Neigh, Christopher S.R.; Reichstein, Markus

2013-01-01

Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset, the corresponding spatiotemporal resolution, and the applied statistical method. Here we compare the performance of a wide range of trend estimation methods and demonstrate that performance decreases with increasing inter-annual variability in the NDVI time series. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. A breakpoint detection analysis reveals that an overestimation of breakpoints in NDVI trends can result in wrong or even opposite trend estimates. Based on our results, we give practical recommendations for the application of trend methods on long-term NDVI time series. Particularly, we apply and compare different methods on NDVI time series in Alaska, where both greening and browning trends have been previously observed. Here, the multi-method uncertainty of NDVI trends is quantified through the application of the different trend estimation methods. Our results indicate that greening NDVI trends in Alaska are more spatially and temporally prevalent than browning trends. We also show that detected breakpoints in NDVI trends tend to coincide with large fires. Overall, our analyses demonstrate that seasonal trend methods need to be improved against inter-annual variability to quantify changing trends in ecosystem productivity with higher accuracy.

[Vegetation change of Yamzho Yumco Basin in southern Tibet based on SPOT-VGT NDVI].

Science.gov (United States)

Yu, Shu-Mei; Liu, Jing-Shi; Yuan, Jin-Guo

2010-06-01

The area we studied is Lake Yamzho Yumco Basin (28 degrees 27'-29 degrees 12'N, 90 degrees 08'-91 degrees 45'E), the largest inland lake basin in southern Tibetan Plateau, China. Using the SPOT-VGT NDVI vegetation index from 1998 to 2007 in the basin, the temporal and spatial variation characteristics of NDVI and its correlation with the major climatic factors (air temperature, precipitation) were analyzed. The results show that the average NDVI of the lake basin ranges from 0.12 to 0.31 and its seasonal change is obvious; the NDVI begins to rise rapidly in May and reaches the maximum value in early September. The average NDVI of the basin shows the slow increasing trend during 1998 to 2007, and it indicates that the eco-environment of the basin is recovering. The high value of NDVI has close relationships with water supply, altitude and vegetation types, so NDVI is relatively high near water sources and is the highest in meadow grassland. The summer air temperature and precipitation are the important climate elements that influence the vegetation in the basin, and the linear correlation coefficients between NDVI and air temperature and precipitation are 0.7 and 0.71, respectively. In recent years, warm and humid trend of the local climate is prevailing to improve the ecological environment in Yamzho Yumco Basin.

The study for the Spatial Distribution Pattern of NDVI in the Western of Jilin Province

Science.gov (United States)

Yang, Shu-jie; Li, Xiao-dong; Yan, Shou-gang

2018-02-01

Using methods of spatial autocorrelation analysis and trend analysis, the paper studies the spatial distribution pattern of NDVI based on the GIMMS NDVI dataset (1998-2008), in Western Jilin. The maximum value for 15d is got through the method of MAX processing. Results show that: the NDVI in growing season shows a rising trend in western Jilin in 1998-2008. In the study area, the NDVI in Western Jilin shows positive spatial autocorrelation in the whole region, but the partial NDVI is apt to scattered distribution, which means the vegetation cover of Western Jilin is generally fragmental.

A tool for NDVI time series extraction from wide-swath remotely sensed images

Science.gov (United States)

Li, Zhishan; Shi, Runhe; Zhou, Cong

2015-09-01

Normalized Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring the vegetation coverage in land surface. The time series features of NDVI are capable of reflecting dynamic changes of various ecosystems. Calculating NDVI via Moderate Resolution Imaging Spectrometer (MODIS) and other wide-swath remotely sensed images provides an important way to monitor the spatial and temporal characteristics of large-scale NDVI. However, difficulties are still existed for ecologists to extract such information correctly and efficiently because of the problems in several professional processes on the original remote sensing images including radiometric calibration, geometric correction, multiple data composition and curve smoothing. In this study, we developed an efficient and convenient online toolbox for non-remote sensing professionals who want to extract NDVI time series with a friendly graphic user interface. It is based on Java Web and Web GIS technically. Moreover, Struts, Spring and Hibernate frameworks (SSH) are integrated in the system for the purpose of easy maintenance and expansion. Latitude, longitude and time period are the key inputs that users need to provide, and the NDVI time series are calculated automatically.

Using NDVI to assess vegetative land cover change in central Puget Sound.

Science.gov (United States)

Morawitz, Dana F; Blewett, Tina M; Cohen, Alex; Alberti, Marina

2006-03-01

We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986-1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.

Revisiting the coupling between NDVI trends and cropland changes in the Sahel drylands

DEFF Research Database (Denmark)

Tong, Xiaoye; Brandt, Martin Stefan; Hiernaux, Pierre

2017-01-01

The impact of human activities via land use/cover changes on NDVI trends is critical for an improved understanding of satellite-observed changes in vegetation productivity in drylands. The dominance of positive NDVI trends in the Sahel, the so-called re-greening, is sometimes interpreted...... as a combined effect of an increase in rainfall and cropland expansion or agricultural intensification. Yet, the impact of changes in land use has yet to be thoroughly tested and supported by empirical evidence. At present, no studies have considered the importance of the different seasonal NDVI signals...... of cropped and fallowed fields when interpreting NDVI trends, as both field types are commonly merged into a single ‘cropland’ class. We make use of the distinctly different phenology of cropped and fallowed fields and use seasonal NDVI curves to separate these two field types. A fuzzy classifier is applied...

Aggregation and Association of NDVI, Boll Injury, and Stink Bugs in North Carolina Cotton.

Science.gov (United States)

Reisig, Dominic D; Reay-Jones, F P F; Meijer, A D

2015-01-01

Sampling of herbivorous stink bugs in southeastern U.S. cotton remains problematic. Remote sensing was explored to improve sampling of these pests and associated boll injury. Two adjacent 14.5-ha cotton fields were grid sampled in 2011 and 2012 by collecting stink bug adults and bolls every week during the third, fourth, and fifth weeks of bloom. Satellite remote sensing data were collected during the third week of bloom during both years, and normalized difference vegetation index (NDVI) values were calculated. Stink bugs were spatially aggregated on the third week of bloom in 2011. Boll injury from stink bugs was spatially aggregated during the fourth week of bloom in 2012. The NDVI values were aggregated during both years. There was a positive association and correlation between stink bug numbers and NDVI values, as well as injured bolls and NDVI values, during the third week of bloom in 2011. During the third week of bloom in 2012, NDVI values were negatively correlated with stink bug numbers. During the fourth week of bloom in 2011, stink bug numbers and boll injury were both positively associated and correlated with NDVI values. During the fourth week of bloom in 2012, stink bugs were negatively correlated with NDVI values, and boll injury was negatively associated and correlated with NDVI values. This study suggests the potential of remote sensing as a tool to assist with sampling stink bugs in cotton, although more research is needed using NDVI and other plant measurements to predict stink bug injury. © The Author 2015. Published by Oxford University Press on behalf of the Entomological Society of America.

Crop Condition Assessment with Adjusted NDVI Using the Uncropped Arable Land Ratio

Directory of Open Access Journals (Sweden)

Miao Zhang

2014-06-01

Full Text Available Crop condition assessment in the early growing stage is essential for crop monitoring and crop yield prediction. A normalized difference vegetation index (NDVI-based method is employed to evaluate crop condition by inter-annual comparisons of both spatial variability (using NDVI images and seasonal dynamics (based on crop condition profiles. Since this type of method will generate false information if there are changes in crop rotation, cropping area or crop phenology, information on cropped/uncropped arable land is integrated to improve the accuracy of crop condition monitoring. The study proposes a new method to retrieve adjusted NDVI for cropped arable land during the growing season of winter crops by integrating 16-day composite Moderate Resolution Imaging Spectroradiometer (MODIS reflectance data at 250-m resolution with a cropped and uncropped arable land map derived from the multi-temporal China Environmental Satellite (Huan Jing Satellite charge-coupled device (HJ-1 CCD images at 30-m resolution. Using the land map’s data on cropped and uncropped arable land, a pixel-based uncropped arable land ratio (UALR at 250-m resolution was generated. Next, the UALR-adjusted NDVI was produced by assuming that the MODIS reflectance value for each pixel is a linear mixed signal composed of the proportional reflectance of cropped and uncropped arable land. When UALR-adjusted NDVI data are used for crop condition assessment, results are expected to be more accurate, because: (i pixels with only uncropped arable land are not included in the assessment; and (ii the adjusted NDVI corrects for interannual variation in cropping area. On the provincial level, crop growing profiles based on the two kinds of NDVI data illustrate the difference between the regular and the adjusted NDVI, with the difference depending on the total area of uncropped arable land in the region. The results suggested that the proposed method can be used to improve the assessment of

Warming, Sheep and Volcanoes: Land Cover Changes in Iceland Evident in Satellite NDVI Trends

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Martha Raynolds

2015-07-01

Full Text Available In a greening Arctic, Iceland stands out as an area with very high increases in the AVHRR Normalized Difference Vegetation Index (NDVI, 1982–2010. We investigated the possible sources of this anomalous greening in Iceland’s dynamic landscape, analyzing changes due to volcanism and warming temperatures, and the effects of agricultural and industrial land use changes. The analysis showed the increases were likely due to reductions in grazing in erosion-prone rangelands, extensive reclamation and afforestation efforts, as well as a response to warming climate, including glacial retreat. Like Scandinavia and much of the rest of the Arctic, Iceland has shown a recent reduction in NDVI since 2002, but still above pre-2000 levels. Theil-Sen robust regression analysis of MODIS NDVI trends from 2002 to 2013 showed Iceland had a slightly negative NDVI trend of 0.003 NDVI units/year (p < 0.05, with significant decreases in an area three times greater (29,809 km2 than that with increases (9419 km2. Specific areas with large decreases in NDVI during the last decade were due to the formation of a large reservoir as a part of a hydroelectric power project (Kárahnjúkar, 2002–2009, and due to ashfall from two volcanic eruptions (Eyjafjallajökull, 2010; Grímsvötn, 2011. Increases in NDVI in the last decade were found in erosion control areas, around retreating glaciers, and in other areas of plant colonization following natural disturbance. Our analysis demonstrates the effectiveness of MODIS NDVI for identifying the causes of changes in land cover, and confirms the reduction in NDVI in the last decade using both the AVHRR and MODIS satellite data.

Estudo da variabilidade do NDVI sobre o Brasil, utilizando-se a análise de agrupamentos Study of NDVI variability in Brazil using cluster analysis

Directory of Open Access Journals (Sweden)

Helen da C. Gurgel

2003-04-01

Full Text Available Este trabalho analisa a variabilidade do NDVI (Índice de Vegetação por Diferença Normalizada sobre o Brasil, utilizando-se a análise de agrupamentos. As análises foram feitas através de imagens do sensor Advanced Very High Resolution Radiometer (AVHRR para o período de janeiro de 1982 a dezembro de 1993. Os resultados obtidos mostram que na região Amazônica o ciclo anual do NDVI não é bem definido, visto que o máximo tipicamente ocorre em junho, dois meses após o período chuvoso, enquanto o mínimo se dá em dois períodos distintos: entre fevereiro e março e setembro e novembro. Na região central do Brasil, o cerrado apresenta um ciclo anual definido, com valores máximos de NDVI entre março e maio, e mínimos em setembro, final do período seco. Por outro lado, a vegetação das regiões da zona da mata nordestina e dos campos de Roraima apresentam um ciclo anual nítido, sendo que os maiores valores de NDVI ocorrem em junho e julho e os menores entre fevereiro e março, alguns meses antes do início das chuvas. No caso da região nordeste do Brasil, a caatinga mostra um ciclo anual bem definido, com um período seco marcante, sendo que os valores mais elevados de NDVI ocorrem entre os meses de abril e maio, que é o final da época das chuvas, e os menores em setembro e outubro. Em parte do Estado de Santa Catarina e no sul do Paraná, o ciclo anual das formações vegetais dominantes (floresta ombrófila aberta e floresta ombrófila mista não é muito nítido. No sul do Brasil, a região de estepes não apresenta ciclo anual nítido, os valores máximos de NDVI geralmente ocorrem entre março e junho e os valores mínimos no mês de agosto. Além disso, constatou-se que os eventos El Niño, independente da sua intensidade, afetam distintamente os vários tipos de vegetação.This paper deals with vegetation cover variability in Brazil using cluster analysis. The study was done using NDVI (Normalized Difference Vegetation

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

Science.gov (United States)

Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.

2011-01-01

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Deriving phenological metrics from NDVI through an open source tool developed in QGIS

Science.gov (United States)

Duarte, Lia; Teodoro, A. C.; Gonçalves, Hernãni

2014-10-01

Vegetation indices have been commonly used over the past 30 years for studying vegetation characteristics using images collected by remote sensing satellites. One of the most commonly used is the Normalized Difference Vegetation Index (NDVI). The various stages that green vegetation undergoes during a complete growing season can be summarized through time-series analysis of NDVI data. The analysis of such time-series allow for extracting key phenological variables or metrics of a particular season. These characteristics may not necessarily correspond directly to conventional, ground-based phenological events, but do provide indications of ecosystem dynamics. A complete list of the phenological metrics that can be extracted from smoothed, time-series NDVI data is available in the USGS online resources (http://phenology.cr.usgs.gov/methods_deriving.php).This work aims to develop an open source application to automatically extract these phenological metrics from a set of satellite input data. The main advantage of QGIS for this specific application relies on the easiness and quickness in developing new plug-ins, using Python language, based on the experience of the research group in other related works. QGIS has its own application programming interface (API) with functionalities and programs to develop new features. The toolbar developed for this application was implemented using the plug-in NDVIToolbar.py. The user introduces the raster files as input and obtains a plot and a report with the metrics. The report includes the following eight metrics: SOST (Start Of Season - Time) corresponding to the day of the year identified as having a consistent upward trend in the NDVI time series; SOSN (Start Of Season - NDVI) corresponding to the NDVI value associated with SOST; EOST (End of Season - Time) which corresponds to the day of year identified at the end of a consistent downward trend in the NDVI time series; EOSN (End of Season - NDVI) corresponding to the NDVI value

Study of Maowusu Sandy Land Vegetation Coverage Change Based on Modis Ndvi

Science.gov (United States)

Ye, Q.; Liu, H.; Lin, Y.; Han, R.

2018-04-01

This paper selected 2006-2016 MODIS NDVI data with a spatial resolution of 500m and time resolution of 16d, got the 11 years' time series NDVI data of Maowusu sandy land through mosaicking, projection transformation, cutting process in batch. Analysed the spatial and temporal distribution and variation characteristics of vegetation cover in year, season and month time scales by maximum value composite, and unary linear regression analysis. Then, we combined the meteorological data of 33 sites around the sandy area, analysed the response characteristics of vegetation cover change to temperature and precipitation through Pearson correlation coefficient. Studies have shown that: (1) The NDVI value has a stable increase trend, which rate is 0.0075 / a. (2) The vegetation growth have significantly difference in four seasons, the NDVI value of summer > autumn > spring > winter. (3) The NDVI value change trend is conformed to the gauss normal distribution in a year, and it comes to be largest in August, its green season is in April, and yellow season is in the middle of November, the growth period is about 220 d. (4) The vegetation has a decreasing trend from the southeast to the northwest, most part is slightly improved, and Etuokeqianqi improved significantly. (5) The correlation indexes of annual NDVI with temperature and precipitation are -0.2178 and 0.6309, the vegetation growth is mainly affected by precipitation. In this study, a complete vegetation cover analysis and evaluation model for sandy land is established. It has important guiding significance for the sand ecological environment protection.

Estimating tree species diversity in the savannah using NDVI and woody canopy cover

Science.gov (United States)

Madonsela, Sabelo; Cho, Moses Azong; Ramoelo, Abel; Mutanga, Onisimo; Naidoo, Laven

2018-04-01

Remote sensing applications in biodiversity research often rely on the establishment of relationships between spectral information from the image and tree species diversity measured in the field. Most studies have used normalized difference vegetation index (NDVI) to estimate tree species diversity on the basis that it is sensitive to primary productivity which defines spatial variation in plant diversity. The NDVI signal is influenced by photosynthetically active vegetation which, in the savannah, includes woody canopy foliage and grasses. The question is whether the relationship between NDVI and tree species diversity in the savanna depends on the woody cover percentage. This study explored the relationship between woody canopy cover (WCC) and tree species diversity in the savannah woodland of southern Africa and also investigated whether there is a significant interaction between seasonal NDVI and WCC in the factorial model when estimating tree species diversity. To fulfil our aim, we followed stratified random sampling approach and surveyed tree species in 68 plots of 90 m × 90 m across the study area. Within each plot, all trees with diameter at breast height of >10 cm were sampled and Shannon index - a common measure of species diversity which considers both species richness and abundance - was used to quantify tree species diversity. We then extracted WCC in each plot from existing fractional woody cover product produced from Synthetic Aperture Radar (SAR) data. Factorial regression model was used to determine the interaction effect between NDVI and WCC when estimating tree species diversity. Results from regression analysis showed that (i) WCC has a highly significant relationship with tree species diversity (r2 = 0.21; p NDVI and WCC is not significant, however, the factorial model significantly reduced the error of prediction (RMSE = 0.47, p NDVI (RMSE = 0.49) or WCC (RMSE = 0.49) model during the senescence period. The result justifies our assertion

Variations in Growing-Season NDVI and Its Response to Permafrost Degradation in Northeast China

Directory of Open Access Journals (Sweden)

Jinting Guo

2017-04-01

Full Text Available Permafrost is extremely sensitive to climate change. The degradation of permafrost has strong and profound effects on vegetation. The permafrost zone of northeastern China is the second largest region of permafrost in China and lies on the south edge of the Eurasian cryolithozone. This study analyzed the spatiotemporal variations of the growing-season Normalization Difference Vegetation Index (NDVI in the permafrost zone of northeastern China and analyzed the correlation between NDVI and ground surface temperatures (GST during the years 1981–2014. Mean growing-season NDVI (MGS-NDVI experienced a marked increase of 0.003 year−1 across the entire permafrost zone. The spatial dynamics of vegetation cover had a high degree of heterogeneity on a per pixel scale. The MGS-NDVI value increased significantly (5% significance level in 80.57%, and this increase was mostly distributed in permafrost zone except for the western steppe region. Only 7.72% experienced a significant decrease in NDVI, mainly in the cultivated and steppe portions. In addition, MGS-NDVI increased significantly with increasing growing-season mean ground surface temperature (GS-MGST. Our results suggest that a warming of GS-MGST (permafrost degradation in the permafrost region of northeastern China played a positive role in increasing plant growth and activities. Although increasing ground surface temperature resulted in increased vegetation cover and growth in the short time of permafrost degradation, from the long term point of view, permafrost degradation or disappearance may weaken or even hinder vegetation activities.

Detecting leaf pulvinar movements on NDVI time series of desert trees: a new approach for water stress detection.

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Roberto O Chávez

Full Text Available Heliotropic leaf movement or leaf 'solar tracking' occurs for a wide variety of plants, including many desert species and some crops. This has an important effect on the canopy spectral reflectance as measured from satellites. For this reason, monitoring systems based on spectral vegetation indices, such as the normalized difference vegetation index (NDVI, should account for heliotropic movements when evaluating the health condition of such species. In the hyper-arid Atacama Desert, Northern Chile, we studied seasonal and diurnal variations of MODIS and Landsat NDVI time series of plantation stands of the endemic species Prosopis tamarugo Phil., subject to different levels of groundwater depletion. As solar irradiation increased during the day and also during the summer, the paraheliotropic leaves of Tamarugo moved to an erectophile position (parallel to the sun rays making the NDVI signal to drop. This way, Tamarugo stands with no water stress showed a positive NDVI difference between morning and midday (ΔNDVI mo-mi and between winter and summer (ΔNDVI W-S. In this paper, we showed that the ΔNDVI mo-mi of Tamarugo stands can be detected using MODIS Terra and Aqua images, and the ΔNDVI W-S using Landsat or MODIS Terra images. Because pulvinar movement is triggered by changes in cell turgor, the effects of water stress caused by groundwater depletion can be assessed and monitored using ΔNDVI mo-mi and ΔNDVI W-S. For an 11-year time series without rainfall events, Landsat ΔNDVI W-S of Tamarugo stands showed a positive linear relationship with cumulative groundwater depletion. We conclude that both ΔNDVI mo-mi and ΔNDVI W-S have potential to detect early water stress of paraheliotropic vegetation.

Detecting leaf pulvinar movements on NDVI time series of desert trees: a new approach for water stress detection.

Science.gov (United States)

Chávez, Roberto O; Clevers, Jan G P W; Verbesselt, Jan; Naulin, Paulette I; Herold, Martin

2014-01-01

Heliotropic leaf movement or leaf 'solar tracking' occurs for a wide variety of plants, including many desert species and some crops. This has an important effect on the canopy spectral reflectance as measured from satellites. For this reason, monitoring systems based on spectral vegetation indices, such as the normalized difference vegetation index (NDVI), should account for heliotropic movements when evaluating the health condition of such species. In the hyper-arid Atacama Desert, Northern Chile, we studied seasonal and diurnal variations of MODIS and Landsat NDVI time series of plantation stands of the endemic species Prosopis tamarugo Phil., subject to different levels of groundwater depletion. As solar irradiation increased during the day and also during the summer, the paraheliotropic leaves of Tamarugo moved to an erectophile position (parallel to the sun rays) making the NDVI signal to drop. This way, Tamarugo stands with no water stress showed a positive NDVI difference between morning and midday (ΔNDVI mo-mi) and between winter and summer (ΔNDVI W-S). In this paper, we showed that the ΔNDVI mo-mi of Tamarugo stands can be detected using MODIS Terra and Aqua images, and the ΔNDVI W-S using Landsat or MODIS Terra images. Because pulvinar movement is triggered by changes in cell turgor, the effects of water stress caused by groundwater depletion can be assessed and monitored using ΔNDVI mo-mi and ΔNDVI W-S. For an 11-year time series without rainfall events, Landsat ΔNDVI W-S of Tamarugo stands showed a positive linear relationship with cumulative groundwater depletion. We conclude that both ΔNDVI mo-mi and ΔNDVI W-S have potential to detect early water stress of paraheliotropic vegetation.

Relationships between NDVI, canopy structure, and photosynthesis in three California vegetation types

International Nuclear Information System (INIS)

Gamon, J.A.; Field, C.B.; Goulden, M.L.; Griffin, K.L.; Hartley, A.E.; Joel, G.; Penuelas, J.; Valentini, R.

1995-01-01

In a range of plant species from three Californian vegetation types, we examined the widely used ''normalized difference vegetation index'' (NDVI) and ''simple ratio'' (SR) as indicators of canopy structure, light absorption, and photosynthetic activity. These indices, which are derived from canopy reflectance in the red and near-infrared wavebands, highlighted phenological differences between evergreen and deciduous canopies. They were poor indicators of total canopy biomass due to the varying abundance of non-green standing biomass in these vegetation types. However, in sparse canopies (leaf area index (LAI) apprxeq 0-2), NDVI was a sensitive indicator of canopy structure and chemical content (green biomass, green leaf area index, chlorophyll content, and foliar nitrogen content). At higher canopy green LAI values ( gt 2; typical of dense shrubs and trees), NDVI was relatively insensitive to changes in canopy structure. Compared to SR, NDVI was better correlated with indicators of canopy structure and chemical content, but was equivalent to the logarithm of SR. In agreement with theoretical expectations, both NDVI and SR exhibited near-linear correlations with fractional PAR intercepted by green leaves over a wide range of canopy densities. Maximum daily photosynthetic rates were positively correlated with NDVI and SR in annual grassland and semideciduous shrubs where canopy development and photosynthetic activity were in synchrony. The indices were also correlated with peak springtime canopy photosynthetic rates in evergreens. However, over most of the year, these indices were poor predictors of photosynthetic performance in evergreen species due to seasonal reductions in photosynthetic radiation-use efficiency that occurred without substantial declines in canopy greenness. Our results support the use of these vegetation indices as remote indicators of PAR absorption, and thus potential photosynthetic activity, even in

A Kalman Filter-Based Method to Generate Continuous Time Series of Medium-Resolution NDVI Images

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Fernando Sedano

2014-12-01

Full Text Available A data assimilation method to produce complete temporal sequences of synthetic medium-resolution images is presented. The method implements a Kalman filter recursive algorithm that integrates medium and moderate resolution imagery. To demonstrate the approach, time series of 30-m spatial resolution NDVI images at 16-day time steps were generated using Landsat NDVI images and MODIS NDVI products at four sites with different ecosystems and land cover-land use dynamics. The results show that the time series of synthetic NDVI images captured seasonal land surface dynamics and maintained the spatial structure of the landscape at higher spatial resolution. The time series of synthetic medium-resolution NDVI images were validated within a Monte Carlo simulation framework. Normalized residuals decreased as the number of available observations increased, ranging from 0.2 to below 0.1. Residuals were also significantly lower for time series of synthetic NDVI images generated at combined recursion (smoothing than individually at forward and backward recursions (filtering. Conversely, the uncertainties of the synthetic images also decreased when the number of available observations increased and combined recursions were implemented.

Cereal Production Ratio and NDVI in Spain

Science.gov (United States)

Saa-Requejo, Antonio; Recuero, Laura; Palacios, Alicia; Díaz-Ambrona, Carlos G. H.; Tarquis, Ana M.

2014-05-01

Droughts are long-term phenomena affecting large regions causing significant damages both in human lives and economic losses. The use of remote sensing has proved to be very important in monitoring the growth of agricultural crops and trying to asses weather impact on crop loss. Several indices has been developed based in remote sensing data being one of them the normalized difference vegetation index (NDVI). In this study we have focus to know the correlation between NDVI data and the looses of rain fed cereal in the Spanish area where this crop is majority. For this propose data from drought damage in cereal come from the pool of agricultural insurance in Spain (AGROSEGURO) including 2007/2008 to 2011/2012 (five agricultural campaigns). This data is given as a ratio between drought party claims against the insured value of production aggregated at the agrarian region level. Medium resolution (500x500 m2) MODIS images were used during the same campaigns to estimate the eight-day composites NDVI at these locations. The NDVI values are accumulated following the normal cycle of the cereal taking in account the sowing date at different sites. At the same time, CORINE Land Cover (2006) was used to classify the pixels belonging to rain fed cereal use including a set of conditions such as pixels showing dry during summer, area in which there has been no change of use. Fallow presence is studied with particular attention as it imposes an inter annual variation between crop and bare soil and causes decreases in greenness in a pixel and mix both situations. This is more complex in the situation in which the avoid fallow and a continuous monoculture is performed. The results shown that around 40% of the area is subject to the regime of fallow while 60% have growing every year. In addition, another variation is detected if the year is humid (decrease of fallow) or dry (increase of fallow). The level of correlation between the drought damage ratios and cumulative NDVI for the

[Modeling continuous scaling of NDVI based on fractal theory].

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Luan, Hai-Jun; Tian, Qing-Jiu; Yu, Tao; Hu, Xin-Li; Huang, Yan; Du, Ling-Tong; Zhao, Li-Min; Wei, Xi; Han, Jie; Zhang, Zhou-Wei; Li, Shao-Peng

2013-07-01

Scale effect was one of the very important scientific problems of remote sensing. The scale effect of quantitative remote sensing can be used to study retrievals' relationship between different-resolution images, and its research became an effective way to confront the challenges, such as validation of quantitative remote sensing products et al. Traditional up-scaling methods cannot describe scale changing features of retrievals on entire series of scales; meanwhile, they are faced with serious parameters correction issues because of imaging parameters' variation of different sensors, such as geometrical correction, spectral correction, etc. Utilizing single sensor image, fractal methodology was utilized to solve these problems. Taking NDVI (computed by land surface radiance) as example and based on Enhanced Thematic Mapper Plus (ETM+) image, a scheme was proposed to model continuous scaling of retrievals. Then the experimental results indicated that: (a) For NDVI, scale effect existed, and it could be described by fractal model of continuous scaling; (2) The fractal method was suitable for validation of NDVI. All of these proved that fractal was an effective methodology of studying scaling of quantitative remote sensing.

Using NDVI and guided sampling to develop yield prediction maps of processing tomato crop

Energy Technology Data Exchange (ETDEWEB)

Fortes, A.; Henar Prieto, M. del; García-Martín, A.; Córdoba, A.; Martínez, L.; Campillo, C.

2015-07-01

The use of yield prediction maps is an important tool for the delineation of within-field management zones. Vegetation indices based on crop reflectance are of potential use in the attainment of this objective. There are different types of vegetation indices based on crop reflectance, the most commonly used of which is the NDVI (normalized difference vegetation index). NDVI values are reported to have good correlation with several vegetation parameters including the ability to predict yield. The field research was conducted in two commercial farms of processing tomato crop, Cantillana and Enviciados. An NDVI prediction map developed through ordinary kriging technique was used for guided sampling of processing tomato yield. Yield was studied and related with NDVI, and finally a prediction map of crop yield for the entire plot was generated using two geostatistical methodologies (ordinary and regression kriging). Finally, a comparison was made between the yield obtained at validation points and the yield values according to the prediction maps. The most precise yield maps were obtained with the regression kriging methodology with RRMSE values of 14% and 17% in Cantillana and Enviciados, respectively, using the NDVI as predictor. The coefficient of correlation between NDVI and yield was correlated in the point samples taken in the two locations, with values of 0.71 and 0.67 in Cantillana and Enviciados, respectively. The results suggest that the use of a massive sampling parameter such as NDVI is a good indicator of the distribution of within-field yield variation. (Author)

Identification of "ever-cropped" land (1984-2010) using Landsat annual maximum NDVI image composites: Southwestern Kansas case study.

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Maxwell, Susan K; Sylvester, Kenneth M

2012-06-01

A time series of 230 intra- and inter-annual Landsat Thematic Mapper images was used to identify land that was ever cropped during the years 1984 through 2010 for a five county region in southwestern Kansas. Annual maximum Normalized Difference Vegetation Index (NDVI) image composites (NDVI(ann-max)) were used to evaluate the inter-annual dynamics of cropped and non-cropped land. Three feature images were derived from the 27-year NDVI(ann-max) image time series and used in the classification: 1) maximum NDVI value that occurred over the entire 27 year time span (NDVI(max)), 2) standard deviation of the annual maximum NDVI values for all years (NDVI(sd)), and 3) standard deviation of the annual maximum NDVI values for years 1984-1986 (NDVI(sd84-86)) to improve Conservation Reserve Program land discrimination.Results of the classification were compared to three reference data sets: County-level USDA Census records (1982-2007) and two digital land cover maps (Kansas 2005 and USGS Trends Program maps (1986-2000)). Area of ever-cropped land for the five counties was on average 11.8 % higher than the area estimated from Census records. Overall agreement between the ever-cropped land map and the 2005 Kansas map was 91.9% and 97.2% for the Trends maps. Converting the intra-annual Landsat data set to a single annual maximum NDVI image composite considerably reduced the data set size, eliminated clouds and cloud-shadow affects, yet maintained information important for discriminating cropped land. Our results suggest that Landsat annual maximum NDVI image composites will be useful for characterizing land use and land cover change for many applications.

Markov Chain Modelling for Short-Term NDVI Time Series Forecasting

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Stepčenko Artūrs

2016-12-01

Full Text Available In this paper, the NDVI time series forecasting model has been developed based on the use of discrete time, continuous state Markov chain of suitable order. The normalised difference vegetation index (NDVI is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation; therefore, it is an important variable for vegetation forecasting. A Markov chain is a stochastic process that consists of a state space. This stochastic process undergoes transitions from one state to another in the state space with some probabilities. A Markov chain forecast model is flexible in accommodating various forecast assumptions and structures. The present paper discusses the considerations and techniques in building a Markov chain forecast model at each step. Continuous state Markov chain model is analytically described. Finally, the application of the proposed Markov chain model is illustrated with reference to a set of NDVI time series data.

Stability of Spatial Distributions of Stink Bugs, Boll Injury, and NDVI in Cotton.

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Reay-Jones, Francis P F; Greene, Jeremy K; Bauer, Philip J

2016-10-01

A 3-yr study was conducted to determine the degree of aggregation of stink bugs and boll injury in cotton, Gossypium hirsutum L., and their spatial association with a multispectral vegetation index (normalized difference vegetation index [NDVI]). Using the spatial analysis by distance indices analyses, stink bugs were less frequently aggregated (17% for adults and 4% for nymphs) than boll injury (36%). NDVI values were also significantly aggregated within fields in 19 of 48 analyses (40%), with the majority of significant indices occurring in July and August. Paired NDVI datasets from different sampling dates were frequently associated (86.5% for weekly intervals among datasets). Spatial distributions of both stink bugs and boll injury were less stable than for NDVI, with positive associations varying from 12.5 to 25% for adult stink bugs for weekly intervals, depending on species. Spatial distributions of boll injury from stink bug feeding were more stable than stink bugs, with 46% positive associations among paired datasets with weekly intervals. NDVI values were positively associated with boll injury from stink bug feeding in 11 out of 22 analyses, with no significant negative associations. This indicates that NDVI has potential as a component of site-specific management. Future work should continue to examine the value of remote sensing for insect management in cotton, with an aim to develop tools such as risk assessment maps that will help growers to reduce insecticide inputs. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Does NDVI reflect variation in the structural attributes associated with increasing shrub dominance in arctic tundra?

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Boelman, Natalie T [Lamont-Doherty Earth Observatory, Columbia University, 61 Route 9W, Palisades, NY 10964 (United States); Gough, Laura; McLaren, Jennie R [Department of Biology, University of Texas at Arlington, Arlington, TX 76019 (United States); Greaves, Heather, E-mail: nboelman@ldeo.columbia.edu [Department of Forest Ecosystems and Society, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 (United States)

2011-07-15

This study explores relationships between the normalized difference vegetation index (NDVI) and structural characteristics associated with deciduous shrub dominance in arctic tundra. Our structural measures of shrub dominance are stature, branch abundance, aerial per cent woody stem cover (deciduous and evergreen species), and per cent deciduous shrub canopy cover. All measurements were taken across a suite of transects that together represent a gradient of deciduous shrub height. The transects include tussock tundra shrub and riparian shrub tundra communities located in the northern foothills of the Brooks Range, in northern Alaska. Plot-level NDVI measurements were made in 2010 during the snow-free period prior to deciduous shrub leaf-out (early June, NDVI{sub pre-leaf}), at the point in the growing season when canopy NDVI has reached half of its maximum growing season value (mid-June, NDVI{sub demi-leaf}) and during the period of maximum leaf-out (late July, NDVI{sub peak-leaf}). We found that: (1) NDVI{sub pre-leaf} is best suited to capturing variation in the per cent woody stem cover, maximum shrub height, and branch abundance, particularly between 10 and 50 cm height in the canopy; (2) NDVI{sub peak-leaf} is best suited to capturing variation in deciduous canopy cover; and (3) NDVI{sub demi-leaf} does not capture variability in any of our measures of shrub dominance. These findings suggest that in situ NDVI measurements made prior to deciduous canopy leaf-out could be used to identify small differences in maximum shrub height, woody stem cover, and branch abundance (particularly between 10 and 50 cm height in the canopy). Because shrubs are increasing in size and regional extent in several regions of the Arctic, investigation into spectrally based tools for monitoring these changes are worthwhile as they provide a first step towards development of remotely sensed techniques for quantifying associated changes in regional carbon cycling, albedo, radiative

Does NDVI reflect variation in the structural attributes associated with increasing shrub dominance in arctic tundra?

International Nuclear Information System (INIS)

Boelman, Natalie T; Gough, Laura; McLaren, Jennie R; Greaves, Heather

2011-01-01

This study explores relationships between the normalized difference vegetation index (NDVI) and structural characteristics associated with deciduous shrub dominance in arctic tundra. Our structural measures of shrub dominance are stature, branch abundance, aerial per cent woody stem cover (deciduous and evergreen species), and per cent deciduous shrub canopy cover. All measurements were taken across a suite of transects that together represent a gradient of deciduous shrub height. The transects include tussock tundra shrub and riparian shrub tundra communities located in the northern foothills of the Brooks Range, in northern Alaska. Plot-level NDVI measurements were made in 2010 during the snow-free period prior to deciduous shrub leaf-out (early June, NDVI pre-leaf ), at the point in the growing season when canopy NDVI has reached half of its maximum growing season value (mid-June, NDVI demi-leaf ) and during the period of maximum leaf-out (late July, NDVI peak-leaf ). We found that: (1) NDVI pre-leaf is best suited to capturing variation in the per cent woody stem cover, maximum shrub height, and branch abundance, particularly between 10 and 50 cm height in the canopy; (2) NDVI peak-leaf is best suited to capturing variation in deciduous canopy cover; and (3) NDVI demi-leaf does not capture variability in any of our measures of shrub dominance. These findings suggest that in situ NDVI measurements made prior to deciduous canopy leaf-out could be used to identify small differences in maximum shrub height, woody stem cover, and branch abundance (particularly between 10 and 50 cm height in the canopy). Because shrubs are increasing in size and regional extent in several regions of the Arctic, investigation into spectrally based tools for monitoring these changes are worthwhile as they provide a first step towards development of remotely sensed techniques for quantifying associated changes in regional carbon cycling, albedo, radiative energy balance, and wildlife

[Variation trends of the vegetations in distribution region of Amur tiger based on MODIS NDVI].

Science.gov (United States)

Wang, Hua-Ru; Wang, Tian-Ming; Ge, Han-Ping

2012-10-01

By using the averaged 250 m MODIS NDVI data in growth seasons of 2000-2010 and the approach of ordinary linear regression, this paper analyzed the variation trends of the vegetations in the distribution region of Amur tiger (Panthera tigris altaica), the Far East region of Russia and the eastern part of Northeast China, as well as the relationships between these variation trends and the anthropogenic activities. In 2000 - 2010, the areas with significantly decreased NDVI were sparsely distributed and accounted for 9.6% of the total, while the areas with significantly increased NDVI were mainly concentrated in the central part of northern Russia Far East Region and only accounted for 0.5% of the total. The percentage of the areas with significantly decreased NDVI in the distribution region of Amur tiger was slightly higher than that in the whole study region. The areas with significantly decreased NDVI were mainly distributed in the places of low elevation, gentle slope, and close to roads/railroads. The number of the pixels with significantly decreased NDVI increased with the increase of the nearest distance to residential locations first, and then decreased gradually. The significant decrease of the NDVI was closely related to the anthropogenic activities, and thus, to adopt effective measures to reduce human disturbances could control the vegetation degradation, and further, provide sustainable basis for the protection of Amur tiger and the conservation of the biodiversity in the studied region.

Studies on MODIS NDVI and its relation with the south west monsoon, western ghats, India

Science.gov (United States)

Lakshmi Kumar, Tv; Barbosa, Humberto; Uma, R.; Rao, Koteswara

2012-07-01

Eleven years (2000 to 2010) of Normalized Difference Vegetation Index (NDVI) data, derived from Moderate Imaging Spectroradiometer (MODIS) Terra with 250m resolution are used in the present study to discuss the changes in the trends of vegetal cover. The interannual variability of NDVI over western ghats (number of test sites are 17) showed increasing trend and the pronounced changes are resulted due to the monsoon variability in terms of its distribution (wide spread/fairly wide spread/scattered/isolated) and activity (vigorous/normal/weak) and are studied in detail. The NDVI progression is observed from June with a minimum value of 0.179 and yielded to maximum at 0.565 during September/October, on average. The study then relates the NDVI with the no of light, moderate and heavy rainfall events via statistical techniques such as correlation and regression to understand the connection in between the ground vegetation and the south west monsoon. The results of the study inferred i) NDVI, Antecedent Precipitation Index (API) are in good agreement throughout the monsoon which is evidenced by correlation as well as by Morlett Wavelet Analysis, ii) NDVI maintained good correlation with no of Light Rainy and Moderate Rainy alternatively but not with no of Heavy Rainy days, iii) Relation of NDVI with Isolated, Scattered distributions and active monsoons is substantial and iv) Phenological stages captured the Rate of Green Up during the crop season over western ghats.

Global Trends in Seasonality of Normalized Difference Vegetation Index (NDVI, 1982–2011

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Assaf Anyamba

2013-09-01

Full Text Available A 30-year series of global monthly Normalized Difference Vegetation Index (NDVI imagery derived from the Global Inventory Modeling and Mapping Studies (GIMMS NDVI3g archive was analyzed for the presence of trends in changing seasonality. Using the Seasonal Trend Analysis (STA procedure, over half (56.30% of land surfaces were found to exhibit significant trends. Almost half (46.10% of the significant trends belonged to three classes of seasonal trends (or changes. Class 1 consisted of areas that experienced a uniform increase in NDVI throughout the year, and was primarily associated with forested areas, particularly broadleaf forests. Class 2 consisted of areas experiencing an increase in the amplitude of the annual seasonal signal whereby increases in NDVI in the green season were balanced by decreases in the brown season. These areas were found primarily in grassland and shrubland regions. Class 3 was found primarily in the Taiga and Tundra biomes and exhibited increases in the annual summer peak in NDVI. While no single attribution of cause could be determined for each of these classes, it was evident that they are primarily found in natural areas (as opposed to anthropogenic land cover conversions and that they are consistent with climate-related ameliorations of growing conditions during the study period.

The Influence of Drought and Flood Disasters on Rice NDVI in Summer

International Nuclear Information System (INIS)

Piao, Meihua; Hongyan, Zhang; Zhao, Jianjun; Guo, Xiaoyi

2014-01-01

During the period from 1995 to 2010, flooding and drought occurred frequently in North Korea. This greatly affected agriculture. The precipitation data was the main factor evaluated in flood and drought monitoring. In this study, the Z index method was used to estimate the change in precipitation, calculated from TRMM (Tropical Rainfall Measuring Mission) data. The Z index and the NDVI were combined with the map of distribution of rice to analyze the relationship between the Z index and NDVI during the growing months of rice in recent 12 years. The results revealed that the Z index is a good indicator to study the relative changes of precipitation in North Korea, and that the relationship between the Z index and NDVI in a quadratic function

[Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province].

Science.gov (United States)

Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding

2010-05-01

Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.

Using ESAP Software for Predicting the Spatial Distributions of NDVI and Transpiration of Cotton

Science.gov (United States)

The normalized difference vegetation index (NDVI) has many applications in agricultural management, including monitoring real-time crop coefficients for estimating crop evapotranspiration (ET). However, frequent monitoring of NDVI as needed in such applications is generally not feasible from aerial ...

NDVI saturation adjustment: a new approach for improving cropland performance estimates in the Greater Platte River Basin, USA

Science.gov (United States)

Gu, Yingxin; Wylie, Bruce K.; Howard, Daniel M.; Phuyal, Khem P.; Ji, Lei

2013-01-01

In this study, we developed a new approach that adjusted normalized difference vegetation index (NDVI) pixel values that were near saturation to better characterize the cropland performance (CP) in the Greater Platte River Basin (GPRB), USA. The relationship between NDVI and the ratio vegetation index (RVI) at high NDVI values was investigated, and an empirical equation for estimating saturation-adjusted NDVI (NDVIsat_adjust) based on RVI was developed. A 10-year (2000–2009) NDVIsat_adjust data set was developed using 250-m 7-day composite historical eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. The growing season averaged NDVI (GSN), which is a proxy for ecosystem performance, was estimated and long-term NDVI non-saturation- and saturation-adjusted cropland performance (CPnon_sat_adjust, CPsat_adjust) maps were produced over the GPRB. The final CP maps were validated using National Agricultural Statistics Service (NASS) crop yield data. The relationship between CPsat_adjust and the NASS average corn yield data (r = 0.78, 113 samples) is stronger than the relationship between CPnon_sat_adjust and the NASS average corn yield data (r = 0.67, 113 samples), indicating that the new CPsat_adjust map reduces the NDVI saturation effects and is in good agreement with the corn yield ground observations. Results demonstrate that the NDVI saturation adjustment approach improves the quality of the original GSN map and better depicts the actual vegetation conditions of the GPRB cropland systems.

[Spatiotemporal variation of vegetation in northern Shaanxi of Northwest China based on SPOT-VGT NDVI].

Science.gov (United States)

Yang, Yan-Zheng; Zhao, Peng-Xiang; Hao, Hong-Ke; Chang, Ming

2012-07-01

By using 1998-2010 SPOT-VGT NDVI images, this paper analyzed the spatiotemporal variation of vegetation in northern Shaanxi. In 1998-2010, the NDVI in northern Shaanxi had an obvious seasonal variation. The average monthly NDVI was the minimum (0.14) in January and the maximum (0.46) in August, with a mean value of 0.28. The average annual NDVI presented an overall increasing trend, indicating that the vegetation in this area was in restoring. Spatially, the restoration of vegetation in this area was concentrated in central south part, and the degradation mainly occurred in the north of the Great Wall. Air temperature and precipitation were the important climate factors affecting the variation of vegetation, with the linear correlation coefficients to NDVI being 0.72 and 0.58, respectively. The regions with better restored vegetation were mainly on the slopes of 15 degrees-25 degrees, indicating that the Program of Conversion of Cropland to Forestland and Grassland had a favorable effect in the vegetation restoration in northern Shaanxi.

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands.

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Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela; Jarchow, Christopher J; Roberts, Dar A

2017-04-15

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24m resolution WorldView-3 and a 0.1m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure. Copyright © 2017 Elsevier B.V. All rights reserved.

Seasonal variations of leaf and canopy properties tracked by ground-based NDVI imagery in a temperate forest.

Science.gov (United States)

Yang, Hualei; Yang, Xi; Heskel, Mary; Sun, Shucun; Tang, Jianwu

2017-04-28

Changes in plant phenology affect the carbon flux of terrestrial forest ecosystems due to the link between the growing season length and vegetation productivity. Digital camera imagery, which can be acquired frequently, has been used to monitor seasonal and annual changes in forest canopy phenology and track critical phenological events. However, quantitative assessment of the structural and biochemical controls of the phenological patterns in camera images has rarely been done. In this study, we used an NDVI (Normalized Difference Vegetation Index) camera to monitor daily variations of vegetation reflectance at visible and near-infrared (NIR) bands with high spatial and temporal resolutions, and found that the infrared camera based NDVI (camera-NDVI) agreed well with the leaf expansion process that was measured by independent manual observations at Harvard Forest, Massachusetts, USA. We also measured the seasonality of canopy structural (leaf area index, LAI) and biochemical properties (leaf chlorophyll and nitrogen content). We found significant linear relationships between camera-NDVI and leaf chlorophyll concentration, and between camera-NDVI and leaf nitrogen content, though weaker relationships between camera-NDVI and LAI. Therefore, we recommend ground-based camera-NDVI as a powerful tool for long-term, near surface observations to monitor canopy development and to estimate leaf chlorophyll, nitrogen status, and LAI.

Integrated NDVI images for Niger 1986-1987. [Normalized Difference Vegetation Index

Science.gov (United States)

Harrington, John A., Jr.; Wylie, Bruce K.; Tucker, Compton J.

1988-01-01

Two NOAA AVHRR images are presented which provide a comparison of the geographic distribution of an integration of the normalized difference vegetation index (NDVI) for the Sahel zone in Niger for the growing seasons of 1986 and 1987. The production of the images and the application of the images for resource management are discussed. Daily large area coverage with a spatial resolution of 1.1 km at nadir were transformed to the NDVI and geographically registered to produce the images.

UAV-based NDVI calculation over grassland: An alternative approach

Science.gov (United States)

Mejia-Aguilar, Abraham; Tomelleri, Enrico; Asam, Sarah; Zebisch, Marc

2016-04-01

The Normalised Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring and assessing vegetation in remote sensing. The index relies on the reflectance difference between the near infrared (NIR) and red light and is thus able to track variations of structural, phenological, and biophysical parameters for seasonal and long-term monitoring. Conventionally, NDVI is inferred from space-borne spectroradiometers, such as MODIS, with moderate resolution up to 250 m ground resolution. In recent years, a new generation of miniaturized radiometers and integrated hyperspectral sensors with high resolution became available. Such small and light instruments are particularly adequate to be mounted on airborne unmanned aerial vehicles (UAV) used for monitoring services reaching ground sampling resolution in the order of centimetres. Nevertheless, such miniaturized radiometers and hyperspectral sensors are still very expensive and require high upfront capital costs. Therefore, we propose an alternative, mainly cheaper method to calculate NDVI using a camera constellation consisting of two conventional consumer-grade cameras: (i) a Ricoh GR modified camera that acquires the NIR spectrum by removing the internal infrared filter. A mounted optical filter additionally obstructs all wavelengths below 700 nm. (ii) A Ricoh GR in RGB configuration using two optical filters for blocking wavelengths below 600 nm as well as NIR and ultraviolet (UV) light. To assess the merit of the proposed method, we carry out two comparisons: First, reflectance maps generated by the consumer-grade camera constellation are compared to reflectance maps produced with a hyperspectral camera (Rikola). All imaging data and reflectance maps are processed using the PIX4D software. In the second test, the NDVI at specific points of interest (POI) generated by the consumer-grade camera constellation is compared to NDVI values obtained by ground spectral measurements using a

NDVI as a predictor of canopy arthropod biomass in the Alaskan arctic tundra.

Science.gov (United States)

Sweet, Shannan K; Asmus, Ashley; Rich, Matthew E; Wingfield, John; Gough, Laura; Boelman, Natalie T

2015-04-01

The physical and biological responses to rapid arctic warming are proving acute, and as such, there is a need to monitor, understand, and predict ecological responses over large spatial and temporal scales. The use of the normalized difference vegetation index (NDVI) acquired from airborne and satellite sensors addresses this need, as it is widely used as a tool for detecting and quantifying spatial and temporal dynamics of tundra vegetation cover, productivity, and phenology. Such extensive use of the NDVI to quantify vegetation characteristics suggests that it may be similarly applied to characterizing primary and secondary consumer communities. Here, we develop empirical models to predict canopy arthropod biomass with canopy-level measurements of the NDVI both across and within distinct tundra vegetation communities over four growing seasons in the Arctic Foothills region of the Brooks Range, Alaska, USA. When canopy arthropod biomass is predicted with the NDVI across all four growing seasons, our overall model that includes all four vegetation communities explains 63% of the variance in canopy arthropod biomass, whereas our models specific to each of the four vegetation communities explain 74% (moist tussock tundra), 82% (erect shrub tundra), 84% (riparian shrub tundra), and 87% (dwarf shrub tundra) of the observed variation in canopy arthropod biomass. Our field-based study suggests that measurements of the NDVI made from air- and spaceborne sensors may be able to quantify spatial and temporal variation in canopy arthropod biomass at landscape to regional scales.

Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: an example at corn fields in western Mexico.

Science.gov (United States)

Chen, Pei-Yu; Fedosejevs, Gunar; Tiscareño-López, Mario; Arnold, Jeffrey G

2006-08-01

Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.

Using MODIS NDVI phenoclasses and phenoclusters to characterize wildlife habitat: Mexican spotted owl as a case study

Science.gov (United States)

Serra J. Hoagland; Paul Beier; Danny Lee

2018-01-01

Most uses of remotely sensed satellite data to characterize wildlife habitat have used metrics such as mean NDVI (Normalized Difference Vegetation Index) in a year or season. These simple metrics do not take advantage of the temporal patterns in NDVI within and across years and the spatial arrangement of cells with various temporal NDVI signatures. Here we use 13 years...

Climate and land use change in an Andean watershed: An NDVI analysis for the years 1985 to 2010

Science.gov (United States)

Mazzarino, M.; Finn, J.

2013-12-01

We perform a Landsat 5-TM derived Normalized Difference Vegetation Index (NDVI) analysis in a watershed (approximately 2700 km2) in southern Peru for the years 1985 through 2010. There in the Andes the livelihoods of the predominately Quechua speaking agro-pastoralists depend on access to natural resources. Vegetation within high-elevation wetlands, locally known as bofedales, is a critical resource that sustains herds of alpaca, sheep, and cattle especially during dry season months (June through August) and in drought. The watershed experiences high inter-annual variability in precipitation (attributed to the El Niño Southern Oscillation) and there are documented increases in air temperature and glacier retreat throughout the Andes. Using one dry-season scene per year for 20 of the 26 years from 1985 to 2010, we calculated NDVI for each pixel in the watershed and used these calculations to perform three objectives. First, we calculated mean NDVI for the Nuñoa watershed for each dry season scene. Using this annual watershed averaged NDVI as the response variable we performed a multiple linear regression with the covariates year, precipitation, and temperature in order to determine the relationship between the response and explanatory variables and if there is a trend in mean watershed dry-season NDVI from 1985 to 2010. Second, we delineated the wetlands (bofedales) based on a threshold value applied to the 26 year dry-season mean NDVI for each pixel in the watershed. Third, we performed a multiple linear regression for each pixel in the watershed (3,070,160) using cell specific annual dry-season NDVI as the response variable (n=20) and year, regional precipitation, and regional temperature indices as the predictor variables in order to review the spatial nature of NDVI changes in vegetation in the watershed throughout time (1985-2010), particularly with respect to bofedales. The results of these analyses indicate that there is reduced variability in dry season

FREQUENCY ANALYSIS OF MODIS NDVI TIME SERIES FOR DETERMINING HOTSPOT OF LAND DEGRADATION IN MONGOLIA

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E. Nasanbat

2018-04-01

Full Text Available This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.

Frequency Analysis of Modis Ndvi Time Series for Determining Hotspot of Land Degradation in Mongolia

Science.gov (United States)

Nasanbat, E.; Sharav, S.; Sanjaa, T.; Lkhamjav, O.; Magsar, E.; Tuvdendorj, B.

2018-04-01

This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.

[Dynamic changes in vegetation NDVI from 1982 to 2012 and its responses to climate change and human activities in Xinjiang, China].

Science.gov (United States)

Du, Jia-qiang; Jiaerheng, Ahati; Zhao, Chenxi; Fang, Guang-ling; Yin, Jun-qi; Xiang, Bao; Yuan, Xin-jie; Fang, Shi-feng

2015-12-01

Vegetation plays an important role in regulating the terrestrial carbon balance and the climate system, and also overwhelmingly dominates the provisioning of ecosystem services. Therefore, it has significance to monitor the growth of vegetation. Based on AVHRR GIMMS NDVI and MODIS NDVI datasets, we analyzed the spatiotemporal patterns of change in NDVI and their linkage with climate change and human activity from 1982 to 2012 in the typical arid region, Xinjiang of northwestern China, at pixel and regional scales. At regional scale, although a statistically significant positive trend of growing season NDVI with a rate of 4.09 x 10⁻⁴· a⁻¹ was found during 1982-2012, there were two distinct periods with opposite trends in growing season NDVI before and after 1998, respectively. NDVI in growing season first significantly increased with a rate of 10 x 10⁻⁴· a⁻¹ from 1982 to 1998, and then decreased with a rate of -3 x 10⁻⁴· a⁻¹ from 1998 to 2012. The change in trend of NDVI from increase to decrease mainly occurred in summer, followed by autumn, and the reversal wasn't observed in spring. At pixel scale, the NDVI in farmland significantly increased; the NDVI changes in the growing season and all seasons showed polarization: Areas with significant change mostly increased in size as the NDVI record grown in length. The rate of increase in size of areas with significantly decreasing NDVI was larger than that with significantly increasing NDVI, which led to the NDVI increase obviously slowing down or stopping at regional scale. The vegetation growth in the study area was regulated by both climate change and human activity. Temperature was the most important driving factor in spring and autumn, whereas precipitation in summer. Extensive use of fertilizers and increased farmland irrigated area promoted the vegetation growth. However, the rapid increase in the proportion of cotton cultivation and use of drip irrigation might reduce spring NDVI in the

[Correlation analysis on normalized difference vegetation index (NDVI) of different vegetations and climatic factors in Southwest China].

Science.gov (United States)

Zhang, Yuan-Dong; Zhang, Xiao-He; Liu, Shi-Rong

2011-02-01

Based on the 1982-2006 NDVI remote sensing data and meteorological data of Southwest China, and by using GIS technology, this paper interpolated and extracted the mean annual temperature, annual precipitation, and drought index in the region, and analyzed the correlations of the annual variation of NDVI in different vegetation types (marsh, shrub, bush, grassland, meadow, coniferous forest, broad-leaved forest, alpine vegetation, and cultural vegetation) with corresponding climatic factors. In 1982-2006, the NDVI, mean annual temperature, and annual precipitation had an overall increasing trend, and the drought index decreased. Particularly, the upward trend of mean annual temperature was statistically significant. Among the nine vegetation types, the NDVI of bush and mash decreased, and the downward trend was significant for bush. The NDVI of the other seven vegetation types increased, and the upward trend was significant for coniferous forest, meadow, and alpine vegetation, and extremely significant for shrub. The mean annual temperature in the areas with all the nine vegetation types increased significantly, while the annual precipitation had no significant change. The drought index in the areas with marsh, bush, and cultural vegetation presented an increasing trend, that in the areas with meadow and alpine vegetation decreased significantly, and this index in the areas with other four vegetation types had an unobvious decreasing trend. The NDVI of shrub and coniferous forest had a significantly positive correlation with mean annual temperature, and that of shrub and meadow had significantly negative correlation with drought index. Under the conditions of the other two climatic factors unchanged, the NDVI of coniferous forest, broad-leaved forest, and alpine vegetation showed the strongest correlation with mean annual temperature, that of grass showed the strongest correlation with annual precipitation, and the NDVI of mash, shrub, grass, meadow, and cultural

An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

Energy Technology Data Exchange (ETDEWEB)

Dagg, J.; Lafleur, P.

2010-07-01

This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO{sub 2}) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO{sub 2} exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO{sub 2} fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO{sub 2} uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO{sub 2} exchange in heterogeneous Tundra vegetation is variable.

An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

International Nuclear Information System (INIS)

Dagg, J.; Lafleur, P.

2010-01-01

This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO 2 ) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO 2 exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO 2 fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO 2 uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO 2 exchange in heterogeneous Tundra vegetation is variable.

Evaluation of NDVI to assess avian abundance and richness along the upper San Pedro River

Science.gov (United States)

McFarland, T.M.; van Riper, Charles; Johnson, G.E.

2012-01-01

Remote-sensing models have become increasingly popular for identifying, characterizing, monitoring, and predicting avian habitat but have largely focused on single bird species. The Normalized Difference Vegetation Index (NDVI) has been shown to positively correlate with avian abundance and richness and has been successfully applied to southwestern riparian systems which are uniquely composed of narrow bands of vegetation in an otherwise dry landscape. Desert riparian ecosystems are important breeding and stopover sites for many bird species but have been degraded due to altered hydrology and land management practices. Here we investigated the use of NDVI, coupled with vegetation, to model the avian community structure along the San Pedro River, Arizona. We also investigated how vegetation and physical features measured locally compared to those data that can be gathered through remote-sensing. We found that NDVI has statistically significant relationships with both avian abundance and species richness, although is better applied at the individual species level. However, the amount of variation explained by even our best models was quite low, suggesting that NDVI habitat models may not presently be an accurate tool for extensive modeling of avian communities. We suggest additional studies in other watersheds to increase our understanding of these bird/NDVI relationships.

(measured as NDVI) over mine tailings at Mhangura Copper Mine

African Journals Online (AJOL)

chari

Remote sensing techniques are increasingly being employed in monitoring environmental ... normalised difference vegetation index (NDVI), remote sensing, tailings ..... rehabilitation monitoring by adding landscape function characteristics.

Response of vegetation NDVI to climatic extremes in the arid region of Central Asia: a case study in Xinjiang, China

Science.gov (United States)

Yao, Junqiang; Chen, Yaning; Zhao, Yong; Mao, Weiyi; Xu, Xinbing; Liu, Yang; Yang, Qing

2018-02-01

Observed data showed the climatic transition from warm-dry to warm-wet in Xinjiang during the past 30 years and will probably affect vegetation dynamics. Here, we analyze the interannual change of vegetation index based on the satellite-derived normalized difference vegetation index (NDVI) with temperature and precipitation extreme over the Xinjiang, using the 8-km NDVI third-generation (NDVI3g) from the Global Inventory Modelling and Mapping Studies (GIMMS) from 1982 to 2010. Few previous studies analyzed the link between climate extremes and vegetation response. From the satellite-based results, annual NDVI significantly increased in the first two decades (1981-1998) and then decreased after 1998. We show that the NDVI decrease over the past decade may conjointly be triggered by the increases of temperature and precipitation extremes. The correlation analyses demonstrated that the trends of NDVI was close to the trend of extreme precipitation; that is, consecutive dry days (CDD) and torrential rainfall days (R24) positively correlated with NDVI during 1998-2010. For the temperature extreme, while the decreases of NDVI correlate positively with warmer mean minimum temperature ( Tnav), it correlates negatively with the number of warmest night days ( Rwn). The results suggest that the climatic extremes have possible negative effects on the ecosystem.

Evaluation of vegetation cover using the normalized difference vegetation index (NDVI

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Gabriela Camargos Lima

2013-08-01

Full Text Available Soil loss by water erosion is the main cause of soil degradation in Brazil. However, erosion can be reduced by the presence of vegetation. The Normalized Difference Vegetation Index (NDVI makes it possible to identify the vegetative vigor of crops or natural vegetation which facilities the identification of areas with vegetation covers. This information is very important in identifying the phenomena which might be occurring in a particular area, especially those related to soil degradation by water erosion. Thus, the aim of this work was to assess the canopy cover by using NDVI, checking the image accuracy using the Coverage Index (CI based on the Stocking method, in the Sub-basin of Posses, which belongs to the Cantareira System, located in the Extrema municipality, Minas Gerais, Brazil. Landsat-5 TM images were used. The sub-basin of Posses was very altered in comparison to the surrounding areas. The NDVI technique proved to be a suitable tool to assess the uses that occur in the sub-basin of Posses, as validated by the Stocking methodology. The map derived from NDVI allowed the geographic distribution of different land uses to be observed and allowed for the identification of critical areas in relation to vegetation cover as well. This finding can be used to optimize efforts to recover and protect soil in areas with bare soil and degraded pasture, in order to reduce environmental degradation. The CI has not exceeded 40% for land use classes that occur in the majority of the sub-basin (91%, except in areas of woody vegetation.

Influence of using date-specific values when extracting phenological metrics from 8-day composite NDVI data

CSIR Research Space (South Africa)

Bachoo, A

2007-07-01

Full Text Available ): this is the integral under the NDVI curve. Due to the contribution of bare soil to NDVI, a value of 0.1 instead of 0 was used as the minimum NDVI value (zero production). C. Algorithm parameters The parameters specified for the different algorithms were..., “Atmospheric correction of modis data in the visible to middle infrared- First results,” Remote Sensing of Enviroment, vol. 83, pp. 97–111, 2002. [3] P. Jonsson and L. Eklundh, “Seasonality extraction by function fitting to time-series of satellite sensor...

Detecting land cover change using an extended Kalman filter on MODIS NDVI time-series data

CSIR Research Space (South Africa)

Kleynhans, W

2011-05-01

Full Text Available A method for detecting land cover change using NDVI time-series data derived from 500-m MODIS satellite data is proposed. The algorithm acts as a per-pixel change alarm and takes the NDVI time series of a 3 × 3 grid of MODIS pixels as the input...

Inter-annual variability of NDVI in response to long-term warming and fertilization in wet sedge and tussock tundra.

Science.gov (United States)

Boelman, Natalie T; Stieglitz, Marc; Griffin, Kevin L; Shaver, Gaius R

2005-05-01

This study explores the relationship between the normalized difference vegetation index (NDVI) and aboveground plant biomass for tussock tundra vegetation and compares it to a previously established NDVI-biomass relationship for wet sedge tundra vegetation. In addition, we explore inter-annual variation in NDVI in both these contrasting vegetation communities. All measurements were taken across long-term experimental treatments in wet sedge and tussock tundra communities at the Toolik Lake Long Term Ecological Research (LTER) site, in northern Alaska. Over 15 years (for wet sedge tundra) and 14 years (for tussock tundra), N and P were applied in factorial experiments (N, P and N+P), air temperature was increased using greenhouses with and without N+P fertilizer, and light intensity was reduced by 50% using shade cloth. during the peak growing seasons of 2001, 2002, and 2003, NDVI measurements were made in both the wet sedge and tussock tundra experimental treatment plots, creating a 3-year time series of inter-annual variation in NDVI. We found that: (1) across all tussock experimental tundra treatments, NDVI is correlated with aboveground plant biomass (r2 = 0.59); (2) NDVI-biomass relationships for tussock and wet sedge tundra communities are community specific, and; (3) NDVI values for tussock tundra communities are typically, but not always, greater than for wet sedge tundra communities across all experimental treatments. We suggest that differences between the response of wet sedge and tussock tundra communities in the same experimental treatments result from the contrasting degree of heterogeneity in species and functional types that characterize each of these Arctic tundra vegetation communities.

Response of NDVI, biomass, and ecosystem gas exchange to long-term warming and fertilization in wet sedge tundra.

Science.gov (United States)

Boelman, Natalie T; Stieglitz, Marc; Rueth, Heather M; Sommerkorn, Martin; Griffin, Kevin L; Shaver, Gaius R; Gamon, John A

2003-05-01

This study explores the relationship between the normalized difference vegetation index (NDVI), aboveground plant biomass, and ecosystem C fluxes including gross ecosystem production (GEP), ecosystem respiration (ER) and net ecosystem production. We measured NDVI across long-term experimental treatments in wet sedge tundra at the Toolik Lake LTER site, in northern Alaska. Over 13 years, N and P were applied in factorial experiments (N, P and N + P), air temperature was increased using greenhouses with and without N + P fertilizer, and light intensity (photosynthetically active photon flux density) was reduced by 50% using shade cloth. Within each treatment plot, NDVI, aboveground biomass and whole-system CO(2) flux measurements were made at the same sampling points during the peak-growing season of 2001. We found that across all treatments, NDVI is correlated with aboveground biomass ( r(2)=0.84), GEP ( r(2)=0.75) and ER ( r(2)=0.71), providing a basis for linking remotely sensed NDVI to aboveground biomass and ecosystem carbon flux.

Mapping Rice Cropping Systems in Vietnam Using an NDVI-Based Time-Series Similarity Measurement Based on DTW Distance

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Xudong Guan

2016-01-01

Full Text Available Normalized Difference Vegetation Index (NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS time-series data has been widely used in the fields of crop and rice classification. The cloudy and rainy weather characteristics of the monsoon season greatly reduce the likelihood of obtaining high-quality optical remote sensing images. In addition, the diverse crop-planting system in Vietnam also hinders the comparison of NDVI among different crop stages. To address these problems, we apply a Dynamic Time Warping (DTW distance-based similarity measure approach and use the entire yearly NDVI time series to reduce the inaccuracy of classification using a single image. We first de-noise the NDVI time series using S-G filtering based on the TIMESAT software. Then, a standard NDVI time-series base for rice growth is established based on field survey data and Google Earth sample data. NDVI time-series data for each pixel are constructed and the DTW distance with the standard rice growth NDVI time series is calculated. Then, we apply thresholds to extract rice growth areas. A qualitative assessment using statistical data and a spatial assessment using sampled data from the rice-cropping map reveal a high mapping accuracy at the national scale between the statistical data, with the corresponding R2 being as high as 0.809; however, the mapped rice accuracy decreased at the provincial scale due to the reduced number of rice planting areas per province. An analysis of the results indicates that the 500-m resolution MODIS data are limited in terms of mapping scattered rice parcels. The results demonstrate that the DTW-based similarity measure of the NDVI time series can be effectively used to map large-area rice cropping systems with diverse cultivation processes.

Monitoring cotton root rot by synthetic Sentinel-2 NDVI time series using improved spatial and temporal data fusion.

Science.gov (United States)

Wu, Mingquan; Yang, Chenghai; Song, Xiaoyu; Hoffmann, Wesley Clint; Huang, Wenjiang; Niu, Zheng; Wang, Changyao; Li, Wang; Yu, Bo

2018-01-31

To better understand the progression of cotton root rot within the season, time series monitoring is required. In this study, an improved spatial and temporal data fusion approach (ISTDFA) was employed to combine 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Different Vegetation Index (NDVI) and 10-m Sentinetl-2 NDVI data to generate a synthetic Sentinel-2 NDVI time series for monitoring this disease. Then, the phenology of healthy cotton and infected cotton was modeled using a logistic model. Finally, several phenology parameters, including the onset day of greenness minimum (OGM), growing season length (GLS), onset of greenness increase (OGI), max NDVI value, and integral area of the phenology curve, were calculated. The results showed that ISTDFA could be used to combine time series MODIS and Sentinel-2 NDVI data with a correlation coefficient of 0.893. The logistic model could describe the phenology curves with R-squared values from 0.791 to 0.969. Moreover, the phenology curve of infected cotton showed a significant difference from that of healthy cotton. The max NDVI value, OGM, GSL and the integral area of the phenology curve for infected cotton were reduced by 0.045, 30 days, 22 days, and 18.54%, respectively, compared with those for healthy cotton.

JST Thesaurus Headwords and Synonyms: NDVI [MeCab user dictionary for science technology term[Archive

Lifescience Database Archive (English)

Full Text Available MeCab user dictionary for science technology term NDVI 名詞 一般 * * * * 正規化植生指数 セイキカショクセイシスウ セイキカショクセイシスー Thesaurus2015 200906004799738475 C KA01 UNKNOWN_1 NDVI

NDVI Variation and Its Responses to Climate Change on the Northern Loess Plateau of China from 1998 to 2012

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Tingting Ning

2015-01-01

Full Text Available This study analyzed temporal and spatial changes of normalized difference vegetation index (NDVI on the northern Loess Plateau and their correlation with climatic factors from 1998 to 2012. The possible impacts of human activities on the NDVI changes were also explored. The results showed that (1 the annual maximum NDVI showed an upward trend. The significantly increased NDVI and decreasing severe desertification areas demonstrate that the vegetation condition improved in this area. (2 Over the past decades, climate tended to be warmer and drier. However, the mean temperature significantly decreased and precipitation slightly increased from 1998 to 2012, especially in spring and summer, which was one of the major reasons for the increase in the annual maximum NDVI. Compared to temperature, vegetation was more sensitive to precipitation changes in this area. The NDVI and annual precipitation changes were highly synchronous over the first half of the year, while a 1-month time lag existed between the two variables during the second half of the year. (3 Positive human activities, including the “Grain for Green” program and successful environmental treatments at coal mining bases, were some of the other factors that improved the vegetation condition.

Variation of biomass and carbon pool with NDVI and altitude in sub-tropical forests of northwestern Himalaya.

Science.gov (United States)

Bhardwaj, D R; Banday, Muneesa; Pala, Nazir A; Rajput, Bhalendra Singh

2016-11-01

In the present study, forests at three altitudes, viz., A 1 (600-900 m), A 2 (900-1200 m) and A 3 (1200-1500 m) above mean sea level having normalised differential vegetation index (NDVI) values of N 1 (0.0-0.1), N 2 (0.1-0.2), N 3 (0.2-0.3), N 4 (0.3-0.4) and N 5 (0.4-0.5) were selected for studying their relationship with the biomass and carbon pool in the state of Himachal Pradesh, India. The study reported maximum stem density of (928 trees ha -1 ) at the A 2 altitude and minimum in the A 3 and A 1 with 600 trees ha -1 each. The stem densities in relation to NDVIs were observed in the order N 5 > N 3 > N 4 > N 1 > N 2 and did not show any definite trend with increasing altitude. Highest stem volume (295.7 m 3  ha -1 ) was observed in N 1 NDVI and minimum (194.1 m 3  ha -1 ) in N 3 index. The trend observed for stem biomass at different altitudes was A 3 > A 1 > A 2 and for NDVIs, it was N 5 > N 1 > N 4 > N 2 > N 3 . Maximum aboveground biomass (265.83 t ha -1 ) was recorded in the 0.0-0.1 NDVI and minimum (169.05 t ha -1 ) in 0.2-0.3 NDVI index. Significantly, maximum total soil carbon density (90.82 t C ha -1 ) was observed in 0.4-0.5 NDVI followed by 0.3-0.4 NDVI (77.12 t C ha -1 ). The relationship between soil carbon and other studied parameters was derived through different functions simultaneously. Cubic function showed highest r 2 in most cases, followed by power, inverse and exponential function. The relationship with NDVI showed highest r 2 (0.62) through cubic functions. In relationship between ecosystem carbon with other parameters of different altitudinal gradient and NDVI, only one positively significant relation was formed with total density (0.579) through cubic function. The present study thus reveals that soil carbon density was directly related to altitude and NDVIs, but the vegetation carbon density did not bear any significant relation with altitude and NDVI.

Evaluating the utility and seasonality of NDVI values for assessing post-disturbance recovery in a subalpine forest.

Science.gov (United States)

Buma, Brian

2012-06-01

Forest disturbances around the world have the potential to alter forest type and cover, with impacts on diversity, carbon storage, and landscape composition. These disturbances, especially fire, are common and often large, making ground investigation of forest recovery difficult. Remote sensing offers a means to monitor forest recovery in real time, over the entire landscape. Typically, recovery monitoring via remote sensing consists of measuring vegetation indices (e.g., NDVI) or index-derived metrics, with the assumption that recovery in NDVI (for example) is a meaningful measure of ecosystem recovery. This study tests that assumption using MODIS 16-day imagery from 2000 to 2010 in the area of the Colorado's Routt National Forest Hinman burn (2002) and seedling density counts taken in the same area. Results indicate that NDVI is rarely correlated with forest recovery, and is dominated by annual and perennial forb cover, although topography complicates analysis. Utility of NDVI as a means to delineate areas of recovery or non-recovery are in doubt, as bootstrapped analysis indicates distinguishing power only slightly better than random. NDVI in revegetation analyses should carefully consider the ecology and seasonal patterns of the system in question.

Dinámica temporal del NDVI del bosque y pastizal natural en el Chaco de la Provincia de Santiago del Estero, Argentina / The temporal dynamic of NDVI, of forest and grassland in the Chaco Seco of Santiago del Estero province, Argentine

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Hugo Raul Zerda

2010-04-01

Full Text Available Mediante imágenes mapas del índice de vegetación de diferencia normalizada (NDVI derivados del SPOT 4-Vegetation, se analizó la dinámica interanual y mensual de muestras de bosque nativo y pastizal natural de la provincia de Santiago del Estero, Argentina. Los resultados, muestran diferencias significativas (p pequenõs 0.05 para ambas coberturas, en la dinámica interanual y mensual. La actividad fotosintética del bosque se muestra superior a la del pastizal natural, analizada a partir de las curvas de NDVI. La dinámica del bosque y del pastizal natural, sigue el modelo regional de precipitaciones, alcanzando mayores valores de NDVI, durante la estación húmeda estival (Octubre-Mayo y menores valores de NDVI, durante la estación seca invernal (Junio-Septiembre. El bosque presentó mayor estabilidad que el pastizal natural, ante variaciones en las precipitaciones y temperatura, esperable por la mayor diversidad de especies en los bosques, y especialmente por las leñosas de raíces más profundas. La curva NDVI del pastizal natural, muestra sensibilidad al efecto de las elevadas intensidades de radiación en el verano, evapotranspiración y sequías; y debido a la mayor eficiencia del sistema radicular para el aprovechamiento del agua disponible, responde de manera inmediata ante las precipitaciones.AbstarctThe interannual and monthly dynamic of samples of forest and grassland from Santiago del Estero province, Argentine Republic, was analyzed through maps of vegetation of normalized difference (NDVI index derived from Vegetation/SPOT4 sensor. The results demonstrate that both covers, interannual and monthly dynamic mentioned before, have significant differences (p<0.05. The photosynthetic activity of the forest is superior compared with the one of the grassland, analyzed from the NDVI curves. The forest and the grassland dynamic, follows the regional precipitation pattern, reaching higher values from NDVI, during the summer humid

Analyses of GIMMS NDVI Time Series in Kogi State, Nigeria

Science.gov (United States)

Palka, Jessica; Wessollek, Christine; Karrasch, Pierre

2017-10-01

The value of remote sensing data is particularly evident where an areal monitoring is needed to provide information on the earth's surface development. The use of temporal high resolution time series data allows for detecting short-term changes. In Kogi State in Nigeria different vegetation types can be found. As the major population in this region is living in rural communities with crop farming the existing vegetation is slowly being altered. The expansion of agricultural land causes loss of natural vegetation, especially in the regions close to the rivers which are suitable for crop production. With regard to these facts, two questions can be dealt with covering different aspects of the development of vegetation in the Kogi state, the determination and evaluation of the general development of the vegetation in the study area (trend estimation) and analyses on a short-term behavior of vegetation conditions, which can provide information about seasonal effects in vegetation development. For this purpose, the GIMMS-NDVI data set, provided by the NOAA, provides information on the normalized difference vegetation index (NDVI) in a geometric resolution of approx. 8 km. The temporal resolution of 15 days allows the already described analyses. For the presented analysis data for the period 1981-2012 (31 years) were used. The implemented workflow mainly applies methods of time series analysis. The results show that in addition to the classical seasonal development, artefacts of different vegetation periods (several NDVI maxima) can be found in the data. The trend component of the time series shows a consistently positive development in the entire study area considering the full investigation period of 31 years. However, the results also show that this development has not been continuous and a simple linear modeling of the NDVI increase is only possible to a limited extent. For this reason, the trend modeling was extended by procedures for detecting structural breaks in

MODIS NDVI Change Detection Techniques and Products Used in the Near Real Time ForWarn System for Detecting, Monitoring, and Analyzing Regional Forest Disturbances

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Spruce, Joseph P.; Hargrove, William; Gasser, Jerry; Smoot, James; Kuper, Philip D.

2014-01-01

This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Early Warning System (EWS) for near real time (NRT) recognition and tracking of regionally evident forest disturbances throughout the conterminous US (CONUS). The latter has provided NRT forest change products to the forest health protection community since 2010, using temporally processed MODIS Aqua and Terra NDVI time series data to currently compute and post 6 different forest change products for CONUS every 8 days. Multiple change products are required to improve detectability and to more fully assess the nature of apparent disturbances. Each type of forest change product reports per pixel percent change in NDVI for a given 24 day interval, comparing current versus a given historical baseline NDVI. EMODIS 7 day expedited MODIS MOD13 data are used to obtain current and historical NDVIs, respectively. Historical NDVI data is processed with Time Series Product Tool (TSPT); and 2) the Phenological Parameters Estimation Tool (PPET) software. While each change products employ maximum value compositing (MVC) of NDVI, the design of specific products primarily differs in terms of the historical baseline. The three main change products use either 1, 3, or all previous years of MVC NDVI as a baseline. Another product uses an Adaptive Length Compositing (ALC) version of MVC to derive an alternative current NDVI that is the freshest quality NDVI as opposed to merely the MVC NDVI across a 24 day time frame. The ALC approach can improve detection speed by 8 to 16 days. ForWarn also includes 2 change products that improve detectability of forest disturbances in lieu of climatic fluctuations, especially in the spring and fall. One compares current MVC NDVI to the zonal maximum under the curve NDVI per pheno-region cluster class, considering all previous years in the MODIS record. The other compares current maximum NDVI to the mean of maximum NDVI for all previous MODIS years.

Spatiotemporal changes of normalized difference vegetation index (NDVI) and response to climate extremes and ecological restoration in the Loess Plateau, China

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Zhao, Anzhou; Zhang, Anbing; Liu, Xianfeng; Cao, Sen

2018-04-01

Extreme drought, precipitation, and other extreme climatic events often have impacts on vegetation. Based on meteorological data from 52 stations in the Loess Plateau (LP) and a satellite-derived normalized difference vegetation index (NDVI) from the third-generation Global Inventory Modeling and Mapping Studies (GIMMS3g) dataset, this study investigated the relationship between vegetation change and climatic extremes from 1982 to 2013. Our results showed that the vegetation coverage increased significantly, with a linear rate of 0.025/10a ( P NDVI revealed an increasing trend from the northwest to the southeast, with about 61.79% of the LP exhibiting a significant increasing trend ( P NDVI at the yearly time scale ( P NDVI during the spring and autumn ( P NDVI and RX1day, TMAXmean, TXn, and TXx was insignificant in summer. Vegetation exhibited a significant negative relationship with precipitation extremes in winter ( P NDVI in Yan'an and Yulin during 1998-2013, r = 0.859 and 0.85, n = 16, P < 0.001.

Improving agricultural drought monitoring in West Africa using root zone soil moisture estimates derived from NDVI

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McNally, A.; Funk, C. C.; Yatheendradas, S.; Michaelsen, J.; Cappelarere, B.; Peters-Lidard, C. D.; Verdin, J. P.

2012-12-01

The Famine Early Warning Systems Network (FEWS NET) relies heavily on remotely sensed rainfall and vegetation data to monitor agricultural drought in Sub-Saharan Africa and other places around the world. Analysts use satellite rainfall to calculate rainy season statistics and force crop water accounting models that show how the magnitude and timing of rainfall might lead to above or below average harvest. The Normalized Difference Vegetation Index (NDVI) is also an important indicator of growing season progress and is given more weight over regions where, for example, lack of rain gauges increases error in satellite rainfall estimates. Currently, however, near-real time NDVI is not integrated into a modeling framework that informs growing season predictions. To meet this need for our drought monitoring system a land surface model (LSM) is a critical component. We are currently enhancing the FEWS NET monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System. Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following questions: What is the relationship between NDVI and in-situ soil moisture measurements over the West Africa Sahel? How can we use this relationship to improve modeled water and energy fluxes over the West Africa Sahel? We investigate soil moisture and NDVI cross-correlation in the time and frequency domain to develop a transfer function model to predict soil moisture from NDVI. This work compares sites in southwest Niger, Benin, Burkina Faso, and Mali to test the generality of the transfer function. For several sites with fallow and millet vegetation in the Wankama catchment in southwest Niger we developed a non-parametric frequency response model, using NDVI inputs and soil moisture outputs, that accurately estimates root zone soil moisture (40-70cm). We extend this analysis by developing a low order parametric transfer function

Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia

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Zaitunah, A.; Samsuri; Ahmad, A. G.; Safitri, R. A.

2018-03-01

Watershed is an ecosystem area confined by topography and has function as a catcher, storage, and supplier of water, sediments, pollutants and nutrients in the river system and exit through a single outlet. Various activities around watershed areas of Besitang have changed the land cover and vegetation index (NDVI) that exist in the region. In order to detect changes in land cover and NDVI quickly and accurately, we used remote sensing technology and geographic information systems (GIS). The study aimed to assess changes in land cover and vegetation density (NDVI) between 2005 and 2015, as well as obtaining the density of vegetation (NDVI) on each of the land cover of 2005 and 2015. The research showed the extensive of forest area of 949.65 Ha and a decline of mangrove forest area covering an area of 2,884.06 Ha. The highest vegetation density reduced 39,714.58 Ha, and rather dense increased 24,410.72 Ha between 2005 and 2015. The land cover that have the highest NDVI value range with very dense vegetation density class is the primary dry forest (0.804 to 0.876), followed by secondary dry forest (0.737 to 0.804) for 2015. In 2015 the land cover has NDVI value range the primary dry forest (0.513 to 0.57), then secondary dry forest (0.456 to 0.513) with dense vegetation density class

Patrones fenológicos de la Provincia de Mendoza, Argentina, mediante serie temporal de imágenes NOAA-AVHRR NDVI GAC Phenological patterns of the province of Mendoza, Argentina, through a temporal series of NOAA-AVHRR NDVI GAC images

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M. M González Loyarte

2010-12-01

Full Text Available Se describe la dinámica temporal de la vegetación de Mendoza mediante análisis de la fenología foliar regional con una serie de 108 imágenes mensuales de índice de vegetación NOAA-AVHRR NDVI GAC. La serie se descompone aplicando la Transformada Rápida de Fourier en parámetros dinámicos: NDVI medio, amplitudes (máxima variabilidad del NDVI y fases (tiempo entre inicio del ciclo y máximo NDVI para diferentes períodos. Con los parámetros con mayor información (variablilidad inter e intraanual se hace una clasificación y se obtiene un mapa de 18 áreas de comportamiento fenológico. Éste se vincula con los ecosistemas y con las unidades de vegetación. Se modela el patrón fenológico (curva NDVI mensual para 17 unidades de vegetación. El mapa aporta elementos dinámicos al estudio regional de la vegetación generando una zonificación nueva explicada por variables que determinan la actividad vegetativa. El patrón fenológico describe el funcionamiento de la vegetación y permite comprender sus variaciones geográficas. El conjunto de la vegetación de Mendoza responde a un ciclo anual con matices localizados de ligera bimodalidad. Los patrones de bajo contraste invierno-verano corresponden a condiciones climáticas xéricas expresando su máximo vegetativo al final del verano; la disponibilidad hídrica incrementa este contraste acortando el tiempo de máxima expresión vegetativa.The temporal dynamics of vegetation in Mendoza is described through analysis of regional foliar phenology using a series of 108 monthly NOAA-AVHRR NDVI GAC images. A Fast Fourier Transform was used to decompose the series into dynamic parameters: mean NDVI, amplitudes (maximum NDVI variability and phases (time from start of cycle to maximum NDVI for different time periods. A classification is made based on those parameters with larger information content (inter- and intra-annual variability, achieving a map of 18 areas of phenological behaviour. This

A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series

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David Helman

2015-09-01

Full Text Available We present an efficient method for monitoring woody (i.e., evergreen and herbaceous (i.e., ephemeral vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS. The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI in the dry season was attributed to the woody vegetation (NDVIW. A constant NDVI value was assumed for soil background during this period. In the wet season, changes in NDVI were attributed to the development of ephemeral herbaceous vegetation in the forest floor and its maximum value to the peak green cover (NDVIH. NDVIW and NDVIH agreed well with field estimates of leaf area index and fraction of vegetation cover in two differently structured Mediterranean forests. To further assess the method’s assumptions, understory NDVI was retrieved form MODIS Bidirectional Reflectance Distribution Function (BRDF data and compared with NDVIH. After calibration, leaf area index and woody and herbaceous vegetation covers were assessed for those forests. Applicability for pre- and post-fire monitoring is presented as a potential use of this method for forest management in Mediterranean-climate regions.

Woody plant richness and NDVI response to drought events in Catalonian (northeastern Spain) forests.

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Lloret, F; Lobo, A; Estevan, H; Maisongrande, P; Vayreda, J; Terradas, J

2007-09-01

The role of species diversity on ecosystem resistance in the face of strong environmental fluctuations has been addressed from both theoretical and experimental viewpoints to reveal a variety of positive and negative relationships. Here we explore empirically the relationship between the richness of forest woody species and canopy resistance to extreme drought episodes. We compare richness data from an extensive forest inventory to a temporal series of satellite imagery that estimated drought impact on forest canopy as NDVI (normalized difference vegetation index) anomalies of the dry summer in 2003 in relation to records of previous years. We considered five different types of forests that are representative of the main climatic and altitudinal gradients of the region, ranging from lowland Mediterranean to mountain boreal-temperate climates. The observed relationship differed among forest types and interacted with the climate, summarised by the Thorntwaite index. In Mediterranean Pinus halepensis forests, NDVI decreased during the drought. This decrease was stronger in forests with lower richness. In Mediterranean evergreen forests of Quercus ilex, drought did not result in an overall NDVI loss, but lower NDVI values were observed in drier localities with lower richness, and in more moist localities with higher number of species. In mountain Pinus sylvestris forests NDVI decreased, mostly due to the drought impact on drier localities, while no relation to species richness was observed. In moist Fagus sylvatica forests, NDVI only decreased in plots with high richness. No effect of drought was observed in the high mountain Pinus uncinata forests. Our results show that a shift on the diversity-stability relationship appears across the regional, climatic gradient. A positive relationship appears in drier localities, supporting a null model where the probability of finding a species able to cope with drier conditions increases with the number of species. However, in

Estimating the effect of urease inhibitor on rice yield based on NDVI at key growth stages

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Kailou LIU,Yazhen LI,Huiwen HU

2014-06-01

Full Text Available The effect of the urease inhibitor, N-(n-butyl thiophosphoric triamide (NBPT at a range of application rates on rice production was examined in a field experiment at Jinxian County, Jiangxi Province, China. The normalized difference vegetation index (NDVI was measured at key growth stages in both early and late rice. The results showed that the grain yield increased significantly when urea was applied with NBPT, with the highest yield observed at 1.00% NBPT (wt/wt. NDVI differed with the growth stage of rice; it remained steady from the heading to the filling stage. Rice yield could be predicted from the NDVI taken at key rice growing stages, with R2 ranging from 0.34 to 0.69 in early rice and 0.49 to 0.70 in late rice. The validation test showed that RMSE (t·hm-2 values were 0.77 and 0.87 in early and late rice, respectively. Therefore, it was feasible to estimate rice yield for different amounts of urease inhibitor using NDVI.

Trauma dos ossos temporais e suas complicações: aspectos na tomografia computadorizada Temporal bone trauma and complications: computed tomography findings

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Ana Maria Doffémond Costa

2013-04-01

Full Text Available A maioria das fraturas dos ossos temporais resulta de traumas cranianos bruscos, de alta energia, estando muitas vezes relacionadas a outras fraturas cranianas ou a politraumatismo. As fraturas e os deslocamentos da cadeia ossicular, na orelha média, representam umas das principais complicações das injúrias nos ossos temporais e, por isso, serão abordadas de maneira mais profunda neste artigo. Os outros tipos de injúrias englobam as fraturas labirínticas, fístula dural, paralisia facial e extensão da linha de fratura ao canal carotídeo. A tomografia computadorizada tem papel fundamental na avaliação inicial dos pacientes politraumatizados, pois é capaz de identificar injúrias em importantes estruturas que podem causar graves complicações, como perda auditiva de condução ou neurossensorial, tonturas e disfunções do equilíbrio, fístulas perilinfáticas, paralisia do nervo facial, lesões vasculares, entre outras.Most temporal bone fractures result from high-energy blunt head trauma, and are frequently related to other skull fractures or to polytrauma. Fractures and displacements of ossicular chain in the middle ear represent some of the main complications of temporal bone injury, and hence they will be more deeply approached in the present article. Other types of injuries include labyrinthine fractures, dural fistula, facial nerve paralysis and extension into the carotid canal. Computed tomography plays a fundamental role in the initial evaluation of polytrauma patients, as it can help to identify important structural injuries that may lead to severe complications such as sensorineural hearing loss, conductive hearing loss, dizziness and balance dysfunction, perilymphatic fistulas, facial nerve paralysis, vascular injury and others.

Anopheles atroparvus density modeling using MODIS NDVI in a former malarious area in Portugal.

Science.gov (United States)

Lourenço, Pedro M; Sousa, Carla A; Seixas, Júlia; Lopes, Pedro; Novo, Maria T; Almeida, A Paulo G

2011-12-01

Malaria is dependent on environmental factors and considered as potentially re-emerging in temperate regions. Remote sensing data have been used successfully for monitoring environmental conditions that influence the patterns of such arthropod vector-borne diseases. Anopheles atroparvus density data were collected from 2002 to 2005, on a bimonthly basis, at three sites in a former malarial area in Southern Portugal. The development of the Remote Vector Model (RVM) was based upon two main variables: temperature and the Normalized Differential Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite. Temperature influences the mosquito life cycle and affects its intra-annual prevalence, and MODIS NDVI was used as a proxy for suitable habitat conditions. Mosquito data were used for calibration and validation of the model. For areas with high mosquito density, the model validation demonstrated a Pearson correlation of 0.68 (pNDVI. RVM is a satellite data-based assimilation algorithm that uses temperature fields to predict the intra- and inter-annual densities of this mosquito species using MODIS NDVI. RVM is a relevant tool for vector density estimation, contributing to the risk assessment of transmission of mosquito-borne diseases and can be part of the early warning system and contingency plans providing support to the decision making process of relevant authorities. © 2011 The Society for Vector Ecology.

Aspectos temporais auditivos em adolescentes do 6º ano do Ensino Fundamental Temporal aspects of hearing in adolescents from the 6th year of elementary education

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Sulamita da Silva Marcelino Terto

2012-01-01

Full Text Available OBJETIVO: esclarecer a relação entre desempenho escolar e aspectos temporais auditivos. MÉTODO: estudo descritivo-transversal com amostra de conveniência, composta por 82 estudantes, na faixa etária de 11 a 13 anos, sendo 43 do sexo feminino e 38 do sexo masculino do 6º ano de uma escola de financiamento privado na Região Metropolitana de Belo Horizonte. Cada estudante respondeu a um formulário de caracterização da amostra, realizou o Teste de Desempenho Escolar e foi submetido aos testes que avaliam os aspectos temporais auditivos: Teste Padrão de Duração, Teste Padrão de Frequência e Teste Gap-in-Noise. RESULTADOS: os testes que avaliam os aspectos temporais auditivos não sofreram influência relacionada às variáveis sexo, idade, realização de atividades de musicalização e preferência manual. Com exceção da variável "acompanhamento fonoaudiológico" que apresentou significância estatística no teste Gap-in-Noise. Os subtestes do Teste de Desempenho Escolar que exerceram maior influencia no desempenho nos testes Padrão de Duração e Padrão de Frequência foram Escrita, seguida de Leitura e Aritmética. CONCLUSÃO: a análise dos dados revelou que há correlação entre desempenho escolar e aspectos temporais auditivos. Cabe ressaltar que os testes que avaliam a ordenação temporal complexa (Teste Padrão de Frequência e Teste Padrão de Duração são influenciados pelo desempenho no Teste de Desempenho Escolar. Porém o mesmo não ocorre com o teste que avalia resolução temporal (Gap-in-Noise.PURPOSE: to elucidate the relationship between school performance and temporal aspects of hearing. METHOD: a descriptive cross-sectional convenience sample composed of 82 students, aged 11-13 years, 43 females, and 38 males in the 6th grade at a private funding school in the Metropolitan Region of Belo Horizonte. Each student responded to one form of sample characterization, performed the Academic Performance Test and was

Aspectos temporais auditivos em adolescentes do 6º ano do ensino fundamental Temporal aspects of hearing in adolescents from the 6th year of elementary education

Directory of Open Access Journals (Sweden)

Sulamita da Silva Marcelino Terto

2013-04-01

Full Text Available OBJETIVO: esclarecer a relação entre desempenho escolar e aspectos temporais auditivos. MÉTODO: estudo descritivo-transversal com amostra de conveniência, composta por 82 estudantes, na faixa etária de 11 a 13 anos, sendo 43 do sexo feminino e 38 do sexo masculino do 6º ano de uma escola de financiamento privado na Região Metropolitana de Belo Horizonte. Cada estudante respondeu a um formulário de caracterização da amostra, realizou o Teste de Desempenho Escolar e foi submetido aos testes que avaliam os aspectos temporais auditivos: Teste Padrão de Duração, Teste Padrão de Frequência e Teste Gap-in-Noise. RESULTADOS: os testes que avaliam os aspectos temporais auditivos não sofreram influência relacionada às variáveis sexo, idade, realização de atividades de musicalização e preferência manual. Com exceção da variável "acompanhamento fonoaudiológico" que apresentou significância estatística no teste Gap-in-Noise. Os subtestes do Teste de Desempenho Escolar que exerceram maior influencia no desempenho nos testes Padrão de Duração e Padrão de Frequência foram Escrita, seguida de Leitura e Aritmética. CONCLUSÃO: a análise dos dados revelou que há correlação entre desempenho escolar e aspectos temporais auditivos. Cabe ressaltar que os testes que avaliam a ordenação temporal complexa (Teste Padrão de Frequência e Teste Padrão de Duração são influenciados pelo desempenho no Teste de Desempenho Escolar. Porém o mesmo não ocorre com o teste que avalia resolução temporal (Gap-in-Noise.PURPOSE: to elucidate the relationship between school performance and temporal aspects of hearing. METHOD: a descriptive cross-sectional convenience sample composed of 82 students, aged 11-13 years, 43 females, and 38 males in the 6th grade at a private funding school in the Metropolitan Region of Belo Horizonte. Each student responded to one form of sample characterization, performed the Academic Performance Test and was

Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products.

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Guo, Xiaoyi; Zhang, Hongyan; Wu, Zhengfang; Zhao, Jianjun; Zhang, Zhengxiang

2017-06-06

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI

The response of Arctic vegetation to the summer climate: relation between shrub cover, NDVI, surface albedo and temperature

Energy Technology Data Exchange (ETDEWEB)

Blok, Daan; Heijmans, Monique M P D; Berendse, Frank [Nature Conservation and Plant Ecology Group, Wageningen University, PO Box 47, 6700 AA, Wageningen (Netherlands); Schaepman-Strub, Gabriela [Institute of Evolutionary Biology and Environmental Studies, University of Zuerich, Winterthurerstrasse 190, 8057 Zuerich (Switzerland); Bartholomeus, Harm [Centre for Geo-Information, Wageningen University, PO Box 47, 6700 AA, Wageningen (Netherlands); Maximov, Trofim C, E-mail: daan.blok@wur.nl [Biological Problems of the Cryolithozone, Russian Academy of Sciences, Siberian Division, 41, Lenin Prospekt, Yakutsk, The Republic of Sakha, Yakutia 677980 (Russian Federation)

2011-07-15

Recently observed Arctic greening trends from normalized difference vegetation index (NDVI) data suggest that shrub growth is increasing in response to increasing summer temperature. An increase in shrub cover is expected to decrease summer albedo and thus positively feed back to climate warming. However, it is unknown how albedo and NDVI are affected by shrub cover and inter-annual variations in the summer climate. Here, we examine the relationship between deciduous shrub fractional cover, NDVI and albedo using field data collected at a tundra site in NE Siberia. Field data showed that NDVI increased and albedo decreased with increasing deciduous shrub cover. We then selected four Arctic tundra study areas and compiled annual growing season maximum NDVI and minimum albedo maps from MODIS satellite data (2000-10) and related these satellite products to tundra vegetation types (shrub, graminoid, barren and wetland tundra) and regional summer temperature. We observed that maximum NDVI was greatest in shrub tundra and that inter-annual variation was negatively related to summer minimum albedo but showed no consistent relationship with summer temperature. Shrub tundra showed higher albedo than wetland and barren tundra in all four study areas. These results suggest that a northwards shift of shrub tundra might not lead to a decrease in summer minimum albedo during the snow-free season when replacing wetland tundra. A fully integrative study is however needed to link results from satellite data with in situ observations across the Arctic to test the effect of increasing shrub cover on summer albedo in different tundra vegetation types.

The response of Arctic vegetation to the summer climate: relation between shrub cover, NDVI, surface albedo and temperature

International Nuclear Information System (INIS)

Blok, Daan; Heijmans, Monique M P D; Berendse, Frank; Schaepman-Strub, Gabriela; Bartholomeus, Harm; Maximov, Trofim C

2011-01-01

Recently observed Arctic greening trends from normalized difference vegetation index (NDVI) data suggest that shrub growth is increasing in response to increasing summer temperature. An increase in shrub cover is expected to decrease summer albedo and thus positively feed back to climate warming. However, it is unknown how albedo and NDVI are affected by shrub cover and inter-annual variations in the summer climate. Here, we examine the relationship between deciduous shrub fractional cover, NDVI and albedo using field data collected at a tundra site in NE Siberia. Field data showed that NDVI increased and albedo decreased with increasing deciduous shrub cover. We then selected four Arctic tundra study areas and compiled annual growing season maximum NDVI and minimum albedo maps from MODIS satellite data (2000-10) and related these satellite products to tundra vegetation types (shrub, graminoid, barren and wetland tundra) and regional summer temperature. We observed that maximum NDVI was greatest in shrub tundra and that inter-annual variation was negatively related to summer minimum albedo but showed no consistent relationship with summer temperature. Shrub tundra showed higher albedo than wetland and barren tundra in all four study areas. These results suggest that a northwards shift of shrub tundra might not lead to a decrease in summer minimum albedo during the snow-free season when replacing wetland tundra. A fully integrative study is however needed to link results from satellite data with in situ observations across the Arctic to test the effect of increasing shrub cover on summer albedo in different tundra vegetation types.

Using MODIS NDVI products for vegetation state monitoring on the oil production territory in Western Siberia

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Kovalev Anton

2016-01-01

Full Text Available Article describes the results of using remote sensing data for vegetation state monitoring on the oil field territories in Western Siberia. We used MODIS data product providing the normalized difference vegetation index (NDVI values. Average NDVI values of each studied area were calculated for the period from 2010 to 2015 with one year interval for June, July and August. Analysis was carried out via an open tool of geographic information system QGIS used for spatial analysis and calculation of statistical parameters within chosen polygons. Results are presented in graphs showing the variation of NDVI for each study area and explaining the changes in trend lines for each field. It is shown that the majority of graphs are similar in shape which is caused by similar weather conditions. To confirm these results, we have conducted data analysis including temperature conditions and information about the accidents for each area. Abnormal changes in NDVI values revealed an emergency situation on the Priobskoe oil field caused by the flood in 2015. To sum up, the research results show that vegetation of studied areas is in a sufficiently stable state.

Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China).

Science.gov (United States)

Liu, Xiaojun; Ferguson, Richard B; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

2017-03-24

The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI = ( 1 + e - 15.2829 × ( R A G D D i - 0.1944 ) ) - 1 - ( 1 + e - 11.6517 × ( R A G D D i - 1.0267 ) ) - 1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status.

Quantification of Impact of Orbital Drift on Inter-Annual Trends in AVHRR NDVI Data

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Jyoteshwar R. Nagol

2014-07-01

Full Text Available The Normalized Difference Vegetation Index (NDVI time-series data derived from Advanced Very High Resolution Radiometer (AVHRR have been extensively used for studying inter-annual dynamics of global and regional vegetation. However, there can be significant uncertainties in the data due to incomplete atmospheric correction and orbital drift of the satellites through their active life. Access to location specific quantification of uncertainty is crucial for appropriate evaluation of the trends and anomalies. This paper provides per pixel quantification of orbital drift related spurious trends in Long Term Data Record (LTDR AVHRR NDVI data product. The magnitude and direction of the spurious trends was estimated by direct comparison with data from MODerate resolution Imaging Spectrometer (MODIS Aqua instrument, which has stable inter-annual sun-sensor geometry. The maps show presence of both positive as well as negative spurious trends in the data. After application of the BRDF correction, an overall decrease in positive trends and an increase in number of pixels with negative spurious trends were observed. The mean global spurious inter-annual NDVI trend before and after BRDF correction was 0.0016 and −0.0017 respectively. The research presented in this paper gives valuable insight into the magnitude of orbital drift related trends in the AVHRR NDVI data as well as the degree to which it is being rectified by the MODIS BRDF correction algorithm used by the LTDR processing stream.

Relationship among land surface temperature and LUCC, NDVI in typical karst area.

Science.gov (United States)

Deng, Yuanhong; Wang, Shijie; Bai, Xiaoyong; Tian, Yichao; Wu, Luhua; Xiao, Jianyong; Chen, Fei; Qian, Qinghuan

2018-01-12

Land surface temperature (LST) can reflect the land surface water-heat exchange process comprehensively, which is considerably significant to the study of environmental change. However, research about LST in karst mountain areas with complex topography is scarce. Therefore, we retrieved the LST in a karst mountain area from Landsat 8 data and explored its relationships with LUCC and NDVI. The results showed that LST of the study area was noticeably affected by altitude and underlying surface type. In summer, abnormal high-temperature zones were observed in the study area, perhaps due to karst rocky desertification. LSTs among different land use types significantly differed with the highest in construction land and the lowest in woodland. The spatial distributions of NDVI and LST exhibited opposite patterns. Under the spatial combination of different land use types, the LST-NDVI feature space showed an obtuse-angled triangle shape and showed a negative linear correlation after removing water body data. In summary, the LST can be retrieved well by the atmospheric correction model from Landsat 8 data. Moreover, the LST of the karst mountain area is controlled by altitude, underlying surface type and aspect. This study provides a reference for land use planning, ecological environment restoration in karst areas.

Analysis of postfire vegetation dynamics of Mediterranean shrub species based on terrestrial and NDVI data.

Science.gov (United States)

Hernández-Clemente, Rocío; Cerrillo, R M Navarro; Hernández-Bermejo, J E; Royo, S Escuin; Kasimis, N A

2009-05-01

The present study offers an analysis of regeneration patterns and diversity dynamics after a wildfire, which occurred in 1993 and affected about 7000 ha in southern Spain. The aim of the work was to analyze the rule in the succession of shrub species after fire, relating it to the changes registered in the Normalized Difference Vegetation Index (NDVI). Fractional vegetation cover was recorded from permanent plots in 2000 and 2005. NDVI data related to each time were obtained from Landsat images. Both data sets, from fieldwork and remote sensing, were analyzed through statistical and quantitative analyses and then correlated. Results have permitted the description of the change in plant cover and species composition on a global and plot scale. It can be affirmed that, from the seventh to the twelfth year after the fire, the floristic composition within the burned area remained unchanged at a global level. However, on a smaller scale (plot level), the major shrub species, Ulex parviflorus, Rosmarinus officinalis, and Cistus clusii, underwent significant changes. The regeneration dynamics established by these species conditioned plant species composition and, consequently, diversity indexes such as Shannon (H) and Simpson (D). The changes recorded in the NDVI values corresponding to the surveyed plots were highly correlated with those found in the regrowth of the main species. Areas dominated by U. parviflorus in a senile phase were related to a decrease in NDVI values and an increase in the number of species. This result describes the successional dynamics; the dryness of the main colonizer shrub species is allowing the regrowth and re-establishment of other species. Within the study area, NDVI shows sensitivity to postfire plant cover changes and indirectly expresses the diversity dynamics.

Analysis of Postfire Vegetation Dynamics of Mediterranean Shrub Species Based on Terrestrial and NDVI Data

Science.gov (United States)

Hernández-Clemente, Rocío; Navarro Cerrillo, R. M.; Hernández-Bermejo, J. E.; Escuin Royo, S.; Kasimis, N. A.

2009-05-01

The present study offers an analysis of regeneration patterns and diversity dynamics after a wildfire, which occurred in 1993 and affected about 7000 ha in southern Spain. The aim of the work was to analyze the rule in the succession of shrub species after fire, relating it to the changes registered in the Normalized Difference Vegetation Index (NDVI). Fractional vegetation cover was recorded from permanent plots in 2000 and 2005. NDVI data related to each time were obtained from Landsat images. Both data sets, from fieldwork and remote sensing, were analyzed through statistical and quantitative analyses and then correlated. Results have permitted the description of the change in plant cover and species composition on a global and plot scale. It can be affirmed that, from the seventh to the twelfth year after the fire, the floristic composition within the burned area remained unchanged at a global level. However, on a smaller scale (plot level), the major shrub species, Ulex parviflorus, Rosmarinus officinalis, and Cistus clusii, underwent significant changes. The regeneration dynamics established by these species conditioned plant species composition and, consequently, diversity indexes such as Shannon (H) and Simpson (D). The changes recorded in the NDVI values corresponding to the surveyed plots were highly correlated with those found in the regrowth of the main species. Areas dominated by U. parviflorus in a senile phase were related to a decrease in NDVI values and an increase in the number of species. This result describes the successional dynamics; the dryness of the main colonizer shrub species is allowing the regrowth and re-establishment of other species. Within the study area, NDVI shows sensitivity to postfire plant cover changes and indirectly expresses the diversity dynamics.

Spatiotemporal dynamics of grassland aboveground biomass on the Qinghai-Tibet Plateau based on validated MODIS NDVI.

Science.gov (United States)

Liu, Shiliang; Cheng, Fangyan; Dong, Shikui; Zhao, Haidi; Hou, Xiaoyun; Wu, Xue

2017-06-23

Spatiotemporal dynamics of aboveground biomass (AGB) is a fundamental problem for grassland environmental management on the Qinghai-Tibet Plateau (QTP). Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data can feasibly be used to estimate AGB at large scales, and their precise validation is necessary to utilize them effectively. In our study, the clip-harvest method was used at 64 plots in QTP grasslands to obtain actual AGB values, and a handheld hyperspectral spectrometer was used to calculate field-measured NDVI to validate MODIS NDVI. Based on the models between NDVI and AGB, AGB dynamics trends during 2000-2012 were analyzed. The results showed that the AGB in QTP grasslands increased during the study period, with 70% of the grasslands undergoing increases mainly in the Qinghai Province. Also, the meadow showed a larger increasing trend than steppe. Future AGB dynamic trends were also investigated using a combined analysis of the slope values and the Hurst exponent. The results showed high sustainability of AGB dynamics trends after the study period. Predictions indicate 60% of the steppe and meadow grasslands would continue to increase in AGB, while 25% of the grasslands would remain in degradation, with most of them distributing in Tibet.

NDVI-Based analysis on the influence of human activities on vegetation variation on Hainan Island

Science.gov (United States)

Luo, Hongxia; Dai, Shengpei; Xie, Zhenghui; Fang, Jihua

2018-02-01

Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index (NDVI) dataset, we analyzed the predicted NDVI values variation and the influence of human activities on vegetation on Hainan Island during 2001-2015. We investigated the roles of human activities in vegetation variation, particularly from 2002 when implemented the Grain-for-Greenprogram on Hainan Island. The trend analysis, linear regression model and residual analysis were used to analyze the data. The results of the study showed that (1) The predicted vegetation on Hainan Island showed an general upward trend with a linear growth rate of 0.0025/10y (phuman activities. (3) In general, human activities had played a positive role in the vegetation increase on Hainan Island, and the residual NDVI trend of this region showed positive outcomes for vegetation variation after implementing ecological engineering projects. However, it indicated a growing risk of vegetation degradation in the coastal region of Hainan Island as a result of rapid urbanization, land reclamation.

Using NDVI to estimate carbon fluxes from small rotationally grazed pastures

Science.gov (United States)

Satellite-based Normalized Difference Vegetation Index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northea...

Multifractal Downscaling of Rainfall Using Normalized Difference Vegetation Index (NDVI) in the Andes Plateau.

Science.gov (United States)

Duffaut Espinosa, L A; Posadas, A N; Carbajal, M; Quiroz, R

2017-01-01

In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

Science.gov (United States)

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

VIABILIDADE ECONÔMICA DA PRODUÇÃO DE BIOGÁS EM GRANJAS DE SUÍNOS, POR MEIO DA ANÁLISE DE SÉRIES TEMPORAIS

OpenAIRE

Felipe Luis Rockenbach

2014-01-01

O presente estudo visa reunir, analisar e interpretar o potencial e a viabilidade econômica do sequestro de gás carbônico e/ou a geração de energia renovável proveniente do tratamento de dejetos suínos, por meio da análise de séries temporais, com utilização dos modelos de previsão Box e Jenkins (1970). Como os sistemas de produção de suínos geram grande quantidade de dejetos altamente poluentes e impactantes no meio ambiente, principalmente os gases de efeito estufa, estes, ao serem tratados...

Using NDVI-based measures to derive geographic information on drought-prone areas for developing countries

Science.gov (United States)

Gurusamy, Kumari Vadivel

Remotely sensed NDVI imagery was used to detect drought in developing countries in three continents. The study shows that in spite of the various limitations the NDVI data provide valuable information on drought probabilities due to their significant correlation with rainfall time series (0.4 - 0.7). NDVI data are also accessible at different resolutions (1 degree, 8 km and 1 km) at a global scale in spatiotemporally continuous form for up to 19 years enabling this study to contribute a uniform and simultaneous analysis of drought in poor developing countries. The current study is also done with due consideration to the ecosystem underlying the pixel. Special consideration for the ecosystem is achieved by holding the temporal and spatial identity intact throughout the analysis. The study uses NDVI data from 19 years for a vigorous and quick estimate, using a new method called the 'percent carrying capacity index' method which is shown to perform better than the 'vegetation condition index' method. For a few selected geographic areas, the computed image analysis results were verified against actual occurrence of drought. The image analysis results were found to be consistent with reality in those cases, validating the analysis results for areas for which drought observations have not been recorded. The final continental scale drought maps show the frequently drought-prone areas derived from uniform spatial (8km * 8km) and temporal (decadal) resolution data across three continents.

Applying Markov Chains for NDVI Time Series Forecasting of Latvian Regions

Directory of Open Access Journals (Sweden)

Stepchenko Arthur

2015-12-01

Full Text Available Time series of earth observation based estimates of vegetation inform about variations in vegetation at the scale of Latvia. A vegetation index is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation. NDVI index is an important variable for vegetation forecasting and management of various problems, such as climate change monitoring, energy usage monitoring, managing the consumption of natural resources, agricultural productivity monitoring, drought monitoring and forest fire detection. In this paper, we make a one-step-ahead prediction of 7-daily time series of NDVI index using Markov chains. The choice of a Markov chain is due to the fact that a Markov chain is a sequence of random variables where each variable is located in some state. And a Markov chain contains probabilities of moving from one state to other.

Using MODIS NDVI products for vegetation state monitoring on the oil production territory in Western Siberia

OpenAIRE

Kovalev, Anton; Tokareva, Olga Sergeevna

2016-01-01

Article describes the results of using remote sensing data for vegetation state monitoring on the oil field territories in Western Siberia. We used MODIS data product providing the normalized difference vegetation index (NDVI) values. Average NDVI values of each studied area were calculated for the period from 2010 to 2015 with one year interval for June, July and August. Analysis was carried out via an open tool of geographic information system QGIS used for spatial analysis and calculation ...

TESTES ESTATISTICOS DE ESTACIONARIEDADE NO VALOR ESPERADO PARA SÉRIES TEMPORAIS COM DEPENDÊNCIA TEMPORAL SENSÍVEIS A MUDANÇAS GRADUAIS OU ABRUPTAS

Directory of Open Access Journals (Sweden)

Jorge Machado Damázio

2014-08-01

Full Text Available 10.12957/cadest.2011.15729O artigo apresenta o desenvolvimento de testes estatísticos de verificação de estacionariedade no valor esperado para séries temporais com estrutura de dependência temporal com vistas a distinguir flutuações naturais de mudanças de valor esperado suaves ou abruptas. Os testes são aplicados à série de 75 anos de afluências anuais ao aproveitamento hidroelétrico de São Luiz do Tapajós fornecida pelos estudos hidrológicos dos Estudos de Inventário da Bacia dos Rios Tapajós e Jimanxim, localizadas na região Amazônica

NDVI and meteorological data as indicators of the Pampa biome natural grasslands growth

Directory of Open Access Journals (Sweden)

Denise Cybis Fontana

2018-04-01

Full Text Available ABSTRACT The present study aimed to characterize the dynamics of NDVI and meteorological conditions, relating both to the annual dynamics of biomass accumulation in natural pastures of the Pampa biome as a way of subsidizing growth modeling. Forage accumulation rate data from a long-term experiment, NDVI data from the MODIS images, and meteorological data measured at the surface were used. We verify that the agrometeorological element associated to the accumulation of forage in the natural grasslands is different according to the season, which is typical of the subtropical climate. Winter is the critical season for livestock production due to the lower forage accumulation rate and lower values of NDVI, conditioned by the decrease of solar radiation and air temperature. In the summer, the limiting factor to forage accumulation is the hydric condition. It was also verified that the variability in the growth of grasslands can be associated with the ENSO phenomenon, being the El Niño favorable and the La Niña unfavorable, especially in the spring-summer period. Considering the verified associations, spectral indices combined with agrometeorological elements are recommended to the adjustment of models of forage accumulation in the Pampa biome natural grasslands.

Repercussões temporais da ligadura do ducto biliar principal em ratos Wistar

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Maia Eugenio Lincoln Campos

2003-01-01

Full Text Available OBJETIVO: Objetivou-se investigar os efeitos temporais da ligadura do ducto biliar principal, em ratos Wistar. MÉTODOS: Utilizaram-se 48 ratos machos distribuídos em 2 grupos e redistribuídos em 4 subgrupos (n=06, identificados pelo tempo estipulado para a coleta das amostras (12, 24, 48 e 168 horas. Após laparotomia, os animais foram submetidos à dissecção e passagem de dois fios circundando o ducto biliar principal, sem ligadura (Grupo 1 e com ligadura (Grupo 2. RESULTADOS: As concentrações das bilirrubinas séricas (total, direte e indireta quando comparadas ao repectivo grupo controle, aumentaram (p<0,05 nos animais do grupo 2, nos tempos 24, 48 e 168 horas. As concentrações de proteína C reativa e fosfatase alcalina aumentaram (p<0,05 no grupo 2 no tempo 24 horas e nos tempos 24 e 48 horas, respectivamente. Concentrações de albumina e gamaglutamil transferase, não apresentaram diferenças significantes nos dois grupos. Foram observadas, no exame histopatológico, hiperplasia ductal, pericolangite e colangite no grupo 2 e pericolangite no grupo 1. CONCLUSÕES: A ligadura do ducto biliar principal induz aumento das concentrações séricas de bilirrubinas, proteína C reativa e fosfatase alcalina. Hiperplasia ductal, pericolangite e colangite são as principais alterações histológicas encontradas nos fígados dos ratos submetidos à ligadura do ducto biliar principal.

Mapping and Evaluation of NDVI Trends from Synthetic Time Series Obtained by Blending Landsat and MODIS Data around a Coalfield on the Loess Plateau

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Kun Wang

2013-09-01

Full Text Available The increasingly intensive and extensive coal mining activities on the Loess Plateau pose a threat to the fragile local ecosystems. Quantifying the effects of coal mining activities on environmental conditions is of great interest for restoring and managing the local ecosystems and resources. This paper generates dense NDVI (Normalized Difference Vegetation Index time series between 2000 and 2011 at a spatial resolution of 30 m by blending Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer data using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM and further evaluates its capability for mapping vegetation trends around a typical coalfield on the Loss Plateau. Synthetic NDVI images were generated using (1 STARFM-generated NIR (near infrared and red band reflectance data (scheme 1 and (2 Landsat and MODIS NDVI images directly as inputs for STARFM (scheme 2. By comparing the synthetic NDVI images with the corresponding Landsat NDVI, we found that scheme 2 consistently generated better results (0.70 < R2 < 0.76 than scheme 1 (0.56 < R2 < 0.70 in this study area. Trend analysis was then performed with the synthetic dense NDVI time series and the annual maximum NDVI (NDVImax time series. The accuracy of these trends was evaluated by comparing to those from the corresponding MODIS time series, and it was concluded that both the trends from synthetic/MODIS NDVI dense time series and synthetic/MODIS NDVImax time series (2000–2011 were highly consistent. Compared to trends from MODIS time series, trends from synthetic time series are better able to capture fine scale vegetation changes. STARFM-generated synthetic NDVI time series could be used to quantify the effects of mining activities on vegetation, but the test areas should be selected with caution, as the trends derived from synthetic and MODIS time series may be significantly different in some areas.

Increased wetness confounds Landsat-derived NDVI trends in the central Alaska North Slope region, 1985-2011

Science.gov (United States)

Raynolds, Martha K.; Walker, Donald A.

2016-08-01

Satellite data from the circumpolar Arctic have shown increases in vegetation indices correlated to warming air temperatures (e.g. Bhatt et al 2013 Remote Sensing 5 4229-54). However, more information is needed at finer scales to relate the satellite trends to vegetation changes on the ground. We examined changes using Landsat TM and ETM+ data between 1985 and 2011 in the central Alaska North Slope region, where the vegetation and landscapes are relatively well-known and mapped. We calculated trends in the normalized difference vegetation index (NDVI) and tasseled-cap transformation indices, and related them to high-resolution aerial photographs, ground studies, and vegetation maps. Significant, mostly negative, changes in NDVI occurred in 7.3% of the area, with greater change in aquatic and barren types. Large reflectance changes due to erosion, deposition and lake drainage were evident. Oil industry-related changes such as construction of artificial islands, roads, and gravel pads were also easily identified. Regional trends showed decreases in NDVI for most vegetation types, but increases in tasseled-cap greenness (56% of study area, greatest for vegetation types with high shrub cover) and tasseled-cap wetness (11% of area), consistent with documented degradation of polygon ice wedges, indicating that increasing cover of water may be masking increases in vegetation when summarized using the water-sensitive NDVI.

Trend analysis of GIMMS and MODIS NDVI time series for establishing a land degradation neutrality national baseline

Science.gov (United States)

Gichenje, Helene; Godinho, Sergio

2017-04-01

Land degradation is a key global environment and development problem that is recognized as a priority by the international development community. The Sustainable Development Goals (SDGs) were adopted by the global community in 2015, and include a goal related to land degradation and the accompanying target to achieve a land degradation-neutral (LDN) world by 2030. The LDN concept encompasses two joint actions of reducing the rate of degradation and increasing the rate of restoration. Using Kenya as the study area, this study aims to develop and test a spatially explicit methodology for assessing and monitoring the operationalization of a land degradation neutrality scheme at the national level. Time series analysis is applied to Normalized Difference Vegetation Index (NDVI) satellite data records, based on the hypothesis that the resulting NDVI residual trend would enable successful detection of changes in vegetation photosynthetic capacity and thus serve as a proxy for land degradation and regeneration processes. Two NDVI data sets are used to identify the spatial and temporal distribution of degraded and regenerated areas: the long term coarse resolution (8km, 1982-2015) third generation Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g data record; and the shorter-term finer resolution (250m, 2001-2015) Moderate Resolution Imaging Spectroradiometer (MODIS) derived NDVI data record. Climate data (rainfall, temperature and soil moisture) are used to separate areas of human-induced vegetation productivity decline from those driven by climate dynamics. Further, weekly vegetation health (VH) indexes (4km, 1982-2015) developed by National Oceanic and Atmospheric Administration (NOAA), are assessed as indicators for early detection and monitoring of land degradation by estimating vegetation stress (moisture, thermal and combined conditions).

Short-term drought assessment in Pakistan and adjoining areas by remote sensing MODIS-NDVI data: A potential consequence of climate change

International Nuclear Information System (INIS)

Khan, I.A.; Kiran, N.; Arsalan, M.H.

2016-01-01

Currently normalized difference vegetation index (NDVI) is extensively used for appraise vegetation composition, structure, stratification and distribution. Spatial and temporal rainfall distribution and its effect on NDVI can be helpful for drought examining. This study has been done to improved comprehend this association. The response of vegetation growth to current climate change in Pakistan and adjoining south Asian countries (22-42 degree N, 60-80 degree E) were investigated by analyzing the time series of the NDVI maps. We also obtained and analyzed time series of different variable i.e. rainfall, soil moisture, evapotranspiration and soil temperature model data, through NASA Geospatial Interactive Online Visualization and analysis Infrastructure (Giovanni) system, during Jan- Dec, 2014 for every three month interval. The NOAA Climate Prediction Center from International Research institute (IRI) for climate and society platform was also used for rainfall anomaly data. We found that NDVI values varies and depend on land cover types and its spatial location and dependant on rainfall. We found a strong positive relationship among NDVI, rainfall and soil moisture. Seasonal variations of rainfall are having also affects on evapotranspiration, soil temperature, and soil moisture conditions. (author)

A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series

OpenAIRE

David Helman; Itamar M. Lensky; Naama Tessler; Yagil Osem

2015-01-01

We present an efficient method for monitoring woody (i.e., evergreen) and herbaceous (i.e., ephemeral) vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI) time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI ...

High-Resolution NDVI from Planet's Constellation of Earth Observing Nano-Satellites: A New Data Source for Precision Agriculture

KAUST Repository

Houborg, Rasmus; McCabe, Matthew

2016-01-01

Planet Labs ("Planet") operate the largest fleet of active nano-satellites in orbit, offering an unprecedented monitoring capacity of daily and global RGB image capture at 3-5 m resolution. However, limitations in spectral resolution and lack of accurate radiometric sensor calibration impact the utility of this rich information source. In this study, Planet's RGB imagery was translated into a Normalized Difference Vegetation Index (NDVI): a common metric for vegetation growth and condition. Our framework employs a data mining approach to build a set of rule-based regression models that relate RGB data to atmospherically corrected Landsat-8 NDVI. The approach was evaluated over a desert agricultural landscape in Saudi Arabia where the use of near-coincident (within five days) Planet and Landsat-8 acquisitions in the training of the regression models resulted in NDVI predictabilities with an r2 of approximately 0.97 and a Mean Absolute Deviation (MAD) on the order of 0.014 (~9%). The MAD increased to 0.021 (~14%) when the Landsat NDVI training image was further away (i.e., 11-16 days) from the corrected Planet image. In these cases, the use of MODIS observations to inform on the change in NDVI occurring between overpasses was shown to significantly improve prediction accuracies. MAD levels ranged from 0.002 to 0.011 (3.9% to 9.1%) for the best performing 80% of the data. The technique is generic and extendable to any region of interest, increasing the utility of Planet's dense time-series of RGB imagery.

High-Resolution NDVI from Planet's Constellation of Earth Observing Nano-Satellites: A New Data Source for Precision Agriculture

KAUST Repository

Houborg, Rasmus

2016-09-19

Planet Labs ("Planet") operate the largest fleet of active nano-satellites in orbit, offering an unprecedented monitoring capacity of daily and global RGB image capture at 3-5 m resolution. However, limitations in spectral resolution and lack of accurate radiometric sensor calibration impact the utility of this rich information source. In this study, Planet\\'s RGB imagery was translated into a Normalized Difference Vegetation Index (NDVI): a common metric for vegetation growth and condition. Our framework employs a data mining approach to build a set of rule-based regression models that relate RGB data to atmospherically corrected Landsat-8 NDVI. The approach was evaluated over a desert agricultural landscape in Saudi Arabia where the use of near-coincident (within five days) Planet and Landsat-8 acquisitions in the training of the regression models resulted in NDVI predictabilities with an r2 of approximately 0.97 and a Mean Absolute Deviation (MAD) on the order of 0.014 (~9%). The MAD increased to 0.021 (~14%) when the Landsat NDVI training image was further away (i.e., 11-16 days) from the corrected Planet image. In these cases, the use of MODIS observations to inform on the change in NDVI occurring between overpasses was shown to significantly improve prediction accuracies. MAD levels ranged from 0.002 to 0.011 (3.9% to 9.1%) for the best performing 80% of the data. The technique is generic and extendable to any region of interest, increasing the utility of Planet\\'s dense time-series of RGB imagery.

Cotton NDVI response to applied N at different soil EC levels

Science.gov (United States)

Many fields in the southeastern Coastal Plain are highly variable in soil physical properties and are irregular in shape. These two conditions may make it difficult to determine the ‘best’ area in the field to place nitrogen (N) -rich strips for normalized difference vegetative index (NDVI) -based s...

NOAA Climate Data Record (CDR) of Normalized Difference Vegetation Index (NDVI), Version 4

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains gridded daily Normalized Difference Vegetation Index (NDVI) derived from the NOAA Climate Data Record (CDR) of Advanced Very High Resolution...

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring.

Science.gov (United States)

Skakun, Sergii; Justice, Christopher O; Vermote, Eric; Roger, Jean-Claude

2018-01-01

The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration's (NASA) Terra and Aqua remote sensing satellites. The VIIRS will eventually replace MODIS for both land science and applications and add to the coarse-resolution, long term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provide critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties related the transitioning from using MODIS to VIIRS-based NDVI's. In particular, we compare NDVI's derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily Climate Modelling Grid (CMG) images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red - NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, NDVI uncertainties were 0.014, 0.029 and 0.056 respectively for the 500 m product and 0.013, 0.016 and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

Science.gov (United States)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

NDVI indicated long-term interannual changes in vegetation activities and their responses to climatic and anthropogenic factors in the Three Gorges Reservoir Region, China.

Science.gov (United States)

Wen, Zhaofei; Wu, Shengjun; Chen, Jilong; Lü, Mingquan

2017-01-01

Natural and social environmental changes in the China's Three Gorges Reservoir Region (TGRR) have received worldwide attention. Identifying interannual changes in vegetation activities in the TGRR is an important task for assessing the impact these changes have on the local ecosystem. We used long-term (1982-2011) satellite-derived Normalized Difference Vegetation Index (NDVI) datasets and climatic and anthropogenic factors to analyze the spatiotemporal patterns of vegetation activities in the TGRR, as well as their links to changes in temperature (TEM), precipitation (PRE), downward radiation (RAD), and anthropogenic activities. At the whole TGRR regional scale, a statistically significant overall uptrend in NDVI variations was observed in 1982-2011. More specifically, there were two distinct periods with different trends split by a breakpoint in 1991: NDVI first sharply increased prior to 1991, and then showed a relatively weak rate of increase after 1991. At the pixel scale, most parts of the TGRR experienced increasing NDVI before the 1990s but different trend change types after the 1990s: trends were positive in forests in the northeastern parts, but negative in farmland in southwest parts of the TGRR. The TEM warming trend was the main climate-related driver of uptrending NDVI variations pre-1990s, and decreasing PRE was the main climate factor (42%) influencing the mid-western farmland areas' NDVI variations post-1990s. We also found that anthropogenic factors such as population density, man-made ecological restoration, and urbanization have notable impacts on the TGRR's NDVI variations. For example, large overall trend slopes in NDVI were more likely to appear in TGRR regions with large fractions of ecological restoration within the last two decades. The findings of this study may help to build a better understanding of the mechanics of NDVI variations in the periods before and during TGDP construction for ongoing ecosystem monitoring and assessment in the

A Simple Method for Retrieving Understory NDVI in Sparse Needleleaf Forests in Alaska Using MODIS BRDF Data

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Wei Yang

2014-12-01

Full Text Available Global products of leaf area index (LAI usually show large uncertainties in sparsely vegetated areas because the understory contribution is not negligible in reflectance modeling for the case of low to intermediate canopy cover. Therefore, many efforts have been made to include understory properties in LAI estimation algorithms. Compared with the conventional data bank method, estimation of forest understory properties from satellite data is superior in studies at a global or continental scale over long periods. However, implementation of the current remote sensing method based on multi-angular observations is complicated. As an alternative, a simple method to retrieve understory NDVI (NDVIu for sparse boreal forests was proposed in this study. The method is based on the fact that the bidirectional variation in NDVIu is smaller than that in canopy-level NDVI. To retrieve NDVIu for a certain pixel, linear extrapolation was applied using pixels within a 5 × 5 target-pixel-centered window. The NDVI values were reconstructed from the MODIS BRDF data corresponding to eight different solar-view angles. NDVIu was estimated as the average of the NDVI values corresponding to the position in which the stand NDVI had the smallest angular variation. Validation by a noise-free simulation data set yielded high agreement between estimated and true NDVIu, with R2 and RMSE of 0.99 and 0.03, respectively. Using the MODIS BRDF data, we achieved an estimate of NDVIu close to the in situ measured value (0.61 vs. 0.66 for estimate and measurement, respectively and reasonable seasonal patterns of NDVIu in 2010 to 2013. The results imply a potential application of the retrieved NDVIu to improve the estimation of overstory LAI for sparse boreal forests and ultimately to benefit studies on carbon cycle modeling over high-latitude areas.

Comparison of Gross Primary Productivity Derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia

Directory of Open Access Journals (Sweden)

Junbang Wang

2014-03-01

Full Text Available Gross primary production (GPP plays an important role in the net ecosystem exchange of CO2 between the atmosphere and terrestrial ecosystems. It is particularly important to monitor GPP in Southeast Asia because of increasing rates of tropical forest degradation and deforestation in the region in recent decades. The newly available, improved, third generation Normalized Difference Vegetation Index (NDVI3g from the Global Inventory Modelling and Mapping Studies (GIMMS group provides a long temporal dataset, from July 1981 to December 2011, for terrestrial carbon cycle and climate response research. However, GIMMS NDVI3g-based GPP estimates are not yet available. We applied the GLOPEM-CEVSA model, which integrates an ecosystem process model and a production efficiency model, to estimate GPP in Southeast Asia based on three independent results of the fraction of photosynthetically active radiation absorbed by vegetation (FPAR from GIMMS NDVI3g (GPPNDVI3g, GIMMS NDVI1g (GPPNDVI1g, and the Moderate Resolution Imaging Spectroradiometer (MODIS MOD15A2 FPAR product (GPPMOD15. The GPP results were validated using ground data from eddy flux towers located in different forest biomes, and comparisons were made among the three GPPs as well as the MOD17A2 GPP products (GPPMOD17. Based on validation with flux tower derived GPP estimates the results show that GPPNDVI3g is more accurate than GPPNDVI1g and is comparable in accuracy with GPPMOD15. In addition, GPPNDVI3g and GPPMOD15 have good spatial-temporal consistency. Our results indicate that GIMMS NDVI3g is an effective dataset for regional GPP simulation in Southeast Asia, capable of accurately tracking the variation and trends in long-term terrestrial ecosystem GPP dynamics.

Pattern of NDVI-based vegetation greening along an altitudinal gradient in the eastern Himalayas and its response to global warming.

Science.gov (United States)

Li, Haidong; Jiang, Jiang; Chen, Bin; Li, Yingkui; Xu, Yuyue; Shen, Weishou

2016-03-01

The eastern Himalayas, especially the Yarlung Zangbo Grand Canyon Nature Reserve (YNR), is a global hotspot of biodiversity because of a wide variety of climatic conditions and elevations ranging from 500 to > 7000 m above sea level (a.s.l.). The mountain ecosystems at different elevations are vulnerable to climate change; however, there has been little research into the patterns of vegetation greening and their response to global warming. The objective of this paper is to examine the pattern of vegetation greening in different altitudinal zones in the YNR and its relationship with vegetation types and climatic factors. Specifically, the inter-annual change of the normalized difference vegetation index (NDVI) and its variation along altitudinal gradient between 1999 and 2013 was investigated using SPOT-VGT NDVI data and ASTER global digital elevation model (GDEM) data. We found that annual NDVI increased by 17.58% in the YNR from 1999 to 2013, especially in regions dominated by broad-leaved and coniferous forests at lower elevations. The vegetation greening rate decreased significantly as elevation increased, with a threshold elevation of approximately 3000 m. Rising temperature played a dominant role in driving the increase in NDVI, while precipitation has no statistical relationship with changes in NDVI in this region. This study provides useful information to develop an integrated management and conservation plan for climate change adaptation and promote biodiversity conservation in the YNR.

Analysis of monotonic greening and browning trends from global NDVI time-series

NARCIS (Netherlands)

Jong, de R.; Bruin, de S.; Wit, de A.J.W.; Schaepman, M.E.; Dent, D.L.

2011-01-01

Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt

[Correlative analysis of the diversity patterns of regional surface water, NDVI and thermal environment].

Science.gov (United States)

Duan, Jin-Long; Zhang, Xue-Lei

2012-10-01

Taking Zhengzhou City, the capital of Henan Province in Central China, as the study area, and by using the theories and methodologies of diversity, a discreteness evaluation on the regional surface water, normalized difference vegetation index (NDVI), and land surface temperature (LST) distribution was conducted in a 2 km x 2 km grid scale. Both the NDVI and the LST were divided into 4 levels, their spatial distribution diversity indices were calculated, and their connections were explored. The results showed that it was of operability and practical significance to use the theories and methodologies of diversity in the discreteness evaluation of the spatial distribution of regional thermal environment. There was a higher overlap of location between the distributions of surface water and the lowest temperature region, and the high vegetation coverage was often accompanied by low land surface temperature. In 1988-2009, the discreteness of the surface water distribution in the City had an obvious decreasing trend. The discreteness of the surface water distribution had a close correlation with the discreteness of the temperature region distribution, while the discreteness of the NDVI classification distribution had a more complicated correlation with the discreteness of the temperature region distribution. Therefore, more environmental factors were needed to be included for a better evaluation.

Responses of the reflectance indices PRI and NDVI to experimental warming and drought in European shrublands along a north–south climatic gradient

DEFF Research Database (Denmark)

Mänd, Pille; Hallik, Lea; Peñuelas, Josep

2010-01-01

NDVI680 [780 nm; 680 nm] using red spectral region, and NDVI570 [780 nm; 570 nm] using the same green spectral region as PRI. All three reflectance indices were significantly related to green LAIe and were able to detect changes in shrubland vegetation among treatments. In general warming treatment...... increased PRI and drought treatment reduced NDVI values. The significant treatment effect on photochemical efficiency of plants detected with PRI could not be detected by fluorescence measurements. However, we found canopy level measured PRI to be very sensitive to soil reflectance properties especially...

[Winter wheat area estimation with MODIS-NDVI time series based on parcel].

Science.gov (United States)

Li, Le; Zhang, Jin-shui; Zhu, Wen-quan; Hu, Tan-gao; Hou, Dong

2011-05-01

Several attributes of MODIS (moderate resolution imaging spectrometer) data, especially the short temporal intervals and the global coverage, provide an extremely efficient way to map cropland and monitor its seasonal change. However, the reliability of their measurement results is challenged because of the limited spatial resolution. The parcel data has clear geo-location and obvious boundary information of cropland. Also, the spectral differences and the complexity of mixed pixels are weak in parcels. All of these make that area estimation based on parcels presents more advantage than on pixels. In the present study, winter wheat area estimation based on MODIS-NDVI time series has been performed with the support of cultivated land parcel in Tongzhou, Beijing. In order to extract the regional winter wheat acreage, multiple regression methods were used to simulate the stable regression relationship between MODIS-NDVI time series data and TM samples in parcels. Through this way, the consistency of the extraction results from MODIS and TM can stably reach up to 96% when the amount of samples accounts for 15% of the whole area. The results shows that the use of parcel data can effectively improve the error in recognition results in MODIS-NDVI based multi-series data caused by the low spatial resolution. Therefore, with combination of moderate and low resolution data, the winter wheat area estimation became available in large-scale region which lacks completed medium resolution images or has images covered with clouds. Meanwhile, it carried out the preliminary experiments for other crop area estimation.

Midwest agriculture and ENSO: A comparison of AVHRR NDVI3g data and crop yields in the United States Corn Belt from 1982 to 2014

Science.gov (United States)

Glennie, Erin; Anyamba, Assaf

2018-06-01

A time series of Advanced Very High Resolution Radiometer (AVHRR) derived normalized difference vegetation index (NDVI) data were compared to National Agricultural Statistics Service (NASS) corn yield data in the United States Corn Belt from 1982 to 2014. The main objectives of the comparison were to assess 1) the consistency of regional Corn Belt responses to El Niño/Southern Oscillation (ENSO) teleconnection signals, and 2) the reliability of using NDVI as an indicator of crop yield. Regional NDVI values were used to model a seasonal curve and to define the growing season - May to October. Seasonal conditions in each county were represented by NDVI and land surface temperature (LST) composites, and corn yield was represented by average annual bushels produced per acre. Correlation analysis between the NDVI, LST, corn yield, and equatorial Pacific sea surface temperature anomalies revealed patterns in land surface dynamics and corn yield, as well as typical impacts of ENSO episodes. It was observed from the study that growing seasons coincident with La Niña events were consistently warmer, but El Niño events did not consistently impact NDVI, temperature, or corn yield data. Moreover, the El Niño and La Niña composite images suggest that impacts vary spatially across the Corn Belt. While corn is the dominant crop in the region, some inconsistencies between corn yield and NDVI may be attributed to soy crops and other background interference. The overall correlation between the total growing season NDVI anomaly and detrended corn yield was 0.61(p = 0.00013), though the strength of the relationship varies across the Corn Belt.

Fourier analysis of temporal NDVI in the Southern African and American continents

NARCIS (Netherlands)

Azzali, S.; Menenti, M.

1996-01-01

Results of applying Fourier analysis of temporal NDVI in southern Africa and southern America are summarized. The decomposition of complex time series of images in simpler periodic components by Fourier analysis allowed the factors that affect the vegetation cover to be analysed much easier. The

LAND-COVER CHARACTERIZATION AND CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

Science.gov (United States)

The purpose of this research and development effort is to investigate the feasibility of using MODIS derived Normalized Difference Vegetation Index (NDVI) data to delineate areas of LC change on an annual basis and identify the outcome of LC conversions (i.e., new steady state). ...

Integrating age in the detection and mapping of incongruous patches in coffee (Coffea arabica) plantations using multi-temporal Landsat 8 NDVI anomalies

Science.gov (United States)

Chemura, Abel; Mutanga, Onisimo; Dube, Timothy

2017-05-01

The development of cost-effective, reliable and easy to implement crop condition monitoring methods is urgently required for perennial tree crops such as coffee (Coffea arabica), as they are grown over large areas and represent long term and higher levels of investment. These monitoring methods are useful in identifying farm areas that experience poor crop growth, pest infestation, diseases outbreaks and/or to monitor response to management interventions. This study compares field level coffee mean NDVI and LSWI anomalies and age-adjusted coffee mean NDVI and LSWI anomalies in identifying and mapping incongruous patches across perennial coffee plantations. To achieve this objective, we first derived deviation of coffee pixels from the global coffee mean NDVI and LSWI values of nine sequential Landsat 8 OLI image scenes. We then evaluated the influence of coffee age class (young, mature and old) on Landsat-scale NDVI and LSWI values using a one-way ANOVA and since results showed significant differences, we adjusted NDVI and LSWI anomalies for age-class. We then used the cumulative inverse distribution function (α ≤ 0.05) to identify fields and within field areas with excessive deviation of NDVI and LSWI from the global and the age-expected mean for each of the Landsat 8 OLI scene dates spanning three seasons. Results from accuracy assessment indicated that it was possible to separate incongruous and healthy patches using these anomalies and that using NDVI performed better than using LSWI for both global and age-adjusted mean anomalies. Using the age-adjusted anomalies performed better in separating incongruous and healthy patches than using the global mean for both NDVI (Overall accuracy = 80.9% and 68.1% respectively) and for LSWI (Overall accuracy = 68.1% and 48.9% respectively). When applied to other Landsat 8 OLI scenes, the results showed that the proportions of coffee fields that were modelled incongruent decreased with time for the young age category and

Historical extension of operational NDVI products for livestock insurance in Kenya

Science.gov (United States)

Vrieling, Anton; Meroni, Michele; Shee, Apurba; Mude, Andrew G.; Woodard, Joshua; de Bie, C. A. J. M. (Kees); Rembold, Felix

2014-05-01

Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981-2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002-2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.

Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series

DEFF Research Database (Denmark)

Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo

2015-01-01

for recultivation hinges on incomplete knowledge about the spatial patterns of fallow and abandoned farmland, especially at broad geographic scales. Our goals were to develop a methodology to map active and fallow land using MODIS Normalized Differenced Vegetation Index (NDVI) time series and to provide the first...

Assessing the effects of human-induced land degradation in the former homelands of northern South Africa with a 1 km AVHRR NDVI time-series

CSIR Research Space (South Africa)

Wessels, Konrad J

2004-05-15

Full Text Available been successfully estimated with the normalized dif- ference vegetation index (NDVI) derived from satellite data (Deering et al., 1975; Jury et al., 1997; Myneni et al., 1997; Prince, 1991b; Prince & Tucker, 1986; Tucker & Sellers, 1986). NDVI captures... productivity (NPP; Schloss et al., 1999). In arid and semiarid lands, seasonal sums of multitemporal NDVI are strongly corre- lated with vegetation production (Prince, 1991b; Prince & Tucker, 1986; Nicholson & Farrar, 1994; Nicholson et al., 1998). Human...

AÇÃO ANTRÓPICA SOBRE AS ESCALAS TEMPORAIS DOS FENÔMENOS GEOMORFOLÓGICOS

Directory of Open Access Journals (Sweden)

Archimedes Perez Filho

2012-02-01

Full Text Available Formas e processos da superfície terrestre possuem manifestação espacial e temporal. Com relação ao tempo, definimos no presente artigo pelo menos quatro escalas de importância na compreensão do objeto de estudo da geomorfologia, a saber: tempo da natureza, histórico do homem, presente e futuro. A verificação da reativação da rede de drenagem e intensificação de processos erosivos relacionados às alterações no nível de base local, devido à construção de represas de usinas hidrelétricas, bem como do fenômeno de desertificação antrópica, ocasionado pela remoção da cobertura vegetal natural em áreas de Neossolos Quartzarênicos são indicadores da capacidade do sistema antrópico de influenciar processos geomorfológicos, impondo-lhes ritmos diferentes, com consequente alteração de suas escalas temporais de ocorrência. Deste modo, comprova-se que processos e formas que se manifestariam na escala de tempo geológico, passam a ocorrer nas escalas do tempo histórico do homem e presente, evidenciando que as formas variadas, rápidas e agressivas com que o homem tem interferido na dinâmica natural da Terra resultam em processos geomorfológicos com gênese antrópica.

PENGGUNAAN ALGORITMA NDVI DAN EVI PADA CITRA MULTISPEKTRAL UNTUK ANALISA PERTUMBUHAN PADI (STUDI KASUS : KABUPATEN INDRAMAYU, JAWA BARAT

Directory of Open Access Journals (Sweden)

Aulia Hafizh S

2015-02-01

Full Text Available Kabupaten Indramayu merupakan salah satu kabupaten yang merupakan daerah sentra pertanian dimana sektor ini menyumbang 43% dari total PDRB (Produk Domestik Regional Bruto. Strategi yang tepat dan cepat harus dicanangkan untuk selalu memenuhi kebutuhan akan bahan pokok tersebut. Teknologi penginderaan jauh dapat mengakomodir informasi suatu objek secara cepat dan akurat tanpa harus berinteraksi langsung dengan objek dan dapat dimanfaatkan dalam berbagai aplikasi yang diinginkan. Pembangunan model - model estimasi produktivitas pada beberapa komoditas vegetasi pertanian seperti padi telah digunakan sejak dua dekade lalu. Dari berbagai macam permodelan vegetasi, indeks vegetasi yang paling umum digunakan adalah NDVI (Normalized Difference Vegetation Index dan EVI (Enhanced Vegetation Index. Hasil dari penelitian ini adalah penentuan fase pertumbuhan , masa tanam, dan masa panen tumbuhan padi pada citra MODIS L1B. Masa tanam padi di kabupaten Indramayu berada pada bulan Juni dan Desember 2011, masa panen berada pada bulan  Mei dan September 2011. Citra Aster digunakan sebagai data pendukung untuk menentukan korelasi linear  terhadap data lapangan (fieldspectometer. Korelasi yang dihasilkan Antara Modis - Aster sebesar 0.9576 pada EVI dan 0.9654 pada NDVI; Modis - Fieldspectometer sebesar 0.8798 pada EVI dan 0.9077 pada NDVI; dan pada Aster - Fieldspectometer sebesar 0.9220 pada EVI dan 0.9460 pada NDVI. Korelasi dari ketiga data tersebut memiliki hubungan yang cukup kuat dikarenakan nilai yang dihasilkan mendekati nilai 1.

Classification of Small-Scale Eucalyptus Plantations Based on NDVI Time Series Obtained from Multiple High-Resolution Datasets

Directory of Open Access Journals (Sweden)

Hailang Qiao

2016-02-01

Full Text Available Eucalyptus, a short-rotation plantation, has been expanding rapidly in southeast China in recent years owing to its short growth cycle and high yield of wood. Effective identification of eucalyptus, therefore, is important for monitoring land use changes and investigating environmental quality. For this article, we used remote sensing images over 15 years (one per year with a 30-m spatial resolution, including Landsat 5 thematic mapper images, Landsat 7-enhanced thematic mapper images, and HJ 1A/1B images. These data were used to construct a 15-year Normalized Difference Vegetation Index (NDVI time series for several cities in Guangdong Province, China. Eucalyptus reference NDVI time series sub-sequences were acquired, including one-year-long and two-year-long growing periods, using invested eucalyptus samples in the study region. In order to compensate for the discontinuity of the NDVI time series that is a consequence of the relatively coarse temporal resolution, we developed an inverted triangle area methodology. Using this methodology, the images were classified on the basis of the matching degree of the NDVI time series and two reference NDVI time series sub-sequences during the growing period of the eucalyptus rotations. Three additional methodologies (Bounding Envelope, City Block, and Standardized Euclidian Distance were also tested and used as a comparison group. Threshold coefficients for the algorithms were adjusted using commission–omission error criteria. The results show that the triangle area methodology out-performed the other methodologies in classifying eucalyptus plantations. Threshold coefficients and an optimal discriminant function were determined using a mosaic photograph that had been taken by an unmanned aerial vehicle platform. Good stability was found as we performed further validation using multiple-year data from the high-resolution Gaofen Satellite 1 (GF-1 observations of larger regions. Eucalyptus planting dates

Spatial-temporal dynamics of NDVI and Chl-a concentration from 1998 to 2009 in the East coastal zone of China: integrating terrestrial and oceanic components.

Science.gov (United States)

Hou, Xiyong; Li, Mingjie; Gao, Meng; Yu, Liangju; Bi, Xiaoli

2013-01-01

Annual normalized difference vegetation index (NDVI) and chlorophyll-a (Chl-a) concentration are the most important large-scale indicators of terrestrial and oceanic ecosystem net primary productivity. In this paper, the Sea-viewing Wide Field-of-view Sensor level 3 standard mapped image annual products from 1998 to 2009 are used to study the spatial-temporal characters of terrestrial NDVI and oceanic Chl-a concentration on two sides of the coastline of China by using the methods of mean value (M), coefficient of variation (CV), the slope of unary linear regression model (Slope), and the Hurst index (H). In detail, we researched and analyzed the spatial-temporal dynamics, the longitudinal zonality and latitudinal zonality, the direction, intensity, and persistency of historical changes. The results showed that: (1) spatial patterns of M and CV between NDVI and Chl-a concentration from 1998 to 2009 were very different. The dynamic variation of terrestrial NDVI was much mild, while the variation of oceanic Chl-a concentration was relatively much larger; (2) distinct longitudinal zonality was found for Chl-a concentration and NDVI due to their hypersensitivity to the distance to shoreline, and strong latitudinal zonality existed for Chl-a concentration while terrestrial NDVI had a very weak latitudinal zonality; (3) overall, the NDVI showed a slight decreasing trend while the Chl-a concentration showed a significant increasing trend in the past 12 years, and both of them exhibit strong self-similarity and long-range dependence which indicates opposite future trends between land and ocean.

Towards Detection of Cutting in Hay Meadows by Using of NDVI and EVI Time Series

Directory of Open Access Journals (Sweden)

Andrej Halabuk

2015-05-01

Full Text Available The main requirement for preserving European hay meadows in good condition is through prerequisite cut management. However, monitoring these practices on a larger scale is very difficult. Our study analyses the use of MODIS vegetation indices products, namely EVI and NDVI, to discriminate cut and uncut meadows in Slovakia. We tested the added value of simple transformations of raw data series (seasonal statistics, first difference series, compared EVI and NDVI, and analyzed optimal periods, the number of scenes and the effect of smoothing on classification performance. The first difference series transformation saw substantial improvement in classification results. The best case NDVI series classification yielded overall accuracy of 85% with balanced rates of producer’s and user’s accuracies for both classes. EVI yielded slightly lower values, though not significantly different, although user accuracy of cut meadows achieved only 67%. Optimal periods for discriminating cut and uncut meadows lay between 16 May and 4 August, meaning only seven consecutive images are enough to accurately detect cutting in hay meadows. More importantly, the 16-day compositing period seemed to be enough for detection of cutting, which would be the time span that might be hopefully achieved by upcoming on-board HR sensors (e.g., Sentinel-2.

Impact of economic growth on vegetation health in China based on GIMMS NDVI

NARCIS (Netherlands)

Jin, X.; Wan, L.; Zhang, Y.K.; Schaepman, M.E.

2008-01-01

The negative impact of economic development on vegetation health in China was assessed using gross domestic product (GDP) and the Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data. Five levels of vegetation changes were established based on the

Analyzing the Velocity of Vegetation Phenology Over the Tibetan Plateau Using Gimms NDVI3g Data

Science.gov (United States)

Zhou, Y. K.

2018-05-01

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, and phenology is a classic proxy to detect the response of vegetation to the changes. On the Tibetan Plateau, the earlier spring and delayed autumn vegetation phenology is widely reported. Remotely sensed NDVI can serve as a good data source for vegetation phenology study. Here GIMMS NDVI3g data was used to detect vegetation phenology status on the Tibetan Plateau. The spatial and temporal gradients are combined to depict the velocity of vegetation expanding process. This velocity index represents the instantaneous local velocity along the Earth's surface needed to maintain constant vegetation condition. This study found that NDVI velocity show a complex spatial pattern. A considerable number of regions display a later starting of growing season (SOS) and earlier end of growing season (EOS) reflected by the velocity change, particularly in the central part of the plateau. Nearly 74 % vegetation experienced a shortened growing season length. Totally, the magnitude of the phenology velocity is at a small level that reveals there is not a significant variation of vegetation phenology under the climate change context.

Does EO NDVI seasonal metrics capture variations in species composition and biomass due to grazing in semi-arid grassland savannas?

DEFF Research Database (Denmark)

Olsen, J. L.; Miehe, S.; Ceccato, Pietro

2015-01-01

Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurements. From a long time series of coarse resolution normalized difference...... vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. However, it is poorly understood how commonly applied remote sensing techniques reflect the influence of extensive grazing (and changes in grazing pressure) on natural rangeland vegetation. This paper analyses the time...... exclosures as compared to grazed areas, substantially exceeding the amount of biomass expected to be ingested by livestock for this area. The seasonal integrated NDVI (NDVI small integral; capturing only the signal inherent to the growing season recurrent vegetation), derived using absolute thresholds...

Near Real-time Operational Use of eMODIS Expedited NDVI for Monitoring Applications and Famine Early Warning

Science.gov (United States)

Rowland, J.; Budde, M. E.

2010-12-01

The Famine Early Warning Systems Network (FEWS NET) has requirements for near real-time monitoring of vegetation conditions for food security applications. Accurate and timely assessments of crop conditions are an important element of food security decision making. FEWS NET scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center are utilizing a new Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset for operational monitoring of crop and pasture conditions in parts of the world where food availability is highly dependent on subsistence agriculture and animal husbandry. The expedited MODIS, or eMODIS, production system processes NDVI data using MODIS surface reflectance provided by the Land Atmosphere Near-real-time Capability for EOS (LANCE). Benefits of this production system include customized compositing schedules, near real-time data availability, and minimized re-sampling. FEWS NET has implemented a 10-day compositing scheme every five days to accommodate the need for timely information on vegetation conditions. The data are currently being processed at 250-meter spatial resolution for Central America, Hispaniola, and Africa. Data are further enhanced by the application of a temporal smoothing filter which helps remove contamination due to clouds and other atmospheric effects. The results of this near real-time monitoring capability have been the timely provision of NDVI and NDVI anomaly maps for each of the FEWS NET monitoring regions and the availability of a consistently processed dataset to aid crop assessment missions and to facilitate customized analyses of crop production, drought, and agro-pastoral conditions.

High Spatial Resolution WorldView-2 Imagery for Mapping NDVI and Its Relationship to Temporal Urban Landscape Evapotranspiration Factors

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Hamideh Nouri

2014-01-01

Full Text Available Evapotranspiration estimation has benefitted from recent advances in remote sensing and GIS techniques particularly in agricultural applications rather than urban environments. This paper explores the relationship between urban vegetation evapotranspiration (ET and vegetation indices derived from newly-developed high spatial resolution WorldView-2 imagery. The study site was Veale Gardens in Adelaide, Australia. Image processing was applied on five images captured from February 2012 to February 2013 using ERDAS Imagine. From 64 possible two band combinations of WorldView-2, the most reliable one (with the maximum median differences was selected. Normalized Difference Vegetation Index (NDVI values were derived for each category of landscape cover, namely trees, shrubs, turf grasses, impervious pavements, and water bodies. Urban landscape evapotranspiration rates for Veale Gardens were estimated through field monitoring using observational-based landscape coefficients. The relationships between remotely sensed NDVIs for the entire Veale Gardens and for individual NDVIs of different vegetation covers were compared with field measured urban landscape evapotranspiration rates. The water stress conditions experienced in January 2013 decreased the correlation between ET and NDVI with the highest relationship of ET-Landscape NDVI (Landscape Normalized Difference Vegetation Index for shrubs (r2 = 0.66 and trees (r2 = 0.63. However, when the January data was excluded, there was a significant correlation between ET and NDVI. The highest correlation for ET-Landscape NDVI was found for the entire Veale Gardens regardless of vegetation type (r2 = 0.95, p > 0.05 and the lowest one was for turf (r2 = 0.88, p > 0.05. In support of the feasibility of ET estimation by WV2 over a longer period, an algorithm recently developed that estimates evapotranspiration rates based on the Enhanced Vegetation Index (EVI from MODIS was employed. The results revealed a

High spatial resolution WorldView-2 imagery for mapping NDVI and its relationship to temporal urban landscape evapotranspiration factors

Science.gov (United States)

Nouri, Hamideh; Beecham, Simon; Anderson, Sharolyn; Nagler, Pamela

2014-01-01

Evapotranspiration estimation has benefitted from recent advances in remote sensing and GIS techniques particularly in agricultural applications rather than urban environments. This paper explores the relationship between urban vegetation evapotranspiration (ET) and vegetation indices derived from newly-developed high spatial resolution WorldView-2 imagery. The study site was Veale Gardens in Adelaide, Australia. Image processing was applied on five images captured from February 2012 to February 2013 using ERDAS Imagine. From 64 possible two band combinations of WorldView-2, the most reliable one (with the maximum median differences) was selected. Normalized Difference Vegetation Index (NDVI) values were derived for each category of landscape cover, namely trees, shrubs, turf grasses, impervious pavements, and water bodies. Urban landscape evapotranspiration rates for Veale Gardens were estimated through field monitoring using observational-based landscape coefficients. The relationships between remotely sensed NDVIs for the entire Veale Gardens and for individual NDVIs of different vegetation covers were compared with field measured urban landscape evapotranspiration rates. The water stress conditions experienced in January 2013 decreased the correlation between ET and NDVI with the highest relationship of ET-Landscape NDVI (Landscape Normalized Difference Vegetation Index) for shrubs (r2 = 0.66) and trees (r2 = 0.63). However, when the January data was excluded, there was a significant correlation between ET and NDVI. The highest correlation for ET-Landscape NDVI was found for the entire Veale Gardens regardless of vegetation type (r2 = 0.95, p > 0.05) and the lowest one was for turf (r2 = 0.88, p > 0.05). In support of the feasibility of ET estimation by WV2 over a longer period, an algorithm recently developed that estimates evapotranspiration rates based on the Enhanced Vegetation Index (EVI) from MODIS was employed. The results revealed a significant positive

Characterizing post-drainage succession in Thermokarst Lake Basins on the Seward Peninsula, Alaska with TerraSAR-X Backscatter and Landsat-based NDVI data

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Regmi, Prajna; Grosse, Guido; Jones, Miriam C.; Jones, Benjamin M.; Walter Anthony, Katey

2012-01-01

Drained thermokarst lake basins accumulate significant amounts of soil organic carbon in the form of peat, which is of interest to understanding carbon cycling and climate change feedbacks associated with thermokarst in the Arctic. Remote sensing is a tool useful for understanding temporal and spatial dynamics of drained basins. In this study, we tested the application of high-resolution X-band Synthetic Aperture Radar (SAR) data of the German TerraSAR-X satellite from the 2009 growing season (July–September) for characterizing drained thermokarst lake basins of various age in the ice-rich permafrost region of the northern Seward Peninsula, Alaska. To enhance interpretation of patterns identified in X-band SAR for these basins, we also analyzed the Normalized Difference Vegetation Index (NDVI) calculated from a Landsat-5 Thematic Mapper image acquired on July 2009 and compared both X-band SAR and NDVI data with observations of basin age. We found significant logarithmic relationships between (a) TerraSAR-X backscatter and basin age from 0 to 10,000 years, (b) Landat-5 TM NDVI and basin age from 0 to 10,000 years, and (c) TerraSAR-X backscatter and basin age from 50 to 10,000 years. NDVI was a better indicator of basin age over a period of 0–10,000 years. However, TerraSAR-X data performed much better for discriminating radiocarbon-dated basins (50–10,000 years old). No clear relationships were found for either backscatter or NDVI and basin age from 0 to 50 years. We attribute the decreasing trend of backscatter and NDVI with increasing basin age to post-drainage changes in the basin surface. Such changes include succession in vegetation, soils, hydrology, and renewed permafrost aggradation, ground ice accumulation and localized frost heave. Results of this study show the potential application of X-band SAR data in combination with NDVI data to map long-term succession dynamics of drained thermokarst lake basins.

Characterizing Post-Drainage Succession in Thermokarst Lake Basins on the Seward Peninsula, Alaska with TerraSAR-X Backscatter and Landsat-based NDVI Data

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Prajna Regmi

2012-11-01

Full Text Available Drained thermokarst lake basins accumulate significant amounts of soil organic carbon in the form of peat, which is of interest to understanding carbon cycling and climate change feedbacks associated with thermokarst in the Arctic. Remote sensing is a tool useful for understanding temporal and spatial dynamics of drained basins. In this study, we tested the application of high-resolution X-band Synthetic Aperture Radar (SAR data of the German TerraSAR-X satellite from the 2009 growing season (July–September for characterizing drained thermokarst lake basins of various age in the ice-rich permafrost region of the northern Seward Peninsula, Alaska. To enhance interpretation of patterns identified in X-band SAR for these basins, we also analyzed the Normalized Difference Vegetation Index (NDVI calculated from a Landsat-5 Thematic Mapper image acquired on July 2009 and compared both X-band SAR and NDVI data with observations of basin age. We found significant logarithmic relationships between (a TerraSAR-X backscatter and basin age from 0 to 10,000 years, (b Landat-5 TM NDVI and basin age from 0 to 10,000 years, and (c TerraSAR-X backscatter and basin age from 50 to 10,000 years. NDVI was a better indicator of basin age over a period of 0–10,000 years. However, TerraSAR-X data performed much better for discriminating radiocarbon-dated basins (50–10,000 years old. No clear relationships were found for either backscatter or NDVI and basin age from 0 to 50 years. We attribute the decreasing trend of backscatter and NDVI with increasing basin age to post-drainage changes in the basin surface. Such changes include succession in vegetation, soils, hydrology, and renewed permafrost aggradation, ground ice accumulation and localized frost heave. Results of this study show the potential application of X-band SAR data in combination with NDVI data to map long-term succession dynamics of drained thermokarst lake basins.

A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery.

Science.gov (United States)

Tan, Kok Chooi; Lim, Hwee San; Matjafri, Mohd Zubir; Abdullah, Khiruddin

2012-06-01

Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.

Sugarcane leaf area estimate obtained from the corrected Normalized Difference Vegetation Index (NDVI

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Rodrigo Moura Pereira

2016-06-01

Full Text Available Large farmland areas and the knowledge on the interaction between solar radiation and vegetation canopies have increased the use of data from orbital remote sensors in sugarcane monitoring. However, the constituents of the atmosphere affect the reflectance values obtained by imaging sensors. This study aimed at improving a sugarcane Leaf Area Index (LAI estimation model, concerning the Normalized Difference Vegetation Index (NDVI subjected to atmospheric correction. The model generated by the NDVI with atmospheric correction showed the best results (R2 = 0.84; d = 0.95; MAE = 0.44; RMSE = 0.55, in relation to the other models compared. LAI estimation with this model, during the sugarcane plant cycle, reached a maximum of 4.8 at the vegetative growth phase and 2.3 at the end of the maturation phase. Thus, the use of atmospheric correction to estimate the sugarcane LAI is recommended, since this procedure increases the correlations between the LAI estimated by image and by plant parameters.

Atmospheric effects on the NDVI - Strategies for its removal. [Normalized Difference Vegetation Index

Science.gov (United States)

Kaufman, Y. J.; Tanre, D.; Holben, B. N.; Markham, B.; Gitelson, A.

1992-01-01

The compositing technique used to derive global vegetation index (NDVI) from the NOAA AVHRR radiances reduces the residual effect of water vapor and aerosol on the NDVI. The reduction in the atmospheric effect is shown using a comprehensive measured data set for desert conditions, and a simulation for grass with continental aerosol. A statistical analaysis of the probability of occurrence of aerosol optical thickness and precipitable water vapor measured in different climatic regimes is used for this simulation. It is concluded that for a long compositing period (e.g., 27 days), the residual aerosol optical thickness and precipitable water vapor are usually too small to be corrected. For a 9-day compositing, the residual average aerosol effect may be about twice the correction uncertainty. For Landsat TM or Earth Observing System Moderate Resolution Imaging Spectrometer (EOS-MODIS) data, the newly defined atmospherically resistant vegetation index (ARVI) is more promising than possible direct atmospheric correction schemes, except for heavy desert dust conditions.

HUBUNGAN ANTARA INDEKS VEGETASI NDVI (NORMALIZED DIFFERENCE VEGETATION INDEX DAN KOEFISIEN RESESI BASEFLOW PADA BEBERAPA SUBDAS PROPINSI JAWA TENGAH DAN DAERAH ISTIMEWA YOGYAKARTA

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Bokiraiya Latuamury

2013-06-01

Full Text Available The background of this research is the decrease of environment capacity in cacthment ecosystem, especially impact of vegetation forest on behavior streamflow. The indicators of cacthment destruction can be seen through hydrograph characteristics. Evaluation of cactment respons of flow hydrographic as an evaluation tools of river catchment responses becomes very important to analyze because it is a benchmark in determination several policy about flood, drough, sedimentation and landslide handling. The research purpose is to analyze the relationship between vegetation index NDVI (Normalized Difference Vegetation Index and the characteristic of baseflow recession coefficient at several subcatchment areas in province of Central Java and Specific District of Yogjakarta.The method of this research is surveillance on data recording of AWLR (Automatic Water Level Recorder and data of River Flow Measuring Stations in order to separate the baseflow by calibration curve, and image interpretation of Landsat ETM+ for the transformation of vegetation index (NDVI-Normalized Difference Vegetation Index.The analysis on recession coefficient data (Krb and NDVI were correlated to analyze the strength of relationship between these two parameters. The results of statistical analysis on index NDVI and recession coefficient showsthat NDVI and recession coefficient value at R2 is 0.1427, F = 2.17 which is not significant at 1% significance level of 0.1646. The result shows a very weak correlation of 0.077 which mean that vegetation density (NDVI indexhas a very weak control on low flows. Basically, river baseflow is a genetic component of river flow which comes from aquifer storage and/or other low flow sources. Thus, geology and soil have a significant effect on baseflow.

Evaluating EO-based canopy water stress from seasonally detrended NDVI and SIWSI with modeled evapotranspiration in the Senegal River Basin

DEFF Research Database (Denmark)

Olsen, Jørgen L.; Stisen, Simon; Proud, Simon Richard

2015-01-01

the Shortwave Infrared Water Stress Index (SIWSI) as compared to Normalized Difference Vegetation Index (NDVI). We perform a spatio-temporal evaluation of NDVI and SIWSI using geostationary remote sensing imagery from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The indices and their seasonally......Satellite remote sensing of vegetation parameters and stress is a key issue for semi-arid areas such as the Sahel, where vegetation is an important part of the natural resource base. In this study we examine if additional information can be obtained on intra-seasonal short term scale by using...... gradient in the river catchment. The hypothesis that short term evolution of index anomalies are related to canopy water status was tested by comparing 10-day averages of ETa with short term changes in daily NDVI and SIWSI anomalies, and moderate to strong coefficients of determination where found when...

A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity

Science.gov (United States)

Rune Karlsen, Stein; Anderson, Helen B.; van der Wal, René; Bremset Hansen, Brage

2018-02-01

Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000-2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-Normalised Difference Vegetation Index (NDVI) data set (2000-2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R 2 = 0.51 and 0.44, respectively). The commonly used ‘maximum NDVI’ plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images.

Efficient Maize and Sunflower Multi-year Mapping with NDVI Time Series of HJ-1A/1B in Hetao Irrigation District of Inner Mongolia, China

Science.gov (United States)

Yu, B.; Shang, S.

2016-12-01

Food shortage is one of the major challenges that human beings are facing. It is urgent to improve the monitoring of the plantation and distribution of the main crops to solve the following economic and social issues. Recently, with the extensive use of remote sensing satellite data, it has provided favorable conditions for crop identification in large irrigation district with complex planting structure. Difference of different crop phenology is the main basis for crop identification, and the normalized difference vegetation index (NDVI) time-series could better delineate crop phenology cycle. Therefore, the key of crop identification is to obtain high quality NDVI time-series. MODIS and Landsat TM satellite images are the most frequently used, however, neither of them could guarantee high temporal and spatial resolutions at once. Accordingly, this paper makes use of NDVI time-series extracted from China Environment Satellites data, which has two-day-repeat temporal and 30m spatial resolutions. The NDVI time-series are fitted with an asymmetric logistic curve, the fitting effect is good and the correlation coefficient is greater than 0.9. The phonological parameters are derived from NDVI fitting curves, and crop identification is carried out by different relation ellipses between NDVI and its phonological parameters of different crops. This paper takes Hetao Irrigation District of Inner Mongolia as an example, to identify multi-year maize and sunflower in the district, and the identification result is good. Compared with the official statistics, the relative errors are both lower than 5%. The results show that the NDVI time-series dataset derived from HJ-1A/1B CCD could delineate the crop phenology cycle accurately and demonstrate its application in crop identification in irrigated district.

NDVI e fluxo de CO2 em lavoura de soja no Rio Grande do Sul NDVI and CO2 flow in a soybean crop in Rio Grande do Sul, Brasil

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Celso Pinheiro Rodrigues

2013-03-01

Full Text Available O aumento das emissões dos gases de efeito estufa (GEE se configura, atualmente, como um dos principais problemas ambientais, o que pode afetar significativamente as atividades humanas e os ecossistemas terrestres. Um dos principais GEE é o CO2, o qual tem sido emitido indiscriminadamente em função do estilo de vida atual, assim como pela intensificação das atividades agrícolas. Neste contexto, o objetivo da pesquisa foi estudar a relação entre o comportamento espectral da cultura de soja ao longo de seu ciclo de desenvolvimento, utilizando imagens NDVI (Normalized Difference Vegetation Index e o fluxo de CO2, calculado pelo método de covariância de vórtices (eddy covariance, gerando informações e metodologia para investigar as trocas de carbono em uma área de cultivo de soja no estado do Rio Grande do Sul, durante a safra de 2008/2009. Utilizou-se imagens TM do satélite Landsat 5, dados fenológicos e dados coletados em estação micrometeorológica ao longo do ciclo de desenvolvimento da soja. Os resultados mostraram que o padrão temporal do fluxo de CO2 ao longo do dia é cíclico, sendo que no período diurno apresenta valores negativos (captura e no período noturno, positivos (liberação. A radiação solar global determina a magnitude do aprisionamento de CO2 pela cultura da soja, mas o fluxo é modulado pelo estádio fenológico da cultura. A atividade fotossintética das plantas de soja é maior durante o estádio vegetativo, quando coincide a maior incidência de radiação solar e o maior aparato fotossintético. O NDVI, obtido de imagens Landsat, é um indicador da evolução da biomassa da soja ao longo do ciclo. Existe correlação entre o NDVI e o fluxo negativo de CO2 (captura, ocorridos no período diurno. Portanto, técnicas de sensoriamento remoto demonstram potencialidade na geração de informações úteis sobre as trocas de CO2 entre a superfície e a atmosfera.The increasing on the greenhouse gases (GHG

Change detection of bare areas in the Xolobeni region, South Africa using Landsat NDVI

CSIR Research Space (South Africa)

Singh, RG

2015-06-01

Full Text Available to provide some information on the inter-relationship between vegetated classes and bare areas. Normalised Difference Vegetation Index (NDVI) data derived from multi-temporal Landsat 5 imagery has formed the baseline information for this study. A density...

Browning of the landscape of interior Alaska based on 1986-2009 Landsat sensor NDVI

Science.gov (United States)

Rebecca A. Baird; David Verbyla; Teresa N. Hollingsworth

2012-01-01

We used a time series of 1986-2009 Landsat sensor data to compute the Normalized Difference Vegetation Index (NDVI) for 30 m pixels within the Bonanza Creek Experimental Forest of interior Alaska. Based on simple linear regression, we found significant (p

Análisis de la evolución espacio-temporal del NDVI sobre áreas vegetadas y zonas de riesgo de erosión en el Pirineo Central

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Vicente-Serrano, S. M.

2010-12-01

Full Text Available The temporal evolution of vegetation activity on various land cover classes in the Spanish Pyrenees was analyzed. Two time series of the normalized difference vegetation index (NDVI were used, corresponding to March (early spring and August (the end of summer. The series were generated from Landsat TM and Landsat ETM+ images for the period 1984-2007. An increase in the NDVI in March was found for vegetated areas, and the opposite trend was found in both March and August for degraded areas (badlands and erosion risk areas. The rise in minimum temperature during the study period appears to be the most important factor explaining the increased NDVI in the vegetated areas. In degraded areas, no climatic or topographic variable was associated with the negative trend in the NDVI, which may be related to erosion processes taking place in these regions.

En este trabajo se ha analizado la evolución temporal y espacial de la dinámica vegetal sobre varias coberturas de suelo en el Pirineo central, España. Se han utilizado dos series temporales de NDVI, la primera corresponde al mes de Abril (inicio de primavera y la segunda al mes de Agosto (final de verano. Las series fueron construidas a partir de imágenes Landsat TM y ETM+ para el periodo del 1984-2007. Los resultados muestran un incremento del NDVI en el mes de Marzo para las áreas vegetadas, mientras que las áreas degradadas (cárcavas y zonas de riesgo de erosión presentaron una tendencia negativa del NDVI. El incremento de las temperaturas mínimas durante el periodo de estudio fue el factor más importante para explicar el incremento del NDVI en las áreas vegetadas. En las áreas degradadas, no se encontró ninguna variable climática o topográfica que explicará la tendencia negativa del NDVI, lo cual se ha relacionado con los procesos de erosión acelerada que tienen lugar en la región.

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

Science.gov (United States)

Spruce, Joseph P.; Hargrove, William; Gasser, Gerald; Smoot, James; Kuper, Philip D.

2012-01-01

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product

NDVI statistical distribution of pasture areas at different times in the Community of Madrid (Spain)

Science.gov (United States)

Martín-Sotoca, Juan J.; Saa-Requejo, Antonio; Díaz-Ambrona, Carlos G. H.; Tarquis, Ana M.

2015-04-01

The severity of drought has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. However, its impacts on rain-fed agriculture are especially direct. Because of the importance of drought, there have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). 'Biomass index' based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in countries like United States of America, Canada and Spain for pasture and forage crops for some years (Rao, 2010). This type of agricultural insurance is named as 'index-based insurance' (IBI). IBI is perceived to be substantially less costly to operate and manage than multiple peril insurance. IBI contracts pay indemnities based not on the actual yield (or revenue) losses experienced by the insurance purchaser but rather based on realized NDVI values (historical data) that is correlated with farm-level losses (Xiaohui Deng et al., 2008). Definition of when drought event occurs is defined on NDVI threshold values mainly based in statistical parameters, average and standard deviation that characterize a normal distribution. In this work a pasture area at the north of Community of Madrid (Spain) has been delimited. Then, NDVI historical data was reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. A statistical analysis of the NDVI histograms at consecutives 46 intervals of that area was applied to search for the best statistical distribution based on the maximum likelihood criteria. The results show that the normal distribution is not the optimal representation when IBI is available; the implications in the context of crop insurance are discussed (Martín-Sotoca, 2014). References Kolli N Rao. 2010. Index based Crop Insurance. Agriculture and Agricultural Science Procedia 1, 193-203. Martín-Sotoca, J.J. (2014) Estructura Espacial

Monitoring Agricultural Cropping Patterns across the Laurentian Great Lakes Basin Using MODIS-NDVI Data

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The Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composite data product (MOD12Q) was used to develop annual cropland and crop-specific map products (corn, soybeans, and wheat) for the Laurentian Great Lakes Basin (GLB). Th...

Assessing onset and length of greening period in six vegetation types in Oaxaca, Mexico, using NDVI-precipitation relationships.

Science.gov (United States)

Gómez-Mendoza, L; Galicia, L; Cuevas-Fernández, M L; Magaña, V; Gómez, G; Palacio-Prieto, J L

2008-07-01

Variations in the normalized vegetation index (NDVI) for the state of Oaxaca, in southern Mexico, were analyzed in terms of precipitation anomalies for the period 1997-2003. Using 10-day averages in NDVI data, obtained from AVHRR satellite information, the response of six types of vegetation to intra-annual and inter-annual fluctuations in precipitation were examined. The onset and temporal evolution of the greening period were studied in terms of precipitation variations through spectral analysis (coherence and phase). The results indicate that extremely dry periods, such as those observed in 1997 and 2001, resulted in low values of NDVI for much of Oaxaca, while good precipitation periods produced a rapid response (20-30 days of delay) from a stressed to a non-stressed condition in most vegetation types. One of these rapid changes occurred during the transition from dry to wet conditions during the summer of 1998. As in many parts of the tropics and subtropics, the NDVI reflects low frequency variations in precipitation on several spatial scales. Even after long dry periods (2001-2002), the various regional vegetation types are capable of recovering when a good rainy season takes place, indicating that vegetation types such as the evergreen forests in the high parts of Oaxaca respond better to rainfall characteristics (timing, amount) than to temperature changes, as is the case in most mid-latitudes. This finding may be relevant to prepare climate change scenarios for forests, where increases in surface temperature and precipitation anomalies are expected.

Monitoring Agricultural Cropping Patterns in the Great Lakes Basin Using MODIS-NDVI Time Series Data

Science.gov (United States)

This research examined changes in agricultural cropping patterns across the Great Lakes Basin (GLB) using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data. Specific research objectives were to characterize the distribut...

Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.

Science.gov (United States)

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-11-26

Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed

Evaluating the consistency of the 1982-1999 NDVI trends in the Iberian Peninsula across four time-series derived from the AVHRR sensor: LTDR, GIMMS, FASIR, and PAL-II.

Science.gov (United States)

Alcaraz-Segura, Domingo; Liras, Elisa; Tabik, Siham; Paruelo, José; Cabello, Javier

2010-01-01

Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations' carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982-1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast.

Sensitivity of Climate to Changes in NDVI

Science.gov (United States)

Bounoua, L.; Collatz, G. J.; Los, S. O.; Sellers, P. J.; Dazlich, D. A.; Tucker, C. J.; Randall, D. A.

1999-01-01

The sensitivity of global and regional climate to changes in vegetation density is investigated using a coupled biosphere-atmosphere model. The magnitude of the vegetation changes and their spatial distribution are based on natural decadal variability of the normalized difference vegetation index (ndvi). Different scenarios using maximum and minimum vegetation cover were derived from satellite records spanning the period 1982-1990. Albedo decreased in the northern latitudes and increased in the tropics with increased ndvi. The increase in vegetation density revealed that the vegetation's physiological response was constrained by the limits of the available water resources. The difference between the maximum and minimum vegetation scenarios resulted in a 46% increase in absorbed visible solar radiation and a similar increase in gross photosynthetic C02 uptake on a global annual basis. This caused the canopy transpiration and interception fluxes to increase, and reduced those from the soil. The redistribution of the surface energy fluxes substantially reduced the Bowen ratio during the growing season, resulting in cooler and moister near-surface climate, except when soil moisture was limiting. Important effects of increased vegetation on climate are : (1) A cooling of about 1.8 K in the northern latitudes during the growing season and a slight warming during the winter, which is primarily due to the masking of high albedo of snow by a denser canopy. and (2) A year round cooling of 0.8 K in the tropics. These results suggest that increases in vegetation density could partially compensate for parallel increases in greenhouse warming . Increasing vegetation density globally caused both evapotranspiration and precipitation to increase. Evapotranspiration, however increased more than precipitation resulting in a global soil-water deficit of about 15 %. A spectral analysis on the simulated results showed that changes in the state of vegetation could affect the low

Relative sensitivity of Normalized Difference Vegetation Index (NDVI) and Microwave Polarization Difference Index (MPDI) for vegetation and desertification monitoring

Science.gov (United States)

Becker, Francois; Choudhury, Bhaskar J.

1988-01-01

A simple equation relating the Microwave Polarization Difference Index (MPDI) and the Normalized Difference Vegetation Index (NDVI) is proposed which represents well data obtained from Nimbus 7/SMMR at 37 GHz and NOAA/AVHRR Channels 1 and 2. It is found that there is a limit which is characteristic of a particular type of cover for which both indices are equally sensitive to the variation of vegetation, and below which MPDI is more efficient than NDVI. The results provide insight into the relationship between water content and chlorophyll absorption at pixel size scales.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Smoothed Normalized Difference Vegetation Index (NDVI) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Visible Infrared Imaging Radiometer Suite (VIIRS) Smoothed Normalized Difference Vegetation Index (NDVI) from NDE is a weekly product derived from the VIIRS...

Assessing the Accuracy of MODIS-NDVI Derived Land-Cover Across the Great Lakes Basin

Science.gov (United States)

This research describes the accuracy assessment process for a land-cover dataset developed for the Great Lakes Basin (GLB). This land-cover dataset was developed from the 2007 MODIS Normalized Difference Vegetation Index (NDVI) 16-day composite (MOD13Q) 250 m time-series data. Tr...

[NDVI difference rate recognition model of deciduous broad-leaved forest based on HJ-CCD remote sensing data].

Science.gov (United States)

Wang, Yan; Tian, Qing-Jiu; Huang, Yan; Wei, Hong-Wei

2013-04-01

The present paper takes Chuzhou in Anhui Province as the research area, and deciduous broad-leaved forest as the research object. Then it constructs the recognition model about deciduous broad-leaved forest was constructed using NDVI difference rate between leaf expansion and flowering and fruit-bearing, and the model was applied to HJ-CCD remote sensing image on April 1, 2012 and May 4, 2012. At last, the spatial distribution map of deciduous broad-leaved forest was extracted effectively, and the results of extraction were verified and evaluated. The result shows the validity of NDVI difference rate extraction method proposed in this paper and also verifies the applicability of using HJ-CCD data for vegetation classification and recognition.

Environment, vegetation and greenness (NDVI) along the North America and Eurasia Arctic transects

International Nuclear Information System (INIS)

Walker, D A; Raynolds, M K; Kuss, P; Kade, A N; Epstein, H E; Frost, G V; Kopecky, M A; Daniëls, F J A; Leibman, M O; Moskalenko, N G; Khomutov, A V; Matyshak, G V; Khitun, O V; Forbes, B C; Bhatt, U S; Vonlanthen, C M; Tichý, L

2012-01-01

Satellite-based measurements of the normalized difference vegetation index (NDVI; an index of vegetation greenness and photosynthetic capacity) indicate that tundra environments are generally greening and becoming more productive as climates warm in the Arctic. The greening, however, varies and is even negative in some parts of the Arctic. To help interpret the space-based observations, the International Polar Year (IPY) Greening of the Arctic project conducted ground-based surveys along two >1500 km transects that span all five Arctic bioclimate subzones. Here we summarize the climate, soil, vegetation, biomass, and spectral information collected from the North America Arctic transect (NAAT), which has a more continental climate, and the Eurasia Arctic transect (EAT), which has a more oceanic climate. The transects have broadly similar summer temperature regimes and overall vegetation physiognomy, but strong differences in precipitation, especially winter precipitation, soil texture and pH, disturbance regimes, and plant species composition and structure. The results indicate that summer warmth and NDVI increased more strongly along the more continental transect. (letter)

Evaluating the Consistency of the 1982–1999 NDVI Trends in the Iberian Peninsula across Four Time-series Derived from the AVHRR Sensor: LTDR, GIMMS, FASIR, and PAL-II

Science.gov (United States)

Alcaraz-Segura, Domingo; Liras, Elisa; Tabik, Siham; Paruelo, José; Cabello, Javier

2010-01-01

Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations’ carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982–1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast. PMID:22205868

Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

Energy Technology Data Exchange (ETDEWEB)

Tourre, Y M [METEO-France, Meteopole, 42 Avenue Coriolis, 31057 Toulouse Cedex 1 (France); Jarlan, L [Centre d' Etudes Spatiales de la Biosphere (CESBIO), 18 avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France); Lacaux, J-P [Universite Paul Sabatier (UPS), Observatoire Midi Pyrenees (OMP), 12 Avenue Edouard Belin, 31400 Toulouse (France); Rotela, C H [Instituto de Altos Estudios Espaciales ' Mario Gulich' , Comision Nacional de Actividades Espaciales (CONAE), Universidad Nacional de Cordoba (Argentina); Lafaye, M [CNES, DSP/ARP/AV, 18 Avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France)

2008-10-15

Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high

Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

Energy Technology Data Exchange (ETDEWEB)

Tourre, Y M [METEO-France, Meteopole, 42 Avenue Coriolis, 31057 Toulouse Cedex 1 (France); Jarlan, L [Centre d' Etudes Spatiales de la Biosphere (CESBIO), 18 avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France); Lacaux, J-P [Universite Paul Sabatier (UPS), Observatoire Midi Pyrenees (OMP), 12 Avenue Edouard Belin, 31400 Toulouse (France); Rotela, C H [Instituto de Altos Estudios Espaciales ' Mario Gulich' , Comision Nacional de Actividades Espaciales (CONAE), Universidad Nacional de Cordoba (Argentina); Lafaye, M [CNES, DSP/ARP/AV, 18 Avenue Edouard Belin, F-31401 Toulouse Cedex 4 (France)

2008-10-15

Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high-frequency climate signals such as the

Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

Science.gov (United States)

Tourre, Y. M.; Jarlan, L.; Lacaux, J.-P.; Rotela, C. H.; Lafaye, M.

2008-10-01

Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high-frequency climate signals such as the

Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

International Nuclear Information System (INIS)

Tourre, Y M; Jarlan, L; Lacaux, J-P; Rotela, C H; Lafaye, M

2008-01-01

Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high-frequency climate signals such as the

Characterisation of macrophyte phenology in the Doñana marshland using MODIS NDVI time series from 2000 to 2015

Science.gov (United States)

Fernandez-Carrillo, A.; Rodriguez-Galiano, V. F.; Sanchez-Rodriguez, E.

2017-10-01

The study of the interaction between vegetation development and climate factors is paramount for the management of protected natural areas. Data provided by remote-sensing satellites and derivative products, such as vegetation indices, permit the extraction of basic information regarding the functioning of vegetation masses and their interaction with certain environmental factors. This paper carries out an approach regarding the behaviour of radiation intercepted by aquatic macrophytes present in the Doñana National Park marshland, represented by the plant association Bolboschoenetum maritimi. Based on MODIS NDVI (Normalised Difference Vegetation Index) data, the temporal dynamics of these vegetation masses were studied over a 16-year period (2000-2015), as was their typical annual behaviour, thereby deriving different indicators for seasonal dynamics (NDVI-I, RREL, MAX, MIN, MMAX and MMIN), which help to understand the basic functional characteristics for this type of vegetation. Afterwards, different regression analyses were performed between precipitation and the indicators derived from the NDVI time series. The obtained results indicated that the examined association has a strong dependence on the marshland's flooding processes, requiring a minimum annual precipitation volume (350 mm/year) for proper flooding and vegetation growth development. Furthermore, a strong correlation (r2 =0.70; <0.05) was found between seasonal nature of the vegetation masses, measured via RREL, and precipitation, as well as slightly weaker relationships between precipitation and other indicators, such as the maximum and minimum annual NDVI (r2 =0.43 and r2 =0.61; p<0.05 and p<0.05, respectively).

Categorical likelihood method for combining NDVI and elevation information for cotton precision agricultural applications

Science.gov (United States)

This presentation investigates an algorithm to fuse the Normalized Difference Vegetation Index (NDVI) with LiDAR elevation data to produce a map useful for the site-specific scouting and pest management (Willers et al. 1999; 2005; 2009) of the cotton insect pests, the tarnished plant bug (Lygus lin...

Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia

Directory of Open Access Journals (Sweden)

Dyah R. Panuju

2010-03-01

Full Text Available In addition to forest encroachment, forest fire is a serious problem in Indonesia. Attempts at managing its widespread and frequent occurrence has led to intensive use of remote sensing data. Coarse resolution images have been employed to derive hot spots as an indicator of forest fire. However, most efforts to verify the hot spot data and to verify fire accidents have been restricted to the use of medium or high resolution data. At present, it is difficult to verify solely upon those data due to severe cloud cover and low revisit time. In this paper, we present a method to validate forest fire using NDVI time series data. With the freely available NDVI data from SPOT VEGETATION, we successfully detected changes in time series data which were associated with fire accidents.

Using Moderate-Resolution Temporal NDVI Profiles for High-Resolution Crop Mapping in Years of Absent Ground Reference Data: A Case Study of Bole and Manas Counties in Xinjiang, China

Directory of Open Access Journals (Sweden)

Pengyu Hao

2016-05-01

Full Text Available Most methods used for crop classification rely on the ground-reference data of the same year, which leads to considerable financial and labor cost. In this study, we presented a method that can avoid the requirements of a large number of ground-reference data in the classification year. Firstly, we extracted the Normalized Difference Vegetation Index (NDVI time series profiles of the dominant crops from MODIS data using the historical ground-reference data in multiple years (2006, 2007, 2009 and 2010. Artificial Antibody Network (ABNet was then employed to build reference NDVI time series for each crop based on the historical NDVI profiles. Afterwards, images of Landsat and HJ were combined to obtain 30 m image time series with 15-day acquisition frequency in 2011. Next, the reference NDVI time series were transformed to Landsat/HJ NDVI time series using their linear model. Finally, the transformed reference NDVI profiles were used to identify the crop types in 2011 at 30 m spatial resolution. The result showed that the dominant crops could be identified with overall accuracy of 87.13% and 83.48% in Bole and Manas, respectively. In addition, the reference NDVI profiles generated from multiple years could achieve better classification accuracy than that from single year (such as only 2007. This is mainly because the reference knowledge from multiple years contains more growing conditions of the same crop. Generally, this approach showed potential to identify crops without using large number of ground-reference data at 30 m resolution.

Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale.

Science.gov (United States)

Bro-Jørgensen, Jakob; Brown, Molly E; Pettorelli, Nathalie

2008-11-01

Lek-breeding species are characterized by a negative association between territorial resource availability and male mating success; however, the impact of resources on the overall distribution patterns of the two sexes in lek systems is not clear. The normalized difference vegetation index (NDVI) has recently emerged as a powerful proxy measure for primary productivity, allowing the links between the distributions of animals and resources to be explored. Using NDVI at four spatial resolutions, we here investigate how the distribution of the two sexes in a lek-breeding population of topi antelopes relates to resource abundance before and during the rut. We found that in the dry season preceding the rut, topi density correlated positively with NDVI at the large, but not the fine, scale. This suggests that before the rut, when resources were relatively scant, topi preferred pastures where green grass was widely abundant. The pattern was less pronounced in males, suggesting that the need for territorial attendance prevents males from tracking resources as freely as females do. During the rut, which occurs in the wet season, both male and female densities correlated negatively with NDVI at the fine scale. At this time, resources were generally plentiful and the results suggest that, rather than by resource maximization, distribution during the rut was determined by benefits of aggregating on relatively resource-poor leks for mating, and possibly antipredator, purposes. At the large scale, no correlation between density and NDVI was found during the rut in either sex, which can be explained by leks covering areas too small to be reflected at this resolution. The study illustrates that when investigating spatial organization, it is important: (1) to choose the appropriate analytic scale, and (2) to consider behavioural as well as strictly ecological factors.

Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems

Directory of Open Access Journals (Sweden)

Ali Akbar Zarezadeh

2013-01-01

Full Text Available The application of (smart cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of fuel. Although research activities have increased in this field, high camera prices reflect low adaptation to applications in all fields of agriculture. Smart, low-cost cameras adapted for agricultural applications can overcome this drawback. The normalized difference vegetation index (NDVI for each image pixel is an applicable algorithm to discriminate plant information from the soil background enabled by a large difference in the reflectance between the near infrared (NIR and the red channel optical frequency band. Two aligned charge coupled device (CCD chips for the red and NIR channel are typically used, but they are expensive because of the precise optical alignment required. Therefore, much attention has been given to the development of alternative camera designs. In this study, the advantage of a smart one-chip camera design with NDVI image performance is demonstrated in terms of low cost and simplified design. The required assembly and pixel modifications are described, and new algorithms for establishing an enhanced NDVI image quality for data processing are discussed.

Strategy for the development of a smart NDVI camera system for outdoor plant detection and agricultural embedded systems.

Science.gov (United States)

Dworak, Volker; Selbeck, Joern; Dammer, Karl-Heinz; Hoffmann, Matthias; Zarezadeh, Ali Akbar; Bobda, Christophe

2013-01-24

The application of (smart) cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of fuel. Although research activities have increased in this field, high camera prices reflect low adaptation to applications in all fields of agriculture. Smart, low-cost cameras adapted for agricultural applications can overcome this drawback. The normalized difference vegetation index (NDVI) for each image pixel is an applicable algorithm to discriminate plant information from the soil background enabled by a large difference in the reflectance between the near infrared (NIR) and the red channel optical frequency band. Two aligned charge coupled device (CCD) chips for the red and NIR channel are typically used, but they are expensive because of the precise optical alignment required. Therefore, much attention has been given to the development of alternative camera designs. In this study, the advantage of a smart one-chip camera design with NDVI image performance is demonstrated in terms of low cost and simplified design. The required assembly and pixel modifications are described, and new algorithms for establishing an enhanced NDVI image quality for data processing are discussed.

Mapping Cropland and Major Crop Types Across the Great Lakes Basin Using MODIS-NDVI Data

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This research evaluated the potential for using the MODIS Normalized Difference Vegetation Index (NDVI) 16-day composite (MOD13Q) 250-m time-series data to develop a cropland mapping capability throughout the 480 000 km2 Great Lakes Basin (GLB). Cropland mapping was conducted usi...

[Responses of normalized difference vegetation index (NDVI) to precipitation changes on the grassland of Tibetan Plateau from 2000 to 2015.

Science.gov (United States)

Wang, Zhi Peng; Zhang, Xian Zhou; He, Yong Tao; Li, Meng; Shi, Pei Li; Zu, Jia Xing; Niu, Ben

2018-01-01

Precipitation change is an important factor in the inter-annual variation of grassland growth on the Tibetan Plateau. The total amount, distribution pattern and concentration time are three basic characteristics of precipitation change. The temporal and spatial characteristics of precipitation change were analyzed based on climate data of 145 meteorological stations on the Tibetan Plateau and nearby areas from 2000 to 2015. The total precipitation amount was characterized by annual precipitation, distribution pattern of precipitation during the year was characterized by improved precipitation concentration index (PCI), and precipitation centroid (PC) was defined to indicate the change in precipitation concentrated time. To better illustrate the response of grassland to precipitation change, vegetation growth status was characterized by the maximum value of normalized difference vegetation index (NDVI max ). Results indicated that the annual precipitation and PCI had an apparent gradient across the whole plateau and the latest PC occurred in the southern plateau. NDVI max of alpine shrub grassland was significantly correlated with the change of PCI,increased with even distribution of precipitation during growth period, and limited by the total annual precipitation. Alpine meadow did not show significantly correlations with these three indices. The inter-annual variability of NDVI max of steppe was controlled by both PCI and PC. NDVI max of alpine desert grassland was mainly controlled by annual precipitation. In addition to annual total amount of precipitation, the distribution characteristics of precipitation should be further considered when the influence of precipitation change on different types of vegetation on the Qinghai Tibet Plateau was studied.

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI.

Science.gov (United States)

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km(2). The lake area decreased by -9.3% at an annual rate of -53.7 km(2) yr(-1) during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability.

Insensitivity of Tree-Ring Growth to Temperature and Precipitation Sharpens the Puzzle of Enhanced Pre-Eruption NDVI on Mt. Etna (Italy).

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Seiler, Ruedi; Kirchner, James W; Krusic, Paul J; Tognetti, Roberto; Houlié, Nicolas; Andronico, Daniele; Cullotta, Sebastiano; Egli, Markus; D'Arrigo, Rosanne; Cherubini, Paolo

2017-01-01

On Mt. Etna (Italy), an enhanced Normalized Difference in Vegetation Index (NDVI) signature was detected in the summers of 2001 and 2002 along a distinct line where, in November 2002, a flank eruption subsequently occurred. These observations suggest that pre-eruptive volcanic activity may have enhanced photosynthesis along the future eruptive fissure. If a direct relation between NDVI and future volcanic eruptions could be established, it would provide a straightforward and low-cost method for early detection of upcoming eruptions. However, it is unclear if, or to what extent, the observed enhancement of NDVI can be attributed to volcanic activity prior to the subsequent eruption. We consequently aimed at determining whether an increase in ambient temperature or additional water availability owing to the rise of magma and degassing of water vapour prior to the eruption could have increased photosynthesis of Mt. Etna's trees. Using dendro-climatic analyses we quantified the sensitivity of tree ring widths to temperature and precipitation at high elevation stands on Mt. Etna. Our findings suggest that tree growth at high elevation on Mt. Etna is weakly influenced by climate, and that neither an increase in water availability nor an increase in temperature induced by pre-eruptive activity is a plausible mechanism for enhanced photosynthesis before the 2002/2003 flank eruption. Our findings thus imply that other, yet unknown, factors must be sought as causes of the pre-eruption enhancement of NDVI on Mt. Etna.

CO2, Temperature, and Soil Moisture Interactions Affect NDVI and Reproductive Phenology in Old-Field Plant Communities

Science.gov (United States)

Engel, C.; Weltzin, J.; Norby, R.

2004-12-01

Plant community composition and ecosystem function may be altered by global atmospheric and climate change, including increased atmospheric [CO2], temperature, and varying precipitation regimes. We are conducting an experiment at Oak Ridge National Laboratory (ORNL) utilizing open-top chambers to administer experimental treatments of elevated CO2 (+300 ppm), warming (+ 3 degrees Celsius), and varying soil moisture availability to experimental plant communities constructed of seven common old-field species, including C3 and C4 grasses, forbs, and legumes. During 2004 we monitored plant community phenology (NDVI) and plant reproductive phenology. Early in the year, NDVI was greater in wet treatment plots, and was unaffected by main effects of temperature or CO2. This result suggests that early in the season warming is insufficient to affect early canopy development. Differences in soil moisture sustained throughout the winter and into early spring may constitute an important control on early canopy greenup. Elevated CO2 alleviated detrimental effects of warming on NDVI, but only early in the season. As ambient temperatures increased, elevated temperatures negatively impacted NDVI only in the dry plots. Wetter conditions ameliorate the effects of warming on canopy greenness during the warmer seasons of the year. Warming increased rates of bolting, number of inflorescences, and time to reproductive maturity for Andropogon virginicus (a C4 bunchgrass). Solidago Canadensis (a C3 late-season forb) also produced flowers earlier in elevated temperatures. Conversely, none of the C3 grasses and forbs that bolt or flower in late spring or early summer responded to temperature or CO2. Results indicate that warming and drought may impact plant community phenology, and plant species reproductive phenology. Clearly community phenology is driven by complex interactions among temperature, water, and CO2 that change throughout the season. Our data stresses the importance of

PRESENTED 11/01/05 LAND-COVER CHARACTERIZATION AND CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

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Land-Cover (LC) composition and conversions are important factors that affect ecosystem condition and function. The purpose of this research and development effort is to investigate the feasibility of using MODIS derived Normalized Difference Vegetation Index (NDVI) data to deli...

A normalized difference vegetation index (NDVI) time-series of idle agriculture lands: A preliminary study

NARCIS (Netherlands)

Vaiphasa, C.; Piamduaytham, S.; Vaiphasa, T.; Skidmore, A.K.

2011-01-01

In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all land cover types are plotted and compared. The study area is the agricultural zones in Banphai District, Khonkean, Thailand. The LANDSAT satellite images of different dates were first transformed into

Spatial variability of NDVI at different seasons in the Community of Madrid (Spain)

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Sotoca, Juan J. Martin; Saa-Requejo, Antonio; Borondo, Javier; Tarquis, Ana M.

2015-04-01

Agricultural drought quantification is one of the most important tasks in the characterization process of this natural hazard and its implications in crop insurance. Recently, several vegetation indexes based on remote-sensing data (VI) has been applied to quantify it (Dalezios et al, 2012). VIs are obtained combining several frequency bands that represent the relationship between photosynthesis and absorbed/reflected radiation. The most widely used VI is the Normalized Difference Vegetation Index (NDVI). It is based on the principle that healthy vegetation mainly absorbs visible light and reflects the near-infrared frequency band. Drought can be highly localized, and several authors have recognized the critical role of soil moisture and its spatial variability in agricultural losses (Anderson et al., 2011). Therefore, it is important to delimit locations within a homogeneous area that will share main NDVI statistics and in which the same threshold value can be applied to define drought event. In order to do so, we have applied for the first time in this context the method of singularity maps (Cheng and Agterberg, 1996) commonly used in localization of mineral deposits. The NDVI singularity maps calculated in each season through 2011/2012 are showed and discussed (Martín-Sotoca, 2014). References Anderson, M:C:, C. R. Hain, B. Wardlow, J. R. Mecikalski and W. P. Kustas (2011) Evaluation of drought indices based on thermal remote sensing of evapotranspiration over the continental United States. J. Climate, 24, 2025-2044. Dalezios, N.R., A. Blanta, N.V. Spyropoulos and A.M. Tarquis (2012) Risk identification of agricultural drought for sustainable Agroecosystems. Nat. Hazards Earth Syst. Sci., 14, 2435-2448. Cheng, Q. and F.P. Agterberg (1996) Multifractal modeling and spatial statistics. Math. Geol., 28, 1-16. Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones en el Seguro Agrario. Master Thesis, UPM (In Spanish

High NDVI and Potential Canopy Photosynthesis of South American Subtropical Forests despite Seasonal Changes in Leaf Area Index and Air Temperature

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Piedad M. Cristiano

2014-02-01

Full Text Available The canopy photosynthesis and carbon balance of the subtropical forests are not well studied compared to temperate and tropical forest ecosystems. The main objective of this study was to assess the seasonal dynamics of Normalized Difference Vegetation Index (NDVI and potential canopy photosynthesis in relation to seasonal changes in leaf area index (LAI, chlorophyll concentration, and air temperatures of NE Argentina subtropical forests throughout the year. We included in the analysis several tree plantations (Pinus, Eucalyptus and Araucaria species that are known to have high productivity. Field studies in native forests and tree plantations were conducted; stem growth rates, LAI and leaf chlorophyll concentration were measured. MODIS satellite-derived LAI (1 km SIN Grid and NDVI (250m SIN Grid from February 2000 to 2012 were used as a proxy of seasonal dynamics of potential photosynthetic activity at the stand level. The remote sensing LAI of the subtropical forests decreased every year from 6 to 5 during the cold season, similar to field LAI measurements, when temperatures were 10 °C lower than during the summer. The yearly maximum NDVI values were observed during a few months in autumn and spring (March through May and November, respectively because high and low air temperatures may have a small detrimental effect on photosynthetic activity during both the warm and the cold seasons. Leaf chlorophyll concentration was higher during the cold season than the warm season which may have a compensatory effect on the seasonal variation of the NDVI values. The NDVI of the subtropical forest stands remained high and fairly constant throughout the year (the intra-annual coefficient of variation was 1.9%, and were comparable to the values of high-yield tree plantations. These results suggest that the humid subtropical forests in NE Argentina potentially could maintain high canopy photosynthetic activity throughout the year and thus this ecosystem may

An NDVI-Based Vegetation Phenology Is Improved to be More Consistent with Photosynthesis Dynamics through Applying a Light Use Efficiency Model over Boreal High-Latitude Forests

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Siheng Wang

2017-07-01

Full Text Available Remote sensing of high-latitude forests phenology is essential for understanding the global carbon cycle and the response of vegetation to climate change. The normalized difference vegetation index (NDVI has long been used to study boreal evergreen needleleaf forests (ENF and deciduous broadleaf forests. However, the NDVI-based growing season is generally reported to be longer than that based on gross primary production (GPP, which can be attributed to the difference between greenness and photosynthesis. Instead of introducing environmental factors such as land surface or air temperature like previous studies, this study attempts to make VI-based phenology more consistent with photosynthesis dynamics through applying a light use efficiency model. NDVI (MOD13C2 was used as a proxy for both fractional of absorbed photosynthetically active radiation (APAR and light use efficiency at seasonal time scale. Results show that VI-based phenology is improved towards tracking seasonal GPP changes more precisely after applying the light use efficiency model compared to raw NDVI or APAR, especially over ENF.

Monitoring Grassland Seasonal Carbon Dynamics, by Integrating MODIS NDVI, Proximal Optical Sampling, and Eddy Covariance Measurements

Czech Academy of Sciences Publication Activity Database

Nestola, E.; Calfapietra, Carlo; Emmerton, C. A.; Wrong, Ch. Y. S.; Thayer, D. R.; Gamon, J. A.

2016-01-01

Roč. 8, č. 3 (2016), č. článku 260. ISSN 2072-4292 Institutional support: RVO:67179843 Keywords : grassland * NDVI * CO2 flux * optical remote sensing * LUE model * gap filling Subject RIV: EH - Ecology, Behaviour Impact factor: 3.244, year: 2016

Evaluating the Relationship between Field Aerodynamic Roughness and the MODIS BRDF, NDVI, and Wind Speed over Grassland

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Qiang Xing

2017-01-01

Full Text Available Aerodynamic roughness (AR is an important parameter that influences the momentum and energy exchange between the earth’s surface and the atmosphere. In this study, profile wind data observed during the vegetation growing period (April–September in 2013 and 2014 at the A’rou grassland station, which is in the upstream of the Heihe River Basin (HRB, were used to determine the relationship between the field AR and the Moderate-resolution Imaging Spectroradiometer (MODIS near-infrared (NIR bi-directional reflectance distribution function (BRDF R index, the normalized difference vegetation index (NDVI, and a combination of these indices. In addition, the relationship between the average wind speed at a height of 1 m and the field AR is also presented. The results indicate that the MODIS NIR BRDF_R index and the NDVI are both sensitive indicators of the AR over grassland (R2: 0.5228 for NIR BRDF_R; R2: 0.579 for NDVI. Moreover, the combined index shows a significantly increased R2 value of 0.721, which is close to the result inferred from the wind speed (R2: 0.7411. The proposed remote sensing-based combination index (CI has the potential for use in evaluations of the AR over grasslands during growing season and its sensitivity can reach levels that are comparable to considering the effects of wind speed, which usually requires ground-based observations.

Correlation of meteorological parameters and remotely sensed normalized difference vegetation index (NDVI) with cotton leaf curl virus (CLCV) in Multan

International Nuclear Information System (INIS)

Ahmed, A; Akhtar, A; Khalid, B; Shamim, A

2013-01-01

Climate change and weather has a profound effect on the spread of Cotton Leaf Curl Virus (CLCV) which is transmitted by whitefly. Climate change is altering temperature and precipitation patterns, resulting in the shift of some insect/pest from small population to large population thus effecting crops yield. To find out the relationship between the weather conditions, outburst of CLCV and changes in Normalized Difference Vegetation Index (NDVI) values due to the outburst of CLCV, a study was carried out for tehsil Multan. Data was acquired for the months of June, July, August and September for the year 2010. Regression analysis between CLCV and meteorological conditions as well as between CLCV and NDVI was performed. Meteorological parameters included temperature, humidity, precipitation, cloud cover, wind direction, pan evaporation and sunshine hours. NDVI values were calculated from SPOT satellite imagery (1km) using ArcMap10 and WinDisp v5.1. Correlation coefficients obtained in most of the cases were acceptable however the significance F and P-value were higher than their critical value at 95% level of significance. Therefore significant correlation was found only between CLCV and temperature and between CLCV and PAN evaporation during the month of July.

Utilização do software estatístico r na previsão de séries temporais: série prêmio de resseguro

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Rafael Ferraz de Moraes

2014-08-01

Full Text Available 10.12957/cadest.2011.15727O objetivo dos autores no presente artigo é a utilização de modelos estocásticos da família SARIMA multiplicativo, de Box & Jenkins, para análise e previsão de séries temporais. Para tanto, é utilizado o software R, um pacote estatístico desenvolvido em ambiente livre e muito utilizado nas universidades. Para o estudo de caso de aplicação e funcionalidade do software, nas fases de identificação e estimação de modelos, foi utilizada a série temporal Prêmio de Resseguro de jan/2001 a dez/2008. Dessa forma, são descritos os modelos utilizados, os passos básicos com a linguagem de programação R, os resultados obtidos e as considerações finais

Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data

International Nuclear Information System (INIS)

Kasischke, E.S.; French, N.H.F.; Harrell, P.; Christensen, N.L. Jr.; Ustin, S.L.; Barry, D.

1993-01-01

Normalized difference vegetation index (NDVI) composite image data, produced from AVHRR data collected in 1990, were evaluated for locating and mapping the areal extent of wildfires in the boreal forests of Alaska during that year. A technique was developed to map forest fire boundaries by subtracting a late-summer AVHRR NDVI image from an early summer scene. The locations and boundaries of wildfires within the interior region of Alaska were obtained from the Alaska Fire Service, and compared to the AVHRR-derived fire-boundary map. It was found that AVHRR detected 89.5% of all fires with sizes greater than 2,000ha with no false alarms and that, for most cases, the general shape of the fire boundary detected by AVHRR matched those mapped by field observers. However, the total area contained within the fire boundaries mapped by AVHRR were only 61% of those mapped by the field observers. However, the AVHRR data used in this study did not span the entire time period during which fires occurred, and it is believed the areal estimates could be improved significantly if an expanded AVHRR data set were used

Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale

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Louis Kouadio

2014-10-01

Full Text Available Crop yield forecasting plays a vital role in coping with the challenges of the impacts of climate change on agriculture. Improvements in the timeliness and accuracy of yield forecasting by incorporating near real-time remote sensing data and the use of sophisticated statistical methods can improve our capacity to respond effectively to these challenges. The objectives of this study were (i to investigate the use of derived vegetation indices for the yield forecasting of spring wheat (Triticum aestivum L. from the Moderate resolution Imaging Spectroradiometer (MODIS at the ecodistrict scale across Western Canada with the Integrated Canadian Crop Yield Forecaster (ICCYF; and (ii to compare the ICCYF-model based forecasts and their accuracy across two spatial scales-the ecodistrict and Census Agricultural Region (CAR, namely in CAR with previously reported ICCYF weak performance. Ecodistricts are areas with distinct climate, soil, landscape and ecological aspects, whereas CARs are census-based/statistically-delineated areas. Agroclimate variables combined respectively with MODIS-NDVI and MODIS-EVI indices were used as inputs for the in-season yield forecasting of spring wheat during the 2000–2010 period. Regression models were built based on a procedure of a leave-one-year-out. The results showed that both agroclimate + MODIS-NDVI and agroclimate + MODIS-EVI performed equally well predicting spring wheat yield at the ECD scale. The mean absolute error percentages (MAPE of the models selected from both the two data sets ranged from 2% to 33% over the study period. The model efficiency index (MEI varied between −1.1 and 0.99 and −1.8 and 0.99, respectively for the agroclimate + MODIS-NDVI and agroclimate + MODIS-EVI data sets. Moreover, significant improvement in forecasting skill (with decreasing MAPE of 40% and 5 times increasing MEI, on average was obtained at the finer, ecodistrict spatial scale, compared to the coarser CAR scale. Forecast

CHARACTERIZING LANDSCAPE SPATIAL HETEROGENEITY USING SEMIVARIOGRAM PARAMETERS DERIVED FROM NDVI IMAGES

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Eduarda Martiniano de Oliveira Silveira

2017-12-01

Full Text Available Assuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index was generated in an area of Brazilian amazon tropical forest (1,000 km².We selected samples (1 x 1 km from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property and range (φ-the length scale of the spatial structures of objects parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA approaches.

Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data

Science.gov (United States)

Jarchow, Christopher J.; Nagler, Pamela L.; Glenn, Edward P.

2017-01-01

In the southwestern U.S., many riparian ecosystems have been altered by dams, water diversions, and other anthropogenic activities. This is particularly true of the Colorado River, where numerous dams and agricultural diversions have affected this water course, especially south of the U.S.–Mexico border. In the spring of 2014, 130 million cubic meters of water was released to the lower Colorado River Delta in Mexico. To understand the impact of this pulse flow release on vegetation in the delta’s riparian corridor, we analyzed a modified form of Landsat 8 Operational Land Imager (OLI) Normalized Difference Vegetation Index (NDVI*) data. We assessed greenup during the growing period and estimated actual evapotranspiration (ETa) for the period prior to (yr. 2013) and following (i.e., yr. 2014 and 2015) the pulse flow. We found a significant increase in NDVI* from 2013 to 2014 (P NDVI*. As a long term solution to the declining condition of vegetation, additional pulse releases are likely needed for restoration and survival of riparian plant communities in the Colorado River Delta.

A Remote Sensing Approach for Regional-Scale Mapping of Agricultural Land-Use Systems Based on NDVI Time Series

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Beatriz Bellón

2017-06-01

Full Text Available In response to the need for generic remote sensing tools to support large-scale agricultural monitoring, we present a new approach for regional-scale mapping of agricultural land-use systems (ALUS based on object-based Normalized Difference Vegetation Index (NDVI time series analysis. The approach consists of two main steps. First, to obtain relatively homogeneous land units in terms of phenological patterns, a principal component analysis (PCA is applied to an annual MODIS NDVI time series, and an automatic segmentation is performed on the resulting high-order principal component images. Second, the resulting land units are classified into the crop agriculture domain or the livestock domain based on their land-cover characteristics. The crop agriculture domain land units are further classified into different cropping systems based on the correspondence of their NDVI temporal profiles with the phenological patterns associated with the cropping systems of the study area. A map of the main ALUS of the Brazilian state of Tocantins was produced for the 2013–2014 growing season with the new approach, and a significant coherence was observed between the spatial distribution of the cropping systems in the final ALUS map and in a reference map extracted from the official agricultural statistics of the Brazilian Institute of Geography and Statistics (IBGE. This study shows the potential of remote sensing techniques to provide valuable baseline spatial information for supporting agricultural monitoring and for large-scale land-use systems analysis.

Estimation of leaf area index using ground-based remote sensed NDVI measurements: validation and comparison with two indirect techniques

International Nuclear Information System (INIS)

Pontailler, J.-Y.; Hymus, G.J.; Drake, B.G.

2003-01-01

This study took place in an evergreen scrub oak ecosystem in Florida. Vegetation reflectance was measured in situ with a laboratory-made sensor in the red (640-665 nm) and near-infrared (750-950 nm) bands to calculate the normalized difference vegetation index (NDVI) and derive the leaf area index (LAI). LAI estimates from this technique were compared with two other nondestructive techniques, intercepted photosynthetically active radiation (PAR) and hemispherical photographs, in four contrasting 4 m 2 plots in February 2000 and two 4m 2 plots in June 2000. We used Beer's law to derive LAI from PAR interception and gap fraction distribution to derive LAI from photographs. The plots were harvested manually after the measurements to determine a 'true' LAI value and to calculate a light extinction coefficient (k). The technique based on Beer's law was affected by a large variation of the extinction coefficient, owing to the larger impact of branches in winter when LAI was low. Hemispherical photographs provided satisfactory estimates, slightly overestimated in winter because of the impact of branches or underestimated in summer because of foliage clumping. NDVI provided the best fit, showing only saturation in the densest plot (LAI = 3.5). We conclude that in situ measurement of NDVI is an accurate and simple technique to nondestructively assess LAI in experimental plots or in crops if saturation remains acceptable. (author)

Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA

Science.gov (United States)

Gu, Yingxin; Wylie, Bruce K.; Bliss, Norman B.

2013-01-01

This study assessed and described a relationship between satellite-derived growing season averaged Normalized Difference Vegetation Index (NDVI) and annual productivity for grasslands within the Greater Platte River Basin (GPRB) of the United States. We compared growing season averaged NDVI (GSN) with Soil Survey Geographic (SSURGO) database rangeland productivity and flux tower Gross Primary Productivity (GPP) for grassland areas. The GSN was calculated for each of nine years (2000–2008) using the 7-day composite 250-m eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. Strong correlations exist between the nine-year mean GSN (MGSN) and SSURGO annual productivity for grasslands (R2 = 0.74 for approximately 8000 pixels randomly selected from eight homogeneous regions within the GPRB; R2 = 0.96 for the 14 cluster-averaged points). Results also reveal a strong correlation between GSN and flux tower growing season averaged GPP (R2 = 0.71). Finally, we developed an empirical equation to estimate grassland productivity based on the MGSN. Spatially explicit estimates of grassland productivity over the GPRB were generated, which improved the regional consistency of SSURGO grassland productivity data and can help scientists and land managers to better understand the actual biophysical and ecological characteristics of grassland systems in the GPRB. This final estimated grassland production map can also be used as an input for biogeochemical, ecological, and climate change models.

NDVI, scale invariance and the modifiable areal unit problem : An assessment of vegetation in the Adelaide Parklands

NARCIS (Netherlands)

Nouri, Hamideh; Anderson, Sharolyn; Sutton, Paul; Beecham, Simon; Nagler, Pamela; Jarchow, Christopher J.; Roberts, Dar A.

2017-01-01

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem

Social vulnerability to heat in Greater Atlanta, USA: spatial pattern of heat, NDVI, socioeconomics and household composition

Science.gov (United States)

Sim, Sunhui

2017-10-01

The purpose of the article is evaluating spatial patterns of social vulnerability to heat in Greater Atlanta in 2015. The social vulnerability to heat is an index of socioeconomic status, household composition, land surface temperature and normalized differential vegetation index (NDVI). Land surface temperature and NDVI were derived from the red, NIR and thermal infrared (TIR) of a Landsat OLI/TIRS images collected on September 14, 2015. The research focus is on the variation of heat vulnerability in Greater Atlanta. The study found that heat vulnerability is highly clustered spatially, resulting in "hot spots" and "cool spots". The results show significant health disparities. The hotspots of social vulnerability to heat occurred in neighborhoods with lower socioeconomic status as measured by low education, low income and more poverty, greater proportion of elderly people and young children. The findings of this study are important for identifying clusters of heat vulnerability and the relationships with social factors. These significant results provide a basis for heat intervention services.

Modelling the Phenological Relationships of Questing Immature Ixodes Ricinus (Ixodidae) Using Temperature and NDVI Data.

Science.gov (United States)

Alonso-Carné, J; García-Martín, A; Estrada-Peña, A

2016-02-01

All active stages of the tick Ixodes ricinus were collected monthly at two sites in northern Spain between the years 2000 and 2007. We used percentile accumulation of the active stage in the environment to evaluate simple and coherent correlations between accumulation of the active stages of larvae and nymphs and medium-resolution MODIS satellite-derived information on the climate, including monthly and accumulated temperature and the Normalized Difference Vegetation Index (NDVI). This framework is not intended to predict the actual abundance of ticks in the field as a measure of the hazard to humans, but to provide a basic structure for addressing the phenology of the tick in its geographic range. We demonstrated that the accumulation of larval ticks in the active stage is a sigmoid function of the accumulated temperature from the beginning of the calendar year. We also demonstrated that the accumulated temperature necessary to recruit nymphs from the questing larval stage is a function of the changes in accumulated larvae and nymphs and the accumulated temperature and NDVI recorded by the Aqua sensor. The low p-values obtained in the regressions confirmed that such recruitment can be calculated using time intervals to estimate, for example, the beginning of the questing period or the time of the year when a population peak can be expected. The comparison among predicted and actual accumulated temperatures between larvae and nymph recruitment had an averaged error of ±20 days in one complete year. The use of accumulated temperature and NDVI proposed in this study opens up the re-evaluation of reports on the phenology of the tick in Europe. This framework is intended to evaluate the same correlations along the tick's range and predict its phenological patterns in areas of pathogen transmission risk for humans. © 2015 Blackwell Verlag GmbH.

QTL mapping of root traits in phosphorus-deficient soils reveals important genomic regions for improving NDVI and grain yield in barley.

Science.gov (United States)

Gong, Xue; McDonald, Glenn

2017-09-01

Major QTLs for root rhizosheath size are not correlated with grain yield or yield response to phosphorus. Important QTLs were found to improve phosphorus efficiency. Root traits are important for phosphorus (P) acquisition, but they are often difficult to characterize and their breeding values are seldom assessed under field conditions. This has shed doubts on using seedling-based criteria of root traits to select and breed for P efficiency. Eight root traits were assessed under controlled conditions in a barley doubled-haploid population in soils differing in P levels. The population was also phenotyped for grain yield, normalized difference vegetation index (NDVI), grain P uptake and P utilization efficiency at maturity (PutE GY ) under field conditions. Several quantitative traits loci (QTLs) from the root screening and the field trials were co-incident. QTLs for root rhizosheath size and root diameter explained the highest phenotypic variation in comparison to QTLs for other root traits. Shared QTLs were found between root diameter and grain yield, and total root length and PutE GY . A common major QTL for rhizosheath size and NDVI was mapped to the HvMATE gene marker on chromosome 4H. Collocations between major QTLs for NDVI and grain yield were detected on chromosomes 6H and 7H. When results from BIP and MET were combined, QTLs detected for grain yield were also those QTLs found for NDVI. QTLs qGY5H, qGY6H and qGY7Hb on 7H were robust QTLs in improving P efficiency. A selection of multiple loci may be needed to optimize the breeding outcomes due to the QTL x Environment interaction. We suggest that rhizosheath size alone is not a reliable trait to predict P efficiency or grain yield.

A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

Energy Technology Data Exchange (ETDEWEB)

Huang, Shengzhi; Ming, Bo; Huang, Qiang; Leng, Guoyong; Hou, Beibei

2017-05-05

It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecasting models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.

Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data

DEFF Research Database (Denmark)

Proud, Simon Richard; Rasmussen, M.O.; Fensholt, R.

2010-01-01

. When examining the Normalised Difference Vegetation Index (NDVI), the relative difference between SMAC and in-situ values decreases by 1.5% with the improvements in place. Similarly, the mean relative difference between SMAC and 6S reflectance values decreases by a mean of 13, 14.5 and 8...

Monitoring phenology of photosynthesis in temperate evergreen and mixed deciduous forests using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) at leaf and canopy scales

Science.gov (United States)

Wong, C. Y.; Arain, M. A.; Ensminger, I.

2016-12-01

Evergreen conifers in boreal and temperate regions undergo strong seasonal changes in photoperiod and temperatures, which determines their phenology of high photosynthetic activity in the growing season and downregulation during the winter. Monitoring the timing of the transition between summer activity and winter downregulation in evergreens is difficult since this is a largely invisible process, unlike in deciduous trees that have a visible budding and a sequence of leaf unfolding in the spring and leaf abscission in the fall. The light-use efficiency (LUE) model estimates gross primary productivity (GPP) and may be parameterized using remotely sensed vegetation indices. Using spectral reflectance data, we derived the normalized difference vegetation index (NDVI), a measure of leaf "greenness", and the photochemical reflectance index (PRI), a proxy for chlorophyll:carotenoid ratios which is related to photosynthetic activity. To better understand the relationship between these vegetation indices and photosynthetic activity and to contrast this relationship between plant functional types, the phenology of NDVI, PRI and photosynthesis was monitored in an evergreen forest and a mixed deciduous forest at the leaf and canopy scale. Our data indicates that the LUE model can be parameterized by NDVI and PRI to track forest phenology. Differences in the sensitivity of PRI and NDVI will be discussed. These findings have implications to address the phenology of evergreen conifers by using PRI to complement NDVI in the LUE model, potentially improving model productivity estimates in northern hemisphere forests, that are dominated by conifers.

Relation of NDVI obtained from different remote sensing at different space and resolutions sensors in Spanish Dehesas

Science.gov (United States)

Escribano Rodríguez, Juan; Tarquis, Ana M.; Saa-Requejo, Antonio; Díaz-Ambrona, Carlos G. H.

2015-04-01

Satellite data are an important source of information and serve as monitoring crops on large scales. There are several indexes, but the most used for monitoring vegetation is NDVI (Normalized Difference Vegetation Index), calculated from the spectral bands of red (RED) and near infrared (NIR), obtaining the value according to relationship: [(NIR - RED) / (NIR + RED)]. During the years 2010-2013 monthly monitoring was conducted in three areas of Spain (Salamanca, Caceres and Cordoba). Pasture plots were selected and satellite images of two different sensors, DEIMOS-1 and MODIS were obtained. DEIMOS-1 is based on the concept Microsat-100 from Surrey. It is designed for imaging the Earth with a resolution good enough to study terrestrial vegetation cover (20x20 m), although with a wide range of visual field (600 km) to get those images with high temporal resolution. By contrast, MODIS images present a much lower spatial resolution (500x500 m). Indices obtained from both sensors to the same area and date are compared and the results show r2 = 0.56; r2 = 0.65 and r2 = 0.90 for the areas of Salamanca, Cáceres and Cordoba respectively. According to the results obtained show that the NDVI obtained by MODIS is slightly larger than that obtained by the sensor for DEIMOS for same time and area. References J.A. Escribano, C.G.H. Diaz-Ambrona, L. Recuero, M. Huesca, V. Cicuendez, A. Palacios-Orueta y A.M. Tarquis. Aplicacion de Indices de Vegetacion para evaluar la falta de produccion de pastos y montaneras en dehesas. I Congreso Iberico de la Dehesa y el Montado. 6-7 Noviembre, 2013, Badajoz. J.A. Escribano Rodriguez, A.M. Tarquis, C.G. Hernandez Diaz-Ambrona. Pasture Drought Insurance Based on NDVI and SAVI. Geophysical Research Abstracts, 14, EGU2012-13945, 2012. EGU General Assembly 2012. Juan Escribano Rodriguez, Carmelo Alonso, Ana Maria Tarquis, Rosa Maria Benito, Carlos Hernandez Diaz-Ambrona. Comparison of NDVI fields obtained from different remote sensors

Estimation of leaf area index using ground-based remote sensed NDVI measurements: validation and comparison with two indirect techniques

Energy Technology Data Exchange (ETDEWEB)

Pontailler, J.-Y. [Univ. Paris-Sud XI, Dept. d' Ecophysiologie Vegetale, Orsay Cedex (France); Hymus, G.J.; Drake, B.G. [Smithsonian Environmental Research Center, Kennedy Space Center, Florida (United States)

2003-06-01

This study took place in an evergreen scrub oak ecosystem in Florida. Vegetation reflectance was measured in situ with a laboratory-made sensor in the red (640-665 nm) and near-infrared (750-950 nm) bands to calculate the normalized difference vegetation index (NDVI) and derive the leaf area index (LAI). LAI estimates from this technique were compared with two other nondestructive techniques, intercepted photosynthetically active radiation (PAR) and hemispherical photographs, in four contrasting 4 m{sup 2} plots in February 2000 and two 4m{sup 2} plots in June 2000. We used Beer's law to derive LAI from PAR interception and gap fraction distribution to derive LAI from photographs. The plots were harvested manually after the measurements to determine a 'true' LAI value and to calculate a light extinction coefficient (k). The technique based on Beer's law was affected by a large variation of the extinction coefficient, owing to the larger impact of branches in winter when LAI was low. Hemispherical photographs provided satisfactory estimates, slightly overestimated in winter because of the impact of branches or underestimated in summer because of foliage clumping. NDVI provided the best fit, showing only saturation in the densest plot (LAI = 3.5). We conclude that in situ measurement of NDVI is an accurate and simple technique to nondestructively assess LAI in experimental plots or in crops if saturation remains acceptable. (author)

Assessing the Influence of Precipitation Variability on the Vegetation Dynamics of the Mediterranean Rangelands using NDVI and Machine Learning

Science.gov (United States)

Daliakopoulos, Ioannis; Tsanis, Ioannis

2017-04-01

Mitigating the vulnerability of Mediterranean rangelands against degradation is limited by our ability to understand and accurately characterize those impacts in space and time. The Normalized Difference Vegetation Index (NDVI) is a radiometric measure of the photosynthetically active radiation absorbed by green vegetation canopy chlorophyll and is therefore a good surrogate measure of vegetation dynamics. On the other hand, meteorological indices such as the drought assessing Standardised Precipitation Index (SPI) are can be easily estimated from historical and projected datasets at the global scale. This work investigates the potential of driving Random Forest (RF) models with meteorological indices to approximate NDVI-based vegetation dynamics. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The updated E-OBS-v13.1 dataset of the ENSEMBLES EU FP6 program provides observed monthly meteorological input to estimate SPI over the Mediterranean rangelands. RF models are trained to depict vegetation dynamics using the latest version (3g.v1) of the third generation GIMMS NDVI generated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) sensors. Analysis is conducted for the period 1981-2015 at a gridded spatial resolution of 25 km. Preliminary results demonstrate the potential of machine learning algorithms to effectively mimic the underlying physical relationship of drought and Earth Observation vegetation indices to provide estimates based on precipitation variability.

Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer

CSIR Research Space (South Africa)

Wessels, Konrad J

2011-04-01

Full Text Available of sufficient field data. The authors suggest that such an approach is not sufficiently rigorous. Therefore, they demonstrate an approach which simulates land degradation so that the intensity, rate and timing of the reduction in NDVI can be controlled, in order...

Using classification and NDVI differencing methods for monitoring sparse vegetation coverage: a case study of saltcedar in Nevada, USA.

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A change detection experiment for an invasive species, saltcedar, near Lovelock, Nevada, was conducted with multi-date Compact Airborne Spectrographic Imager (CASI) hyperspectral datasets. Classification and NDVI differencing change detection methods were tested, In the classification strategy, a p...

Confiabilidade de medidas volumétricas de estruturas temporais mesiais Reliability of mesial temporal lobe volumetric measures

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Renato L. Marchetti

2002-06-01

Full Text Available MOTIVO DO ESTUDO: O desenvolvimento de técnicas confiáveis para a realização de medidas volumétricas de estruturas temporais mesiais (amígdala, hipocampo e giro para-hipocampal em exames de ressonância magnética (RM pode fornecer dados para o estudo de vários transtornos neuropsiquiátricos, particularmente epilepsia do lobo temporal, doença de Alzheimer e esquizofrenia. MÉTODO: Investigamos essas técnicas realizando estudo de confiabilidade intra-observador (IO e entre-observador (EO, envolvendo controles normais, pacientes com epilepsia e pacientes com doença de Alzheimer, através do coeficiente de correlação intra-classe (CCI. RESULTADOS: A confiabilidade IO para as estruturas analisadas variou de 0,93 a 0,99 (pRATIONALE: The development of reliable techniques for volumetric measurement of mesial temporal structures (amygdala, hypocampus and parahypocampal gyrus on magnetic resonance imaging (MRI can provide data for the study of neuropsychiatric disorders, mainly temporal lobe epilepsy, Alzheimer´s disease and schizophrenia. METHOD: We investigated these techniques performing intraobserver and interobserver reliability study concerning normal controls, epilepsy and Alzheimer's disease patients using the intra-class correlation coefficient. RESULTS: Intra-observer reliability of evaluated structures ranged from 0.93 to 0.99 (p<0.001. Inter-observer reliability ranged from 0.70 to 0.95 (p <= 0.001. CONCLUSION: The results suggest that the technique of MRI morphometry of mesial temporal regions can be considered a reliable tool which may help in the investigation of neuropsychiatric disorders, since used by adequately trained clinicians and researchers.

Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI

Science.gov (United States)

Pervez, Md Shahriar; Budde, Michael; Rowland, James

2014-01-01

Agricultural production capacity contributes to food security in Afghanistan and is largely dependent on irrigated farming, mostly utilizing surface water fed by snowmelt. Because of the high contribution of irrigated crops (> 80%) to total agricultural production, knowing the spatial distribution and year-to-year variability in irrigated areas is imperative to monitoring food security for the country. We used 16-day composites of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to create 23-point time series for each year from 2000 through 2013. Seasonal peak values and time series were used in a threshold-dependent decision tree algorithm to map irrigated areas in Afghanistan for the last 14 years. In the absence of ground reference irrigated area information, we evaluated these maps with the irrigated areas classified from multiple snapshots of the landscape during the growing season from Landsat 5 optical and thermal sensor images. We were able to identify irrigated areas using Landsat imagery by selecting as irrigated those areas with Landsat-derived NDVI greater than 0.30–0.45, depending on the date of the Landsat image and surface temperature less than or equal to 310 Kelvin (36.9 ° C). Due to the availability of Landsat images, we were able to compare with the MODIS-derived maps for four years: 2000, 2009, 2010, and 2011. The irrigated areas derived from Landsat agreed well r2 = 0.91 with the irrigated areas derived from MODIS, providing confidence in the MODIS NDVI threshold approach. The maps portrayed a highly dynamic irrigated agriculture practice in Afghanistan, where the amount of irrigated area was largely determined by the availability of surface water, especially snowmelt, and varied by as much as 30% between water surplus and water deficit years. During the past 14 years, 2001, 2004, and 2008 showed the lowest levels of irrigated area (~ 1.5 million hectares), attesting to

Patterns of zone management uncertainty in cotton using tarnished plant bug distributions, NDVI, soil EC, yield and thermal imagery

Science.gov (United States)

Management zones for various crops have been delineated using NDVI (Normalized Difference Vegetation Index), apparent bulk soil electrical conductivity (ECa - Veris), and yield data; however, estimations of uncertainty for these data layers are equally important considerations. The objective of this...

Environmental Drivers of NDVI-Based Vegetation Phenology in Central Asia

Directory of Open Access Journals (Sweden)

Jahan Kariyeva

2011-02-01

Full Text Available Through the application and use of geospatial data, this study aimed to detect and characterize some of the key environmental drivers contributing to landscape-scale vegetation response patterns in Central Asia. The objectives of the study were to identify the variables driving the year-to-year vegetation dynamics in three regional landscapes (desert, steppe, and mountainous; and to determine if the identified environmental drivers can be used to explain the spatial-temporal variability of these spatio-temporal dynamics over time. It was posed that patterns of change in terrestrial phenology, derived from the 8 km bi-weekly time series of Normalized Difference Vegetation Index (NDVI data acquired by the Advanced Very High Resolution Radiometer (AVHRR satellites (1981–2008, can be explained through a multi-scale analysis of a suite of environmental drivers. Multiple linear stepwise regression analyses were used to test the hypotheses and address the objectives of the study. The annually computed phenological response variables or pheno-metricstime (season start, season length, and an NDVI-based productivity metric were modeled as a function of ten environmental factors relating to soil, topography, and climate. Each of the three studied regional landscapes was shown to be governed by a distinctive suite of environmental drivers. The phenological responses of the steppe landscapes were affected by the year-to-year variation in temperature regimes. The phenology of the mountainous landscapes was influenced primarily by the elevation gradient. The phenological responses of desert landscapes were demonstrated to have the greatest variability over time and seemed to be affected by soil carbon content and year-to-year variation of both temperature regimes and winter precipitation patterns. Amounts and scales of observed phenological variability over time (measured through coefficient of variation for each pheno-metrictime in each of the regional

Assessment of MODIS sun-sensor geometry variations effect on observed NDVI using MSG SEVIRI geostationary data

DEFF Research Database (Denmark)

Fensholt, R.; Sandholt, I.; Proud, Simon Richard

2010-01-01

The quality of Earth observation (EO) based vegetation monitoring has improved during recent years, which can be attributed to the enhanced sensor design of new satellites such as MODIS (Moderate Resolution Imaging Spectroradiometer) on Terra and Aqua. It is however expected that sun-sensor geome......The quality of Earth observation (EO) based vegetation monitoring has improved during recent years, which can be attributed to the enhanced sensor design of new satellites such as MODIS (Moderate Resolution Imaging Spectroradiometer) on Terra and Aqua. It is however expected that sun......-sensor geometry variations will have a more visible impact on the Normalized Difference Vegetation Index (NDVI) from MODIS compared to earlier data sources, since noise related to atmosphere and sensor calibration is substantially reduced in the MODIS data stream. For this reason, the effect of varying MODIS......, including a red and NIR band, and the high temporal resolution (15 min) of data, enabling MSG data to be used as a reference for estimating MODIS surface reflectance and NDVI variations caused by varying sun-sensor geometry. The study was performed on data covering West Africa for periods of lowest possible...

Downscaling of Open Coarse Precipitation Data through Spatial and Statistical Analysis, Integrating NDVI, NDWI, Elevation, and Distance from Sea

Directory of Open Access Journals (Sweden)

Hicham Ezzine

2017-01-01

Full Text Available This study aims to improve the statistical spatial downscaling of coarse precipitation (TRMM 3B43 product and also to explore its limitations in the Mediterranean area. It was carried out in Morocco and was based on an open dataset including four predictors (NDVI, NDWI, DEM, and distance from sea that explain TRMM 3B43 product. For this purpose, four groups of models were established based on different combinations of the four predictors, in order to compare from one side NDVI and NDWI based models and the other side stepwise with multiple regression. The models that have given rise to the best approximations and best fits were used to downscale TRMM 3B43 product. The resulting downscaled and calibrated precipitations were validated by independent RGS. Aside from that, the limitations of the proposed approach were assessed in five bioclimatic stages. Furthermore, the influence of the sea was analyzed in five classes of distance. The findings showed that the models built using NDVI and NDWI have a high correlation and therefore can be used to downscale precipitation. The integration of elevation and distance improved the correlation models. According to R2, RMSE, bias, and MAE, the study revealed that there is a great agreement between downscaled precipitations and RGS measurements. In addition, the analysis showed that the contribution of the variable (distance from sea is evident around the coastal area and decreases progressively. Likewise, the study demonstrated that the approach performs well in humid and arid bioclimatic stages compared to others.

On the characterization of vegetation recovery after fire disturbance using Fisher-Shannon analysis and SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series

Science.gov (United States)

Lasaponara, Rosa; Lanorte, Antonio; Lovallo, Michele; Telesca, Luciano

2015-04-01

Time series can fruitfully support fire monitoring and management from statistical analysis of fire occurrence (Tuia et al. 2008) to danger estimation (lasaponara 2005), damage evaluation (Lanorte et al 2014) and post fire recovery (Lanorte et al. 2014). In this paper, the time dynamics of SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) time series are analyzed by using the statistical approach of the Fisher-Shannon (FS) information plane to assess and monitor vegetation recovery after fire disturbance. Fisher-Shannon information plane analysis allows us to gain insight into the complex structure of a time series to quantify its degree of organization and order. The analysis was carried out using 10-day Maximum Value Composites of NDVI (MVC-NDVI) with a 1 km × 1 km spatial resolution. The investigation was performed on two test sites located in Galizia (North Spain) and Peloponnese (South Greece), selected for the vast fires which occurred during the summer of 2006 and 2007 and for their different vegetation covers made up mainly of low shrubland in Galizia test site and evergreen forest in Peloponnese. Time series of MVC-NDVI have been analyzed before and after the occurrence of the fire events. Results obtained for both the investigated areas clearly pointed out that the dynamics of the pixel time series before the occurrence of the fire is characterized by a larger degree of disorder and uncertainty; while the pixel time series after the occurrence of the fire are featured by a higher degree of organization and order. In particular, regarding the Peloponneso fire, such discrimination is more evident than in the Galizia fire. This suggests a clear possibility to discriminate the different post-fire behaviors and dynamics exhibited by the different vegetation covers. Reference Lanorte A, R Lasaponara, M Lovallo, L Telesca 2014 Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to

Trends in NDVI and tundra community composition in the Arctic of NE Alaska between 1984 and 2009

Science.gov (United States)

Robert R. Pattison; Janet C. Jorgenson; Martha K. Raynolds; Jeffery M. Welker

2015-01-01

As Arctic ecosystems experience increases in surface air temperatures, plot-level analyses of tundra vegetation composition suggest that there are important changes occurring in tundra communities that are typified by increases in shrubs and declines in non-vascular species. At the same time analyses of NDVI indicate that the Arctic tundra is greening. Few studies have...

Séries temporais e redes neurais: uma análise comparativa de técnicas na previsão de vendas do varejo brasileiro

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Claudio Felisoni de Angelo

2011-01-01

Full Text Available Uma importante atividade econômica em qualquer sociedade diz respeito à comercialização de bens. O varejo consiste exatamente no vínculo que se estabelece entre a indústria e o consumidor final. Prever as vendas é essencial para que se possa gerenciar de modo adequado os processos produtivos e de comercialização. No varejo esse aspecto reveste-se de importância ainda maior. Vender significa harmonizar os interesses dos que produzem com aqueles que compram. Portanto, o presente trabalho tem por propósito examinar comparativamente a aplicação de dois métodos de previsão de vendas de varejo no mercado brasileiro: as séries temporais e as redes neurais. A escolha dessas duas técnicas como objeto dessa comparação foi suscitada pela importância que essas duas concepções têm assumido na literatura. Embora a utilização de redes neurais tenha proporcionado a menor soma dos quadrados dos resíduos, pode-se dizer que os resultados empregando modelos do tipo ARIMA se mostraram praticamente equivalentes.

Studying the Post-Fire Response of Vegetation in California Protected Areas with NDVI-based Pheno-Metrics

Science.gov (United States)

Jia, S.; Gillespie, T. W.

2016-12-01

Post-fire response from vegetation is determined by the intensity and timing of fires as well as the nature of local biomes. Though the field-based studies focusing on selected study sites helped to understand the mechanisms of post-fire response, there is a need to extend the analysis to a broader spatial extent with the assistance of remotely sensed imagery of fires and vegetation. Pheno-metrics, a series of variables on the growing cycle extracted from basic satellite measurements of vegetation coverage, translate the basic remote sensing measurements such as NDVI to the language of phenology and fire ecology in a quantitative form. In this study, we analyzed the rate of biomass removal after ignition and the speed of post-fire recovery in California protected areas from 2000 to 2014 with USGS MTBS fire data and USGS eMODIS pheno-metrics. NDVI drop caused by fire showed the aboveground biomass of evergreen forest was removed much slower than shrubland because of higher moisture level and greater density of fuel. In addition, the above two major land cover types experienced a greatly weakened immediate post-fire growing season, featuring a later start and peak of season, a shorter length of season, and a lower start and peak of NDVI. Such weakening was highly correlated with burn severity, and also influenced by the season of fire and the land cover type, according to our modeling between the anomalies of pheno-metrics and the difference of normalized burn ratio (dNBR). The influence generally decayed over time, but can remain high within the first 5 years after fire, mostly because of the introduction of exotic species when the native species were missing. Local-specific variables are necessary to better address the variance within the same fire and improve the outcomes of models. This study can help ecologists in validating the theories of post-fire vegetation response mechanisms and assist local fire managers in post-fire vegetation recovery.

Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland

Science.gov (United States)

Olexa, Edward M.; Lawrence, Rick L

2014-01-01

Federal land management agencies provide stewardship over much of the rangelands in the arid andsemi-arid western United States, but they often lack data of the proper spatiotemporal resolution andextent needed to assess range conditions and monitor trends. Recent advances in the blending of com-plementary, remotely sensed data could provide public lands managers with the needed information.We applied the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to five Landsat TMand concurrent Terra MODIS scenes, and used pixel-based regression and difference image analyses toevaluate the quality of synthetic reflectance and NDVI products associated with semi-arid rangeland. Pre-dicted red reflectance data consistently demonstrated higher accuracy, less bias, and stronger correlationwith observed data than did analogous near-infrared (NIR) data. The accuracy of both bands tended todecline as the lag between base and prediction dates increased; however, mean absolute errors (MAE)were typically ≤10%. The quality of area-wide NDVI estimates was less consistent than either spectra lband, although the MAE of estimates predicted using early season base pairs were ≤10% throughout the growing season. Correlation between known and predicted NDVI values and agreement with the 1:1regression line tended to decline as the prediction lag increased. Further analyses of NDVI predictions,based on a 22 June base pair and stratified by land cover/land use (LCLU), revealed accurate estimates through the growing season; however, inter-class performance varied. This work demonstrates the successful application of the STARFM algorithm to semi-arid rangeland; however, we encourage evaluation of STARFM’s performance on a per product basis, stratified by LCLU, with attention given to the influence of base pair selection and the impact of the time lag.

SACRA - global data sets of satellite-derived crop calendars for agricultural simulations: an estimation of a high-resolution crop calendar using satellite-sensed NDVI

Science.gov (United States)

Kotsuki, S.; Tanaka, K.

2015-01-01

To date, many studies have performed numerical estimations of food production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC) is an essential input datum to estimate food production and agricultural water demand accurately with the numerical estimations. CC defines the date or month when farmers plant and harvest in cropland. This study aims to develop a new global data set of a satellite-derived crop calendar for agricultural simulations (SACRA) and reveal advantages and disadvantages of the satellite-derived CC compared to other global products. We estimate global CC at a spatial resolution of 5 min (≈10 km) using the satellite-sensed NDVI data, which corresponds well to vegetation growth and death on the land surface. We first demonstrate that SACRA shows similar spatial pattern in planting date compared to a census-based product. Moreover, SACRA reflects a variety of CC in the same administrative unit, since it uses high-resolution satellite data. However, a disadvantage is that the mixture of several crops in a grid is not considered in SACRA. We also address that the cultivation period of SACRA clearly corresponds to the time series of NDVI. Therefore, accuracy of SACRA depends on the accuracy of NDVI used for the CC estimation. Although SACRA shows different CC from a census-based product in some regions, multiple usages of the two products are useful to take into consideration the uncertainty of the CC. An advantage of SACRA compared to the census-based products is that SACRA provides not only planting/harvesting dates but also a peak date from the time series of NDVI data.

A categorical, improper probability method for combining NDVI and LiDAR elevation information for potential cotton precision agricultural applications

Science.gov (United States)

An algorithm is presented to fuse the Normalized Difference Vegetation Index (NDVI) with Light Detection and Ranging (LiDAR) elevation data to produce a map potentially useful for the site-specific scouting and pest management of several insect pests. In cotton, these pests include the Tarnished Pl...

Multifractal characteristics of NDVI maps in space and time in the Community of Madrid (Spain)

Science.gov (United States)

Sotoca, Juan J. Martin; Saa-Requejo, Antonio; Grau, Juan B.; Tarquis, Ana M.

2015-04-01

Satellite information has contributed to improve our understanding of the spatial variability of hydro-climatic and ecological processes. Vegetation activity is tightly coupled with climate, hydro-ecological fluxes, and terrain dynamics in river basins at a wide range of space-time scales (Scheuring and Riedi, 1994). Indices of vegetation activity are constructed using satellite information of reflectance of the relevant spectral bands which enhance the contribution of vegetation being Normalized Difference Vegetation Index (NDVI) widely used. How can we study such a complex system? Multifractals and fractals are related techniques mainly used in physics to characterize the scaling behaviour of a system; they differ in that fractals look at the geometry of presence/absence patterns, while multifractals look at the arrangement of quantities such as population or biomass densities (Saravia et al., 2012). Scaling laws are an emergent general feature of ecological systems; they reflect constraints in their organization that can provide tracks about the underlying mechanisms (Solé and Bascompte, 2006). In this work, we have applied these techniques to study the spatial pattern through one year of NDVI maps. A rectangular area that includes the Community of Madrid and part of the surroundings, consisting of 300 x 280 pixels with a resolution of 500 x 500 m2 has been selected and monthly NDVI maps analyzed using the multifractal spectrum and the map of singularities (Cheng and Agterberg, 1996). The results show a cyclical pattern in the multifractal behaviour and singularity points related to river basin networks (Martín-Sotoca, 2014). References Cheng, Q. and Agterberg, F.P. (1996). Multifractal modeling and spatial statistics. Math. Geol. Vol 28, 1-16. Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones en el Seguro Agrario. Master Thesis, UPM (In Spanish). Saravia LA, Giorgi A, Momo F.: Multifractal growth in periphyton

Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

Science.gov (United States)

Gamon, John A.; Huemmrich, K. Fred; Stone, Robert S.; Tweedie, Craig E.

2015-01-01

In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.

Effects of distribution density and cell dimension of 3D vegetation model on canopy NDVI simulation base on DART

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Tao, Zhu; Shi, Runhe; Zeng, Yuyan; Gao, Wei

2017-09-01

The 3D model is an important part of simulated remote sensing for earth observation. Regarding the small-scale spatial extent of DART software, both the details of the model itself and the number of models of the distribution have an important impact on the scene canopy Normalized Difference Vegetation Index (NDVI).Taking the phragmitesaustralis in the Yangtze Estuary as an example, this paper studied the effect of the P.australias model on the canopy NDVI, based on the previous studies of the model precision, mainly from the cell dimension of the DART software and the density distribution of the P.australias model in the scene, As well as the choice of the density of the P.australiass model under the cost of computer running time in the actual simulation. The DART Cell dimensions and the density of the scene model were set by using the optimal precision model from the existing research results. The simulation results of NDVI with different model densities under different cell dimensions were analyzed by error analysis. By studying the relationship between relative error, absolute error and time costs, we have mastered the density selection method of P.australias model in the simulation of small-scale spatial scale scene. Experiments showed that the number of P.australias in the simulated scene need not be the same as those in the real environment due to the difference between the 3D model and the real scenarios. The best simulation results could be obtained by keeping the density ratio of about 40 trees per square meter, simultaneously, of the visual effects.

A Method for Estimating the Aerodynamic Roughness Length with NDVI and BRDF Signatures Using Multi-Temporal Proba-V Data

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Mingzhao Yu

2016-12-01

Full Text Available Aerodynamic roughness length is an important parameter for surface fluxes estimates. This paper developed an innovative method for estimation of aerodynamic roughness length (z0m over farmland with a new vegetation index, the Hot-darkspot Vegetation Index (HDVI. To obtain this new index, the normalized-difference hot-darkspot index (NDHD is introduced using a semi-empirical, kernel-driven bidirectional reflectance model with multi-temporal Proba-V 300-m top-of-canopy (TOC reflectance products. A linear relationship between HDVI and z0m was found during the crop growth period. Wind profiles data from two field automatic weather station (AWS were used to calibrate the model: one site is in Guantao County in Hai Basin, in which double-cropping systems and crop rotations with summer maize and winter wheat are implemented; the other is in the middle reach of the Heihe River Basin from the Heihe Watershed Allied Telemetry Experimental Research (HiWATER project, with the main crop of spring maize. The iterative algorithm based on Monin–Obukhov similarity theory is employed to calculate the field z0m from time series. Results show that the relationship between HDVI and z0m is more pronounced than that between NDVI and z0m for spring maize at Yingke site, with an R2 value that improved from 0.636 to 0.772. At Guantao site, HDVI also exhibits better performance than NDVI, with R2 increasing from 0.630 to 0.793 for summer maize and from 0.764 to 0.790 for winter wheat. HDVI can capture the impacts of crop residue on z0m, whereas NDVI cannot.

Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

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Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

2015-01-01

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush-steppe ecosystem

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Wylie, B.K.; Johnson, D.A.; Laca, Emilio; Saliendra, Nicanor Z.; Gilmanov, T.G.; Reed, B.C.; Tieszen, L.L.; Worstell, B.B.

2003-01-01

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes (Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rn were measured with a Bowen ratio-energy balance (BREB) technique in a sagebrush (Artemisia spp.)-steppe ecosystem in northeast Idaho, USA, during 1996-1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996-1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday (R2 = 0.79, n = 66, P improved predictions of Fday (R2= 0.82, n = 66, P management strategies, carbon certification, and validation and calibration of carbon flux models. ?? 2003 Elsevier Science Inc. All rights reserved.

Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush–steppe ecosystem

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Wylie, Bruce K.; Johnson, Douglas A.; Laca, Emilio; Saliendra, Nicanor Z.; Gilmanov, Tagir G.; Reed, Bradley C.; Tieszen, Larry L.; Worstell, Bruce B.

2003-01-01

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes (Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rnwere measured with a Bowen ratio–energy balance (BREB) technique in a sagebrush (Artemisia spp.)–steppe ecosystem in northeast Idaho, USA, during 1996–1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996–1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday(R2=0.79, n=66, Pimproved predictions of Fday (R2=0.82, n=66, Pmanagement strategies, carbon certification, and validation and calibration of carbon flux models.

NDVI-Based Analysis on the Influence of Climate Change and Human Activities on Vegetation Restoration in the Shaanxi-Gansu-Ningxia Region, Central China

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Shuangshuang Li

2015-08-01

Full Text Available In recent decades, climate change has affected vegetation growth in terrestrial ecosystems. We investigated spatial and temporal patterns of vegetation cover on the Loess Plateau’s Shaanxi-Gansu-Ningxia region in central China using MODIS-NDVI data for 2000–2014. We examined the roles of regional climate change and human activities in vegetation restoration, particularly from 1999 when conversion of sloping farmland to forestland or grassland began under the national Grain-for-Green program. Our results indicated a general upward trend in average NDVI values in the study area. The region’s annual growth rate greatly exceeded those of the Three-North Shelter Forest, the upper reaches of the Yellow River, the Qinling–Daba Mountains, and the Three-River Headwater region. The green vegetation zone has been annually extending from the southeast toward the northwest, with about 97.4% of the region evidencing an upward trend in vegetation cover. The NDVI trend and fluctuation characteristics indicate the occurrence of vegetation restoration in the study region, with gradual vegetation stabilization associated with 15 years of ecological engineering projects. Under favorable climatic conditions, increasing local vegetation cover is primarily attributable to ecosystem reconstruction projects. However, our findings indicate a growing risk of vegetation degradation in the northern part of Shaanxi Province as a result of energy production facilities and chemical industry infrastructure, and increasing exploitation of mineral resources.

Integração de modelos espaciais e temporais para predições de níveis freáticos extremos

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Rodrigo Lilla Manzione

2012-09-01

Full Text Available O objetivo deste trabalho foi avaliar cenários de níveis freáticos extremos, em bacia hidrográfica, por meio de métodos de análise espacial de dados geográficos. Avaliou-se a dinâmica espaço‑temporal dos recursos hídricos subterrâneos em área de afloramento do Sistema Aquífero Guarani. As alturas do lençol freático foram estimadas por meio do monitoramento de níveis em 23 piezômetros e da modelagem das séries temporais disponíveis de abril de 2004 a abril de 2011. Para a geração de cenários espaciais, foram utilizadas técnicas geoestatísticas que incorporaram informações auxiliares relativas a padrões geomorfológicos da bacia, por meio de modelo digital de terreno. Esse procedimento melhorou as estimativas, em razão da alta correlação entre altura do lençol e elevação, e agregou sentido físico às predições. Os cenários apresentaram diferenças quanto aos níveis considerados extremos - muito profundos ou muito superficiais - e podem subsidiar o planejamento, o uso eficiente da água e a gestão sustentável dos recursos hídricos na bacia.

AVALIAÇÃO DOS ÍNDICES DE VEGETAÇÃO NDVI, SR E TVI NA DISCRIMINAÇÃO DE FITOFISIONOMIAS DOS AMBIENTES DO PANTANAL DE CÁCERES/MT

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Edinéia Aparecida dos Santos Galvanin

2014-01-01

Full Text Available This paper compares the performance of some vegetation indexes: Normalized Difference Vegetation Index (NDVI, Simple Ratio (SR e Transformed Vegetation Index (TVI, applied in seasonal periods to verify which one best fits to discriminate the vegetation types of environments of ‘Pantanal’ in Cáceres, Mato Grosso state, Brazil, in Landsat TM 5 image of 2009 in the dry period and 2010 in the humid period. Result verification of indexes images showed that NDVI provide a better performance than the SR and TVI indexes for different environments.

[Variability of vegetation growth season in different latitudinal zones of North China: a monitoring by NOAA NDVI and MSAVI].

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Wang, Hong; Li, Xiaobing; Han, Ruibo; Ge, Yongqin

2006-12-01

In this study, North China was latitudinally divided into five zones, i.e., 32 degrees - 36 degrees N (Zone I), 36 degrees - 40 degrees N (Zone II), 40 degrees - 44 degrees N (Zone III), 44 degrees - 48 degrees N (Zone IV) and 48 degrees - 52 degrees N (Zone V), and the NOAA/ AVHRR NDVI and MSAVI time-series images from 1982 to 1999 were smoothed with Savitzky-Golay filter algorithm. Based on the EOF analysis, the principal components of NDVI and MSAVI for the vegetations in different latitudinal zones of North China were extracted, the annual beginning and ending dates and the length of growth season in 1982 - 1999 were estimated, and the related parameters were linearly fitted, aimed to analyze the variability of vegetation growth season. The results showed that the beginning date of the growth season in different zones tended to be advanced, while the ending date tended to be postponed with increasing latitude. The length of the growth season was also prolonged, with the prolonging time exceeded 10 days.

Assessing vegetation response to climatic variations and human activities: spatiotemporal NDVI variations in the Hexi Corridor and surrounding areas from 2000 to 2010

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Guan, Qingyu; Yang, Liqin; Guan, Wenqian; Wang, Feifei; Liu, Zeyu; Xu, Chuanqi

2018-03-01

Vegetation cover is a commonly used indicator for evaluating terrestrial environmental conditions, and for revealing environmental evolution and transitions. Spatiotemporal variations in the vegetation cover of the Hexi Corridor and surrounding areas from 2000 to 2010 were investigated using MODIS NDVI data, and the causes of vegetation cover changes were analyzed, considering both climatic variability and human activities. The vegetation cover of the study area increased during 2000-2010. The greenness of the vegetation showed a significant increase from the northwest to the southeast, which was similar to the spatial distribution of the annual precipitation. Variations in vegetation have a close relationship with those in precipitation within the Qilian Mountains region, but the NDVI is negatively correlated with precipitation in oasis areas. Increasing temperatures led to drought, inhibiting vegetation growth in summer; however, increasing temperatures may have also advanced and prolonged the growing periods in spring and autumn. The NDVI showed a slight degradation in March and July, primarily in the Qilian Mountains, and especially the Wushao Mountains. In March, due to low temperatures, the metabolism rate of vegetation was too slow to enable strong plant growth in high elevations of the Qilian Mountains. In July, increasing temperatures enhanced the intensity of transpiration and decreasing precipitation reduced the moisture available to plants, producing a slight degradation of vegetation in the Qilian Mountains. In May and August, the NDVI showed a significant improvement, primarily in the artificial oases and the Qilian Mountains. Abundant precipitation provided the necessary water for plant growth, and suitable temperatures increased the efficiency of photosynthesis, resulting in a significant improvement of vegetation in the Qilian Mountains. The improvement of production technologies, especially in irrigation, has been beneficial to the growth of

The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

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Yoshida, Y.; Joiner, J.; Tucker, C.; Berry, J.; Lee, J. -E.; Walker, G.; Reichle, R.; Koster, R.; Lyapustin, A.; Wang, Y.

2015-01-01

We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

Análise de séries temporais na operação de sistema de tratamento de águas residuárias de abatedouro de frango Time series analysis on the operation of a poultry slaughterhouse wastewater treatment plant

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Ivana Ribeiro de Nardi

2005-12-01

Full Text Available Esse trabalho apresenta a avaliação de dados de operação de sistema de tratamento de águas residuárias de abatedouro de frango, através da análise de séries temporais. O objetivo principal foi a obtenção de modelo de previsão capaz de antecipar o controle da operação do sistema de tratamento de águas residuárias do abatedouro, constituindo subsídio para obtenção de estratégias de gestão do sistema de tratamento existente. Registros de 42 meses de parâmetros de monitoramento foram utilizados na modelagem de séries temporais. O modelo de ajuste exponencial para previsão dos valores de demanda química de oxigênio do efluente industrial e do afluente dos reatores biológicos apresentou bom ajuste (erro percentual absoluto da média aritmética menor que 20% com diferenças na capacidade de previsão menores que 15%.This paper presents the evaluation of the operating data of the poultry slaughterhouse wastewater treatment plant, by means of time series analysis. It aimed at obtaining a forecasting model able to have the operation of the slaughterhouse wastewater treatment system under control, what leads to subsidy for acquiring the management strategies of the wastewater treatment system. Records of 42 months of the monitoring parameters were used in the time series modeling. The exponentially weighted moving average model for obtaining chemical oxygen demand values of the industrial effluent and the reactors influent stream showed proper adjustment (mean absolute percentage error values smaller than 20%, where the differences on the prediction feasibility were smaller than 15%.

Potential of ALOS2 and NDVI to Estimate Forest Above-Ground Biomass, and Comparison with Lidar-Derived Estimates

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Gaia Vaglio Laurin

2016-12-01

Full Text Available Remote sensing supports carbon estimation, allowing the upscaling of field measurements to large extents. Lidar is considered the premier instrument to estimate above ground biomass, but data are expensive and collected on-demand, with limited spatial and temporal coverage. The previous JERS and ALOS SAR satellites data were extensively employed to model forest biomass, with literature suggesting signal saturation at low-moderate biomass values, and an influence of plot size on estimates accuracy. The ALOS2 continuity mission since May 2014 produces data with improved features with respect to the former ALOS, such as increased spatial resolution and reduced revisit time. We used ALOS2 backscatter data, testing also the integration with additional features (SAR textures and NDVI from Landsat 8 data together with ground truth, to model and map above ground biomass in two mixed forest sites: Tahoe (California and Asiago (Alps. While texture was useful to improve the model performance, the best model was obtained using joined SAR and NDVI (R2 equal to 0.66. In this model, only a slight saturation was observed, at higher levels than what usually reported in literature for SAR; the trend requires further investigation but the model confirmed the complementarity of optical and SAR datatypes. For comparison purposes, we also generated a biomass map for Asiago using lidar data, and considered a previous lidar-based study for Tahoe; in these areas, the observed R2 were 0.92 for Tahoe and 0.75 for Asiago, respectively. The quantitative comparison of the carbon stocks obtained with the two methods allows discussion of sensor suitability. The range of local variation captured by lidar is higher than those by SAR and NDVI, with the latter showing overestimation. However, this overestimation is very limited for one of the study areas, suggesting that when the purpose is the overall quantification of the stored carbon, especially in areas with high carbon

Long-term trends in vegetation phenology and productivity over Namaqualand using the GIMMS AVHRR NDVI3g data from 1982 to 2011

CSIR Research Space (South Africa)

Davis, CL

2017-07-01

Full Text Available Vegetation monitoring of arid and semi-arid environments using remotely sensed vegetation indices over long periods of time is essential to improve the understanding of the processes related to change. In this paper, 30 years of biweekly AVHRR NDVI3...

Estimativa do balanço de radiação por sensoriamento remoto de diferentes ssos de solo so sudoeste da Amazônia Brasileira / Estimative of radiation balance by remote sensing of different soil uses in the brazilian southern amazon

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Luiz Carlos da Silva

2016-09-01

Full Text Available Mudanças no uso do solo têm motivado pesquisas sobre a dinâmica de trocas radiativas e energéticas na Amazônia Brasileira que, por sua vez, geram demanda destas informações de superfície em escalas espaciais e temporais. Enquanto a medição destas trocas em torres micrometeorológicas fornece resultados pontuais, o sensoriamento remoto apresenta resultados acurados e de baixo custo para estimá-las em escala regional. Este estudo objetivou avaliar a distribuição espacial e temporal de estimativas de saldo de radiação e parâmetros biofísicos por sensoriamento remoto de diferentes usos do solo no sudoeste da Amazônia Brasileira. Foram selecionadas 04 áreas de solo coberto por floresta amazônica natural, floresta amazônica manejada, sistema silvipastoril e pastagem. O saldo de radiação, NDVI, índice de área foliar, albedo e temperatura radiométrica foram estimados pelo algoritmo SEBAL, usando imagens do sensor TM do satélite Landsat 5 em julho de 2009, 2010 e 2011. O NDVI, IAF, albedo e saldo de radiação apresentaram maiores valores na floresta natural, seguida por floresta manejada, sistema silvipastoril e pastagem. A temperatura radiométrica da superfície apresentou maiores valores para o sistema silvipastoril seguido por pastagem, floresta natural e floresta manejada.

Mapping tropical dry forest habitats integrating landsat NDVI, Ikonos imagery, and topographic information in the Caribbean island of Mona.

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Martinuzzi, Sebastiáin; Gould, William A; Ramos Gonzalez, Olga M; Martinez Robles, Alma; Calle Maldonado, Paulina; Pérez-Buitrago, Néstor; Fumero Caban, José J

2008-06-01

Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference Vegetation Index (NDVI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDVI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5500 ha area, with a kappa coefficient of accuracy equal to 79%. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island.

Spatial distribution of volcanic ash deposits of 2011 Puyehue-Cordón Caulle eruption in Patagonia as measured by a perturbation in NDVI temporal dynamics

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Easdale, M. H.; Bruzzone, O.

2018-03-01

Volcanic ash fallout is a recurrent environmental disturbance in forests, arid and semi-arid rangelands of Patagonia, South America. The ash deposits over large areas are responsible for several impacts on ecological processes, agricultural production and health of local communities. Public policy decision making needs monitoring information of the affected areas by ash fallout, in order to better orient social, economic and productive aids. The aim of this study was to analyze the spatial distribution of volcanic ash deposits from the eruption of Puyehue-Cordón Caulle in 2011, by identifying a sudden change in the Normalized Difference Vegetation Index (NDVI) temporal dynamics, defined as a perturbation located in the time series. We applied a sparse-wavelet transform using the Basis Pursuit algorithm to NDVI time series obtained from the Moderate Resolution Image Spectroradiometer (MODIS) sensor, to identify perturbations at a pixel level. The spatial distribution of the perturbation promoted by ash deposits in Patagonia was successfully identified and characterized by means of a perturbation in NDVI temporal dynamics. Results are encouraging for the future development of a new platform, in combination with data from forecasting models and tracking of ash cloud trajectories and dispersion, to inform stakeholders to mitigate impact of volcanic ash on agricultural production and to orient public intervention strategies after a volcanic eruption followed by ash fallout over a wide region.

Evapotranspiração real obtida através da relação entre o coeficiente dual de cultura da FAO-56 e o NDVI Real actual evapotranspiration obtained through the relationship between the FAO-56 crop dual coefficient and NDVI

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Bergson Guedes Bezerra

2010-09-01

Full Text Available Um requisito fundamental para adoção de manejo da irrigação é a determinação diária da evapotranspiração (ET das culturas. Em caráter operacional o método do coeficiente de cultura proposto pela Food Agriculture Organization (FAO, através do seu relatório 56 (Irrigation and Drainage Paper, é largamente utilizado na determinação da ET, e tem apresentado precisões que o tornam mundialmente aceito. A ET com base no coeficiente de cultura (Kc, obtido a partir de índices de vegetação, particularmente o NDVI, tem sido calculada em vários estudos e para diversas culturas alcançando muita precisão, quando comparado com observações de campo. Diante do exposto, este trabalho teve por objetivo calcular a ET diária e sazonal da cultura do algodoeiro utilizando o método do Kc dual obtido em função do Índice de Vegetação por Diferença Normalizada - NDVI, obtido a partir de imagens TM - Landsat 5 livre da presença de nuvens. Os resultados revelaram precisões bastante confiáveis, pois foram verificadas diferenças menores que 10%, quando comparados com valores da ET obtidos pela técnica da Bowen, corroborando com o desempenho alcançado pelo método em outras pesquisas realizadas em outras regiões do planeta. Dessa forma, pode-se concluir que o método apresenta bastante confiabilidade e simplicidade.A fundamental requirement for adoption of irrigation management is to determine the crop daily evapotranspiration (ET. On an operational basis the crop coefficient method proposed by the Food and Agriculture Organization (FAO through its report 56 (Irrigation and Drainage Paper is widely used in the determination of ET and due to its accurate estimative, it has been globally accepted. The ET-based crop coefficient (Kc obtained from vegetation indices, particularly the Vegetation Index Normalized Difference (NDVI has been measured in several studies and various crops showing great accuracy when compared to field observations

Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

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Moreno-de las Heras, M.; Diaz-Sierra, R.; Turnbull, L.; Wainwright, J.

2015-01-01

Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000-2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation

Hillslope terracing effects on the spatial variability of plant development as assessed by NDVI in vineyards of the Priorat region (NE Spain).

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Martínez-Casasnovas, José A; Ramos, María Concepción; Espinal-Utgés, Sílvia

2010-04-01

The availability of heavy machinery and the vineyard restructuring and conversion plans of the European Union Common Agricultural Policy (Commission Regulation EC no. 1227/2000 of 31 May 2000) have encouraged the restructuring of many vineyards on hillslopes of Mediterranean Europe, through the creation of terraces to favor the mechanization of agricultural work. Terrace construction requires cutting and filling operations that create soil spatial variability, which affects soil properties and plant development. In the present paper, we study the effects of hillslope terracing on the spatial variability of the normalized difference vegetation index (NDVI) in fields of the Priorat region (NE Spain) during 2004, 2005, and 2006. This index was computed from high-resolution remote sensing data (Quickbird-2). Detailed digital terrain models before and after terrace construction were used to assess the earth movements. The results indicate that terracing by heavy machinery induced high variability on the NDVI values over the years, showing significant differences as effect of the cut and fill operations.

Study on generation and sharing of on-demand global seamless data—Taking MODIS NDVI as an example

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Shen, Dayong; Deng, Meixia; Di, Liping; Han, Weiguo; Peng, Chunming; Yagci, Ali Levent; Yu, Genong; Chen, Zeqiang

2013-04-01

By applying advanced Geospatial Data Abstraction Library (GDAL) and BigTIFF technology in a Geographical Information System (GIS) with Service Oriented Architecture (SOA), this study has derived global datasets using tile-based input data and implemented Virtual Web Map Service (VWMS) and Virtual Web Coverage Service (VWCS) to provide software tools for visualization and acquisition of global data. Taking MODIS Normalized Difference Vegetation Index (NDVI) as an example, this study proves the feasibility, efficiency and features of the proposed approach.

Mapping tropical dry forest habitats integrating Landsat NDVI, Ikonos imagery, and topographic information in the Caribbean Island of Mona

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Sebastián Martinuzzi

2008-06-01

Full Text Available Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference vegetation Index (NDvI from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDvI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5 500 ha area, with a kappa coefficient of accuracy equal to 79 %. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island. Rev. Biol. Trop. 56 (2: 625-639. Epub 2008 June 30.El estudio y evaluación de los bosques tropicales secos mediante herramientas de teledetección es una de las prioridades de investigación en los ambientes neotropicales. Desarrollamos una metodología simple para mapear la vegetación de la isla de Mona, Puerto Rico, mediante el uso del índice de vegetación normalizado (NDVI por sus siglas en inglés de Landsat, información topográfica, e imágenes auxiliares de alta resolución Ikonos. La metodología fue útil para identificar las clases de vegetación en un área de gran variedad de comunidades vegetales y relieve complejo, y puede ser adaptada a otras regiones de bosque seco de las islas del Caribe. El NDVI permitió identificar la distribución de

Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)

Science.gov (United States)

Wilson, Natalie R.; Norman, Laura

2018-01-01

Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

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Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

Refinamento de imagens termais do Landsat 5 - TM com base em classes de NDVI Sharpening of thermal Landsat 5 - TM imagery data based on NDVI classification

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Argemiro Lucena de Araújo

2012-12-01

Full Text Available O objetivo desse estudo foi avaliar um método simplificado, baseado em classes de NDVI para refinamento das imagens de temperatura da superfície (Ts, obtidas pelo sensor TM do Landsat 5 referentes aos anos de 2005 e 2006. Para tanto, foram propostos e comparados três modelos de refinamento baseados no método de regressão linear. Os erros percentuais e erros médios quadráticos obtidos com a utilização dos modelos avaliados foram, respectivamente, da ordem de 0,37% e 1,38 ºC, enquanto o modelo original apresentou erro médio quadrático da ordem de 1,32 ºC. Foram constatados que os erros obtidos com as calibrações realizadas não influenciaram significativamente nos valores médios das imagens termais, e que os resultados contribuíram substancialmente para a melhoria da resolução espacial das mesmas. O refinamento permitiu ainda a identificação precisa de alvos da superfície e a identificação de feições não detectáveis na resolução original. Isto evidencia que o método simplificado sugerido neste estudo, permite um refinamento preciso com uma forma de obtenção mais simples em relação ao modelo original.The objective of this study was to use a simplified method based on NDVI classes for the sharpening of the Landsat 5 - TM surface temperature images (Ts obtained during the years of 2005 and 2006. Thus, three sharpening models, based on the linear regression method, were proposed and compared. The relative and the root mean square errors obtained through the suggested models were of 0.37% and 1.38 ºC, respectively, while the original model presented root mean square error of 1.32 ºC. It was verified that the errors obtained with the accomplished calibrations did not significantly influence in the average values of the thermal images and the results contributed substantially to the improvement of their spatial resolution. The sharpening allowed the precise identification of the targets and features undetectable at

[Spatiotemporal characteristics of MODIS NDVI in Hulunber Grassland].

Science.gov (United States)

Zhang, Hong-Bin; Yang, Gui-Xia; Wu, Wen-Bin; Li, Gang; Chen, Bao-Rui; Xin, Xiao-Ping

2009-11-01

Time-series MODIS NDVI datasets from 2000 to 2008 were used to study the spatial change trend, fluctuation degree, and occurrence time of the annual NDVImax of four typical grassland types, i.e., lowland meadow, temperate steppe, temperate meadow steppe, and upland meadow, in Hulunber Grassland. In 2000-2008, the vegetation in Hulunber Grassland presented an obvious deterioration trend. The mean annual NDVImax of the four grassland types had a great fluctuation, especially in temperate steppe where the maximum change in the mean value of annual NDVImax approximated to 50%. As for the area change of different grade grasslands, the areas with NDVImax between 0.4 and 1 accounted for about 91% of the total grassland area, which suggested the good vegetation coverage in the Grassland. However, though the areas with NDVImax values in (0.4, 0.8) showed an increasing trend, the areas with NDVImax values in (0.2, 0.4) and (0.8, 1) decreased greatly in the study period. Overall, the deteriorating grassland took up about 66.25% of the total area, and the restoring grassland took the rest. There was about 62.85% of the grassland whose NDVImax occurred between the 193rd day and the 225th day in each year, indicating that this period was the most important vegetation growth season in Hulunber Grassland.

Large-scale heterogeneity of Amazonian phenology revealed from 26-year long AVHRR/NDVI time-series

International Nuclear Information System (INIS)

Silva, Fabrício B; Shimabukuro, Yosio E; Aragão, Luiz E O C; Anderson, Liana O; Pereira, Gabriel; Cardozo, Franciele; Arai, Egídio

2013-01-01

Depiction of phenological cycles in tropical forests is critical for an understanding of seasonal patterns in carbon and water fluxes as well as the responses of vegetation to climate variations. However, the detection of clear spatially explicit phenological patterns across Amazonia has proven difficult using data from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this work, we propose an alternative approach based on a 26-year time-series of the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) to identify regions with homogeneous phenological cycles in Amazonia. Specifically, we aim to use a pattern recognition technique, based on temporal signal processing concepts, to map Amazonian phenoregions and to compare the identified patterns with field-derived information. Our automated method recognized 26 phenoregions with unique intra-annual seasonality. This result highlights the fact that known vegetation types in Amazonia are not only structurally different but also phenologically distinct. Flushing of new leaves observed in the field is, in most cases, associated to a continuous increase in NDVI. The peak in leaf production is normally observed from the beginning to the middle of the wet season in 66% of the field sites analyzed. The phenoregion map presented in this work gives a new perspective on the dynamics of Amazonian canopies. It is clear that the phenology across Amazonia is more variable than previously detected using remote sensing data. An understanding of the implications of this spatial heterogeneity on the seasonality of Amazonian forest processes is a crucial step towards accurately quantifying the role of tropical forests within global biogeochemical cycles. (letter)

Comparison of Eight Techniques for Reconstructing Multi-Satellite Sensor Time-Series NDVI Data Sets in the Heihe River Basin, China

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Liying Geng

2014-03-01

Full Text Available More than 20 techniques have been developed to de-noise time-series vegetation index data from different satellite sensors to reconstruct long time-series data sets. Although many studies have compared Normalized Difference Vegetation Index (NDVI noise-reduction techniques, few studies have compared these techniques systematically and comprehensively. This study tested eight techniques for smoothing different vegetation types using different types of multi-temporal NDVI data (Advanced Very High Resolution Radiometer (AVHRR (Global Inventory Modeling and Map Studies (GIMMS and Pathfinder AVHRR Land (PAL, Satellite Pour l’ Observation de la Terre (SPOT VEGETATION (VGT, and Moderate Resolution Imaging Spectroradiometer (MODIS (Terra with the ultimate purpose of determining the best reconstruction technique for each type of vegetation captured with four satellite sensors. These techniques include the modified best index slope extraction (M-BISE technique, the Savitzky-Golay (S-G technique, the mean value iteration filter (MVI technique, the asymmetric Gaussian (A-G technique, the double logistic (D-L technique, the changing-weight filter (CW technique, the interpolation for data reconstruction (IDR technique, and the Whittaker smoother (WS technique. These techniques were evaluated by calculating the root mean square error (RMSE, the Akaike Information Criterion (AIC, and the Bayesian Information Criterion (BIC. The results indicate that the S-G, CW, and WS techniques perform better than the other tested techniques, while the IDR, M-BISE, and MVI techniques performed worse than the other techniques. The best de-noise technique varies with different vegetation types and NDVI data sources. The S-G performs best in most situations. In addition, the CW and WS are effective techniques that were exceeded only by the S-G technique. The assessment results are consistent in terms of the three evaluation indexes for GIMMS, PAL, and SPOT data in the study

Future Climate Impact on the Desertification in the Dry Land Asia Using AVHRR GIMMS NDVI3g Data

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Lijuan Miao

2015-04-01

Full Text Available Dry Land Asia is the largest arid and semi-arid region in the northern hemisphere that suffers from land desertification. Over the period 1982–2011, there were both overall improvement and regional degeneration in the vegetation NDVI. We analyze future climate changes in these area using two ensemble-average methods from CMIP5 data. Bayesian Model Averaging shows a better capability to represent the future climate and less uncertainty represented by the 22-model ensemble than does the Simple Model Average. From 2006 to 2100, the average growing season temperature value will increase by 2.9 °C, from 14.4 °C to 17.3 °C under three climate scenarios (RCP 26, RCP 45 and RCP 85. We then conduct multiple regression analysis between climate changes compiled from the Climate Research Unit database and vegetation greenness from the GIMMS NDVI3g dataset. There is a general acceleration in the desertification trend under the RCP 85 scenario in middle and northern part of Middle Asia, northwestern China except Xinjiang and the Mongolian Plateau (except the middle part. The RCP 85 scenario shows a more severe desertification trend than does RCP 26. Desertification in dry land Asia, particularly in the regions highlighted in this study, calls for further investigation into climate change impacts and adaptations.

[Cross comparison of ASTER and Landsat ETM+ multispectral measurements for NDVI and SAVI vegetation indices].

Science.gov (United States)

Xu, Han-qiu; Zhang, Tie-jun

2011-07-01

The present paper investigates the quantitative relationship between the NDVI and SAVI vegetation indices of Landsat and ASTER sensors based on three tandem image pairs. The study examines how well ASTER sensor vegetation observations replicate ETM+ vegetation observations, and more importantly, the difference in the vegetation observations between the two sensors. The DN values of the three image pairs were first converted to at-sensor reflectance to reduce radiometric differences between two sensors, images. The NDVI and SAVI vegetation indices of the two sensors were then calculated using the converted reflectance. The quantitative relationship was revealed through regression analysis on the scatter plots of the vegetation index values of the two sensors. The models for the conversion between the two sensors, vegetation indices were also obtained from the regression. The results show that the difference does exist between the two sensors, vegetation indices though they have a very strong positive linear relationship. The study found that the red and near infrared measurements differ between the two sensors, with ASTER generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the ETM+ sensor. This results in the ASTER sensor producing lower spectral vegetation index measurements, for the same target, than ETM+. The relative spectral response function differences in the red and near infrared bands between the two sensors are believed to be the main factor contributing to their differences in vegetation index measurements, because the red and near infrared relative spectral response features of the ASTER sensor overlap the vegetation "red edge" spectral region. The obtained conversion models have high accuracy with a RMSE less than 0.04 for both sensors' inter-conversion between corresponding vegetation indices.

Analysis of Vegetation Coverage Change Characteristics in Chongqing Based on MODIS - NDVI Data

Science.gov (United States)

Jianfeng, WU; Cao, Guangjie; Zhang, Fengtai; Li, Wei; Wang, Haiqing

2017-12-01

In order to study the characteristics of vegetation cover change in Chongqing, MODIS-NDVI is used as data source. In this paper, the change of vegetation coverage in Chongqing from 2000 to 2011 was analyzed by mean value method and difference method from year, spring, summer, autumn and winter respectively. The results showed that the change of vegetation cover was larger than that of the western region on the annual scale. On the seasonal scale, the vegetation in the spring was in the middle with a high and low trend. The higher vegetation area was distributed in the summer area, and the lower area of vegetation was concentrated in the western part of the study area. Vegetation in autumn showed a flaky distribution in space. Winter vegetation to the Yangtze River as the boundary, the south cover is slightly higher than the north.

Assessing Habitat Quality of Forest-Corridors through NDVI Analysis in Dry Tropical Forests of South India: Implications for Conservation

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Paramesha Mallegowda

2015-02-01

Full Text Available Most wildlife habitats and migratory routes are extremely threatened due to increasing demands on forestland and forest resources by burgeoning human population. Corridor landscape in Biligiri Rangaswamy Temple Tiger Reserve (BRT is one among them, subjected to various anthropogenic pressures. Human habitation, intensive farming, coffee plantations, ill-planned infrastructure developments and rapid spreading of invasive plant species Lantana camara, pose a serious threat to wildlife habitat and their migration. Aim of this work is to create detailed NDVI based land change maps and to use them to identify time-series trends in greening and browning in forest corridors in the study area and to identify the drivers that are influencing the observed changes. Over the four decades in BRT, NDVI increased in the core area of the forest and reduced in the fringe areas. The change analysis between 1973 and 2014 shows significant changes; browning due to anthropogenic activities as well as natural processes and greening due to Lantana spread. This indicates that the change processes are complex, involving multiple driving factors, such as socio-economic changes, high population growth, historical forest management practices and policies. Our study suggests that the use of updated and accurate change detection maps will be useful in taking appropriate site specific action-oriented conservation decisions to restore and manage the degraded critical wildlife corridors in human-dominated landscape.

Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

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C. Höpfner

2011-11-01

Full Text Available Vegetation phenology as well as the current variability and dynamics of vegetation and land cover, including its climatic and human drivers, are examined in a region in north-western Morocco that is nearly 22 700 km² big. A gapless time series of Normalized Differenced Vegetation Index (NDVI composite raster data from 29 September 2000 to 29 September 2009 is utilised. The data have a spatial resolution of 250 m and were acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS sensor.

The presented approach allows to compose and to analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that the high temporal resolution of 16 d is sufficient for (a determining local land cover better than global land cover classifications of Plant Functional Types (PFT and Global Land Cover 2000 (GLC2000 and (b for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types (i.e. areas that did not change their land cover type show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared with stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland of about 259.3 km². Statistically significant inter-annual trends in vegetation dynamics during the last decade could however not be discovered. A sequence of correlations was respectively carried out to extract the most important periods of rainfall responsible for the production of green biomass and for the extent of land cover types. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r²=0.85 on an intra

Improvement of Alternative Crop Phenology Detection Algorithms using MODIS NDVI Time Series Data in US Corn Belt Region

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Lee, J.; Kang, S.; Seo, B.; Lee, K.

2017-12-01

Predicting crop phenology is important for understanding of crop development and growth processes and improving the accuracy of crop model. Remote sensing offers a feasible tool for monitoring spatio-temporal patterns of crop phenology in region and continental scales. Various methods have been developed to determine the timing of crop phenological stages using spectral vegetation indices (i.e. NDVI and EVI) derived from satellite data. In our study, it was compared four alternative detection methods to identify crop phenological stages (i.e. the emergence and harvesting date) using high quality NDVI time series data derived from MODIS. Also we investigated factors associated with crop development rate. Temperature and photoperiod are the two main factors which would influence the crop's growth pattern expressed in the VI data. Only the effect of temperature on crop development rate was considered. The temperature response function in the Wang-Engel (WE) model was used, which simulates crop development using nonlinear models with response functions that range from zero to one. It has attempted at the state level over 14 years (2003-2016) in Iowa and Illinois state of USA, where the estimated phenology date by using four methods for both corn and soybean. Weekly crop progress reports produced by the USDA NASS were used to validate phenology detection algorithms effected by temperature. All methods showed substantial uncertainty but the threshold method showed relatively better agreement with the State-level data for soybean phenology.

Evaluation of a linear spectral mixture model and vegetation indices (NDVI and EVI) in a study of schistosomiasis mansoni and Biomphalaria glabrata distribution in the state of Minas Gerais, Brazil.

Science.gov (United States)

Guimarães, Ricardo J P S; Freitas, Corina C; Dutra, Luciano V; Scholte, Ronaldo G C; Amaral, Ronaldo S; Drummond, Sandra C; Shimabukuro, Yosio E; Oliveira, Guilherme C; Carvalho, Omar S

2010-07-01

This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

Long-term Satellite NDVI Data Sets: Evaluating Their Ability to Detect Ecosystem Functional Changes in South America.

Science.gov (United States)

Baldi, Germán; Nosetto, Marcelo D; Aragón, Roxana; Aversa, Fernando; Paruelo, José M; Jobbágy, Esteban G

2008-09-03

In the last decades, South American ecosystems underwent important functional modifications due to climate alterations and direct human intervention on land use and land cover. Among remotely sensed data sets, NOAA-AVHRR "Normalized Difference Vegetation Index" (NDVI) represents one of the most powerful tools to evaluate these changes thanks to their extended temporal coverage. In this paper we explored the possibilities and limitations of three commonly used NOAA-AVHRR NDVI series (PAL, GIMMS and FASIR) to detect ecosystem functional changes in the South American continent. We performed pixel-based linear regressions for four NDVI variables (average annual, maximum annual, minimum annual and intra-annual coefficient of variation) for the 1982-1999 period and (1) analyzed the convergences and divergences of significant multi-annual trends identified across all series, (2) explored the degree of aggregation of the trends using the O-ring statistic, and (3) evaluated observed trends using independent information on ecosystem functional changes in five focal regions. Several differences arose in terms of the patterns of change (the sign, localization and total number of pixels with changes). FASIR presented the highest proportion of changing pixels (32.7%) and GIMMS the lowest (16.2%). PAL and FASIR data sets showed the highest agreement, with a convergence of detected trends on 71.2% of the pixels. Even though positive and negative changes showed substantial spatial aggregation, important differences in the scale of aggregation emerged among the series, with GIMMS showing the smaller scale (≤11 pixels). The independent evaluations suggest higher accuracy in the detection of ecosystem changes among PAL and FASIR series than with GIMMS, as they detected trends that match expected shifts. In fact, this last series eliminated most of the long term patterns over the continent. For example, in the "Eastern Paraguay" and "Uruguay River margins" focal regions, the

Sidra5: A Search System with Geographic Signatures

OpenAIRE

Cruz, David José Vaz

2007-01-01

Tese de mestrado em Engenharia Informática, apresentada à Universidade de Lisboa através da Faculdade de Ciências, 2007 Este trabalho consistiu no desenvolvimento de um sistema de pesquisa de informação com raciocínio geográfico, servindo de base para uma nova abordagem para modelação da informação geográfica contida nos documentos, as assinaturas geográficas. Pretendeu-se determinar se a semântica geográfica presente nos documentos, capturada através das assinaturas geográficas, contribui...

Clinical and eeg analysis of mesial and lateral temporal lobe seizures Análise clínica e eletrencefalográfica de crises epilépticas temporais de origem mesial e lateral

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FÁBIO GALVÃO DANTAS

1998-09-01

contralateral à área epileptogênica. Verbalização crítica, automatismo de cuspir, piscamento palpebral bilateral, desorientação espacial prolongada e maior percentual de preservação da linguagem no período pós-crítico foram relacionados a crises temporais direitas. Afasia pós-crítica e desorientação global, a crises temporais esquerdas. O EEG teve importante acurácia lateralizatória em ambos os grupos, especialmente quanto à atividade crítica rítmica e achados pós-críticos.

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Science.gov (United States)

Spruce, Joseph P.; Hargrove, William W.; Gasser, Gerald

2013-01-01

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are

The Vegetation Trends and Drivers in Beijing-Tianjing Region from 1982 TO 2013 Based on Time Series Gimms NDVI3g

Science.gov (United States)

Liu, S.; Tian, H.; Wang, X.; Li, H.; He, Y.

2018-04-01

Vegetation plays a leading role in ecosystems. Plant communities are the main components of ecosystems. Green plants in ecosystems are the primary producers, and they provide the living organic matter for the survival of other organisms. The dynamics of most landscapes are driven by both natural processes and human activities. In this study, the growing season GIMMS NDVI3g and climatic data were used to analyse the vegetation trends and drivers in Beijing-Tianjin-Hebei region from 1982 to 2013. Result shows that, the vegetation in Beijing-Tianjin-Hebei region shows overall restoration and partial degradation trend. The significant restoration region accounts for 61.5 % of Beijing-Tianjin-Hebei region, while the significant degradation region accounts for 2.1 %. The dominant climatic factor for time series NDVI were analyzed using the multi-linear regression model. Vegetation growth in 17.9 % of Beijing-Tianjin-Hebei region is dominated by temperature, 35.5 % is dominated by precipitation, and 11.68 % is dominated by solar radiance. Human activities play important role for vegetation restoration in Beijing-Tianjin-Hebei Region, where the large scale forest restoration programs are the main human activities, such as the three-north shelterbelt construction project, Beijing-Tianjin-Hebei sandstorm source control project and grain for green projects.

Monitoring 2009 Forest Disturbance Across the Conterminous United States, Based on Near-Real Time and Historical MODIS 250 Meter NDVI Products

Science.gov (United States)

Spruce, J.; Hargrove, W. W.; Gasser, G.; Smoot, J. C.; Kuper, P.

2009-01-01

This case study shows the promise of computing current season forest disturbance detection products at regional to CONUS scales. Use of the eMODIS expedited product enabled a NRT CONUS forest disturbance detection product, a requirement for an eventual, operational forest threat EWS. The 2009 classification product from this study can be used to quantify the areal extent of forest disturbance across CONUS, although a quantitative accuracy assessment still needs to be completed. However, the results would not include disturbances that occurred after July 27, such as the Station Fire. While not shown here, the project also produced maximum NDVI products for the June 10-July 27 period of each year of the 2000-2009 time frame. These products could be applied to compute forest change products on an annual basis. GIS could then be used to assess disturbance persistence. Such follow-on work could lead to attribution of year in which a disturbance occurred. These products (e.g., Figures 6 and 7) may also be useful for assessing forest change associated with climate change, such as carbon losses from bark beetle-induced forest mortality in the Western United States. Other MODIS phenological products are being assessed for aiding forest monitoring needs of the EWS, including cumulative NDVI products (Figure 10).

ESTUDO DE PREDIÇÃO E PREVISÃO DE TEMPERATURAS MÉDIAS DIÁRIAS DA CIDADE DE CARIACICA, ESPÍRITO SANTO, BRASIL, UTILIZANDO A METODOLOGIA DE SÉRIES TEMPORAIS

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Wanderson de Paula Pinto

2015-03-01

Full Text Available O estudo de séries temporais consiste em extrair periodicidades relevantes nas observações, descrever seu comportamento e fazer previsões. Neste contexto, o presente trabalho teve por objetivo modelar, bem como realizar estudo de predição e previsão de uma série temporal de temperaturas médias diárias da cidade de Cariacica, ES. A análise estatística foi realizada no software R 2.15.1 (software livre considerando 365 observações compreendidas entre o período de 01 de janeiro de 2012 e 31 de dezembro de 2012, de médias diárias de temperatura na estação de Cariacica/ES. A escolha do modelo mais adequado baseou-se no critério de informação de Akaike (AIC.  Os modelos testados tanto para a modelagem como para a previsão apresentaram resultados acurados. Dentre os modelos ajustados, o modelo ARIMA (1,1,2 foi considerado mais adequado para fazer predições e previsão da temperatura média diária no município de Cariacica, ES. 

A Web Architecture to Geographically Interrogate CHIRPS Rainfall and eMODIS NDVI for Land Use Change

Science.gov (United States)

Burks, Jason E.; Limaye, Ashutosh

2014-01-01

Monitoring of rainfall and vegetation over the continent of Africa is important for assessing the status of crop health and agriculture, along with long-term changes in land use change. These issues can be addressed through examination of long-term precipitation (rainfall) data sets and remote sensing of land surface vegetation and land use types. Two products have been used previously to address these goals: the Climate Hazard Group Infrared Precipitation with Stations (CHIRPS) rainfall data, and multi-day composites of Normalized Difference Vegetation Index (NDVI) from the USGS eMODIS product. Combined, these are very large data sets that require unique tools and architecture to facilitate a variety of data analysis methods or data exploration by the end user community. To address these needs, a web-enabled system has been developed to allow end-users to interrogate CHIRPS rainfall and eMODIS NDVI data over the continent of Africa. The architecture allows end-users to use custom defined geometries, or the use of predefined political boundaries in their interrogation of the data. The massive amount of data interrogated by the system allows the end-users with only a web browser to extract vital information in order to investigate land use change and its causes. The system can be used to generate daily, monthly and yearly averages over a geographical area and range of dates of interest to the user. It also provides analysis of trends in precipitation or vegetation change for times of interest. The data provided back to the end-user is displayed in graphical form and can be exported for use in other, external tools. The development of this tool has significantly decreased the investment and requirements for end-users to use these two important datasets, while also allowing the flexibility to the end-user to limit the search to the area of interest.

Mapping of topsoil organic carbon in agro-ecosystems of a flat terrain area (Lombardy) by means of legacy soil data, climatic data and NDVI time series predictors with machine learning methods

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Schillaci, Calogero; Saia, Sergio; Braun, Andreas; Acutis, Marco

2017-04-01

Topsoil organic carbon plays an important role in the agricultural yield, yield potential, and to deliver many ecosystem services, such as the potential to reduce greenhouse gas (GHG) emission from soil. In particular, SOC content sturdily affects soil properties, thus the precision of its estimation can support broad-scale agricultural and environmental management policy. Soils in temperate agro-ecosystem are generally highly productive and cropland occupies about 60% of their surface (Ramankutty et al 2008). In such contexts, lands is frequently subjected to SOC degrading operations, mostly ploughing, with drawbacks on soil fertility and erosion. In temperate agro-ecosystems, a strong role in SOC maintenance can be played by manure and residues inputs after husbandry and related activities and return of plant biomass to the soil (Acutis et al 2014). In this perspective, soil management can have a major role in SOC spatial distribution to maintain soil fertility and ecosystem services in a target area. Due to the considerable importance of SOC on both agronomical and ecological aspects of the agro-ecosystems, regional soil surveys over the years frequently take into account the measurement of SOC concentration and often stock. In the present study, we integrated a highly detailed legacy SOC dataset with climatic data and RS data to produce a reliable SOC maps from a farm to a district scale. In particular, the Normalized Difference Vegetation Index (NDVI)was used after the computation of its average value in a given pixel derived from several approximately cloud-free images. The input dataset was made of about 3000 Ap horizons implemented of SOC concentration, texture, bulk density and metadata. Climatic data (Worldclim), soil type (from the pedological map 1:250000 WRB), and a time series NDVI were applied. The NDVI data were derived from a set of Landsat 5 scenes (path 193, row 28,29) whereas the path 194, (row 28 and 29) contributes for less than one fourth of

Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

Science.gov (United States)

Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

2017-12-01

Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

Validation for Vegetation Green-up Date Extracted from GIMMS NDVI and NDVI3g Using Variety of Methods

Science.gov (United States)

Chang, Q.; Jiao, W.

2017-12-01

Phenology is a sensitive and critical feature of vegetation change that has regarded as a good indicator in climate change studies. So far, variety of remote sensing data sources and phenology extraction methods from satellite datasets have been developed to study the spatial-temporal dynamics of vegetation phenology. However, the differences between vegetation phenology results caused by the varies satellite datasets and phenology extraction methods are not clear, and the reliability for different phenology results extracted from remote sensing datasets is not verified and compared using the ground observation data. Based on three most popular remote sensing phenology extraction methods, this research calculated the Start of the growing season (SOS) for each pixels in the Northern Hemisphere for two kinds of long time series satellite datasets: GIMMS NDVIg (SOSg) and GIMMS NDVI3g (SOS3g). The three methods used in this research are: maximum increase method, dynamic threshold method and midpoint method. Then, this study used SOS calculated from NEE datasets (SOS_NEE) monitored by 48 eddy flux tower sites in global flux website to validate the reliability of six phenology results calculated from remote sensing datasets. Results showed that both SOSg and SOS3g extracted by maximum increase method are not correlated with ground observed phenology metrics. SOSg and SOS3g extracted by the dynamic threshold method and midpoint method are both correlated with SOS_NEE significantly. Compared with SOSg extracted by the dynamic threshold method, SOSg extracted by the midpoint method have a stronger correlation with SOS_NEE. And, the same to SOS3g. Additionally, SOSg showed stronger correlation with SOS_NEE than SOS3g extracted by the same method. SOS extracted by the midpoint method from GIMMS NDVIg datasets seemed to be the most reliable results when validated with SOS_NEE. These results can be used as reference for data and method selection in future's phenology study.

Optimization of the time series NDVI-rainfall relationship using linear mixed-effects modeling for the anti-desertification area in the Beijing and Tianjin sandstorm source region

Science.gov (United States)

Wang, Jin; Sun, Tao; Fu, Anmin; Xu, Hao; Wang, Xinjie

2018-05-01

Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote sensing data and meteorological data to perform residual trend analysis and identify human-induced vegetation changes. However, complex interactions between vegetation and climate, soil units and topography have not yet been considered. Data used in the study included annual accumulated Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m normalized difference vegetation index (NDVI) from 2002 to 2013, accumulated rainfall from September to August, digital elevation model (DEM) and soil units. This paper presents linear mixed-effect (LME) modeling methods for the NDVI-rainfall relationship. We developed linear mixed-effects models that considered the random effects of sample points nested in soil units for nested two-level modeling and single-level modeling of soil units and sample points, respectively. Additionally, three functions, including the exponential function (exp), the power function (power), and the constant plus power function (CPP), were tested to remove heterogeneity, and an additional three correlation structures, including the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and the compound symmetry structure (CS), were used to address the spatiotemporal correlations. It was concluded that the nested two-level model considering both heteroscedasticity with (CPP) and spatiotemporal correlation with [ARMA(1,1)] showed the best performance (AMR = 0.1881, RMSE = 0.2576, adj- R 2 = 0.9593). Variations between soil units and sample points that may have an effect on the NDVI-rainfall relationship should be included in model structures, and linear mixed-effects modeling achieves this in an effective and accurate way.

De como a letra pode fazer frente ao arquivo: escritura e repetição no K, de Kucinski

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Elielson Figueiredo

2017-01-01

Full Text Available Abordamos o romance K, de Bernardo Kucinsk, a fim de compreendê-lo como Escritura dissidente e resistente cuja Assinatura sob o nome do autor é a própria Repetição dos procedimentos narrativos que costumeiramente são adotados pela ficção em torno dos arché de poder institucional. Tentamos teorizar o conceito de Arquivo segundo as reflexões de Derrida para melhor compreendermos a Escritura de Kucinski como texto nascido da experiência sensível das vítimas da repressão ditatorial militar brasileira. Ao mesmo tempo buscamos investigar de que maneira o K é também Repetição de uma Assinatura da culpa de quem sobrevive a catástrofes. Assim, parece-nos, preliminarmente, que a ficção do K é um acontecimento singular, como ocorre sempre que estamos diante de um relato baseado na experiência catastrófica. Este artigo procura dizer como se configura essa Assinatura e como sua Repetição não anula a Escritura como evento único e tampouco se deixa absorver pela autoridade do Arquivo.

The expansion of the sugarcane in the hydrographic basin from Rio Brilhante, Mato Grosso do Sul state: the use of NDVI technique as an instrument for evidencing territorial dynamics

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Patricia Silva Ferreira

2016-12-01

Full Text Available The areas of sugarcane cultivation have expanding, often at the expense of the agricultural and pasture areas. Under this perspective, this manuscript aims to present a methodological guide in order to identify and to map up the areas of sugarcane cultivation, whose unity of analysis was located in the surrounding area of the Rio Brilhante hydrographic basin. We aimed to identify the changes through TM-Landsat5 and OLI-Landsat8 satellite pictures by comparing the scenarios from the years of 2001 and 2015, respectively. The classification of the vegetation was made through the technique of Normalized Difference Vegetation Index (NDVI. Thus, this study points that the use of some techniques and remote sensing tools, like NDVI, when used together with the field research, are extremely efficient for identifying the areas of the sugarcane cultivation.

Monitoring of spatiotemporal patterns of Net and Gross Primary Productivity (NPP & GPP) and their ratios (NPP/GPP) derived from MODIS data: assessment natural drivers and their effects on NDVI anomalies in arid and semi-arid zones of Central Asia.

Science.gov (United States)

Aralova, Dildora; Jarihani, Ben; Khujanazarov, Timur; Toderich, Kristina; Gafurov, Dilshod; Gismatulina, Liliya

2017-04-01

Previous studies have shown that precipitation anomalies and raising of temperature trends were deteriorate affected on large-scale of vegetation surveys in Central Asia (CA). Nowadays, remote sensing techniques can provide estimation of Net and Gross Primary Productivity (NPP & GPP) for regional and global scales, and selected zones in CA (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan) dominated by C4 plants (biomes) what it reveals more accurately simulate C4 carbon. The estimation of NPP & GPP from source (MOD17A2/A3) would be beneficial to determine natural driver factors, whether on rangeland ecosystem is a carbon sink or source, such as a vast area of the selected zones incorporates exacerbate regional drought-risk factors nowadays. Generally, we have combined last available NPP & GPP (2000-2015) with 1 km resolution from MODIS, with investigation of long-term vegetation patterns under Normalized Difference Vegetation Indices (NDVI) with 8 km resolution from AVHRR-GIMMS 3g sources (2001-2015) within aim to estimate potential values of rangeland ecosystems. Interaction ratios of NPP/GPP are integrating more accurately describe carbon sink process under natural or anthropogenic factors, specifically last results of NDVI trends were described as decreasing trends due to climate anomalies, besides the eastern and northern parts of CA (mostly boreal forest zones) where accumulated or indicated of raising trends of NDVI in last three years (2012-2015). Results revealed that, in CA were averaged annually value NDVI ranges from 0.19-0.21; (Kyrgyzstan: 0.23-0.26; Kazakhstan: 0.21-0.24; Tajikistan: 0.19-0.21); and resting countries as low NDVI accumulated areas were Turkmenistan and Uzbekistan ranges 0.13-0.16; Comparing datasets of GPP given the response dynamic change structures of NDVI values and explicit carbon uptake (CO2) in arid ecosystems and average GPPyearlyin CA ranges 2.42 kg C/m2; including to Tajikistan, Uzbekistan (3.09 kg C/m2) and

Distribución espacial de anomalías del NDVI derivado del sensor VEGETATION SPOT 4/5 ysu relación con las coberturas vegetales, usos de la tierra y características geomorfológicas en la provincia de Santiago del Estero, Argentina / Spatial distribution of anomalies of NDVI derived from sensor VEGETATION SPOT 4/5 and its relation with vegetation cover, uses of ground and geomorphology in Santiago del Estero, Argentina

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Jose Luis Tiedermann

2010-12-01

Full Text Available Se determinaron las anomalías negativas (AN y positivas (AP del NDVI derivado del sensor VEGETATION SPOT 4/5, en la provincia de Santiago del Estero, Argentina. El periodo analizado (1998-2008 tuvo fuertes variaciones en los patrones de precipitación, por efecto del ENSO, por cuanto las anomalías del NDVI fueron evaluadas, mediante tabulación cruzada, en función de dos periodos: húmedo (PH y seco (PS. Las AN, se relacionaron, durante todo el periodo, con vegetación halófila en áreas deprimidas salobres, con vegetación hidrófila en ambientes acuáticos y con suelo rocoso. Durante el PS, las AN se relacionaron con áreas deforestadas con fines agrícolas. Las AP, se relacionaron, durante todo el periodo, con el bosque Chaqueño denso y bosque Chaqueño Serrano denso. La mayor estabilidad y productividad de biomasa verde de los bosques, estaría relacionada, a su mayor biodiversidad, estratificación, al predominio de especies leñosas perennes de raíces profundas y a las estratégicas adaptaciones, morfológicas y fisiológicas, para el uso eficiente del agua. Las regiones geomorfológicas no se relacionan entre si entre periodos.AbstractThe negative (AN and positive (AP anomalies of the NDVI derived from sensor VEGETATION SPOT 4/5 were determined in the province of Santiago del Estero, Argentina. The analyzed period (1998-2008 presented strong variations in rainfall patterns, as a result of the ENSO, inasmuch as the anomalies of the NDVI were evaluated, by means of crossed tabulation, based on two periods: humid (PH and dry (PS. The AN, were related with halophytic species of depressed areas, with vegetation aquatic hydrophilic and rocky ground. During the dry period, the AN were related to deforested areas with agricultural aims. The AP, were related, throughout the period with the forest dense Chaco Semiarid and forest dense Chaco Serrano. The greater stability and productivity of green biomass of forest, would be related, greater

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

Science.gov (United States)

Osunmadewa, Babatunde Adeniyi; Gebrehiwot, Worku Zewdie; Csaplovics, Elmar; Adeofun, Olabinjo Clement

2018-03-01

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

Directory of Open Access Journals (Sweden)

Osunmadewa Babatunde Adeniyi

2018-03-01

Full Text Available Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS and end of season (EOS was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0 and a significant decrease in other greenness trend maps (amplitude 1 and phase 1 was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0 was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1 was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Relationship between herbaceous biomass and 1km (2) advanced very high resolution radiometer (AVHRR) NDVI in Kruger National Park, South Africa

CSIR Research Space (South Africa)

Wessels, Konrad J

2006-03-01

Full Text Available biomass and 1-km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa K. J. WESSELS*{, S. D. PRINCE{, N. ZAMBATIS{, S. MACFADYEN{, P. E. FROST§" and D. VAN ZYL§ {Department of Geography, University of Maryland... production (Prince and Justice 1991, Tucker et al. 1991a,b, Myneni et al. *Corresponding author. Email: wessels@geog.umd.edu International Journal of Remote Sensing Vol. 27, No. 5, 10 March 2006, 951–973 International Journal of Remote Sensing ISSN 0143...

Monitoring Invasive Aquatic Vegetation in Lake Okeechobee, Florida, Using NDVI Derived from Modis Data

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Woods, Kate; Brozen, Madeline; Malik, Sadaf; Maki, Angela

2009-01-01

Lake Okeechobee, located in southern Florida, encompasses approximately 1,700 sq km and is a vital part of the Lake Okeechobee and Everglades ecosystem. Major cyanobacterial blooms have been documented in Lake Okeechobee since the 1970s and have continued to plague the ecosystem. Similarly, hydrilla, water hyacinth, and water lettuce have been documented in the lake and continue to threaten the ecosystem by their rapid growth. This study examines invasive aquatic vegetation occurrence through the use of the Normalized Difference Vegetation Index (NDVI) calculated on MOD09 surface reflectance imagery. Occurrence during 2008 was analyzed using the Time Series Product Tool (TSPT), a MATLAB-based program developed at John C. Stennis Space Center. This project tracked spatial and temporal variability of cyanobacterial blooms, and overgrowth of water lettuce, water hyacinth, and hydrilla. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer (MODIS) data to assist in water quality management.

THE VEGETATION TRENDS AND DRIVERS IN BEIJING-TIANJING-HEIBEI REGION FROM 1982 TO 2013 BASED ON TIME SERIES GIMMS NDVI3g

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S. Liu

2018-04-01

Full Text Available Vegetation plays a leading role in ecosystems. Plant communities are the main components of ecosystems. Green plants in ecosystems are the primary producers, and they provide the living organic matter for the survival of other organisms. The dynamics of most landscapes are driven by both natural processes and human activities. In this study, the growing season GIMMS NDVI3g and climatic data were used to analyse the vegetation trends and drivers in Beijing-Tianjin-Hebei region from 1982 to 2013. Result shows that, the vegetation in Beijing-Tianjin-Hebei region shows overall restoration and partial degradation trend. The significant restoration region accounts for 61.5 % of Beijing-Tianjin-Hebei region, while the significant degradation region accounts for 2.1 %. The dominant climatic factor for time series NDVI were analyzed using the multi-linear regression model. Vegetation growth in 17.9 % of Beijing-Tianjin-Hebei region is dominated by temperature, 35.5 % is dominated by precipitation, and 11.68 % is dominated by solar radiance. Human activities play important role for vegetation restoration in Beijing-Tianjin-Hebei Region, where the large scale forest restoration programs are the main human activities, such as the three-north shelterbelt construction project, Beijing-Tianjin-Hebei sandstorm source control project and grain for green projects.

Mapping crop based on phenological characteristics using time-series NDVI of operational land imager data in Tadla irrigated perimeter, Morocco

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Ouzemou, Jamal-eddine; El Harti, Abderrazak; EL Moujahid, Ali; Bouch, Naima; El Ouazzani, Rabii; Lhissou, Rachid; Bachaoui, El Mostafa

2015-10-01

Morocco is a primarily arid to semi-arid country. These climatic conditions make irrigation an imperative and inevitable technique. Especially, agriculture has a paramount importance for the national economy. Retrieving of crops and their location as well as their spatial extent is useful information for agricultural planning and better management of irrigation water resource. Remote sensing technology was often used in management and agricultural research. Indeed, it's allows crops extraction and mapping based on phenological characteristics, as well as yield estimation. The study area of this work is the Tadla irrigated perimeter which is characterized by heterogeneous areas and extremely small size fields. Our principal objectives are: (1) the delimitation of the major crops for a good water management, (2) the insulation of sugar beet parcels for modeling its yields. To achieve the traced goals, we have used Landsat-8 OLI (Operational Land Imager) data pan-sharpened to 15 m. Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) classifications were applied to the Normalized Difference Vegetation Index (NDVI) time-series of 10 periods. Classifications were calculated for a site of more than 124000 ha. This site was divided into two parts: the first part for selecting, training datasets and the second one for validating the classification results. The SVM and SAM methods classified the principal crops with overall accuracies of 85.27% and 57.17% respectively, and kappa coefficient of 80% and 43% respectively. The study showed the potential of using time-series OLI NDVI data for mapping different crops in irrigated, heterogeneous and undersized parcels in arid and semi-arid environment.

The effect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling

Science.gov (United States)

Sulistyo, Bambang

2016-11-01

The research was aimed at studying the efect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling of The USLE using remote sensing data and GIS technique. Methods applied was by analysing all factors affecting erosion such that all data were in the form of raster. Those data were R, K, LS, C and P factors. Monthly R factor was evaluated based on formula developed by Abdurachman. K factor was determined using modified formula used by Ministry of Forestry based on soil samples taken in the field. LS factor was derived from Digital Elevation Model. Three C factors used were all derived from NDVI and developed by Suriyaprasit (non-linear) and by Sulistyo (linear and non-linear). P factor was derived from the combination between slope data and landcover classification interpreted from Landsat 7 ETM+. Another analysis was the creation of map of Bulk Density used to convert erosion unit. To know the model accuracy, model validation was done by applying statistical analysis and by comparing Emodel with Eactual. A threshold value of ≥ 0.80 or ≥ 80% was chosen to justify. The research result showed that all Emodel using three formulae of C factors have coeeficient of correlation value of > 0.8. The results of analysis of variance showed that there was significantly difference between Emodel and Eactual when using C factor formula developed by Suriyaprasit and Sulistyo (non-linear). Among the three formulae, only Emodel using C factor formula developed by Sulistyo (linear) reached the accuracy of 81.13% while the other only 56.02% as developed by Sulistyo (nonlinear) and 4.70% as developed by Suriyaprasit, respectively.

Avaliação das propriedades temporais de duas redes de controle: CAN e PROFIBUS - DOI: 10.4025/actascitechnol.v25i2.2210

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Max Mauro Dias Santos

2003-04-01

Full Text Available Com a grande disponibilidade e o baixo custo atual da tecnologia de redes, a utilização das redes de computadores para interconectar sensores, atuadores e controladores está tornando-se amplamente aceita para a implementação de sistemas de controle realimentado. Tal tipo de implementação, na qual as malhas de controle são fechadas utilizando uma rede de comunicação de tempo real, são chamadas de Sistemas de Controle via Redes (ou NCS, para Networked Control Systems. Quando implementamos um NCS, a rede de comunicação subjacente deve fornecer um serviço de comunicação de tempo-real que satisfaça os requisitos das aplicações de controle. Em conseqüência, é fundamental a avaliação da correção do tempo de resposta da rede de comunicação, quando comparado com os requisitos da aplicação de controle. As redes CAN e PROFIBUS são habitualmente consideradas aceitáveis para suportar NCS de pequena escala, devido a sua capacidade de comunicação de tempo real. No entanto, é também conhecido que a sua correção temporal é altamente dependente das características dos fluxos de mensagens suportados, tais como a sua periodicidade e o comprimento de mensagens relacionado. Neste artigo, comparamos as propriedades temporais das redes de controle CAN e PROFIBUS. Basicamente, avaliamos a sua capacidade para suportar sistemas controlados por computador, através do cálculo do tempo de resposta das mensagens no pior caso. Um pequeno exemplo de um NCS é utilizado para comparar a capacidade dessas redes de controle para satisfazer os requisitos da aplicação de controle suportada.

Beyond the Normalized Difference Vegetation Index (NDVI): Developing a Natural Space Index for population-level health research.

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Rugel, Emily J; Henderson, Sarah B; Carpiano, Richard M; Brauer, Michael

2017-11-01

Natural spaces can provide psychological benefits to individuals, but population-level epidemiologic studies have produced conflicting results. Refining current exposure-assessment methods is necessary to advance our understanding of population health and to guide the design of health-promoting urban forms. The aim of this study was to develop a comprehensive Natural Space Index that robustly models potential exposure based on the presence, form, accessibility, and quality of multiple forms of greenspace (e.g., parks and street trees) and bluespace (e.g., oceans and lakes). The index was developed for greater Vancouver, Canada. Greenness presence was derived from remote sensing (NDVI/EVI); forms were extracted from municipal and private databases; and accessibility was based on restrictions such as private ownership. Quality appraisals were conducted for 200 randomly sampled parks using the Public Open Space Desktop Appraisal Tool (POSDAT). Integrating these measures in GIS, exposure was assessed for 60,242 postal codes using 100- to 1,600-m buffers based on hypothesized pathways to mental health. A single index was then derived using principal component analysis (PCA). Comparing NDVI with alternate approaches for assessing natural space resulted in widely divergent results, with quintile rankings shifting for 22-88% of postal codes, depending on the measure. Overall park quality was fairly low (mean of 15 on a scale of 0-45), with no significant difference seen by neighborhood-level household income. The final PCA identified three main sets of variables, with the first two components explaining 68% of the total variance. The first component was dominated by the percentages of public and private greenspace and bluespace and public greenspace within 250m, while the second component was driven by lack of access to bluespace within 1 km. Many current approaches to modeling natural space may misclassify exposures and have limited specificity. The Natural Space Index

Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

Science.gov (United States)

Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

2012-04-01

Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed

Discriminating the Mediterranean Pinus spp. using the land surface phenology extracted from the whole MODIS NDVI time series and machine learning algorithms

Science.gov (United States)

Rodriguez-Galiano, Victor; Aragones, David; Caparros-Santiago, Jose A.; Navarro-Cerrillo, Rafael M.

2017-10-01

Land surface phenology (LSP) can improve the characterisation of forest areas and their change processes. The aim of this work was: i) to characterise the temporal dynamics in Mediterranean Pinus forests, and ii) to evaluate the potential of LSP for species discrimination. The different experiments were based on 679 mono-specific plots for the 5 native species on the Iberian Peninsula: P. sylvestris, P. pinea, P. halepensis, P. nigra and P. pinaster. The entire MODIS NDVI time series (2000-2016) of the MOD13Q1 product was used to characterise phenology. The following phenological parameters were extracted: the start, end and median days of the season, and the length of the season in days, as well as the base value, maximum value, amplitude and integrated value. Multi-temporal metrics were calculated to synthesise the inter-annual variability of the phenological parameters. The species were discriminated by the application of Random Forest (RF) classifiers from different subsets of variables: model 1) NDVI-smoothed time series, model 2) multi-temporal metrics of the phenological parameters, and model 3) multi-temporal metrics and the auxiliary physical variables (altitude, slope, aspect and distance to the coastline). Model 3 was the best, with an overall accuracy of 82%, a kappa coefficient of 0.77 and whose most important variables were: elevation, coast distance, and the end and start days of the growing season. The species that presented the largest errors was P. nigra, (kappa= 0.45), having locations with a similar behaviour to P. sylvestris or P. pinaster.

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

Science.gov (United States)

Budde, M.E.; Tappan, G.; Rowland, James; Lewis, J.; Tieszen, L.L.

2004-01-01

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Tendências temporais de atividade física no Brasil (2006-2009 Time trends of physical activity in Brazil (2006-2009

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Pedro C Hallal

2011-09-01

Full Text Available OBJETIVO: Analisar as tendências temporais de atividade física (AF nas capitais brasileiras entre 2006 e 2009. MÉTODOS: A análise apresentada neste artigo é baseada nos dados do VIGITEL, totalizando uma amostra anual aproximada de 54.000 indivíduos. Foram analisados indicadores de AF no tempo livre, trabalho, em casa e no deslocamento, além do tempo assistindo à televisão e de inatividade considerando todos os domínios de AF. A variação dos indicadores no período foi aferida por meio de modelos de regressão de Poisson, tendo como variável explanatória o ano do inquérito. Foi considerada significativa a evolução correspondente a um coeficiente de regressão diferente de zero (pOBJECTIVE: To examine time trends in physical activity (PA in Brazilian state capitals from 2006 to 2009. METHODS: This analysis is based on data from the Telephone-based Surveillance of Risk and Protective Factors for Chronic Diseases (VIGITEL accounting for an annual sample of approximately 54,000 individuals. PA indicators were analyzed in free time (leisure, work, home and transportation, time spent in front of the television and inactivity considering all PA domains. Poisson regression models were used to measure the variation of indicators over time. We considered the changes corresponding to a regression coefficient different from zero as being statistically significant (p<0.05. RESULTS: The percentage of active commuters increased from 11.7 to 14.4% (p<0.001 whereas the proportion of physically inactive individuals in the four domains decreased from 11.7 to 8.7% (p<0.001. There were no significant changes in the other indicators. Women were less active than men in all indicators, except for household chores. However, in this indicator the percentage of active women decreased from 71.4 to 67.1% (p<0.001. Between 2006 and 2009, PA levels in the Brazilian population were stable during free time and household chores, but increased in transportation

Deriving Vegetation Dynamics of Natural Terrestrial Ecosystems from MODIS NDVI/EVI Data over Turkey.

Science.gov (United States)

Evrendilek, Fatih; Gulbeyaz, Onder

2008-09-01

The 16-day composite MODIS vegetation indices (VIs) at 500-m resolution for the period between 2000 to 2007 were seasonally averaged on the basis of the estimated distribution of 16 potential natural terrestrial ecosystems (NTEs) across Turkey. Graphical and statistical analyses of the time-series VIs for the NTEs spatially disaggregated in terms of biogeoclimate zones and land cover types included descriptive statistics, correlations, discrete Fourier transform (DFT), time-series decomposition, and simple linear regression (SLR) models. Our spatio-temporal analyses revealed that both MODIS VIs, on average, depicted similar seasonal variations for the NTEs, with the NDVI values having higher mean and SD values. The seasonal VIs were most correlated in decreasing order for: barren/sparsely vegetated land > grassland > shrubland/woodland > forest; (sub)nival > warm temperate > alpine > cool temperate > boreal = Mediterranean; and summer > spring > autumn > winter. Most pronounced differences between the MODIS VI responses over Turkey occurred in boreal and Mediterranean climate zones and forests, and in winter (the senescence phase of the growing season). Our results showed the potential of the time-series MODIS VI datasets in the estimation and monitoring of seasonal and interannual ecosystem dynamics over Turkey that needs to be further improved and refined through systematic and extensive field measurements and validations across various biomes.

The value of different vegetative indices (NDVI, GAI for the assessment of yield potential of pea (Pisum sativum L. at different growth stages and under varying management practices

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Agnieszka Klimek-Kopyra

2018-03-01

Full Text Available This research evaluated the NDVI (normalized difference vegetation index and GAI (green area index in order to indicate the productivity and developmental effects of Rhizobium inoculants and microelement foliar fertilizer on pea crops. Two inoculants, Nitragina (a commercial inoculant and IUNG (a noncommercial inoculant gel and a foliar fertilizer (Photrel were studied over a 4-year period, 2009–2012. The cultivars chosen for the studies were characterized by different foliage types, namely a semileafless pea ‘Tarchalska’ and one with regular foliage, ‘Klif’. Foliar fertilizer significantly increased the length of the generative shoots and the number of fruiting nodes in comparison to the control, which in turn had a negative impact on the harvest index. Pea seed yield was highly dependent on the interaction between the years of growth and the microbial inoculant, and was greater for ‘Tarchalska’ (4.33 t ha−1. Presowing inoculation of seeds and foliar fertilization resulted in a significantly higher value of GAI at the flowering (3.91 and 3.81, respectively and maturity stages (4.82 and 4.77, respectively, whereas the value of NDVI was higher for these treatments only at the maturity stage (0.67 and 0.79, respectively. A significantly greater yield (5.0–5.4 t ha−1 was obtained after inoculation with IUNG during the dry years.

Aplicação de índices das condições de vegetação no monitoramento em tempo quase real da seca em Moçambique usando NOAA_AVHRR- NDVI

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Paulo Alberto Covele

2011-12-01

Full Text Available Este artigo tem por objetivo aplicar diferentes índices das condições de vegetação e avaliar suas diferenças e aptidão no monitoramento da distribuição espacial e temporal da seca em Moçambique com base em imagens NDVI da NOAA- AVHRR. Para tanto, avalia as differenças de aptidão dos índices das condições de vegetação especialmente o Índice das Condições de Vegetação (Vegetation Condition Index- VCI, Índice Padronizado de Vegetação (Standardized Vegetation Index- SVI e o Indicador de Productividade da Vegetação (Vegetation Productivity Indicator- VPI no monitoramento da seca em Moçambique. Estes índices são derivados a partir de imagens da Diferença Normalizada do Índice da Vegetação (Normalized Difference Vegetation Index- NDVI de 1981 a 2005, produzidas a partir dos canais 1 e 2 do sensor Advanced Very Higher Resolution Radiometer (AVHRR a bordo dos satélites da National Oceanic and Atmospheric Administration (NOAA.

Poluição do ar e doenças respiratórias e cardiovasculares: estudo de séries temporais em Cubatão, São Paulo, Brasil

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Adelaide Cassia Nardocci

2013-09-01

Full Text Available Foi avaliado o impacto da poluição do ar nas internações por doenças respiratórias e cardiovasculares em residentes do Município de Cuba-tão, São Paulo, Brasil. Utilizaram-se modelos de séries temporais, com modelos aditivos generalizados, em regressão de Poisson, testando como variáveis independentes as concentrações diárias de material particulado (PM10; dióxido de enxofre (SO2 e o ozônio (O3. Como variáveis de controle a temperatura, umidade, dias da semana e feriados. Para cada incremento de 10µg/m³ de PM10, encontrou-se um excesso de internações de 4,25% (IC95%: 2,82; 5,71; 5,74% (IC95%: 3,80; 7,71 e 2,29% (IC95%: 0,86; 3,73 para doenças respiratórias totais, doenças respiratórias em menores de 5 anos e doenças cardiovasculares em maiores de 39 anos, respectivamente. O SO2 apresentou relação com as doenças cardiovasculares em maiores de 39 anos de 3,51% (IC95%: 1,24; 5,83 e o O3 com as doenças cardiovasculares em maiores de 39 anos: 2,85% (IC95%: 0,77; 4,98 e doenças respiratórias em menores de 5 anos: 3,91% (IC95%: 1,37; 6,51. Os efeitos da poluição atmosférica na saúde em Cubatão são pronunciados, indicando a necessidade de melhoria das políticas de controle.

Global patterns of NDVI-indicated vegetation extremes and their sensitivity to climate extremes

International Nuclear Information System (INIS)

Liu Guo; Liu Hongyan; Yin Yi

2013-01-01

Extremes in climate have significant impacts on ecosystems and are expected to increase under future climate change. Extremes in vegetation could capture such impacts and indicate the vulnerability of ecosystems, but currently have not received a global long-term assessment. In this study, a robust method has been developed to detect significant extremes (low values) in biweekly time series of global normalized difference vegetation index (NDVI) from 1982 to 2006 and thus to acquire a global pattern of vegetation extreme frequency. This pattern coincides with vegetation vulnerability patterns suggested by earlier studies using different methods over different time spans, indicating a consistent mechanism of regulation. Vegetation extremes were found to aggregate in Amazonia and in the semi-arid and semi-humid regions in low and middle latitudes, while they seldom occurred in high latitudes. Among the environmental variables studied, extreme low precipitation has the highest slope against extreme vegetation. For the eight biomes analyzed, these slopes are highest in temperate broadleaf forest and temperate grassland, suggesting a higher sensitivity in these environments. The results presented here contradict the hypothesis that vegetation in water-limited semi-arid and semi-humid regions might be adapted to drought and suggest that vegetation in these regions (especially temperate broadleaf forest and temperate grassland) is highly prone to vegetation extreme events under more severe precipitation extremes. It is also suggested here that more attention be paid to precipitation-induced vegetation changes than to temperature-induced events. (letter)

Monitoring Regional Forest Disturbances across the US with Near Real Time MODIS NDVI Products included in the ForWarn Forest Threat Early Warning System

Science.gov (United States)

Spruce, Joseph; Hargrove, William W.; Gasser, Gerald; Norman, Steve

2013-01-01

U.S. forests occupy approx.1/3 of total land area (approx. 304 million ha). Since 2000, a growing number of regionally evident forest disturbances have occurred due to abiotic and biotic agents. Regional forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest disturbance monitoring products are needed to aid forest health management work. Near Real Time (NRT) twice daily MODIS NDVI data provide a means to monitor U.S. regional forest disturbances every 8 days. Since 2010, these NRT forest change products have been produced and posted on the US Forest Service ForWarn Early Warning System for Forest Threats.

Processamento auditivo: comparação entre potenciais evocados auditivos de média latência e testes de padrões temporais Auditory processing: comparision between auditory middle latency response and temporal pattern tests

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Eliane Schochat

2009-06-01

Full Text Available OBJETIVO: verificar a concordância entre os resultados da avaliação do Potencial Evocado Auditivo de Média Latência e testes de padrões temporais. MÉTODOS: foram avaliados 155 sujeitos de ambos os sexos, idade entre sete e 16 anos, com audição periférica normal. Os sujeitos foram submetidos aos testes de Padrão de Frequência e Duração e Potenciais Evocados auditivos de Média Latência. RESULTADOS: os sujeitos foram distribuídos em dois grupos: normal ou alterado para o processamento auditivo. O índice de alteração foi em torno de 30%, exceto para Potencial Evocado Auditivo de Média Latência que foi pouco menor (17,4%. Os padrões de frequência e duração foram concordantes até 12 anos. A partir dos 13 anos, observou-se maior ocorrência de alteração no padrão de frequência que no padrão de duração. Os padrões de frequência e duração (orelhas direita e esquerda e Potencial Evocado Auditivo de Média Latência não foram concordantes. Para 7 e 8 anos a combinação padrão de frequência e duração normal / Média Latência alterado tem maior ocorrência que a combinação padrão de frequência e duração alterada / Média Latência normal. Nas demais idades, ocorreu o contrário. Não houve diferença estatística entre as faixas etárias quanto à distribuição de normal e alterado no padrão de frequência (orelhas direita e esquerda, nem para o Potencial Evocado Auditivo de Média Latência, com exceção do padrão de duração para o grupo de 9 e 10 anos. CONCLUSÃO: não houve concordância entre os resultados do Potencial Evocado Auditivo de Média Latência e os testes de padrões temporais aplicados.PURPOSE: to check the concordance between the Middle Latency Response and temporal processing tests. METHODS: 155 normal hearing subjects of both genders (age group range between 7 to 16 years were evaluated with the Pitch and Duration Pattern Tests (behavioral and Middle Latency Response

Conhecimento e voluntariedade para participação em pesquisas: um estudo descritivo com participantes de um ensaio clínico

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Lucas Lobato

2014-06-01

Full Text Available O objetivo deste estudo é avaliar o conhecimento sobre as informações do Termo de Consentimento Livre e Esclarecido (TCLE e a voluntariedade de participantes de um ensaio clínico. Trata-se de um estudo quantitativo, descritivo, transversal, realizado em novembro de 2011 com participantes de um ensaio clínico realizado em Americaninhas, no Nordeste de Minas Gerais, Brasil. Amostra por conveniência, com 143 adultos de 18 a 45 anos, de ambos os sexos. Utilizou-se um questionário estruturado, aplicado uma semana após a assinatura do TCLE. A maioria dos participantes do ensaio clínico assinou o TCLE sem o conhecimento suficiente das informações da pesquisa, e sofreu influência em sua decisão de participar do ensaio clínico. Concluímos que a assinatura do TCLE não garante a expressão da autonomia de todos os participantes de pesquisa clínica.

A procedure to derive intra-and inter-annual changes on vegetation from NDVI time series. A case study in Spain

International Nuclear Information System (INIS)

Gilabert, M. A; Martinez, B.; Melia, J.

2009-01-01

The objective of this work is to study the spatial patterns of vegetation activity over spain and its temporal variability throughout the period 1989-2002. A multi-resolution analysis (MRA) bases on the wavelet transform has been implemented on NDVI time series from the MEDOKADS database. The MRA decomposes the original signal as a sum of series associated with temporal scales. Specifically, the intra-annual series is processed to define several key features in relation with the vegetation penology. In contras, the inter-annual components of the signal is used to detect trends by means of a Mann-Kendall test and map the magnitude of the land-cover change. Finally, a comprehensive identification of the areas presenting a negative value of the magnitude of change is carried out to select those linked to land degradation processes. Results show a major presence of these areas the Southeast of Spain. (Author) 5 refs.

A procedure to derive intra-and inter-annual changes on vegetation from NDVI time series. A case study in Spain

Energy Technology Data Exchange (ETDEWEB)

Gilabert, M. A; Martinez, B.; Melia, J.

2009-07-01

The objective of this work is to study the spatial patterns of vegetation activity over spain and its temporal variability throughout the period 1989-2002. A multi-resolution analysis (MRA) bases on the wavelet transform has been implemented on NDVI time series from the MEDOKADS database. The MRA decomposes the original signal as a sum of series associated with temporal scales. Specifically, the intra-annual series is processed to define several key features in relation with the vegetation penology. In contras, the inter-annual components of the signal is used to detect trends by means of a Mann-Kendall test and map the magnitude of the land-cover change. Finally, a comprehensive identification of the areas presenting a negative value of the magnitude of change is carried out to select those linked to land degradation processes. Results show a major presence of these areas the Southeast of Spain. (Author) 5 refs.

Situação de saúde da criança em área da região sul do Brasil, 1980-1992: tendências temporais e distribuição espacial

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Cesar G. Victora

1994-12-01

Full Text Available Embora as estatísticas vitais sejam de fundamental importância para o planejamento e avaliação das ações de saúde, são poucos os Estados brasileiros que dispõem de sistema de registro com cobertura e agilidade suficiente para atingir estas metas. Objetivou, portanto, analisar os dados gerados no Rio Grande do Sul, Brasil, para descrever tendências temporais e distribuição espacial de indicadores de saúde infantil, incluindo os coeficientes de mortalidade infantil e de mortalidade proporcional de menores de um ano, prevalência de baixo peso ao nascer, e cobertura vacinal. Entre 1980 e 1992, observaram-se reduções marcantes na mortalidade infantil (de 39,0 para 19,3 por mil e na mortalidade proporcional de menores de um ano (de 13,9% para 5,9%. A prevalência de baixo peso ao nascer mostrou-se estável entre 8 e 10%, tendo mesmo sido observado discreto aumento até 1991. A cobertura de vacina tríplice oscilou marcadamente de ano a ano, entre 79% e 99%. Houve forte correlação, ao nível de Delegacias Regionais de Saúde, entre mortalidade infantil e baixo peso ao nascer. Os 4 indicadores estudados foram combinados de forma a construir um escore para identificar as Delegacias de Saúde com maiores necessidades de intervenções sanitárias. A região sul do Estado, caracterizada pela presença de grandes latifúndios, mostrou os piores índices de saúde infantil.

Factores psicológicos e cronobiológicos do rendimento desportivo

OpenAIRE

Silvério, Jorge Manuel Amaral

2003-01-01

A cronobiologia é o estudo sistemático das características temporais da matéria viva em todos os seus níveis de organização sendo a ciência que investiga e quantifica mecanismos de estruturas temporais biológicas (Halberg, Carandente, Cornélissen & Katinas, 1977). Apesar de a ritmicidade em diversos organismos ser descrita desde a antiguidade a Cronobiologia só foi reconhecida como ciência a partir de 1960, data da realização do Cold Spring Harbor Symposium on Biological Clocks, onde foram ad...

ESTUDO COMPARATIVO ENTRE OS ÍNDICES NDVI OBTIDOS A PARTIR DOS SENSORES LANDSAT 5 - TM E RESOURCESAT - LISS III

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Cesar Vinícius Mendes Nery

2013-07-01

Full Text Available A importância das imagens de sensoriamento remoto para o monitoramento da cobertura vegetal é algo inegável. Por mais de três décadas a série Landsat tem fornecido imagens da terra, porém a partir de novembro de 2011 o satélite interrompeu a disponibilização de suas imagens para o monitoramento ambiental. Uma das alternativas de imagens ao Landsat têm sido as imagens do sensor LISS III a bordo do satélite indiano Resourcesat 1. O presente trabalho tem como área de estudo o município de Janaúba, por estar em uma área de transição de dois biomas, e o mesmo tem por objetivo comparar os dois sensores, o sensor TM que se encontra a bordo do satélite Landsat 5 e o sensor LISS III a bordo do satélite Resourcesat 1. Para esse estudo comparativo as imagens foram adquiridas do site do Instituto Nacional de Pesquisas Espaciais (INPE e seus valores de níveis digitais (ND foram convertidos em reflectância com correção atmosférica utilizando o método de correção DOS. Amostras de pixels das imagens índice foram coletadas para o estudo de correlação e ajuste de uma equação linear por meio da técnica de regressão. Utilizando a equação ajustada foram gerados dois mapas temáticos de ambos os sensores, sendo os mesmos comparados pelo teste estatístico Kappa. Os resultados mostraram uma forte correlação entre os valores de NDVI (0,81, sendo possível o ajuste de uma equação linear que expresse a forma dessa relação. O sensor TM, superestimou os valores de NDVI em relação ao sensor LISS III (Inclinação de 1,1035. O valor de Kappa para os mapas temáticos obtidos foi de 0,5894 e o índice de acerto foi de 98,81%, o que mostra uma boa similaridade entre eles. O sensor LISS III pode ser perfeitamente utilizado como alternativa ao Landsat 5.

[The variability of vegetation beginning date of greenness period in spring in the north-south transect of eastern China based on NOAA NDVI].

Science.gov (United States)

Wang, Zhi; Liu, Shi-rong; Sun, Peng-sen; Guo, Zhi-hua; Zhou, Lian-di

2010-10-01

NDVI based on NOAA/AVHRR from 1982 to 2003 are used to monitor variable rules for the growing season in spring of vegetation in the north-south transect of eastern China (NSTEC). The following, mainly, are included: (1) The changing speed of greenness period in spring of most regions in NSTEC is slow and correlation with the year is not distinct; (2) The regions in which greenness period in spring distinctly change mainly presented an advance; (3) The regions in which inter-annual fluctuation of greenness period in spring is over 10 days were found in 3 kinds of areas: the area covered with agricultural vegetation types; the areas covered with evergreen vegetation types; the areas covered with steppe vegetation types; (4) changes of vegetation greenness period in spring have spatio-temporal patterns.

O tempo no conto "Testemunha", de Lídia Jorge

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Letícia Braz da Silva

2013-10-01

Full Text Available O presente artigo tem por fito analisar a estrutura temporal do conto “Testemunha”, de Lídia Jorge, a partir da aplicação teórica da metodologia do estudo do texto narrativo proposto por Gérard Genette, mas se apropriando também de outros teóricos que estudaram o assunto: Paul Ricoeur e Benedito Nunes. O conto em questão permite esse tipo de abordagem, pelo fato da escritora se valer do tempo narrativo como categoria central em sua história, apresentando evocações de cenas da infância, no período escolar, rememoradas pela protagonista. A alteração da ordem temporal (anacronia é, portanto, evidente nesta narrativa, tendo a organização discursiva subvertida por meio de recuos temporais (analepses, que contribuem para a motivação da história. Como método, o levantamento de referências temporais contribuiu tanto no entendimento da configuração da analepse no discurso narrativo de “Testemunha”, quanto em sua classificação no que concerne à tipologia narrativa: narração ulterior, em sua totalidade. Por se tratar de um conto contemporâneo, notam-se inversões da ordem dos acontecimentos, por vezes, sem dizer; sendo cabível, portanto, a análise do aspecto linguístico (expressões, indícios temporais para auxiliar nas identificações das variações temporais e, consequentemente, do movimento retrospectivo do conto de Lídia Jorge.

Os Transgênicos na Imprensa: o caso da liberação da soja Roundup Ready

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Mariana Pereira Barbosa

2004-12-01

Full Text Available Os organismos geneticamente modificados necessitam de regulamentação no Brasil. A sua chegada ao mercado de alimentos, ainda que de forma ilegal, tem exposto a variedade de argumentos e interesses que permeiam a sua liberação e comercialização. A assinatura da Medida Provisória 131/03, em setembro de 2003 (BRASIL. Medida..., 2003b, pelo presidente da República Luiz Inácio Lula da Silva, permitiu temporariamente o plantio legal de soja transgênica pelos agricultores. O fato motivou uma cobertura diária e massiva da imprensa gaúcha durante muitas edições. Partindo dos referenciais éticos jornalísticos e do conceito de jornalismo ambiental, o trabalho pretende analisar a cobertura de quatro jornais gaúchos no período que antecedeu a assinatura. O objetivo é levantar quais as fontes e os argumentos que foram evidenciados na cobertura com a intenção de analisar se houve eficiência na informação dos posicionamentos opostos sobre o tema.

Tabagismo em estudantes de Medicina: tendências temporais e fatores associados Smoking among medical students: temporal trends and related variables

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Ana Maria Baptista Menezes

2004-06-01

Full Text Available INTRODUÇÃO: Após o declínio observado na prevalência de tabagismo entre estudantes de Medicina entre as décadas de 1960 e 1980, parece estar ocorrendo, atualmente, uma estabilização nessa prevalência. OBJETIVO: Avaliar as tendências temporais de tabagismo entre estudantes de Medicina da Universidade Federal de Pelotas (RS nos últimos dezessete anos, e alguns dos fatores associados ao hábito de fumar desses estudantes. MÉTODO: Estudos transversais com metodologias comparáveis foram conduzidos em 1986, 1991, 1996 e 2002. Questionários auto-aplicáveis foram utilizados. Definiu-se como fumante o indivíduo que fumava mais de um cigarro por dia há mais de um mês. Foram realizadas análises descritivas iniciais, análises brutas com utilização dos testes de qui-quadrado para heterogeneidade e tendência linear, e regressão de Poisson para avaliar o efeito do ano cursado sobre a freqüência de tabagismo, com controle para a idade do estudante. RESULTADOS: A prevalência atual de tabagismo entre os estudantes foi de 10,1%, valor estatisticamente similar ao dos levantamentos de 1991 e 1996. Não foram encontradas diferenças na prevalência de tabagismo por sexo, idade, tabagismo materno ou paterno. A freqüência de tabagismo aumentou durante a faculdade. CONCLUSÕES: A tendência de declínio na prevalência de tabagismo em estudantes de Medicina da Universidade Federal de Pelotas parece estar sendo substituída por uma estabilização em torno de 10% a 15%. O combate ao fumo ainda parece indispensável em ambientes universitários, especialmente nas escolas de Medicina.BACKGROUND: Although the prevalence of smoking among medical students declined steadily between the 1960s and 1980s, it seems to have stabilized in recent years. OBJECTIVES: To evaluate temporal trends, over the last 17 years, in the smoking habits of medical students at the Universidade Federal de Pelotas, in the state of Rio Grande do Sul, Brazil, and to identify

Aspectos prosódicos temporais da leitura de escolares com dislexia do desenvolvimento Temporal prosodic aspects of reading in students with developmental dyslexia

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Luciana Mendonça Alves

2009-01-01

Full Text Available OBJETIVO: Analisar, do ponto de vista fonético, por meio de medidas acústicas e perceptivas, os aspectos prosódicos temporais presentes na leitura em voz alta de escolares com e sem dislexia, a fim de identificar diferenças de desempenho entre os dois tipos de leitores que possam apontar para características peculiares da dislexia. MÉTODOS: Gravação da leitura de um texto por 40 escolares (entre nove e 14 anos, cursando da 3ª à 5ª série, sendo 10 disléxicos (grupo clínico e 30 escolares sem queixas de alterações de aprendizagem (grupo não-clínico. Os dados foram analisados perceptivamente e acusticamente, utilizando-se o programa WinPitch. As seguintes medidas foram realizadas: duração e localização das pausas, tempo total de elocução, taxa de elocução, tempo de articulação e taxa de articulação. RESULTADOS: Em comparação com o grupo não-clínico, o grupo clínico apresentou maior número de pausas e pausas mais longas; os valores obtidos para as taxas de elocução e de articulação indicaram respectivamente menor velocidade de leitura e uma lentidão na produção de cada gesto articulatório. CONCLUSÃO: As dificuldades identificadas no processamento da leitura pelas crianças com dislexia dificultam a organização prosódica na leitura de um texto.PURPOSE: To analyze the temporal prosodic aspect in loud reading of students with and without dyslexia from the phonetic point of view through acoustic and perceptual evaluation, in order to identify differences in performance between the two types of readers that may point to particular characteristics of dyslexia. METHODS: Forty students from 3rd to 5th grades with ages ranging from nine to 14 years, ten dyslexic (clinical group and 30 without any complaints of learning deficits (non-clinical group were recorded during loud reading of a text. Data were perceptually and acoustically analyzed using the software WinPitch. The following measures were taken: pause

Development and Application of an Annual Vegetation-Monitoring Tool in Gishwati Forest Reserve using MODIS NDVI product and Landsat-5 and 7

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Makar, N. I.; Butler, K.; Fox, T.; Geddes, Q. A.; Janse van Vuuren, L.; Li, A.; Sharma, A.

2012-12-01

As the most densely populated country in Africa, Rwanda relies heavily on a limited supply of natural resources to sustain its agrarian economy. Population pressures, economic policy, and the aftermath of the genocide have placed particular stress on the Gishwati Forest in Rwanda's Western Province. Deforestation for agricultural purposes and fuel consumption has disrupted the local climate, soil structure, and topography, leading to increased erosion, landslides and flooding. Once 280 km2, by 1995 the Gishwati Forest was only 6 km2. The Rwandan government and international NGOs have started initiatives to reverse deforestation, which would benefit from monitoring and evaluation using remote sensing technology. This study filled the gaps in the tumultuous history of Gishwati Forest since 1982 using NASA's Earth Observing System, specifically Landsat 5 and AVHRR. In collaboration with partner organizations, we developed a robust, yet simple to use, forest monitoring tool employing MODIS NDVI product and Landsat that provide annual estimates of the forest's health.

MODIS-derived EVI, NDVI and WDRVI time series to estimate phenological metrics in French deciduous forests

Science.gov (United States)

Testa, S.; Soudani, K.; Boschetti, L.; Borgogno Mondino, E.

2018-02-01

Monitoring forest phenology allows us to study the effects of climate change on vegetated land surfaces. Daily and composite time series (TS) of several vegetation indices (VIs) from MODerate resolution Imaging Spectroradiometer (MODIS) data have been widely used in scientific works for phenological studies since the beginning of the MODIS mission. The objective of this work was to use MODIS data to find the best VI/TS combination to estimate start-of-season (SOS) and end-of-season (EOS) dates across 50 temperate deciduous forests. Our research used as inputs 2001-2012 daily reflectance from MOD09GQ/MOD09GA products and 16-day composite VIs from the MOD13Q1 dataset. The 50 pixels centered on the 50 forest plots were extracted from the above-mentioned MODIS imagery; we then generated 5 different types of TS (1 daily from MOD09 and 4 composite from MOD13Q1) and used all of them to implement 6 VIs, obtaining 30 VI/TS combinations. SOS and EOS estimates were determined for each pixel/year and each VI/TS combination. SOS/EOS estimations were then validated against ground phenological observations. Results showed that, in our test areas, composite TS, if actual acquisition date is considered, performed mostly better than daily TS. EVI, WDRVI0.20 and NDVI were more suitable to SOS estimation, while WDRVI0.05 and EVI were more convenient in estimating early and advanced EOS, respectively.

Variações temporais na passagem de peixes pelo elevador da Usina Hidrelétrica de Santa Clara, rio Mucuri, leste brasileiro Temporal patterns of fish passage in Santa Clara Power Plant's fish lift, Mucuri River, east Brazil

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Paulo dos S. Pompeu

2006-06-01

Full Text Available O presente estudo teve como objetivo determinar padrões temporais na passagem de peixes pelo elevador da Usina Hidrelétrica de Santa, localizado no rio Mucuri. Durante quatro meses, de novembro de 2003 a março de 2004, foram realizados ciclos de transposição a cada duas horas, quando todos os indivíduos foram contados e identificados. Durante este período foram transpostos 67.838 indivíduos de 31 espécies. A abundância de Characiformes migradores no elevador foi maior no período diurno, enquanto Siluriformes foram observados em maior quantidade à noite. A abundância de peixes no elevador foi relacionada significativamente com as vazões no rio Mucuri. O padrão encontrado torna possível a melhor utilização do elevador, priorizando sua operação durante o dia e em períodos de maior vazão.The current study had the objective of determining temporal patterns of fish passage in Santa Clara Power Plant's fish lift, Mucuri River. During four months, from November 2003 to March 2004, transposition cycles were performed each two hours, when the specimens were counted and identified. During this migration period 67,838 individuals of 31 species passed through the lift. Migratory Characiformes abundance was larger during the day, whereas the Siluriformes were registered mainly at night. Fish abundance in the lift was significantly related to the Mucuri river flow. The temporal pattern found makes possible a better utilization of the lift, focusing cycles during the day and high flows periods.

Segundo termo aditivo [ao] Acordo de cooperação cultural, educacional e científico entre a Universidade Presbiteriana Mackenzie - UPM e Universidades Lusíada

OpenAIRE

Universidade Lusíada de Lisboa; Universidade Lusíada do Porto; Universidade Lusíada de Vila Nova de Famalicão; Universidade Presbiteriana Mackenzie

2014-01-01

Data da assinatura: 22 de outubro de 2014 Promover a cooperação académica entre as Faculdades de Arquitectura e Artes das Universidades Lusíada e a Faculdade de Arquitectura e Urbanismo da Universidade Presbiteriana Mackenzie, através do reconhecimento mútuo de formação em vista da possível outorga de dupla titulação.

CERTIFICAÇÃO DIGITAL E ARQUIVOLOGIA: benefícios e aplicações

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Tatiane Rodrigues do Nascimento

2015-06-01

Full Text Available A sociedade da informação abriu novos campos e oportunidades, e a informação nas redes digitais ganhou dimensões sem fronteiras, surgindo a necessidade de políticas de segurança para garantir a autenticação, privacidade, autorização e integridade dos dados. A solução encontrada para solucionar esses problemas foi a utilização de um sistema de criptografia. O governo brasileiro criou padrões técnicos para suportar um sistema criptográfico, chamado de Infraestrutura de Chaves Públicas Brasileira (ICP-Brasil, com o objetivo de regulamentar o uso de certificados digitais. Com o surgimento e crescimento intenso desse novo formato de documento, a Arquivologia sentiu necessidade de incorporar essa ferramenta. Se por um lado a assinatura digital confere autenticidade e integridade à informação, por outro os avanços não garantem a sua preservação no longo prazo. O valor legal da autenticidade desse documento está relacionado às assinaturas digitais. Sob a ótica da arquivística e da diplomática, a autenticidade dos documentos não depende apenas da assinatura, mas de um conjunto de elementos. O presente trabalho tem por objetivo analisar o mercado de certificado digital na cidade de Manaus, sob a ótica da Arquivologia, ou seja, da autenticidade e sigilo nos documentos digitais. Metodologicamente, refere-se a uma pesquisa de natureza qualitativa, com caráter exploratório-descritivo, realizada por meio de um estudo de caso e por possuir um objetivo definido. Buscou-se avaliar se as autoridades certificadoras possuem estruturas para garantir a segurança e transação dos documentos digitais na cidade de Manaus-AM. Como resultado, observou-se que o setor financeiro foi o primeiro a utilizar o certificado digital, seguido pelo setor fiscal, que ganhou destaque com a nota fiscal eletrônica, e mais tarde pelo judiciário, com o processo eletrônico, que ao mesmo tempo foi responsável por aumentar o número de advogados

Previsão e séries temporais para tomada de decisão empresarial em uma indústria moveleira da região de Criciúma–SC = A study of forecasting and time series for business decision making in a furniture industry in Criciúma-SC

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Fernanda Cristina Barbosa Pereira Queiroz

2012-07-01

Full Text Available Uma previsão adequada deve dar suporte a uma decisão minimizadora de risco por parte dos tomadores de decisão, sendo essencial para o planejamento individual e organizacional de agentes econômicos. Neste sentido, o objetivo deste artigo é realizar um estudo sobre previsão e séries temporais para tomada de decisão empresarial em uma indústria moveleira da região de Criciúma–SC. A metodologia utilizada fundamenta-se na construção de modelos univariados de previsão de preços, com base em dados de séries temporais. O estudo é classificado como exploratório, bibliográfico e um estudo de caso com dados quantitativos. Há uma grande variedade de modelos aplicáveis a estudos desta natureza. Para fins desta pesquisa, optou-se por selecionar o método linear Holt e Holt-Winters e o modelo ARIMA (Auto Regressive Integrate Moving Average. Procurou-se, neste sentido, apresentar os diferentes modelos disponíveis na literatura, objetivando estimar a demanda por móveis para banheiro e projetar vendas futuras. Os resultados mostraram que o modelo ARIMA (Auto Regressive Integrate Moving Average não se mostrou eficiente no caso analisado, devido ao número pequeno de dados, o que impossibilitou uma análise da sazonalidade, sugerindo-se que a empresa utilize o método de Holt, a fim de estimar o número de produtos a ser vendido e que, à medida que os novos produtos sejam vendidos, os demais modelos sejam testados novamente, uma vez que a incorporação de novos dados irá permitir confirmar a existência ou não da sazonalidade. An adequate forecast should give support to minimize risk decisions by the decision makers, being essential for individual and organizational planning of economic agents. In this sense, the purpose of this paper is to conduct a study about forecast and time series for business decision-making in a furniture industry in the region of Criciúma, SC. The methodology was based on the construction of univariate models

Monitoring irrigation water consumption using high resolution NDVI image time series (Sentinel-2 like). Calibration and validation in the Kairouan plain (Tunisia)

Science.gov (United States)

Saadi, Sameh; Simonneaux, Vincent; Boulet, Gilles; Mougenot, Bernard; Zribi, Mehrez; Lili Chabaane, Zohra

2015-04-01

Water scarcity is one of the main factors limiting agricultural development in semi-arid areas. It is thus of major importance to design tools allowing a better management of this resource. Remote sensing has long been used for computing evapotranspiration estimates, which is an input for crop water balance monitoring. Up to now, only medium and low resolution data (e.g. MODIS) are available on regular basis to monitor cultivated areas. However, the increasing availability of high resolution high repetitivity VIS-NIR remote sensing, like the forthcoming Sentinel-2 mission to be lunched in 2015, offers unprecedented opportunity to improve this monitoring. In this study, regional crops water consumption was estimated with the SAMIR software (Satellite of Monitoring Irrigation) using the FAO-56 dual crop coefficient water balance model fed with high resolution NDVI image time series providing estimates of both the actual basal crop coefficient (Kcb) and the vegetation fraction cover. The model includes a soil water model, requiring the knowledge of soil water holding capacity, maximum rooting depth, and water inputs. As irrigations are usually not known on large areas, they are simulated based on rules reproducing the farmer practices. The main objective of this work is to assess the operationality and accuracy of SAMIR at plot and perimeter scales, when several land use types (winter cereals, summer vegetables…), irrigation and agricultural practices are intertwined in a given landscape, including complex canopies such as sparse orchards. Meteorological ground stations were used to compute the reference evapotranspiration and get the rainfall depths. Two time series of ten and fourteen high-resolution SPOT5 have been acquired for the 2008-2009 and 2012-2013 hydrological years over an irrigated area in central Tunisia. They span the various successive crop seasons. The images were radiometrically corrected, first, using the SMAC6s Algorithm, second, using invariant

Extending R packages to support 64-bit compiled code: An illustration with spam64 and GIMMS NDVI3g data

Science.gov (United States)

Gerber, Florian; Mösinger, Kaspar; Furrer, Reinhard

2017-07-01

Software packages for spatial data often implement a hybrid approach of interpreted and compiled programming languages. The compiled parts are usually written in C, C++, or Fortran, and are efficient in terms of computational speed and memory usage. Conversely, the interpreted part serves as a convenient user-interface and calls the compiled code for computationally demanding operations. The price paid for the user friendliness of the interpreted component is-besides performance-the limited access to low level and optimized code. An example of such a restriction is the 64-bit vector support of the widely used statistical language R. On the R side, users do not need to change existing code and may not even notice the extension. On the other hand, interfacing 64-bit compiled code efficiently is challenging. Since many R packages for spatial data could benefit from 64-bit vectors, we investigate strategies to efficiently pass 64-bit vectors to compiled languages. More precisely, we show how to simply extend existing R packages using the foreign function interface to seamlessly support 64-bit vectors. This extension is shown with the sparse matrix algebra R package spam. The new capabilities are illustrated with an example of GIMMS NDVI3g data featuring a parametric modeling approach for a non-stationary covariance matrix.

[Vegetation spatial and temporal dynamic characteristics based on NDVI time series trajectories in grassland opencast coal mining].

Science.gov (United States)

Jia, Duo; Wang, Cang Jiao; Mu, Shou Guo; Zhao, Hua

2017-06-18

The spatiotemporal dynamic patterns of vegetation in mining area are still unclear. This study utilized time series trajectory segmentation algorithm to fit Landsat NDVI time series which generated from fusion images at the most prosperous period of growth based on ESTARFM algorithm. Combining with the shape features of the fitted trajectory, this paper extracted five vegetation dynamic patterns including pre-disturbance type, continuous disturbance type, stabilization after disturbance type, stabilization between disturbance and recovery type, and recovery after disturbance type. The result indicated that recovery after disturbance type was the dominant vegetation change pattern among the five types of vegetation dynamic pattern, which accounted for 55.2% of the total number of pixels. The follows were stabilization after disturbance type and continuous disturbance type, accounting for 25.6% and 11.0%, respectively. The pre-disturbance type and stabilization between disturbance and recovery type accounted for 3.5% and 4.7%, respectively. Vegetation disturbance mainly occurred from 2004 to 2009 in Shengli mining area. The onset time of stable state was 2008 and the spatial locations mainlydistributed in open-pit stope and waste dump. The reco-very state mainly started since the year of 2008 and 2010, while the areas were small and mainly distributed at the periphery of open-pit stope and waste dump. Duration of disturbance was mainly 1 year. The duration of stable period usually sustained 7 years. The duration of recovery state of the type of stabilization between disturbances continued 2 to 5 years, while the type of recovery after disturbance often sustained 8 years.

COMPARISON OF UNCALIBRATED RGBVI WITH SPECTROMETER-BASED NDVI DERIVED FROM UAV SENSING SYSTEMS ON FIELD SCALE

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G. Bareth

2016-06-01

Full Text Available The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (< 5 kg is well established, the miniaturization of sensors in the last years also enables hyperspectral data acquisition from those platforms. From both, RGB and hyperspectral data, vegetation indices (VIs are computed to estimate crop growth parameters. In this contribution, we compare two different sensing approaches from a low-weight UAV platform (< 5 kg for monitoring a nitrogen field experiment of winter wheat and a corresponding farmers’ field in Western Germany. (i A standard digital compact camera was flown to acquire RGB images which are used to compute the RGBVI and (ii NDVI is computed from a newly modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1 to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2 investigate the UAV-based performance of the modified Yara N-Sensor, and (3 compare the results of the two different UAV-based sensing approaches for winter wheat.

A comparative study on generating simulated Landsat NDVI images using data fusion and regression method-the case of the Korean Peninsula.

Science.gov (United States)

Lee, Mi Hee; Lee, Soo Bong; Eo, Yang Dam; Kim, Sun Woong; Woo, Jung-Hun; Han, Soo Hee

2017-07-01

Landsat optical images have enough spatial and spectral resolution to analyze vegetation growth characteristics. But, the clouds and water vapor degrade the image quality quite often, which limits the availability of usable images for the time series vegetation vitality measurement. To overcome this shortcoming, simulated images are used as an alternative. In this study, weighted average method, spatial and temporal adaptive reflectance fusion model (STARFM) method, and multilinear regression analysis method have been tested to produce simulated Landsat normalized difference vegetation index (NDVI) images of the Korean Peninsula. The test results showed that the weighted average method produced the images most similar to the actual images, provided that the images were available within 1 month before and after the target date. The STARFM method gives good results when the input image date is close to the target date. Careful regional and seasonal consideration is required in selecting input images. During summer season, due to clouds, it is very difficult to get the images close enough to the target date. Multilinear regression analysis gives meaningful results even when the input image date is not so close to the target date. Average R 2 values for weighted average method, STARFM, and multilinear regression analysis were 0.741, 0.70, and 0.61, respectively.

The investigation of spatiotemporal variations of land surface temperature based on land use changes using NDVI in southwest of Iran

Science.gov (United States)

Fathizad, Hassan; Tazeh, Mahdi; Kalantari, Saeideh; Shojaei, Saeed

2017-10-01

Land use changes can bring about changes in land surface temperature (LST) which is influenced by climatic conditions and physical characteristics of the land surface. In this study, spatiotemporal variations of land surface temperature have been investigated in the desert area of Dasht-e-Abbas, Ilam, based on a variety of land use changes. The investigated periods for the study include 1990, 2000 and 2010 using Landsat image data. First, in mapping land use we used the Fuzzy ARTMAP Neural Network Classification method followed by determination of the NDVI Index to estimate land surface temperature. The results show an increase in LST in areas where degradation, land use and land cover changes have occurred. In 1990, 2000 and 2010, the average land surface temperature of the Fair Rangelands was 26.72 °C, 30.06 °C and 30.95 °C, respectively. This rangeland has been reduced by about 5%. For poor rangelands, the average LSTs were 26.95, 32.83 and 34.49 Cº, respectively which had a 18% reduction. In 1990, 2000 and 2010, the average land surface temperatures of agricultural lands were 24.31 °C, 27.87 °C and 28.61 °C, respectively which has been an increasing trend. The reason can be attributed to changes in cropping patterns of the study area.

Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI

Science.gov (United States)

Ruiz-Pérez, Guiomar; Koch, Julian; Manfreda, Salvatore; Caylor, Kelly; Francés, Félix

2017-12-01

Ecohydrological modeling studies in developing countries, such as sub-Saharan Africa, often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill this gap, but require novel methodologies to exploit their spatio-temporal information that could potentially be incorporated into model calibration and validation frameworks. The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment - the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and data-scarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland.

Science.gov (United States)

Cong, Nan; Shen, Miaogen; Yang, Wei; Yang, Zhiyong; Zhang, Gengxin; Piao, Shilong

2017-08-01

Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (R NDVI-T ) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing R NDVI-T in spring (May-June) and autumn (September) and decreasing R NDVI-T in summer (July-August). Growing season R NDVI-T for alpine steppe increased slightly, mainly due to increasing R NDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (R NDVI-P ) for alpine meadow increased slightly, mainly in spring and summer, and R NDVI-P for alpine steppe increased, mainly in spring. Moreover, R NDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. R NDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity

Vegetation Response to Climate Change in the Southern Part of Qinghai-Tibet Plateau at Basinal Scale

Science.gov (United States)

Liu, X.; Liu, C.; Kang, Q.; Yin, B.

2018-04-01

Global climate change has significantly affected vegetation variation in the third-polar region of the world - the Qinghai-Tibet Plateau. As one of the most important indicators of vegetation variation (growth, coverage and tempo-spatial change), the Normalized Difference Vegetation Index (NDVI) is widely employed to study the response of vegetation to climate change. However, a long-term series analysis cannot be achieved because a single data source is constrained by time sequence. Therefore, a new framework was presented in this paper to extend the product series of monthly NDVI, taking as an example the Yarlung Zangbo River Basin, one of the most important river basins in the Qinghai-Tibet Plateau. NDVI products were acquired from two public sources: Global Inventory Modeling and Mapping Studies (GIMMS) Advanced Very High Resolution Radiometer (AVHRR) and Moderate-Resolution Imaging spectroradiometer (MODIS). After having been extended using the new framework, the new time series of NDVI covers a 384 months period (1982-2013), 84 months longer than previous time series of NDVI product, greatly facilitating NDVI related scientific research. In the new framework, the Gauss Filtering Method was employed to filter out noise in the NDVI product. Next, the standard method was introduced to enhance the comparability of the two data sources, and a pixel-based regression method was used to construct NDVI-extending models with one pixel after another. The extended series of NDVI fit well with original AVHRR-NDVI. With the extended time-series, temporal trends and spatial heterogeneity of NDVI in the study area were studied. Principal influencing factors on NDVI were further determined. The monthly NDVI is highly correlated with air temperature and precipitation in terms of climatic change wherein the spatially averaged NDVI slightly increases in the summer and has increased in temperature and decreased in precipitation in the 32 years period. The spatial heterogeneity of

Regional-scale assessment of soil salinity in the Red River Valley using multi-year MODIS EVI and NDVI.

Science.gov (United States)

Lobell, D B; Lesch, S M; Corwin, D L; Ulmer, M G; Anderson, K A; Potts, D J; Doolittle, J A; Matos, M R; Baltes, M J

2010-01-01

The ability to inventory and map soil salinity at regional scales remains a significant challenge to scientists concerned with the salinization of agricultural soils throughout the world. Previous attempts to use satellite or aerial imagery to assess soil salinity have found limited success in part because of the inability of methods to isolate the effects of soil salinity on vegetative growth from other factors. This study evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery in conjunction with directed soil sampling to assess and map soil salinity at a regional scale (i.e., 10-10(5) km(2)) in a parsimonious manner. Correlations with three soil salinity ground truth datasets differing in scale were made in Kittson County within the Red River Valley (RRV) of North Dakota and Minnesota, an area where soil salinity assessment is a top priority for the Natural Resource Conservation Service (NRCS). Multi-year MODIS imagery was used to mitigate the influence of temporally dynamic factors such as weather, pests, disease, and management influences. The average of the MODIS enhanced vegetation index (EVI) for a 7-yr period exhibited a strong relationship with soil salinity in all three datasets, and outperformed the normalized difference vegetation index (NDVI). One-third to one-half of the spatial variability in soil salinity could be captured by measuring average MODIS EVI and whether the land qualified for the Conservation Reserve Program (a USDA program that sets aside marginally productive land based on conservation principles). The approach has the practical simplicity to allow broad application in areas where limited resources are available for salinity assessment.

Parâmetros biofísicos obtidos por sensoriamento remoto em região semiárida do estado do Rio Grande do Norte, Brasil

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Joel M. Bezerra

2014-01-01

Full Text Available Apesar de ser o único bioma brasileiro cujos limites estão restritos ao território nacional, pouca atenção tem sido dada à conservação da diversificada paisagem da Caatinga. Em virtude da carência de dados de campo para monitorar os parâmetros biofísicos da Caatinga em região semiárida do Nordeste brasileiro, este trabalho teve como objetivo avaliar a dinâmica espaço-temporal por meio de técnicas e produtos de Sensoriamento Remoto. A área de estudo compreendeu a Unidade de Conservação do Parque Nacional da Furna Feia e suas adjacências, situada entre os municípios de Mossoró e Baraúna (RN, Brasil. Utilizaram-se seis imagens orbitais do TM LANDSAT 5, órbita 216 e ponto 63, no período de 2007 a 2010. Com auxílio da ferramenta Sistema de Informação Geográfica se implementaram os algoritmos com geração das cartas temáticas expressando a variabilidade dos parâmetros de albedo da superfície, NDVI e temperatura de superfície. Os resultados obtidos não só foram consistentes com dados da literatura para os diferentes usos do solo e variações climáticas. Além de demonstrar o potencial das geotecnologias, a compreensão da dinâmica dos padrões espaciais e temporais dos processos biofísicos de interação solo-planta-atmosfera da Caatinga no Semiárido.

A politica nuclear da Argentina e do Brasil : Desenvolvimento, nao-proliferacao e democratizacao

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澤田, 眞治

1994-01-01

Este artigo e uma tentativa de analisar o desenvolvimento da politica da energia nuclear da Argentina e do Brasil, com relacao ao regime internacional de naoproliferacao das armas nucleares. Dado o fato de que ambos os paises da America do Sul recusaram a assinatura do TNP(Tratad0 sobre Nao-Proliferacao das Armas Nucleares), em razao do carater discriminatorio de inspecao, a Argentina e o Brasil estavam sendo considerado os estados duvidossos que potencialmente teriam a bomba atomica. A despe...

VEGETATION RESPONSE TO CLIMATE CHANGE IN THE SOUTHERN PART OF QINGHAI-TIBET PLATEAU AT BASINAL SCALE

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X. Liu

2018-04-01

Full Text Available Global climate change has significantly affected vegetation variation in the third-polar region of the world – the Qinghai-Tibet Plateau. As one of the most important indicators of vegetation variation (growth, coverage and tempo-spatial change, the Normalized Difference Vegetation Index (NDVI is widely employed to study the response of vegetation to climate change. However, a long-term series analysis cannot be achieved because a single data source is constrained by time sequence. Therefore, a new framework was presented in this paper to extend the product series of monthly NDVI, taking as an example the Yarlung Zangbo River Basin, one of the most important river basins in the Qinghai-Tibet Plateau. NDVI products were acquired from two public sources: Global Inventory Modeling and Mapping Studies (GIMMS Advanced Very High Resolution Radiometer (AVHRR and Moderate-Resolution Imaging spectroradiometer (MODIS. After having been extended using the new framework, the new time series of NDVI covers a 384 months period (1982–2013, 84 months longer than previous time series of NDVI product, greatly facilitating NDVI related scientific research. In the new framework, the Gauss Filtering Method was employed to filter out noise in the NDVI product. Next, the standard method was introduced to enhance the comparability of the two data sources, and a pixel-based regression method was used to construct NDVI-extending models with one pixel after another. The extended series of NDVI fit well with original AVHRR-NDVI. With the extended time-series, temporal trends and spatial heterogeneity of NDVI in the study area were studied. Principal influencing factors on NDVI were further determined. The monthly NDVI is highly correlated with air temperature and precipitation in terms of climatic change wherein the spatially averaged NDVI slightly increases in the summer and has increased in temperature and decreased in precipitation in the 32 years period. The

Analysis of vegetation condition and its relationship with meteorological variables in the Yarlung Zangbo River Basin of China

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X. Han

2018-06-01

Full Text Available The Yarlung Zangbo River Basin is located in the southwest border of China, which is of great significance to the socioeconomic development and ecological environment of Southwest China. Normalized Difference Vegetation Index (NDVI is an important index for investigating the change of vegetation cover, which is widely used as the representation value of vegetation cover. In this study, the NDVI is adopted to explore the vegetation condition in the Yarlung Zangbo River Basin during the recent 17 years, and the relationship between NDVI and meteorological variables has also been discussed. The results show that the annual maximum value of NDVI usually appears from July to September, in which August occupies a large proportion. The minimum value of NDVI appears from January to March, in which February takes up most of the percentage. The higher values of NDVI are generally located in the lower elevation area. When the altitude is higher than 3250 m, NDVI began to decline gradually, and the NDVI became gradual stabilization as the elevation is up to 6000 m. The correlation coefficient between NDVI and precipitation in the Yarlung Zangbo River Basin is greater than that with temperature. The Hurst index of the whole basin is 0.51, indicating that the NDVI of the Yarlung Zangbo River Basin shows a weak sustainability.

Variações espaço-temporais no estoque de sementes do solo na floresta amazônica Space-time variations in soil seed stock in an amazon rainforest

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Niwton Leal Filho

2013-09-01

Full Text Available A dispersão eficiente, a longevidade e a capacidade das sementes de permanecer em estado latente a espera de condições adequadas de germinação no banco de sementes do solo da floresta garantem a presença de espécies arbóreas pioneiras nas áreas perturbadas. As variações estacionais e espaciais na densidade e na composição florística do banco de sementes em Florestas Tropicais Úmidas são assuntos ainda pouco compreendidos. Este trabalho verificou a existência de modificações espaço-temporais do banco de sementes presente em áreas de Floresta Tropical úmida localizadas próximas a Manaus, AM. Em cada uma das seis áreas estudadas, foram coletadas 40 amostras circulares de solo superficial (10 cm de diâmetro e 2 cm de profundidade ao acaso. Essas amostras foram coletadas a cada dois meses, entre agosto/2004 e junho/2005,. As amostras de solo foram distribuídas em bandejas em casa de vegetação e a emergência das sementes presentes no solo foi acompanhada por 4 meses. Houve uma redução significativa (H: 14,09, p The dispersion efficiency, longevity and the ability of seeds to remain latent waiting for suitable conditions for germination in the forest soil seed bank ensures the presence of pioneer tree species in disturbed areas. The seasonal and spatial variations in the density and floristic composition of the seed bank in tropical rainforests is a subject still little understood. This work verified the existence of spatio-temporal changes of the seed bank present in areas of humid tropical rain forest located near Manaus, Amazonas. In each of the six study areas, 40 circular samples of topsoil (10 cm in diameter and 2 cm deep were randomly collected every two months, from August 2004 to June/2005. Inside a greenhouse, the collected soil samples were distributed in trays and the emergence of seeds present in the soil was accompanied during four months. There was a significant reduction (H: 14.09112, p <0.05 in the mean

MODIS and GIMMS Inferred Northern Hemisphere Spring Greenup in Responses to Preseason Climate

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Xu, X.; Riley, W. J.; Koven, C.; Jia, G.

2017-12-01

We compare the discrepancies in Normalized Difference Vegetation Index (NDVI) inferred spring greenup (SG) between Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) instruments carried by the Global Inventory Monitoring and Modeling Studies (GIMMS) in North Hemisphere. The interannual variation of SG inferred by MODIS and GIMMS NDVI is well correlated in the mid to high latitudes. However, the presence of NDVI discrepancies leads to discrepancies in SG with remarkable latitudinal characteristics. MODIS NDVI inferred later SG in the high latitude while earlier SG in the mid to low latitudes, in comparison to GIMMS NDVI inferred SG. MODIS NDVI inferred SG is better correlated to preseason climate. Interannual variation of SG is only sensitive to preseason temperature. The GIMMS SG to temperature sensitivity over two periods implied that the inter-biome SG to temperature sensitivity is relatively stable, but SG to temperature sensitivity decreased over time. Over the same period, MODIS SG to temperature sensitivity is much higher than GIMMS. This decreased sensitivity demonstrated the findings from previous studies with continuous GIMMS NDVI analysis that vegetation growth (indicated by growing season NDVI) to temperature sensitivity is reduced over time and SG advance trend ceased after 2000s. Our results also explained the contradictive findings that SG advance accelerated after 2000s according to the merged GIMMS and MODIS NDVI time series. Despite the found discrepancies, without ground data support, the quality of NDVI and its inferred SG cannot be effectively evaluated. The discrepancies and uncertainties in different NDVI products and its inferred SG may bias the scientific significance of climate-vegetation relationship. The different NDVI products when used together should be first evaluated and harmonized.

Dynamic variability of the heading-flowering stages of single rice in China based on field observations and NDVI estimations.

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Zhang, Zhao; Song, Xiao; Chen, Yi; Wang, Pin; Wei, Xing; Tao, Fulu

2015-05-01

Although many studies have indicated the consistent impact of warming on the natural ecosystem (e.g., an early flowering and prolonged growing period), our knowledge of the impacts on agricultural systems is still poorly understood. In this study, spatiotemporal variability of the heading-flowering stages of single rice was detected and compared at three different scales using field-based methods (FBMs) and satellite-based methods (SBMs). The heading-flowering stages from 2000 to 2009 with a spatial resolution of 1 km were extracted from the SPOT/VGT NDVI time series data using the Savizky-Golay filtering method in the areas in China dominated by single rice of Northeast China (NE), the middle-lower Yangtze River Valley (YZ), the Sichuan Basin (SC), and the Yunnan-Guizhou Plateau (YG). We found that approximately 52.6 and 76.3 % of the estimated heading-flowering stages by a SBM were within ±5 and ±10 days estimation error (a root mean square error (RMSE) of 8.76 days) when compared with those determined by a FBM. Both the FBM data and the SBM data had indicated a similar spatial pattern, with the earliest annual average heading-flowering stages in SC, followed by YG, NE, and YZ, which were inconsistent with the patterns reported in natural ecosystems. Moreover, diverse temporal trends were also detected in the four regions due to different climate conditions and agronomic factors such as cultivar shifts. Nevertheless, there were no significant differences (p > 0.05) between the FBM and the SBM in both the regional average value of the phenological stages and the trends, implying the consistency and rationality of the SBM at three scales.

Análise de dados de produção em um pomar jovem de laranjeiras Hamlin: II. classificação de dados espaço-temporais Yield data analysis in a commercial orchard of young Hamlin trees: classification of spatial-temporal yield data

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Francisco José de Oliveira Parise

2005-04-01

Full Text Available Em um pomar jovem de laranjeiras Hamlin, não-irrigado, foi realizado um estudo que procurou investigar a potencialidade da utilização de dados espaço-temporais de produção por árvore para o gerenciamento localizado. A produção de 1.471 árvores georreferenciadas foi levantada em dois ciclos sucessivos, 2000-2001 e 2001-2002, e classificada por meio de uma análise de agrupamentos via lógica fuzzy. Ainda, foi realizada uma análise de correlação intraclasse com dados de resposta espectral de 52 árvores, extraída de imagens aéreas multiespectrais de alta resolução espacial. Os resultados mostraram que foi possível a formação de classes distintas de comportamento produtivo, em função dos padrões de variabilidade espacial e temporal da produção. No entanto, as classes apresentaram baixa coerência espacial, o que dificulta o gerenciamento localizado da produção em nível de árvores individuais. A despeito disso, a resposta espectral esteve significativamente relacionada às classes formadas.Yield data of 1471 young Hamlin trees in a commercial orchard were collected in two seasons, 2000/2001 and 2001/2002, to identify the patterns of spatial and temporal yield variability. Fuzzy cluster analysis was used for interpreting the temporal and spatial variation. 52 trees were also selected for calculating the intra-class correlation of the spectral response extracted from high resolution multispectral digital aerial images. The results showed that some general patterns of season-to-season variation could be identified and related to spectral response of the trees. But, these patterns correspond to regions poorly spatially coherent.

Os tempos da enunciação e dos enunciados publicitários e a questão do cronotopo publicitário

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Eneus Trindade

2008-09-01

Full Text Available Este texto refere-se a uma teoria da enunciação publicitária. O objetivo principal é apresentar as nossas reflexões sobre os efeitos temporais nos discursos publicitários. Assim, são considerados os efeitos temporais da enunciação e dos enunciados publicitários. Nossa reflexão discute também a questão da fusão do tempo ao espaço no discurso da publicidade, apresentando o conceito de cronotopo publicitário. Palavras-chave: Enunciação; publicidade; processos midiáticos e culturais; tempo. ABSTRACT This text refers to theory of enunciation process in advertising. The main aim is to present our reflections about time effects in advertising discourses. We considered the time effects of enunciation and advertising messengers announced. Our reflection aims to discuss too relations between space and time in advertising discourse presenting the concept of advertising cronotopo. Keywords: Enunciation; advertising; midiatic and cultural process; time.

Mapping Water Level Dynamics over Central Congo River Using PALSAR Images, Envisat Altimetry, and Landsat NDVI Data

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Kim, D.; Lee, H.; Jung, H. C.; Beighley, E.; Laraque, A.; Tshimanga, R.; Alsdorf, D. E.

2016-12-01

Rivers and wetlands are very important for ecological habitats, and it plays a key role in providing a source of greenhouse gases (CO2 and CH4). The floodplains ecosystems depend on the process between the vegetation and flood characteristics. The water level is a prerequisite to an understanding of terrestrial water storage and discharge. Despite the lack of in situ data over the Congo Basin, which is the world's third largest in size ( 3.7 million km2), and second only to the Amazon River in discharge ( 40,500 m3 s-1 annual average between 1902 and 2015 in the main Brazzaville-Kinshasa gauging station), the surface water level dynamics in the wetlands have been successfully estimated using satellite altimetry, backscattering coefficients (σ0) from Synthetic Aperture Radar (SAR) images and, interferometric SAR technique. However, the water level estimation of the Congo River remains poorly quantified due to the sparse orbital spacing of radar altimeters. Hence, we essentially have limited information only over the sparsely distributed the so-called "virtual stations". The backscattering coefficients from SAR images have been successfully used to distinguish different vegetation types, to monitor flood conditions, and to access soil moistures over the wetlands. However, σ0 has not been used to measure the water level changes over the open river because of very week return signal due to specular scattering. In this study, we have discovered that changes in σ0 over the Congo River occur mainly due to the water level changes in the river with the existence of the water plants (macrophytes, emergent plants, and submersed plant), depending on the rising and falling stage inside the depression of the "Cuvette Centrale". We expand the finding into generating the multi-temporal water level maps over the Congo River using PALSAR σ0, Envisat altimetry, and Landsat Normalized Difference Vegetation Index (NDVI) data. We also present preliminary estimates of the river

Application of a method of analysis of remote sensing data obtained by targeting the estimated productivity in cane for quantifying panela NDVI (normalized difference vegetation index

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Fabio Rueda Calier

2016-01-01

Full Text Available The productivity estimation sugar cane is very important for Colombian economy. The Net Primary Production (NPP model is applied on present investigation from Kumar & Monteith to regional scale. Analyzing spatiotemporal with geomantic techniques and edaphoclimatic environment characterization. Field surveys were conducted too, to acquire physiological information of plants evaluated and soil conditions of the plantation under study. The data acquired was input in ArcGIS10.1 software, to make processing these. A series thematic map was resulted from data processing from spatiotemporal distribution of plantation soil characteristics and biophysical characteristics. The variables fPAR, PAR, EUR was calculate from Kumar & Monteith efficiency model. Remote sensing and mathematic models related and fraction absorbed photosynthetically active radiation derivates from Normalized Difference Vegetation Index (NDVI and incident photosynthetically active radiation in land sensors recorded was calculated. Chemical and physical properties in laboratory tests were realized to soil, for relation knowledge between edaphoclimatic conditions and biophysical variables related with the sugar cane biomass gainer for Panela production. The information integrated from Geographic Information System (GIS and edaphic data and climatic data in country recorded, shows the behavior of the plantation as it develops.

Satellite-derived NDVI, LST, and climatic factors driving the distribution and abundance of Anopheles mosquitoes in a former malarious area in northwest Argentina.

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Dantur Juri, María Julia; Estallo, Elizabet; Almirón, Walter; Santana, Mirta; Sartor, Paolo; Lamfri, Mario; Zaidenberg, Mario

2015-06-01

Distribution and abundance of disease vectors are directly related to climatic conditions and environmental changes. Remote sensing data have been used for monitoring environmental conditions influencing spatial patterns of vector-borne diseases. The aim of this study was to analyze the effect of the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic factors (temperature, humidity, wind velocity, and accumulated rainfall) on the distribution and abundance of Anopheles species in northwestern Argentina using Poisson regression analyses. Samples were collected from December, 2001 to December, 2005 at three localities, Aguas Blancas, El Oculto and San Ramón de la Nueva Orán. We collected 11,206 adult Anopheles species, with the major abundance observed at El Oculto (59.11%), followed by Aguas Blancas (22.10%) and San Ramón de la Nueva Orán (18.79%). Anopheles pseudopunctipennis was the most abundant species at El Oculto, Anopheles argyritarsis predominated in Aguas Blancas, and Anopheles strodei in San Ramón de la Nueva Orán. Samples were collected throughout the sampling period, with the highest peaks during the spring seasons. LST and mean temperature appear to be the most important variables determining the distribution patterns and major abundance of An. pseudopunctipennis and An. argyritarsis within malarious areas. © 2015 The Society for Vector Ecology.

Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China).

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Cui, Lifang; Wang, Lunche; Singh, Ramesh P; Lai, Zhongping; Jiang, Liangliang; Yao, Rui

2018-05-23

The variation in vegetation greenness provides good understanding of the sustainable management and monitoring of land surface ecosystems. The present paper discusses the spatial-temporal changes in vegetation and controlling factors in the Yangtze River Basin (YRB) using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) for the period 2001-2013. Theil-Sen Median trend analysis, Pearson correlation coefficients, and residual analysis have been used, which shows decreasing trend of the annual mean NDVI over the whole YRB. Spatially, the regions with significant decreasing trends were mainly located in parts of central YRB, and pronounced increasing trends were observed in parts of the eastern and western YRB. The mean NDVI during spring and summer seasons increased, while it decreased during autumn and winter seasons. The seasonal mean NDVI shows spatial heterogeneity due to the vegetation types. The correlation analysis shows a positive relation between NDVI and temperature over most of the YRB, whereas NDVI and precipitation show a negative correlation. The residual analysis shows an increase in NDVI in parts of eastern and western YRB and the decrease in NDVI in the small part of Yangtze River Delta (YRD) and the mid-western YRB due to human activities. In general, climate factors were the principal drivers of NDVI variation in YRB in recent years.

Use of optical sensor for in-season nitrogen management and grain yield prediction in maize

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Bandhu Raj Baral

2015-12-01

Full Text Available Precision agriculture technologies have developed optical sensors which can determine plant’s normalized difference vegetation index (NDVI.To evaluate the relationship between maize grain yield and early season NDVI readings, an experiment was conducted at farm land of National Maize Research Program, Rampur, Chitwan during winter season of 2012. Eight different levels of N 0, 30, 60, 90, 120, 150, 180 and 210 kg N/ha were applied for hybrid maize RML 32 × RML 17 to study grain yield response and NDVI measurement. Periodic NDVI was measured at 10 days interval from 55 days after sowing (DAS to 115 DAS by using Green seeker hand held crop sensor. Periodic NDVI measurement taken at a range of growing degree days (GDD was critical for predicting grain yield potential. Poor exponential relationship existed between NDVI from early reading measured before 208 GDD (55 DAS and grain yield. At the 261GDD (65DAS a strong relationship (R2 = 0.70 was achieved between NDVI and grain yield. Later sensor measurements after 571 GDD (95DAS failed to distinguish variation in green biomass as a result of canopy closure. N level had significantly influenced on NDVI reading, measured grain yield, calculated in season estimated yield (INSEY, predicted yield with added N (YPN, response index (RI and grain N demand. Measuring NDVI reading by GDD (261–571 GDD allow a practical window of opportunity for side dress N applications. This study showed that yield potential in maize could be accurately predicted in season with NDVI measured with the Green Seeker crop sensor.

Improving predictive capabilities of environmental change with GLOBE data

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Robin, Jessica Hill

This dissertation addresses two applications of Normalized Difference Vegetation Index (NDVI) essential for predicting environmental changes. The first study focuses on whether NDVI can improve model simulations of evapotranspiration for temperate Northern (>35°) regions. The second study focuses on whether NDVI can detect phenological changes in start of season (SOS) for high Northern (>60°) environments. The overall objectives of this research were to (1) develop a methodology for utilizing GLOBE data in NDVI research; and (2) provide a critical analysis of NDVI as a long-term monitoring tool for environmental change. GLOBE is an international partnership network of K-12 students, teachers, and scientists working together to study and understand the global environment. The first study utilized data collected by one GLOBE school in Greenville, Pennsylvania and the second utilized phenology observations made by GLOBE students in Alaska. Results from the first study showed NDVI could predict transpiration periods for environments like Greenville, Pennsylvania. In phenological terms, these environments have three distinct periods (QI, QII, and QIII). QI reflects onset of the growing season (mid March--mid May) when vegetation is greening up (NDVI 0.60). Results from the second study showed that a climate threshold of 153 +/- 22 growing degree days was a better predictor of SOS for Fairbanks than a NDVI threshold applied to temporal AVHRR and MODIS datasets. Accumulated growing degree days captured the interannual variability of SOS better than the NDVI threshold and most closely resembled actual SOS observations made by GLOBE students. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska. Both studies did show that GLOBE data provides an important source of input and validation information for NDVI research.

Using MODIS-NDVI for the Modeling of Post-Wildfire Vegetation Response as a Function of Environmental Conditions and Pre-Fire Restoration Treatments

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Grant M. Casady

2012-03-01

Full Text Available Post-fire vegetation response is influenced by the interaction of natural and anthropogenic factors such as topography, climate, vegetation type and restoration practices. Previous research has analyzed the relationship of some of these factors to vegetation response, but few have taken into account the effects of pre-fire restoration practices. We selected three wildfires that occurred in Bandelier National Monument (New Mexico, USA between 1999 and 2007 and three adjacent unburned control areas. We used interannual trends in the Normalized Difference Vegetation Index (NDVI time series data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS to assess vegetation response, which we define as the average potential photosynthetic activity through the summer monsoon. Topography, fire severity and restoration treatment were obtained and used to explain post-fire vegetation response. We applied parametric (Multiple Linear Regressions-MLR and non-parametric tests (Classification and Regression Trees-CART to analyze effects of fire severity, terrain and pre-fire restoration treatments (variable used in CART on post-fire vegetation response. MLR results showed strong relationships between vegetation response and environmental factors (p < 0.1, however the explanatory factors changed among treatments. CART results showed that beside fire severity and topography, pre-fire treatments strongly impact post-fire vegetation response. Results for these three fires show that pre-fire restoration conditions along with local environmental factors constitute key processes that modify post-fire vegetation response.

Assessing Vegetation Response to Soil Moisture Fluctuation under Extreme Drought Using Sentinel-2

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Harry West

2018-06-01

Full Text Available The aim of this study was to determine the extent to which Sentinel-2 Normalised Difference Vegetation Index (NDVI reflects soil moisture conditions, and whether this product offers an improvement over Landsat-8. Based on drought exposure, cloud-free imagery availability, and measured soil moisture, five sites in the Southwestern United States were selected. These sites, normally dry to arid, were in various states of drought. A secondary focus was therefore the performance of the NDVI under extreme conditions. Following supervised classification, the NDVI values for one-kilometre radius areas were calculated. Sentinel-2 NDVI variants using Spectral Bands 8 (10 m spatial resolution, 5, 6, 7, and 8A (20 m spatial resolution were calculated. Landsat-8 NDVI was calculated at 30 m spatial resolution. Pearson correlation analysis was undertaken for NDVI against moisture at various depths. To assess the difference in correlation strength, a principal component analysis was performed on the combination of all bands and the combination of the new red-edge bands. Performance of the red-edge NDVI against the standard near infrared (NIR was then evaluated using a Steiger comparison. No significant correlations between Landsat-8 NDVI and soil moisture were found. Significant correlations at depths of less than 30 cm were present between Sentinel-2 NDVI and soil moisture at three sites. The remaining two sites were characterised by low vegetation cover, suggesting a cover threshold of approximately 30–40% is required for a correlation to be present. At all sites of significant positive moisture to NDVI correlation, the linear combination of the red-edge bands produced stronger correlations than the poorer spectral but higher spatial resolution band. NDVI calculated using the higher spectral resolution bands may therefore be of greater use in this context than the higher spatial resolution option. Results suggest potential for the application of Sentinel-2

Dinâmica populacional da mariposa oriental em pomares de pessegueiro e ameixeira

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Hickel Eduardo Rodrigues

2003-01-01

Full Text Available O objetivo deste trabalho foi estudar a dinâmica populacional da mariposa oriental [Grapholita molesta (Busk] em pomares de pessegueiro e ameixeira. Os adultos foram monitorados em dois pomares de pessegueiro e um de ameixeira por cinco anos. Séries temporais equivalentes de temperaturas máximas e mínimas foram correlacionadas aos dados de flutuação populacional para se aferir a correspondência entre a ocorrência da praga e as flutuações de temperatura. A análise de Fourier das séries temporais das armadilhas de coleta de mariposas revelou dinâmicas cíclicas, com período principal médio de 53,91 semanas. Um período menor médio, de 7,45 semanas, também ficou evidente e se aproxima do tempo médio de geração do inseto. A análise do espectro de potência das séries temporais, com e sem periodicidade, revelou que a dinâmica populacional de G. molesta possui um componente regular, caracterizado pelos períodos observados, e outro componente irregular, reminiscente de ruído 1/f, caracterizado pelas variações de amplitude, aparentemente irregulares, na ocorrência do inseto. A combinação desses dois componentes ocasiona um processo com domínio de baixas freqüências, próprio das dinâmicas periódicas ruidosas. Os ciclos de aparecimento da praga ocorrem em fase com os ciclos de flutuação de temperaturas máximas e mínimas.

Modelagem de arranjos institucionais para implementação da diretriz de sistema de gestão de segurança e saúde ocupacional da organização internacional do trabalho ILO/OSH 2001 no brasil

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Carvalho, Gilberto Liberato de

2008-01-01

A assinatura em 2005 de Termo de compromisso do Brasil em adotar a Diretriz de Sistema de Segurança e Saúde Ocupacional da Organização Internacional do Trabalho denominada ILO/OSH 2001 coloca o problema de modelar arranjos que definam papéis e interações de governo, organizações de normas e de segurança e saúde ocupacional, profissionais da área e outras instituições para implementar essa Diretriz. Nesta dissertação investigam-se modelos alternativos de arranjos institucionais ...

DISCOURSES ABOUT URBAN ART IN RIO DE JANEIRO: THE LEGITIMATION OF GRAFFITI IN THE STREETS AND GALLERIES

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ADRIANA MEDEIROS FERREIRA DA SILVA

2012-01-01

Este trabalho procura refletir sobre o crescimento e a consolidação do grafite no Rio de Janeiro. Uma das expressões da cultura hip-hop, o grafite surgiu nos Estados Unidos, na década de 1970. No início eram apenas assinaturas, que depois evoluíram para desenhos elaborados. São Paulo foi a primeira cidade brasileira onde este tipo de escrita urbana se desenvolveu nos anos 1980 e 1990. Mas no Rio, a atividade de pintar muros chegou mais tarde e somente se firmou nos anos 2000...

Espectroscopia de refletância e emissividade de rochas fosfáticas ígneas e sedimentares do centro-oeste do Brasil : estudos de caso nos depósitos de Catalão I (GO), Tapira (MG), Rocinha e Lagamar (MG) = Reflectance and emissivity spectroscopy of igneous and sedimentary rocks from Midwest Brazil: case study of the Catalão I (GO), Tapira (MG), Rocinha and Lagamar deposits

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Emanuel Amorer Hernández

2013-01-01

Resumo: A pesquisa compreende estudos sobre a assinatura ultraespectral e multiespectral de fosfatos de origem ígnea e sedimentar contidos, respectivamente, nos depósitos de Catalão I (GO), Tapira (MG) e Rocinha-Lagamar (MG), centro-oeste do Brasil. Medidas de reflectância e emissividade (focadas na faixa de 8-12µm) foram analisadas em conjunto com dados de Difração de Raios X e Fluorescência de Raios X visando a determinação da mineralogia e quimismo das rochas envolvidas nas áreas de estudo...

Análise acústica de características temporais de consoantes no Português Brasileiro Acoustic analysis of temporal characteristics of consonants from Brazilian Portuguese

Directory of Open Access Journals (Sweden)

Cristina Ferraz Borges Murphy

2009-01-01

Full Text Available OBJETIVO: Analisar acusticamente as consoantes plosivas /p, b, t, d, k, g/ e fricativas /f, v, s, z,∫,/ do Português Brasileiro em relação às variáveis duração, frequência e variação de oitavas por segundo. MÉTODOS: A produção de palavras contendo os sons-alvo foi analisada por meio de uma prova de imitação de palavras. Cada participante, com idades entre oito e dez anos repetiram uma série de palavras isoladas retiradas de uma lista foneticamente balanceada para o Português Brasileiro. Os parâmetros analisados foram: duração do som-alvo (fricativo ou plosivo e valores das frequências inicial e final do F2 medidos em Hz. A partir destes valores foi calculada a variação de oitavas por segundo presente no F2 de cada consoante e, posteriormente, foi realizada a média para todos os sons. RESULTADOS: Quanto à duração das consoantes, os valores variaram entre 31 ms e 170,5 ms. Em relação ao F2, os valores variaram entre 2617 Hz na frequência inicial da plosiva sonora /b/, até 4557 Hz, valor médio da frequência inicial observado na fricativa sonora /z/. Em relação à variação de oitavas por segundo presentes no F2, a maior variação foi encontrada para a plosiva surda /p/ (16,23 oitavas por segundo e a menor para a fricativa surda /S/ (1,624 oitavas por segundo. Considerando a média para todos os sons-alvo analisados, o valor encontrado foi de aproximadamente 6,8 oitavas por segundo. CONCLUSÃO: Os valores observados serão úteis para a elaboração de testes e de treinamentos auditivos contendo estímulos auditivos não-verbais semelhantes às características temporais presentes no Português Brasileiro.PURPOSE: To acoustically analyze the stop consonants /p, b, t, d, k, g/ and the fricatives /f, v, s, z,∫, / from Brazilian Portuguese, regarding the variables duration, frequency and octave variation per second. METHODS: The production of words with the target phonemes was analyzed by using an imitation task

Análise de séries temporais em epidemiologia: uma introdução sobre os aspectos metodológicos Time series analysis in epidemiology: an introduction to methodological aspects

Directory of Open Access Journals (Sweden)

Maria do Rosário Dias de Oliveira Latorre

2001-11-01

Full Text Available Este é um artigo introdutório sobre análise de séries temporais, onde se pretende apresentar, de maneira sumária, alguns modelos estatísticos mais utilizados em análise de séries temporais . Uma série temporal, também denominada série histórica, é uma seqüência de dados obtidos em intervalos regulares de tempo durante um período específico. Na análise de uma série temporal, primeiramente deseja-se modelar o fenômeno estudado para, a partir daí, descrever o comportamento da série, fazer estimativas e, por último, avaliar quais os fatores que influenciaram o comportamento da série, buscando definir relações de causa e efeito entre duas ou mais séries. Para tanto, há um conjunto de técnicas estatísticas disponíveis que dependem do modelo definido (ou estimado para a série, bem como do tipo de série analisada e do objetivo do trabalho. Para analise de tendências, podem se ajustar modelos de regressão polinomial baseados na série inteira ou em vizinhança de um determinado ponto. Isso também pode ser realizado com funções matemáticas. Define-se como um fenômeno sazonal aquele que ocorre regularmente em períodos fixos de tempo e, se existir sazonalidade dita determinística na série, podem-se utilizar modelos de regressão que incorporem funções do tipo seno ou cosseno à variável tempo. Os modelos auto-regressivos formam outra classe de modelos. Na análise do comportamento de uma série histórica livre de tendência e de sazonalidade podem ser utilizados modelos auto-regressivos (AR ou que incorporem médias móveis (ARMA. Quando há tendência, utilizam-se os modelos auto-regressivos integrados de médias móveis (ARIMA e, para incorporar o componente de sazonalidade, utilizam-se os modelos SARIMA. Por último há os modelos lineares generalizados. Neste grupo de modelos estatísticos, a variável resposta é um processo de contagem e as variáveis independentes são variáveis candidatas a explicar o

Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data

Science.gov (United States)

Robin, Jessica; Dubayah, Ralph; Sparrow, Elena; Levine, Elissa

2008-03-01

This work evaluates whether continuity between Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) is achievable for monitoring phenological changes in Alaska. This work also evaluates whether NDVI can detect changes in start of the growing season (SOS) in this region. Six quadratic regression models with NDVI as a function of accumulated growing degree days (AGDD) were developed from 2001 through 2004 AVHRR and MODIS NDVI data sets for urban, mixed, and forested land covers. Model parameters determined NDVI values for start of the observational period as well as peak and length of the growing season. NDVI values for start of the growing season were determined from the model equations and field observations of SOS made by GLOBE students and researchers at University of Alaska Fairbanks. AGDD was computed from daily air temperature. AVHRR and MODIS models were significantly different from one another with differences in the start of the observational season as well as start, peak, and length of the growing season. Furthermore, AGDD for SOS was significantly lower during the 1990s than the 1980s. NDVI values at SOS did not detect this change. There are limitations with using NDVI to monitor phenological changes in these regions because of snow, the large extent of conifers, and clouds, which restrict the composite period. In addition, differing processing and spectral characteristics restrict continuity between AVHRR and MODIS NDVI data sets.

Spatiotemporal variations in vegetation cover on the Loess Plateau, China, between 1982 and 2013: possible causes and potential impacts.

Science.gov (United States)

Kong, Dongxian; Miao, Chiyuan; Borthwick, Alistair G L; Lei, Xiaohui; Li, Hu

2018-03-02

Vegetation is a key component of the ecosystem and plays an important role in water retention and resistance to soil erosion. In this study, we used a multiyear normalized difference vegetation index (NDVI) dataset (1982-2013) and corresponding datasets for observed climatic variables to analyze changes in the NDVI at both temporal and spatial scales. The relationships between NDVI, climate change, and human activities were also investigated. The annual average NDVI showed an upward trend over the 32-year study period, especially in the center of the Loess Plateau. NDVI variations lagged behind monthly temperature changes by approximately 1 month. The contribution of human activities to variations in NDVI has become increasingly significant in recent years, with human activities responsible for 30.4% of the change in NDVI during the period 2001-2013. The increased vegetation coverage has reduced soil erosion on the Loess Plateau in recent years. It is suggested that natural restoration of vegetation is the most effective measure for control of erosion; engineering measures that promote this should feature in the future governance of the Loess Plateau.

[Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

Science.gov (United States)

Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

2018-02-01

Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

Causes of spring vegetation greenness trends in the northern mid-high latitudes from 1982 to 2004

Energy Technology Data Exchange (ETDEWEB)

Mao, Jiafu [ORNL; Shi, Xiaoying [ORNL; Thornton, Peter E [ORNL; Shilong, Dr. Piao [Peking University; Xuhui, Dr. Wang [Peking University

2012-01-01

The Community Land Model version 4 (CLM4) is applied to explore the spatial temporal patterns of spring (April May) vegetation growth trends over the northern mid high latitudes (NMH) (>25 N) between 1982 and 2004. During the spring season through the 23 yr period, both the satellite-derived and simulated normalized difference vegetation index (NDVI) anomalies show a statistically significant correlation and an overall greening trend within the study area. Consistently with the observed NDVI temperature relation, the CLM4 NDVI shows a significant positive association with the spring temperature anomaly for the NMH, North America and Eurasia. Large study areas experience temperature discontinuity associated with contrasting NDVI trends. Before and after the turning point (TP) of the temperature trends, climatic variability plays a dominant role, while the other environmental factors exert minor effects on the NDVI tendencies. Simulated vegetation growth is broadly stimulated by the increasing atmospheric CO2. Trends show that nitrogen deposition increases NDVI mostly in southeastern China, and decreases NDVI mainly in western Russia after the temperature TP. Furthermore, land use-induced NDVI trends vary roughly with the respective changes in land management practices (crop areas and forest coverage). Our results highlight how non-climatic factors mitigate or exacerbate the impact of temperature on spring vegetation growth, particularly across regions with intensive human activity.

Early Season Large-Area Winter Crop Mapping Using MODIS NDVI Data, Growing Degree Days Information and a Gaussian Mixture Model

Science.gov (United States)

Skakun, Sergii; Franch, Belen; Vermote, Eric; Roger, Jean-Claude; Becker-Reshef, Inbal; Justice, Christopher; Kussul, Nataliia

2017-01-01

Knowledge on geographical location and distribution of crops at global, national and regional scales is an extremely valuable source of information applications. Traditional approaches to crop mapping using remote sensing data rely heavily on reference or ground truth data in order to train/calibrate classification models. As a rule, such models are only applicable to a single vegetation season and should be recalibrated to be applicable for other seasons. This paper addresses the problem of early season large-area winter crop mapping using Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI) time-series and growing degree days (GDD) information derived from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product. The model is based on the assumption that winter crops have developed biomass during early spring while other crops (spring and summer) have no biomass. As winter crop development is temporally and spatially non-uniform due to the presence of different agro-climatic zones, we use GDD to account for such discrepancies. A Gaussian mixture model (GMM) is applied to discriminate winter crops from other crops (spring and summer). The proposed method has the following advantages: low input data requirements, robustness, applicability to global scale application and can provide winter crop maps 1.5-2 months before harvest. The model is applied to two study regions, the State of Kansas in the US and Ukraine, and for multiple seasons (2001-2014). Validation using the US Department of Agriculture (USDA) Crop Data Layer (CDL) for Kansas and ground measurements for Ukraine shows that accuracies of greater than 90% can be achieved in mapping winter crops 1.5-2 months before harvest. Results also show good correspondence to official statistics with average coefficients of determination R(exp. 2) greater than 0.85.

Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

Science.gov (United States)

Varlamova, Eugenia V.; Solovyev, Vladimir S.

2017-11-01

Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

Understanding Pan-Arctic Tundra Vegetation Change Through Long-term Remotely Sensed Data

Science.gov (United States)

Bhatt, U.; Walker, D. A.; Bieniek, P.; Raynolds, M. K.; Epstein, H. E.; Comiso, J. C.; Pinzon, J. E.; Tucker, C. J.

2012-12-01

The goal of this paper is to present an analysis of the seasonality of tundra vegetation variability and change using long-term remotely sensed data as well as ground based measurements and reanalyses. An increase of Pan-Arctic tundra vegetation greenness has been documented using the remotely sensed Normalized Difference Vegetation Index (NDVI). Coherent variability between NDVI, springtime coastal sea ice (passive microwave) and land surface temperatures (AVHRR) has also been established. Satellite based snow and cloud cover data sets are being incorporated into this analysis. The Arctic tundra is divided into domains based on Treshnikov divisions that are modified based on floristic provinces. There is notable heterogeneity in Pan-Arctic vegetation and climate trends, which necessitates a regional analysis. This study uses remotely sensed weekly 25-km sea ice concentration, weekly surface temperature, and bi-weekly NDVI from 1982 to 2010. The GIMMS NDVI3g data has been corrected for biases during the spring and fall, with special focus on the Arctic. Trends of Maximum NDVI (MaxNDVI), Time Integrated NDVI (TI-NDVI), Summer Warmth Index (SWI, sum of degree months above freezing during May-August), and open water area are calculated for the Pan Arctic. Remotely sensed snow data trends suggest varying patterns throughout the Arctic and may in part explain the heterogeneous MaxNDVI trends. Standard climate data (station, reanalysis, and model data) and ground observations are used in the analysis to provide additional support for hypothesized mechanisms. Overall, we find that trends over the 30-year record are changing as evidenced by the following examples from recent years. The sea ice decline has increased in Eurasia and slowed in North America. The weekly AVHRR landsurface temperatures reveal that there has been summer cooling over Eurasia and that the warming over North America has slowed. The MaxNDVI rates of change have diverged between N. America and Eurasia

Greenlandic sheep farming controlled by vegetation response today and at the end of the 21st Century

DEFF Research Database (Denmark)

Westergaard-Nielsen, Andreas; Bjørnsson, Anders Boding; Jepsen, Martin Rudbeck

2015-01-01

and fields based on all existing sheep farms in a detailed study area. Time-integrated NDVI (TI-NDVI) from MODIS and observed temperatures (2000–2012) have been combined with a downscaled regional climate model (HIRHAM5) in order to establish a spatio-temporal model for future TI-NDVI, thus forecasting...

O marketing direto como canal de marketing no setor de publicações periódicas (revistas e jornais) em São Paulo

OpenAIRE

Kato, Heitor Takashi

2010-01-01

Trata da utilização do marketing direto como canal de marketing para as empresas editoras de publicações periódicas em São Paulo. Conceitua o marketing direto e descreve suas variantes. Faz um breve histórico das publicações periódicas e do papel das assinaturas desde sua origem. Utilizando-se do esquema teórico de Aspinwall e do estudo do caso de empresas de publicações periódicas em São Paulo, analisa o potencial da utilização do marketing direto como canal de marketing para outras categori...

Origens do paradigma desenvolvimentalista : as contribuições de Oswaldo Aranha e dos militares (1931-1935)

OpenAIRE

Mros, Günther Richter

2011-01-01

Esta dissertação busca entender as origens do perfil desenvolvimentista do Estado brasileiro. Argumenta que as ações empreendidas pelo governo Vargas na política externa do país, a partir de 1930, tiveram forte influência da auditoria da dívida externa realizada no período em que Oswaldo Aranha foi ministro da Fazenda (1931-1934). Trata da busca de Aranha, já como embaixador, pela assinatura de acordo de livre-comércio com os Estados Unidos, motivado, segundo fontes, pela força do dólar após ...

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

Science.gov (United States)

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Evidences of delayed size recovery in Araucaria angustifolia populations after post-glacial colonization of highlands in Southeastern Brazil

Directory of Open Access Journals (Sweden)

Valdir M. Stefenon

2008-09-01

Full Text Available Up to date, little is known about the relationship between historical demography and the current genetic structure of A. Angus As a first effort towards overcoming this lack, microsatellite data scored in six populations and isozyme allele frequencies published for 11 natural stands of this species were analysed in order to assess molecular signatures of populations' demographic history. Signatures of genetic bottlenecks were captured in all analysed populations of southeastern Brazil. Among southern populations, signatures of small effective population size were observed in only three out of 13 populations. Southern populations likely experienced faster recovery of population size after migration onto highlands. Accordingly, current genetic diversity of the southern populations gives evidence of fast population size recovery. In general, demographic history of A. Angusmatches climatic dynamics of southern and southeastern Brazil during the Pleistocene and Holocene. Palynological records and reconstruction of the past climatic dynamics of southeastern and southern Brazil support the hypothesis of different population size recovery dynamics for populations from these regions.Até o momento, pouco se conhece sobre a relação entre história demográfica e a presente estrutura genética da A. Angus Como uma primeira tentativa em transpor esta deficiência, dados de microssatélites coletados em seis populações e freqüências alélicas de isoenzimas publicadas para 11 populações naturais desta espécie foram analisadas com o objetivo de acessar assinaturas moleculares da história demográfica populacional. Assinaturas de gargalos genéticos foram capturadas em todas as populações analisadas provenientes do Sudeste do Brasil. Entre as populações do Sul, assinaturas de pequeno tamanho populacional efetivo foram observadas em somente três entre 13 populações. Populações do Sul provavelmente apresentaram uma rápida recuperação do

Recent change of vegetation growth trend in China

International Nuclear Information System (INIS)

Peng Shushi; Fang Jingyun; Piao Shilong; Chen, Anping; Xu Liang; Myneni, Ranga B; Cao Chunxiang; Pinzon, Jorge E; Tucker, Compton J

2011-01-01

Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982–99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April–October) NDVI significantly increased by 0.0007 yr −1 from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982–99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013 yr −1 ) is larger than those in June, July and August (JJA) (0.0003 yr −1 ) and September and October (SO) (0.0008 yr −1 ). This relatively small increasing trend of JJA NDVI during 1982–2010 compared with that during 1982–99 (0.0012 yr −1 ) (Piao et al 2003 J. Geophys. Res.—Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039 yr −1 ) to slightly decreasing ( − 0.0002 yr −1 ) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020 yr −1 ) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

Spatial and temporal patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index

International Nuclear Information System (INIS)

Walker, D A; Bhatt, U S; Raynolds, M K; Romanovsky, V E; Leibman, M O; Gubarkov, A A; Khomutov, A V; Moskalenko, N G; Orekhov, P; Ukraientseva, N G; Epstein, H E; Yu, Q; Forbes, B C; Kaarlejaervi, E; Comiso, J C; Jia, G J; Kaplan, J O; Kumpula, T; Kuss, P; Matyshak, G

2009-01-01

The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

Spatial and temporal patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index

Energy Technology Data Exchange (ETDEWEB)

Walker, D A; Bhatt, U S; Raynolds, M K; Romanovsky, V E [University of Alaska Fairbanks, Fairbanks, AK (United States); Leibman, M O; Gubarkov, A A; Khomutov, A V; Moskalenko, N G; Orekhov, P; Ukraientseva, N G [Earth Cryosphere Institute, Russian Academy of Science, Siberian Branch, Tyumen (Russian Federation); Epstein, H E; Yu, Q [University of Virginia, Charlottesville, VA (United States); Forbes, B C; Kaarlejaervi, E [Arctic Center, University of Lapland, Rovaniemi (Finland); Comiso, J C [NASA Goddard Space Flight Center, MD (United States); Jia, G J [Chinese Academy of Sciences, Institute for Atmospheric Physics, Beijing (China); Kaplan, J O [Swiss Federal Institute for Forest Snow and Landscape Research, Birmensdorf (Switzerland); Kumpula, T [University of Joensuu, Joensuu (Finland); Kuss, P [University of Berne, Berne (Switzerland); Matyshak, G [Moscow State University, Moscow (Russian Federation)

2009-10-15

The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

Recent Change of Vegetation Growth Trend in China

Science.gov (United States)

Peng, Shushi; Chen, Anping; Xu, Liang; Cao, Chunxiang; Fang, Jingyun; Myneni, Ranga B.; Pinzon, Jorge E.; Tucker, COmpton J.; Piao, Shilong

2011-01-01

Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982-99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April-October) NDVI significantly increased by 0.0007/yr from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982-99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013/yr is larger than those in June, July and August (JJA) (0.0003/yr) and September and October (SO) (0.0008/yr). This relatively small increasing trend of JJA NDVI during 1982-2010 compared with that during 1982-99 (0.0012/yr) (Piao et al 2003 J. Geophys. Res.-Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039/yr) to slightly decreasing (0:0002/yr) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020/yr) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

High-latitude tree growth and satellite vegetation indices: Correlations and trends in Russia and Canada (1982-2008)

Science.gov (United States)

Berner, Logan T.; Beck, Pieter S. A.; Bunn, Andrew G.; Lloyd, Andrea H.; Goetz, Scott J.

2011-03-01

Vegetation in northern high latitudes affects regional and global climate through energy partitioning and carbon storage. Spaceborne observations of vegetation, largely based on the normalized difference vegetation index (NDVI), suggest decreased productivity during recent decades in many regions of the Eurasian and North American boreal forests. To improve interpretation of NDVI trends over forest regions, we examined the relationship between NDVI from the advanced very high resolution radiometers and tree ring width measurements, a proxy of tree productivity. We collected tree core samples from spruce, pine, and larch at 22 sites in northeast Russia and northwest Canada. Annual growth rings were measured and used to generate site-level ring width index (RWI) chronologies. Correlation analysis was used to assess the association between RWI and summer NDVI from 1982 to 2008, while linear regression was used to examine trends in both measurements. The correlation between NDVI and RWI was highly variable across sites, though consistently positive (r = 0.43, SD = 0.19, n = 27). We observed significant temporal autocorrelation in both NDVI and RWI measurements at sites with evergreen conifers (spruce and pine), though weak autocorrelation at sites with deciduous conifers (larch). No sites exhibited a positive trend in both NDVI and RWI, although five sites showed negative trends in both measurements. While there are technological and physiological limitations to this approach, these findings demonstrate a positive association between NDVI and tree ring measurements, as well as the importance of considering lagged effects when modeling vegetation productivity using satellite data.

Identifying the Impact of Natural Hazards on Food Security in Africa: Crop Monitoring Using MODIS NDVI Time-Series

Science.gov (United States)

Freund, J. T.; Husak, G.; Funk, C.; Brown, M. E.; Galu, G.

2005-12-01

Most developing countries rely primarily on the successful cultivation of staple crops to ensure food security. Climatic hazards like drought and flooding often negatively impact economically vulnerable economies such as those in Eastern Africa. Effective tracking of food production is required in this area. Production is typically quantified as the simple product of a planted area and its corresponding crop yield. To date, crop yields have been estimated with reasonable accuracy using grid-cell techniques and a Water Requirement Satisfaction Index (WRSI), which draw from remotely sensed data. However, planted area and hence production estimation remains an arduous manual technique fraught with inevitable inaccuracies. In this study we present ongoing efforts to use MODIS NDVI time-series data as a surrogate for greenness, exploiting phenological contrast between cropland and other land cover types. In regions with small field sizes, variations in land cover can impose uncertainty in food production figures, resulting in a lack of consensus in the donor community as to the amount and type of food aid required during an emergency. To concentrate on this issue, statistical methods were employed to produce sub-pixel estimation, addressing the challenges in a monitoring system for use in subsistence-farmed areas. We will discuss two key results. Firstly, we established an inter-annual evaluation of crop health in primary agricultural areas in Kenya. These estimates will greatly improve our ability to anticipate and prevent famine in risk-prone regions through the FEWS NET early warning system. A primary goal is to build capacity in high-risk areas through the transfer of these results to local entities in the form of an operational tool. The low cost and accessibility of MODIS data lends itself well to this objective. Monitoring of crop health will be instituted for use on a yearly basis, and will draw on MODIS data analysis, ground sampling and valuable local

Determination of Leaf Area Index, Total Foliar N, and Normalized Difference Vegetation Index for Arctic Ecosystems Dominated by Cassiope tetragona

DEFF Research Database (Denmark)

Campioli, M; Street, LE; Michelsen, Anders

2009-01-01

have not been accurately quantified. We address this knowledge gap by (i) direct measurements of LAI and TFN for C. tetragona, and (ii) determining TFN-LAI and LAI–normalized difference vegetation index (NDVI) relationships for typical C. tetragona tundras in the subarctic (Sweden) and High Arctic...... leaf N and biomass. The LAI-NDVI and TFN-LAI relationships showed high correlation and can be used to estimate indirectly LAI and TFN. The LAI-NDVI relationship for C. tetragona vegetation differed from a generic LAI-NDVI relationship for arctic tundra, whereas the TFN-LAI relationship did not. Overall...

Causes of spring vegetation growth trends in the northern mid–high latitudes from 1982 to 2004

International Nuclear Information System (INIS)

Mao Jiafu; Shi Xiaoying; Thornton, Peter E; Piao Shilong; Wang Xuhui

2012-01-01

The Community Land Model version 4 (CLM4) is applied to explore the spatial–temporal patterns of spring (April–May) vegetation growth trends over the northern mid–high latitudes (NMH) (>25°N) between 1982 and 2004. During the spring season through the 23 yr period, both the satellite-derived and simulated normalized difference vegetation index (NDVI) anomalies show a statistically significant correlation and an overall greening trend within the study area. Consistently with the observed NDVI–temperature relation, the CLM4 NDVI shows a significant positive association with the spring temperature anomaly for the NMH, North America and Eurasia. Large study areas experience temperature discontinuity associated with contrasting NDVI trends. Before and after the turning point (TP) of the temperature trends, climatic variability plays a dominant role, while the other environmental factors exert minor effects on the NDVI tendencies. Simulated vegetation growth is broadly stimulated by the increasing atmospheric CO 2 . Trends show that nitrogen deposition increases NDVI mostly in southeastern China, and decreases NDVI mainly in western Russia after the temperature TP. Furthermore, land use-induced NDVI trends vary roughly with the respective changes in land management practices (crop areas and forest coverage). Our results highlight how non-climatic factors mitigate or exacerbate the impact of temperature on spring vegetation growth, particularly across regions with intensive human activity. (letter)

Improving Post-Hurricane Katrina Forest Management with MODIS Time Series Products

Science.gov (United States)

Lewis, Mark David; Spruce, Joseph; Evans, David; Anderson, Daniel

2012-01-01

Hurricane damage to forests can be severe, causing millions of dollars of timber damage and loss. To help mitigate loss, state agencies require information on location, intensity, and extent of damaged forests. NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series data products offers a potential means for state agencies to monitor hurricane-induced forest damage and recovery across a broad region. In response, a project was conducted to produce and assess 250 meter forest disturbance and recovery maps for areas in southern Mississippi impacted by Hurricane Katrina. The products and capabilities from the project were compiled to aid work of the Mississippi Institute for Forest Inventory (MIFI). A series of NDVI change detection products were computed to assess hurricane induced damage and recovery. Hurricane-induced forest damage maps were derived by computing percent change between MODIS MOD13 16-day composited NDVI pre-hurricane "baseline" products (2003 and 2004) and post-hurricane NDVI products (2005). Recovery products were then computed in which post storm 2006, 2007, 2008 and 2009 NDVI data was each singularly compared to the historical baseline NDVI. All percent NDVI change considered the 16-day composite period of August 29 to September 13 for each year in the study. This provided percent change in the maximum NDVI for the 2 week period just after the hurricane event and for each subsequent anniversary through 2009, resulting in forest disturbance products for 2005 and recovery products for the following 4 years. These disturbance and recovery products were produced for the Mississippi Institute for Forest Inventory's (MIFI) Southeast Inventory District and also for the entire hurricane impact zone. MIFI forest inventory products were used as ground truth information for the project. Each NDVI percent change product was classified into 6 categories of forest disturbance intensity. Stand age

Defining a quality index for electric power utilities using multiple criteria decision support and time series analysis Definição de um índice de qualidade para distribuidoras de energia elétrica utilizando o apoio à decisão multicritério e análise de séries temporais

Directory of Open Access Journals (Sweden)

Aderson Campos Passos

2013-03-01

Full Text Available This paper presents a hybrid multi-criteria method developed through the combination of the Analytical Hierarchy Process (AHP and exponential smoothing techniques applied in time series forecasting. To illustrate its use, a model was developed with the aim of creating a quality index for electric power distribution utilities. The conclusions highlight the need to take into account the results obtained in the latest months for those utilities, but giving less attention to those obtained in the earlier months. This characteristic of the problem led to the idea of incorporating the mathematical formulation of the exponential smoothing into the aggregation function of the AHP. At the end, the utility company is given a score between 0 (zero and 10 (ten.Este trabalho apresenta um método multicritério híbrido construído através da fusão entre o Método de Análise Hierárquica (AHP e técnicas de Amortecimento Exponencial, aplicadas na previsão de séries temporais. Para ilustrar a sua utilização foi construído um modelo com a finalidade de criar um índice de qualidade para distribuidoras de energia elétrica. As conclusões apresentadas revelam a necessidade de levar em consideração os resultados obtidos em meses anteriores por essas distribuidoras, mas dando menor importância a períodos mais distantes do tempo presente. Essa característica do problema sugeriu a idéia de incorporar a formulação matemática do amortecimento exponencial à função de agregação do AHP. Ao final é fornecida para a distribuidora avaliada uma nota entre 0 (zero e 10 (dez.

Absolute Radiometric Calibration of the GÖKTÜRK-2 Satellite Sensor Using Tuz GÖLÜ (landnet Site) from Ndvi Perspective

Science.gov (United States)

Sakarya, Ufuk; Hakkı Demirhan, İsmail; Seda Deveci, Hüsne; Teke, Mustafa; Demirkesen, Can; Küpçü, Ramazan; Feray Öztoprak, A.; Efendioğlu, Mehmet; Fehmi Şimşek, F.; Berke, Erdinç; Zübeyde Gürbüz, Sevgi

2016-06-01

TÜBİTAK UZAY has conducted a research study on the use of space-based satellite resources for several aspects of agriculture. Especially, there are two precision agriculture related projects: HASSAS (Widespread application of sustainable precision agriculture practices in Southeastern Anatolia Project Region (GAP) Project) and AKTAR (Smart Agriculture Feasibility Project). The HASSAS project aims to study development of precision agriculture practice in GAP region. Multi-spectral satellite imagery and aerial hyperspectral data along with ground measurements was collected to analyze data in an information system. AKTAR aims to develop models for irrigation, fertilization and spectral signatures of crops in Inner Anatolia. By the end of the project precision agriculture practices to control irrigation, fertilization, pesticide and estimation of crop yield will be developed. Analyzing the phenology of crops using NDVI is critical for the projects. For this reason, absolute radiometric calibration of the Red and NIR bands in space-based satellite sensors is an important issue. The Göktürk-2 satellite is an earth observation satellite which was designed and built in Turkey and was launched in 2012. The Göktürk-2 satellite sensor has a resolution 2.5 meters in panchromatic and 5 meters in R/G/B/NIR bands. The absolute radiometric calibration of the Göktürk-2 satellite sensor was performed via the ground-based measurements - spectra-radiometer, sun photometer, and meteorological station- in Tuz Gölü cal/val site in 2015. In this paper, the first ground-based absolute radiometric calibration results of the Göktürk-2 satellite sensor using Tuz Gölü is demonstrated. The absolute radiometric calibration results of this paper are compared with the published cross-calibration results of the Göktürk-2 satellite sensor utilizing Landsat 8 imagery. According to the experimental comparison results, the Göktürk-2 satellite sensor coefficients for red and NIR bands

ABSOLUTE RADIOMETRIC CALIBRATION OF THE GÖKTÜRK-2 SATELLITE SENSOR USING TUZ GÖLÜ (LANDNET SITE FROM NDVI PERSPECTIVE

Directory of Open Access Journals (Sweden)

U. Sakarya

2016-06-01

Full Text Available TÜBİTAK UZAY has conducted a research study on the use of space-based satellite resources for several aspects of agriculture. Especially, there are two precision agriculture related projects: HASSAS (Widespread application of sustainable precision agriculture practices in Southeastern Anatolia Project Region (GAP Project and AKTAR (Smart Agriculture Feasibility Project. The HASSAS project aims to study development of precision agriculture practice in GAP region. Multi-spectral satellite imagery and aerial hyperspectral data along with ground measurements was collected to analyze data in an information system. AKTAR aims to develop models for irrigation, fertilization and spectral signatures of crops in Inner Anatolia. By the end of the project precision agriculture practices to control irrigation, fertilization, pesticide and estimation of crop yield will be developed. Analyzing the phenology of crops using NDVI is critical for the projects. For this reason, absolute radiometric calibration of the Red and NIR bands in space-based satellite sensors is an important issue. The Göktürk-2 satellite is an earth observation satellite which was designed and built in Turkey and was launched in 2012. The Göktürk-2 satellite sensor has a resolution 2.5 meters in panchromatic and 5 meters in R/G/B/NIR bands. The absolute radiometric calibration of the Göktürk-2 satellite sensor was performed via the ground-based measurements - spectra-radiometer, sun photometer, and meteorological station- in Tuz Gölü cal/val site in 2015. In this paper, the first ground-based absolute radiometric calibration results of the Göktürk-2 satellite sensor using Tuz Gölü is demonstrated. The absolute radiometric calibration results of this paper are compared with the published cross-calibration results of the Göktürk-2 satellite sensor utilizing Landsat 8 imagery. According to the experimental comparison results, the Göktürk-2 satellite sensor coefficients for

Seasonal relationship between normalized difference vegetation index and abundance of the Phlebotomus kala-azar vector in an endemic focus in Bihar, India

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Gouri S. Bhunia

2012-11-01

Full Text Available Remote sensing was applied for the collection of spatio-temporal data to increase our understanding of the potential distribution of the kala-azar vector Phlebotomus argentipes in endemic areas of the Vaishali district of Bihar, India. We produced monthly distribution maps of the normalized difference vegetation index (NDVI based on data from the thematic mapper (TM sensor onboard the Landsat-5 satellite. Minimum, maximum and mean NDVI values were computed for each month and compared with the concurrent incidence of kala-azar and the vector density. Maximum and mean NDVI values (R2 = 0.55 and R2 = 0.60, respectively, as well as the season likelihood ratio (X2 = 17.51; P <0.001, were found to be strongly associated with kala-azar, while the correlation with between minimum NDVI values and kala-azar was weak (R2 = 0.25. Additionally, a strong association was found between the mean and maximum NDVI values with seasonal vector abundance (R2 = 0.60 and R2 = 0.55, respectively but there was only a marginal association between minimum NDVI value and the spatial distribution of kala-azar vis-à-vis P. argentipes density.

No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau

Science.gov (United States)

Wang, Xufeng; Xiao, Jingfeng; Li, Xin; Cheng, Guodong; Ma, Mingguo; Che, Tao; Dai, Liyun; Wang, Shaoying; Wu, Jinkui

2017-12-01

Vegetation phenology is a sensitive indicator of climate change and has significant effects on the exchange of carbon, water, and energy between the terrestrial biosphere and the atmosphere. The Tibetan Plateau, the Earth's "third pole," is a unique region for studying the long-term trends in vegetation phenology in response to climate change because of the sensitivity of its alpine ecosystems to climate and its low-level human disturbance. There has been a debate whether the trends in spring phenology over the Tibetan Plateau have been continuously advancing over the last two to three decades. In this study, we examine the trends in the start of growing season (SOS) for alpine meadow and steppe using the Global Inventory Modeling and Mapping Studies (GIMMS)3g normalized difference vegetation index (NDVI) data set (1982-2014), the GIMMS NDVI data set (1982-2006), the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data set (2001-2014), the Satellite Pour l'Observation de la Terre Vegetation (SPOT-VEG) NDVI data set (1999-2013), and the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) NDVI data set (1998-2007). Both logistic and polynomial fitting methods are used to retrieve the SOS dates from the NDVI data sets. Our results show that the trends in spring phenology over the Tibetan Plateau depend on both the NDVI data set used and the method for retrieving the SOS date. There are large discrepancies in the SOS trends among the different NDVI data sets and between the two different retrieval methods. There is no consistent evidence that spring phenology ("green-up" dates) has been advancing or delaying over the Tibetan Plateau during the last two to three decades. Ground-based budburst data also indicate no consistent trends in spring phenology. The responses of SOS to environmental factors (air temperature, precipitation, soil temperature, and snow depth) also vary among NDVI data sets and phenology retrieval methods. The increases in winter and spring

Vegetation pattern of Istanbul from the Landsat data and the relationship with meteorological parameters

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Zafer Aslan

Full Text Available This paper discusses the preliminary results of a study on the vegetation pattern and its relationship with meteorological parameters in and around Istanbul. The study covers an area of over 6800 km² consisting of urban and suburban centers, and uses the visible and near-infrared bands of Landsat. The spatial variation of the Normalized Difference Vegetation Index (NDVI and meteorological parameters such as sensible heat flux, momentum flux, relative humidity, moist static energy, rainfall rate and temperature have been investigated based on observations in ten stations in the European (Thracian and Anatolian parts of Istanbul. NDVI values have been evaluated from the Landsat data for a single day, viz. 24 October 1986, using ERDAS in ten different classes. The simultaneous spatial variations of sensible heat and momentum fluxes have been computed from the wind and temperature profiles using the Monin-Obukhov similarity theory. The static energy variations are based on the surface meteorological observations. There is very good correlation between NDVI and rainfall rate. Good correlation also exists between: NDVI and relative humidity; NDVI, sensible heat flux and relative humidity; NDVI, momentum flux and emissivity; and NDVI, sensible heat flux and emissivity. The study suggests that the momentum flux has only marginal impact on NDVI. Due to rapid urbanization,the coastal belt is characterized by reduced NDVI compared to the interior areas, suggesting that thermodynamic discontinuities considerably influence the vegetation pattern. This study is useful for the investigation of small-scale circulation models, especially in urban and suburban areas where differential heating leads to the formation of heat islands. In the long run, such studies on a global scale are vital to gain accurate, timely information on the distribution of vegetation on the earth's surface. This may lead to an understanding of how changes in land cover

Vegetation pattern of Istanbul from the Landsat data and the relationship with meteorological parameters

Directory of Open Access Journals (Sweden)

Z. Aslan

1994-05-01

Full Text Available This paper discusses the preliminary results of a study on the vegetation pattern and its relationship with meteorological parameters in and around Istanbul. The study covers an area of over 6800 km2 consisting of urban and suburban centers, and uses the visible and near-infrared bands of Landsat. The spatial variation of the Normalized Difference Vegetation Index (NDVI and meteorological parameters such as sensible heat flux, momentum flux, relative humidity, moist static energy, rainfall rate and temperature have been investigated based on observations in ten stations in the European (Thracian and Anatolian parts of Istanbul. NDVI values have been evaluated from the Landsat data for a single day, viz. 24 October 1986, using ERDAS in ten different classes. The simultaneous spatial variations of sensible heat and momentum fluxes have been computed from the wind and temperature profiles using the Monin-Obukhov similarity theory. The static energy variations are based on the surface meteorological observations. There is very good correlation between NDVI and rainfall rate. Good correlation also exists between: NDVI and relative humidity; NDVI, sensible heat flux and relative humidity; NDVI, momentum flux and emissivity; and NDVI, sensible heat flux and emissivity. The study suggests that the momentum flux has only marginal impact on NDVI. Due to rapid urbanization,the coastal belt is characterized by reduced NDVI compared to the interior areas, suggesting that thermodynamic discontinuities considerably influence the vegetation pattern. This study is useful for the investigation of small-scale circulation models, especially in urban and suburban areas where differential heating leads to the formation of heat islands. In the long run, such studies on a global scale are vital to gain accurate, timely information on the distribution of vegetation on the earth's surface. This may lead to an understanding of how changes in land cover affect phenomena as

Monitoring natural vegetation in Southern Greenland using NOAA AVHRR and field measurements

DEFF Research Database (Denmark)

Hansen, Birger Ulf

1991-01-01

vegetation, sheep farming, biomass production, Remote Sensing, NOAA AVHRR, Southern Greenland, NDVI......vegetation, sheep farming, biomass production, Remote Sensing, NOAA AVHRR, Southern Greenland, NDVI...

Mapping long-term changes in savannah crop productivity in Senegal through trend analysis of time-series of remote sensing data

DEFF Research Database (Denmark)

Tøttrup, Christian; Rasmussen, Michael Schultz

2004-01-01

Remote sensing, NDVI, trend analysis, environmental change, rainfall, land cover change, Senegal......Remote sensing, NDVI, trend analysis, environmental change, rainfall, land cover change, Senegal...

Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California

Science.gov (United States)

Soulard, Christopher E.; Albano, Christine M.; Villarreal, Miguel; Walker, Jessica

2016-01-01

To assess how montane meadow vegetation recovered after a wildfire that occurred in Yosemite National Park, CA in 1996, Google Earth Engine image processing was applied to leverage the entire Landsat Thematic Mapper archive from 1985 to 2012. Vegetation greenness (normalized difference vegetation index [NDVI]) was summarized every 16 days across the 28-year Landsat time series for 26 meadows. Disturbance event detection was hindered by the subtle influence of low-severity fire on meadow vegetation. A hard break (August 1996) was identified corresponding to the Ackerson Fire, and monthly composites were used to compare NDVI values and NDVI trends within burned and unburned meadows before, immediately after, and continuously for more than a decade following the fire date. Results indicate that NDVI values were significantly lower at 95% confidence level for burned meadows following the fire date, yet not significantly lower at 95% confidence level in the unburned meadows. Burned meadows continued to exhibit lower monthly NDVI in the dormant season through 2012. Over the entire monitoring period, the negative-trending, dormant season NDVI slopes in the burned meadows were also significantly lower than unburned meadows at 90% confidence level. Lower than average NDVI values and slopes in the dormant season compared to unburned meadows, coupled with photographic evidence, strongly suggest that evergreen vegetation was removed from the periphery of some meadows after the fire. These analyses provide insight into how satellite imagery can be used to monitor low-severity fire effects on meadow vegetation.

Determination of forest growth trends in Komi Republic (northwestern Russia): combination of tree-ring analysis and remote sensing data

Energy Technology Data Exchange (ETDEWEB)

Lopatin, E. [Joensuu Univ., Faculty of Forestry, Joensuu (Finland); Kolstroem, T. [Joensuu Univ., Mekrijaervi Research Station, Joensuu (Finland); Spiecker, H. [Univ. of Freiburg, Inst. for Forest Growth, Freiburg (Germany)

2006-07-01

It is very important to detect changes in forest productivity due to the global change on a large scale. In this work, the evolution of the vegetation in the Komi Republic (northwestern Russia) from 1982 to 2001 was analyzed using NOAA AVHRR PAL time series. A statistically significant correlation (adjusted r2 = 0.44-0.59) between Normalized Difference Vegetation Index (NDVI) data and tree ring width (261 living trees) was identified for the territory of the Komi Republic. The increased site productivity reflected an increase of integrated NDVI values from June to August. This allows NDVI to be used as a proxy for estimation of forest growth trends for the recent decades. A positive and significant trend in NDVI data was identified from 1982 to 2001, coinciding with an increase in site productivity in the study area. The decrease in precipitations coincided with an increase in site productivity (highest r2 was 0.71). The increase in productivity reflected in NDVI data is maximal on the sites with increased temperature and decreased precipitations. In the Komi Republic the distribution of the trends in NDVI data changes on the south-west to north-east gradient. NDVI data could be used to increase spatial resolution of tree ring width series. Taking into account the relatively small role of human activity in the Komi Republic compared with Europe, the site productivity during recent decades also increased in relatively untouched forests. (orig.)

Remote sensing data with the conditional latin hypercube sampling and geostatistical approach to delineate landscape changes induced by large chronological physical disturbances.

Science.gov (United States)

Lin, Yu-Pin; Chu, Hone-Jay; Wang, Cheng-Long; Yu, Hsiao-Hsuan; Wang, Yung-Chieh

2009-01-01

This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the ChiChi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures and spatial variability of landscapes caused by these large disturbances. The conditional Latin hypercube sampling approach was applied to select samples from multiple NDVI images. Kriging and sequential Gaussian simulation with sufficient samples were then used to generate maps of NDVI images. The variography of NDVI image results demonstrate that spatial patterns of disturbed landscapes were successfully delineated by variogram analysis in study areas. The high-magnitude Chi-Chi earthquake created spatial landscape variations in the study area. After the earthquake, the cumulative impacts of typhoons on landscape patterns depended on the magnitudes and paths of typhoons, but were not always evident in the spatiotemporal variability of landscapes in the study area. The statistics and spatial structures of multiple NDVI images were captured by 3,000 samples from 62,500 grids in the NDVI images. Kriging and sequential Gaussian simulation with the 3,000 samples effectively reproduced spatial patterns of NDVI images. However, the proposed approach, which integrates the conditional Latin hypercube sampling approach, variogram, kriging and sequential Gaussian simulation in remotely sensed images, efficiently monitors, samples and maps the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial variability and heterogeneity.

Hipotaxe e Gramaticalização: uma Análise das Construções de Tempo e de Condição

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NEVES Maria Helena de Moura

1998-01-01

Full Text Available O trabalho estuda construções de orações hipotáticas temporais e construções de orações hipotáticas condicionais, com a finalidade de investigar o grau de gramaticalização que se verifica nesses dois tipos de enunciados. A hipótese é que quanto maior a integração da oração hipotática à nuclear, maior o grau de gramaticalização. Essa maior integração foi medida segundo três grupos de fatores, e os resultados mostraram que, em duas das variáveis avaliadas, as orações condicionais são as mais integradas a seu núcleo, mas, em outra ordem de avaliação, as orações temporais são as mais integradas. Dentro da base funcionalista em que o trabalho se move, esses resultados podem ser interpretados segundo o princípio da existência de competição de motivações no jogo da linguagem, entendendo-se que cada enunciado que se produz é o resultado do equilíbrio dessas pressões.

TV universitária, um modelo de gestão em construção: TV UNAERP de Ribeirão Preto

OpenAIRE

Martelli, Flávia Cortese [UNESP

2012-01-01

Esta pesquisa tem como objetivo traçar o perfil de um grupo de TVs universitárias do Brasil e da TV Unaerp de Ribeirão Preto e analisar os modelos de gestão adotados por elas, já que a maior parte veicula a programação por meio da TV por assinatura via cabo. As características que delineiam as TVs universitárias ainda estão sendo formadas no país, portanto, necessita-se identificar os modelos de negócio e as leis que regulamentaram o setor e, desta maneira, verificar de que forma afetam o des...

Itaipu e as relações brasileiro-paraguaias de 1962 a 1979: fronteira, energia e poder

OpenAIRE

Neto, Tomaz Espósito

2012-01-01

O objetivo do presente trabalho é examinar as relações entre o Brasil e o Paraguai durante as tratativas políticas sobre a construção de Itaipu, que se iniciaram em 1962, com a divulgação do projeto Otávio Marcondes Ferraz, e tiveram seu término em 1979, com a assinatura do Acordo Tripartite, que consolidou um marco legal na exploração hidroelétrica na bacia do Rio da Prata. Esta análise é crucial para o entendimento da atuação da política externa brasileira e das relações de poder interestat...

[Effects of climate and grazing on the vegetation cover change in Xilinguole League of Inner Mongolia, North China].

Science.gov (United States)

Wang, Hai-Mei; Li, Zheng-Hai; Wang, Zhen

2013-01-01

Based on the monthly temperature and precipitation data of 15 meteorological stations and the statistical data of livestock density in Xilinguole League in 1981-2007, and by using ArcGIS, this paper analyzed the spatial distribution of the climate aridity and livestock density in the League, and in combining with the ten-day data of the normalized difference vegetation index (NDVI) in 1981-2007, the driving factors of the vegetation cover change in the League were discussed. In the study period, there was a satisfactory linear regression relationship between the climate aridity and the vegetation coverage. The NDVI and the livestock density had a favorable binomial regression relationship. With the increase of NDVI, the livestock density increased first and decreased then. The vegetation coverage had a complex linear relationship with livestock density and climate aridity. The NDVI had a positive correlation with climate aridity, but a negative correlation with livestock density. Compared with livestock density, climate aridity had far greater effects on the NDVI.

Responses of Vegetation Cover to Environmental Change in Large Cities of China

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Kai Jin

2018-01-01

Full Text Available Vegetation cover is crucial for the sustainability of urban ecosystems; however, this cover has been undergoing substantial changes in cities. Based on climate data, city statistical data, nighttime light data and the Normalized Difference Vegetation Index (NDVI dataset, we investigate the spatiotemporal variations of climate factors, urban lands and vegetation cover in 71 large cities of China during 1998–2012, and explore their correlations. A regression model between growing-season NDVI (G-NDVI and urban land proportion (PU is built to quantify the impact of urbanization on vegetation cover change. The results indicate that the spatiotemporal variations of temperature, precipitation, PU and G-NDVI are greatly different among the 71 cities which experienced rapid urbanization. The spatial difference of G-NDVI is closely related to diverse climate conditions, while the inter-annual variations of G-NDVI are less sensitive to climate changes. In addition, there is a negative correlation between G-NDVI trend and PU change, indicating vegetation cover in cities have been negatively impacted by urbanization. For most of the inland cities, the urbanization impacts on vegetation cover in urban areas are more severe than in suburban areas. But the opposite occurs in 17 cities mainly located in the coastal areas which have been undergoing the most rapid urbanization. Overall, the impacts of urbanization on G-NDVI change are estimated to be −0.026 per decade in urban areas and −0.015 per decade in suburban areas during 1998–2012. The long-term developments of cities would persist and continue to impact on the environmental change and sustainability. We use a 15-year window here as a case study, which implies the millennia of human effects on the natural biotas and warns us to manage landscapes and preserve ecological environments properly.

Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change.

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Antonius G T Schut

Full Text Available Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010 derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity.

Remote sensing of surface water quality in relation to catchment condition in Zimbabwe

Science.gov (United States)

Masocha, Mhosisi; Murwira, Amon; Magadza, Christopher H. D.; Hirji, Rafik; Dube, Timothy

2017-08-01

The degradation of river catchments is one of the most important contemporary environmental problems affecting water quality in tropical countries. In this study, we used remotely sensed Normalised Difference Vegetation Index (NDVI) to assess how catchment condition varies within and across river catchments in Zimbabwe. We then used non-linear regression to test whether catchment condition assessed using the NDVI is significantly (α = 0.05) related with levels of Total Suspended Solids (TSS) measured at different sampling points in thirty-two sub-catchments in Zimbabwe. The results showed a consistent negative curvilinear relationship between Landsat 8 derived NDVI and TSS measured across the catchments under study. In the drier catchments of the country, 98% of the variation in TSS is explained by NDVI, while in wetter catchments, 64% of the variation in TSS is explained by NDVI. Our results suggest that NDVI derived from free and readily available multispectral Landsat series data (Landsat 8) is a potential valuable tool for the rapid assessment of physical water quality in data poor catchments. Overall, the finding of this study underscores the usefulness of readily available satellite data for near-real time monitoring of the physical water quality at river catchment scale, especially in resource-constrained areas, such as the sub-Saharan Africa.

Evaluation of Spatiotemporal Variations of Global Fractional Vegetation Cover Based on GIMMS NDVI Data from 1982 to 2011

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Donghai Wu

2014-05-01

Full Text Available Fractional vegetation cover (FVC is an important biophysical parameter of terrestrial ecosystems. Variation of FVC is a major problem in research fields related to remote sensing applications. In this study, the global FVC from 1982 to 2011 was estimated by GIMMS NDVI data, USGS global land cover characteristics data and HWSD soil type data with a modified dimidiate pixel model, which considered vegetation and soil types and mixed pixels decomposition. The evaluation of the robustness and accuracy of the GIMMS FVC with MODIS FVC and Validation of Land European Remote sensing Instruments (VALERI FVC show high reliability. Trends of the annual FVCmax and FVCmean datasets in the last 30 years were reported by the Mann–Kendall method and Sen’s slope estimator. The results indicated that global FVC change was 0.20 and 0.60 in a year with obvious seasonal variability. All of the continents in the world experience a change in the annual FVCmax and FVCmean, which represents biomass production, except for Oceania, which exhibited a significant increase based on a significance level of p = 0.001 with the Student’s t-test. Global annual maximum and mean FVC growth rates are 0.14%/y and 0.12%/y, respectively. The trends of the annual FVCmax and FVCmean based on pixels also illustrated that the global vegetation had turned green in the last 30 years. A significant trend on the p = 0.05 level was found for 15.36% of the GIMMS FVCmax pixels on a global scale (excluding permanent snow and ice, in which 1.8% exhibited negative trends and 13.56% exhibited positive trends. The GIMMS FVCmean similarly produced a total of 16.64% significant pixels with 2.28% with a negative trend and 14.36% with a positive trend. The North Frigid Zone represented the highest annual FVCmax significant increase (p = 0.05 of 25.17%, which may be caused mainly by global warming, Arctic sea-ice loss and an advance in growing seasons. Better FVC predictions at large regional scales

Výzkum dlouhodobých změn hodnot vegetačních indexů

OpenAIRE

Beránková, Petra

2010-01-01

The work deals with the issue of research of long-term changes of vegetation indices concretely indices NDVI (Normalized Difference Vegetation Index). The first part is devoted to detailed analysis of domestic and foreign literature, which deals with the calculation and interpretation of vegetation indices values. The main theme of this work is to explore relation between temperature and NDVI changes and precipitation and NDVI changes over the period 1982-2006. These connections are examined ...

Exploring Relationships among Tree-Ring Growth, Climate Variability, and Seasonal Leaf Activity on Varying Timescales and Spatial Resolutions

OpenAIRE

Bhuyan, Upasana;Zang, Christian;Vicente-Serrano, Sergio;Menzel, Annette

2018-01-01

In the first section of this study, we explored the relationship between ring width index (RWI) and normalized difference vegetation index (NDVI) time series on varying timescales and spatial resolutions, hypothesizing positive associations between RWI and current and previous- year NDVI at 69 forest sites scattered in the Northern Hemisphere. We noted that the relationship between RWI and NDVI varies over space and between tree types (deciduous versus coniferous), bioclimatic zones, cumulati...

Exploring Relationships among Tree-Ring Growth, Climate Variability, and Seasonal Leaf Activity on Varying Timescales and Spatial Resolutions

OpenAIRE

Upasana Bhuyan; Christian Zang; Sergio M. Vicente-Serrano; Annette Menzel

2017-01-01

In the first section of this study, we explored the relationship between ring width index (RWI) and normalized difference vegetation index (NDVI) time series on varying timescales and spatial resolutions, hypothesizing positive associations between RWI and current and previous- year NDVI at 69 forest sites scattered in the Northern Hemisphere. We noted that the relationship between RWI and NDVI varies over space and between tree types (deciduous versus coniferous), bioclimatic zones, cumulati...

Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

Science.gov (United States)

Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna

2016-01-01

This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

Food and nutrition security trends and challenges in the Ganges Brahmaputra Meghna (GBM delta

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Arnout van Soesbergen

2017-09-01

Full Text Available The population of the Ganges Brahmaputra Meghna (GBM delta is highly vulnerable to food insecurity and malnutrition due to the specific environmental, climatic and human development factors affecting agricultural production and fisheries. To better understand the impacts of climate and environmental change on food security and nutrition in this delta, this study combines spatially explicit data from the 2007 and 2011 Bangladesh Demographic and Health Survey (BDHS with a standard satellite remotely sensed vegetation greenness index (Normalised Difference Vegetation Index, NDVI, used as a proxy for rice production. The strength of association between NDVI and child nutrition in this tropical mega-delta were tested, showing correlations between two widely used indicators of child malnutrition; stunting and wasting, and deviations from a 10 year mean NDVI (anomalies for rice crop growing seasons – regarded as critical to individual children’s early lives. For children surveyed in 2007 we found that the likelihood of being stunted decreased with increased NDVI as a measure of food production. Similarly, for children surveyed in 2011, the likelihood of being wasted reduced with increased NDVI. However, regression results for stunting in 2011 and wasting in 2007 were not statistically significant. Our findings suggest that NDVI can be regarded as indicative of climatic variability and periods of low food production but is only partly successful as an indicator of climate related impacts on child nutrition in the GBM delta. Furthermore, our study highlights some of the uncertainties and challenges with linking environmental indicators such as the NDVI with household survey data across spatial and temporal scales.

Grassland Npp Monitoring Based on Multi-Source Remote Sensing Data Fusion

Science.gov (United States)

Cai, Y. R.; Zheng, J. H.; Du, M. J.; Mu, C.; Peng, J.

2018-04-01

Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycle process.Climate change has an important influence on the carbon cycle of terrestrial ecosystems. Net Primary Productivity (Net Primary Productivity)is an important parameter for evaluating global terrestrial ecosystems. For the Xinjiang region, the study of grassland NPP has gradually become a hot issue in the ecological environment.Increasing the estimation accuracy of NPP is of great significance to the development of the ecosystem in Xinjiang. Based on the third-generation GIMMS AVHRR NDVI global vegetation dataset and the MODIS NDVI (MOD13A3) collected each month by the United States Atmospheric and Oceanic Administration (NOAA),combining the advantages of different remotely sensed datasets, this paper obtained the maximum synthesis fusion for New normalized vegetation index (NDVI) time series in 2006-2015.Analysis of Net Primary Productivity of Grassland Vegetation in Xinjiang Using Improved CASA Model The method described in this article proves the feasibility of applying data processing, and the accuracy of the NPP calculation using the fusion processed NDVI has been greatly improved. The results show that: (1) The NPP calculated from the new normalized vegetation index (NDVI) obtained from the fusion of GIMMS AVHRR NDVI and MODIS NDVI is significantly higher than the NPP calculated from these two raw data; (2) The grassland NPP in Xinjiang Interannual changes show an overall increase trend; interannual changes in NPP have a certain relationship with precipitation.

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali.

Science.gov (United States)

Gaudart, Jean; Touré, Ousmane; Dessay, Nadine; Dicko, A Lassane; Ranque, Stéphane; Forest, Loic; Demongeot, Jacques; Doumbo, Ogobara K

2009-04-10

The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models.Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data.The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia.Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]).The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

Science.gov (United States)

Gaudart, Jean; Touré, Ousmane; Dessay, Nadine; Dicko, A lassane; Ranque, Stéphane; Forest, Loic; Demongeot, Jacques; Doumbo, Ogobara K

2009-01-01

Background The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]). The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error

Monitoring responses of Mason Pine to acid rain in China based on remote sensing vegetation index

International Nuclear Information System (INIS)

Jin, Jiaxin; Jiang, Hong; Zhang, Xiuying; Wang, Ying; Hou, Chunliang

2014-01-01

Since the 1970s, acid rain has remained in the public spotlight in both Europe and the United States and recently has emerged as an important problem in other regions such as Southeast Asia. To reveal responses of Masson Pine to acid rain during a long time series in central China, we used the interpolation dataset of acid rain and the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data to derive the monthly pH and NDVI trajectories based on acidity gradients from 1992 to 2006. Then we analyzed inter-annual and seasonal variation of vegetation growth by improved sinusoidal fitting and regression analysis. In the environment of strong acidity and moderate acidity, the growth of Masson Pine was inhibited during the study period, while the slight acidity promoted growth of Masson Pine to some extent. For the multi-year monthly changing trend of NDVI, late spring to mid autumn, the NDVI showed a decreasing trend, especially in June, while from late autumn to the following spring, the NDVI showed a rising tendency, specifically in December and March

[Study on the relationship between Terra-MODIS image and the snail distribution in marshland of Jiangning county, Jiangsu province].

Science.gov (United States)

Zhang, Bo; Zhang, Zhi-ying; Xu, De-zhong; Sun, Zhi-dong; Zhou, Xiao-nong; Gong, Zi-li; Liu, Shi-jun; Liu, Cheng; Xu, Bin; Zhou, Yun

2003-04-01

To analyze the relationship between the normalized difference vegetation index (NDVI) and the snail distribution in marshland of Jiangning county in Jiangsu province, and to explore the utility of Terra-MODIS image map in the small scale snail habitats surveillance. NDVI were extracted from MODIS image by vector chart of the snail distribution using ArcView 8.1 and ERDAS 8.5 software. The relationship between NDVI and the snail distribution were Investigated using Bivariate correlations and stepwise linear regression. The snail density on marshland was positively correlated with the mean NDVI in the first ten-day of May and the maximum NDVI (N(20max)) in the last ten-day of May. Incidence of pixel with the live snail on marshland was positively correlated with the mean NDVI (N(2mean)) in the first ten-day of May. An equation Y(1) = 0.009 47 x N(20max) (R(2) = 0.73), Y(2) = 0.018 6 x N(2mean) (R(2) = 0.906) was established. This study showed that the Terra-MODIS satellite images reflecting the status of the vegetation on marshland in Jiangning county could be applied to the study to supervise the snail habitat. The results suggested that MODIS images could be used to survey the small scale snail habitats on marshland.

Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

Science.gov (United States)

Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

2015-01-01

Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

Growing Degree Vegetation Production Index (GDVPI): A Novel and Data-Driven Approach to Delimit Season Cycles

Science.gov (United States)

Graham, W. D.; Spruce, J.; Ross, K. W.; Gasser, J.; Grulke, N.

2014-12-01

Growing Degree Vegetation Production Index (GDVPI) is a parametric approach to delimiting vegetation seasonal growth and decline cycles using incremental growing degree days (GDD), and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 8-day composite cumulative integral data. We obtain a specific location's daily minimum and maximum temperatures from the nearest National Oceanic and Atmospheric Administration (NOAA) weather stations posted on the National Climate Data Center (NCDC) Climate Data Online (CDO) archive and compute GDD. The date range for this study is January 1, 2000 through December 31, 2012. We employ a novel process, a repeating logistic product (RLP), to compensate for short-term weather variability and data drops from the recording stations and fit a curve to the median daily GDD values, adjusting for asymmetry, amplitude, and phase shift that minimize the sum of squared errors when comparing the observed and predicted GDD. The resulting curve, here referred to as the surrogate GDD, is the time-temperature phasing parameter used to convert Cartesian NDVI values into polar coordinate pairs, multiplying the NDVI values as the radial by the cosine and sine of the surrogate GDD as the angular. Depending on the vegetation type and the original NDVI curve, the polar NDVI curve may be nearly circular, kidney-shaped, or pear-shaped in the case of conifers, deciduous, or agriculture, respectively. We examine the points of tangency about the polar coordinate NDVI curve, identifying values of 1, 0, -1, or infinity, as each of these represent natural inflection points. Lines connecting the origin to each tangent point illustrate and quantify the parametrically segmentation of the growing season based on the GDD and NDVI ostensible dependency. Furthermore, the area contained by each segment represents the apparent vegetation production. A particular benefit is that the inflection points are determined

Observed Effects of Vegetation Growth on Temperature in the Early Summer over the Northeast China Plain

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Xiaxiang Li

2017-05-01

Full Text Available The effect of vegetation on temperature is an emerging topic in the climate science community. Existing studies have mostly examined the effects of vegetation on daytime temperature (Tmax, whereas this study investigates the effects on nighttime temperature (Tmin. Ground measurements from 53 sites across northeastern China (NEC from 1982 to 2006 show that early summer (June Tmax and Tmin increased at mean rates of approximately 0.61 °C/10 year and 0.67 °C/10 year, respectively. Over the same period, the satellite-based Normalized Difference Vegetation Index (NDVI decreased by approximately 0.10 (accounting for 18% of the climatological NDVI for 1982–1991. It is highlighted that a larger increase in Tmax (Tmin co-occurred spatially with a larger (smaller decrease in NDVI. Deriving from such spatial co-occurrences, we found that the spatial variability of changes in Tmax (i.e., ΔTmax is negatively correlated with the spatial variability of changes in NDVI (i.e., ΔNDVI, while the spatial variability of changes in Tmin (i.e., ΔTmin is positively correlated (r2 = 0.10; p < 0.05 with that of ΔNDVI. Similarly, we detected significant positive correlations between the spatial variability of ΔNDVI and the change in surface latent heat flux (r2 = 0.16; p < 0.01 and in surface air specific humidity (r2 = 0.28; p < 0.001. These findings on the spatial co-occurrences suggest that the vegetation growth intensifies the atmospheric water vapor through evapotranspiration, which enhances the atmospheric downward longwave radiation and strengthens the greenhouse warming effects at night. Thereby, the positive correlation between ΔNDVI and ΔTmin is better understood. These results indicate that vegetation growth may not only exert effects on daytime temperature but also exert warming effects on nighttime temperature by increasing atmospheric water vapor and thus intensifying the local greenhouse effect. This study presents new observation evidence of the

Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA

Data.gov (United States)

U.S. Environmental Protection Agency — The asci files are the probability of the NDVI trend (slope) and the direction of the NDVI trend (+/-). These files can be mapped in ArcMap using ArcToolbox...

Ressonância magnética na esquizofrenia: um estudo morfométrico

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Castro Cláudio Campi de

2001-01-01

Full Text Available Trinta e três pacientes esquizofrênicos crônicos e 21 indivíduos normais foram submetidos a exames de ressonância magnética em aparelho de 1,5 T, sendo realizadas imagens ponderadas em T2 nos planos axial e coronal. Foram analisados, por métodos morfométricos semi-automáticos, os volumes intracraniano, supratentorial, infratentorial, do líquido cefalorraquiano total, ventricular e subaracnóide e do encéfalo. Foram ainda medidos os volumes do complexo amígdala-hipocampo, córtex do giro para-hipocampal, putâmen, globo pálido, lobo temporal e substâncias branca e cinzenta do lobo temporal. Foram calculados os volumes relativos dessas estruturas, corrigidos pelo volume intracraniano. As alterações mais relevantes observadas nos esquizofrênicos, em comparação com os controles, foram de redução do volume relativo do encéfalo, aumento do volume relativo do líquido cefalorraquiano ventricular, subaracnóide e total. Foi ainda observada redução do volume dos complexos amígdala-hipocampo, dos lobos temporais e da substância branca dos lobos temporais, e aumento de volume dos putâmens.

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

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Demongeot Jacques

2009-04-01

Full Text Available Abstract Background The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI, issued from satellite imagery series (NOAA from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001. An NDVI threshold of 0.361 (p = 0.007 provided a Diagnostic Odd Ratio (DOR of 2.64 (CI95% [1.26;5.52]. The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately

Responses of Vegetation Growth to Climatic Factors in Shule River Basin in Northwest China: A Panel Analysis

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Jinghui Qi

2017-03-01

Full Text Available The vegetation response to climatic factors is a hot topic in global change research. However, research on vegetation in Shule River Basin, which is a typical arid region in northwest China, is still limited, especially at micro scale. On the basis of Moderate-resolution Imaging Spectroradiometer (MODIS Normalized Difference Vegetation Index (NDVI data and daily meteorological data, employing panel data models and other mathematical models, the aim of this paper is to reveal the interactive relationship between vegetation variation and climatic factors in Shule River Basin. Results show that there is a widespread greening trend in the whole basin during 2000–2015, and 80.28% of greening areas (areas with vegetation improvement are distributed over upstream region, but the maximum vegetation variation appears in downstream area. The effects of climate change on NDVI lag about half to one month. The parameters estimated using panel data models indicate that precipitation and accumulated temperature have positive contribution to NDVI. With every 1-mm increase in rainfall, NDVI increases by around 0.223‰ in upstream area and 0.6‰ in downstream area. With every 1-°C increase in accumulated temperature, NDVI increases by around 0.241‰ in upstream area and 0.174‰ in downstream area. Responses of NDVI to climatic factors are more sensitive when these factors are limiting than when they are not limiting. NDVI variation has performance in two seasonal and inter-annual directions, and the range of seasonal change is far more than that of inter-annual change. The inverted U-shaped curve of the variable intercepts reflects the seasonal change. Our results might provide some scientific basis for the comprehensive basin management.

Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

Science.gov (United States)

Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

2018-04-01

Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

Vegetation greenness trend (2000 to 2009) and the climate controls in the Qinghai-Tibetan Plateau

Science.gov (United States)

Zhang, Li; Guo, Huadong; Ji, Lei; Lei, Liping; Wang, Cuizhen; Yan, Dongmei; Li, Bin; Li, Jing

2013-01-01

The Qinghai-Tibetan Plateau has been experiencing a distinct warming trend, and climate warming has a direct and quick impact on the alpine grassland ecosystem. We detected the greenness trend of the grasslands in the plateau using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2009. Weather station data were used to explore the climatic drivers for vegetation greenness variations. The results demonstrated that the region-wide averaged normalized difference vegetation index (NDVI) increased at a rate of 0.036  yr−1. Approximately 20% of the vegetation areas, which were primarily located in the northeastern plateau, exhibited significant NDVI increase trend (p-value plateau. A strong positive relationship between NDVI and precipitation, especially in the northeastern plateau, suggested that precipitation was a favorable factor for the grassland NDVI. Negative correlations between NDVI and temperature, especially in the southern plateau, indicated that higher temperature adversely affected the grassland growth. Although a warming climate was expected to be beneficial to the vegetation growth in cold regions, the grasslands in the central and southwestern plateau showed a decrease in trends influenced by increased temperature coupled with decreased precipitation.

Estimating carbon dioxide fluxes from temperate mountain grasslands using broad-band vegetation indices

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G. Wohlfahrt

2010-02-01

Full Text Available The broad-band normalised difference vegetation index (NDVI and the simple ratio (SR were calculated from measurements of reflectance of photosynthetically active and short-wave radiation at two temperate mountain grasslands in Austria and related to the net ecosystem CO₂ exchange (NEE measured concurrently by means of the eddy covariance method. There was no significant statistical difference between the relationships of midday mean NEE with narrow- and broad-band NDVI and SR, measured during and calculated for that same time window, respectively. The skill of broad-band NDVI and SR in predicting CO₂ fluxes was higher for metrics dominated by gross photosynthesis and lowest for ecosystem respiration, with NEE in between. A method based on a simple light response model whose parameters were parameterised based on broad-band NDVI allowed to improve predictions of daily NEE and is suggested to hold promise for filling gaps in the NEE time series. Relationships of CO₂ flux metrics with broad-band NDVI and SR however generally differed between the two studied grassland sites indicting an influence of additional factors not yet accounted for.

Identifying the Relationships between Water Quality and Land Cover Changes in the Tseng-Wen Reservoir Watershed of Taiwan

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Hone-Jay Chu

2013-01-01

Full Text Available The effects on water quality of land use and land cover changes, which are associated with human activities and natural factors, are poorly identified. Fine resolution satellite imagery provides opportunities for land cover monitoring and assessment. The multiple satellite images after typhoon events collected from 2001 to 2010 covering land areas and land cover conditions are evaluated by the Normalized Difference Vegetation Index (NDVI. The relationship between land cover and observed water quality, such as suspended solids (SS and nitrate-nitrogens (NO3-N, are explored in the study area. Results show that the long-term variations in water quality are explained by NDVI data in the reservoir buffer zones. Suspended solid and nitrate concentrations are related to average NDVI values on multiple spatial scales. Annual NO3-N concentrations are positively correlated with an average NDVI with a 1 km reservoir buffer area, and the SS after typhoon events associated with landslides are negatively correlated with the average NDVI in the entire watershed. This study provides an approach for assessing the influences of land cover on variations in water quality.

Investigation on the Patterns of Global Vegetation Change Using a Satellite-Sensed Vegetation Index

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Ainong Li

2010-06-01

Full Text Available The pattern of vegetation change in response to global change still remains a controversial issue. A Normalized Difference Vegetation Index (NDVI dataset compiled by the Global Inventory Modeling and Mapping Studies (GIMMS was used for analysis. For the period 1982–2006, GIMMS-NDVI analysis indicated that monthly NDVI changes show homogenous trends in middle and high latitude areas in the northern hemisphere and within, or near, the Tropic of Cancer and Capricorn; with obvious spatio-temporal heterogeneity on a global scale over the past two decades. The former areas featured increasing vegetation activity during growth seasons, and the latter areas experienced an even greater amplitude in places where precipitation is adequate. The discussion suggests that one should be cautious of using the NDVI time-series to analyze local vegetation dynamics because of its coarse resolution and uncertainties.

Analysis of teleconnections between AVHRR-based sea surface temperature and vegetation productivity in the semi-arid Sahel

DEFF Research Database (Denmark)

Huber Gharib, Silvia; Fensholt, Rasmus

2011-01-01

Vegetation Index (NDVI) in the Sahel, however with different magnitudes in terms of strength for the western, central and eastern Sahel. Also the correlations based on NDVI and global SST anomalies revealed the same East–West gradient, with a stronger association for the western than the eastern Sahel......, we achieved high correlations for SSTs of oceanic basins which are geographically associated to the climate indices yet by far not always these patterns were coherent. The detected SST–NDVI patterns could provide the basis to develop new means for improved forecasts in particular of the western...

Spatio-temporal approach to detecting land cover change using an extended kalman filter on modis time series data

CSIR Research Space (South Africa)

Kleynhans, W

2010-01-01

Full Text Available A method for detecting land cover change using NDVI timeseries data derived fromMODerate-resolution Imaging Spectroradiometer (MODIS) satellite data is proposed. The algorithm acts as a per pixel change alarm and takes as input the NDVI time...

Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA

Science.gov (United States)

Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can be achieved using the Normalized Difference Vegetation Index (NDVI), an indicator of greenness. However, distinguishing gradual shifts in NDVI (e.g. climate change) versus direct and ...

Integração de imagens NOAA/AVHRR: rede de cooperação para monitoramento nacional da safra de soja Integration of NOAA/AVHRR images: cooperation network towards national soybean crop monitoring

Directory of Open Access Journals (Sweden)

Anibal Gusso

2013-04-01

Full Text Available Uma avaliação inicial das condições do desenvolvimento da safra nacional, enquanto as plantas ainda estão nos campos, é altamente necessária para o cálculo correto das projeções na tomada de decisão e políticas relacionadas com o planejamento governamental e segurança alimentar. O objetivo deste trabalho foi avaliar a adequação dos dados NOAA/AVHRR (National Oceanic and Atmospheric Administration / Advanced Very High Resolution Radiometer em detectar mudanças nas condições da vegetação, devidas à ocorrência de estresse hídrico, na soja, por meio de uma combinação do índice NDVI (Normalized Difference Vegetation Index e da LST (Land Surface Temperature. Os dados LST e NDVI foram combinados e comparados pixel a pixel, sobre uma área de cultivo de soja, no Rio Grande do Sul. A relação teórica inversa prevista na combinação de LST e NDVI foi detectada. Foi observado que ocorre um aumento médio na LST em uma safra de ciclo normal (de 301,02 K para 308,36 K, quando comparada a uma safra sob condição de estresse hídrico, no desenvolvimento da cultura. Uma redução média do NDVI foi observada no ciclo normal (de 0,65 para 0,53, comparada com uma safra sob efeitos ocasionados pela estiagem no desenvolvimento da cultura. Foi observado maior correlação da produtividade municipal com LST (R2=0,78 do que com o NDVI (R2 = 0,59. Os resultados obtidos indicam que a integração de imagens do sensor AVHRR, proveniente de diferentes instituições, proporciona a adequada combinação espacial e temporal dos dados LST e NDVI, a fim de detectar a ocorrência de estresse hídrico, bem como sua intensidade, caracterizando as condições do ciclo de desenvolvimento da soja.An early assessment of national crop development conditions while the plants are still in the fields is highly needed to calculate correctly projections for decision-making and policies related to government planning and food security. The aim of this study

Anatomia do osso temporal de ovelhas sob aspectos didáticos Lambs' temporal bone anatomy under didactic aspects

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André Gurr

2011-02-01

Full Text Available É difícil encontrar ossos temporais humanos para o ensino de cirurgia otológica. Ossos temporais de ovelhas podem representar uma possível alternativa. MATERIAIS E MÉTODOS: Os ossos temporais de ovelhas foram dissecados em um programa convencional de dissecação de osso temporal no laboratório. Incluímos mastoidectomia, abordagens endaurais, mas também analisamos a aparência externa, o meato acústico externo e o hipotímpano. Algumas etapas são diferentes das preparações de ossos humanos. Os resultados morfométricos foram comparados à anatomia conhecida de humanos para verificar se o osso temporal de ovelhas seria utilizável para o ensino de cirurgia otológica. RESULTADOS: O osso temporal de ovelhas parece menor do que o humano. Encontramos uma área bolhosa se estendendo ao hipotímpano abaixo do meato acústico externo. A membrana timpânica é muito semelhante à humana. O meato acústico externo é menor e mais curto. A cadeia ossicular exibe analogias para com a humana. DISCUSSÃO: Esse estudo mostra que especificamente o ouvido médio, a membrana timpânica e o conduto auditivo externo são morfologicamente semelhantes às suas contrapartidas encontradas nos ossos temporais humanos. A ovelha parece ser um modelo viável para o ensino da anatomia do ouvido. A menor escala de algumas estruturas, especialmente dos componentes externos do osso temporal representa uma desvantagem. CONCLUSÕES: A ovelha parece representar uma alternativa viável no ensino de cirurgia otológica.Human temporal bones in teaching ear surgery are rare. The lamb's temporal bone might be a possible alternative. MATERIAL AND METHODS: Temporal bones of the lamb were dissected with a typical temporal bone lab drilling program. We included a mastoidectomy, endaural approaches, but also analyzed the outer appearance, the external ear canal and the hypotympanon. Some steps differed from preparation done in humans. The morphometric results were compared to

Analysis of meteorological variations on wheat yield and its estimation using remotely sensed data. A case study of selected districts of Punjab Province, Pakistan (2001-14

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Rafia Mumtaz

2017-10-01

Full Text Available Land management for crop production is an essential human activity that supports life on Earth. The main challenge to be faced by the agriculture sector in coming years is to feed the rapidly growing population while maintaining the key resources such as soil fertility, efficient land use, and water. Climate change is also a critical factor that impacts agricultural production. Among others, a major effect of climate change is the potential alterations in the growth cycle of crops which would likely lead to a decline in the agricultural output. Due to the increasing demand for proper agricultural management, this study explores the effects of meteorological variation on wheat yield in Chakwal and Faisalabad districts of Punjab, Pakistan and used normalised difference vegetation index (NDVI as a predictor for yield estimates. For NDVI data (2001-14, the NDVI product of Moderate Resolution Imaging spectrometer (MODIS 16-day composites data has been used. The crop area mapping has been realised by classifying the satellite data into different land use/land covers using iterative self-organising (ISO data clustering. The land cover for the wheat crop was mapped using a crop calendar. The relation of crop yield with NDVI and the impact of meteorological parameters on wheat growth and its yield has been analysed at various development stages. A strong correlation of rainfall and temperature was found with NDVI data, which determined NDVI as a strong predictor of yield estimation. The wheat yield estimates were obtained by linearly regressing the reported crop yield against the time series of MODIS NDVI profiles. The wheat NDVI profiles have shown a parabolic pattern across the growing season, therefore parabolic least square fit (LSF has been applied prior to linear regression. The coefficients of determination (R2 between the reported and estimated yield was found to be 0.88 and 0.73, respectively, for Chakwal and Faisalabad. This indicates that the

Estimation of different data compositions for early-season crop type classification.

Science.gov (United States)

Hao, Pengyu; Wu, Mingquan; Niu, Zheng; Wang, Li; Zhan, Yulin

2018-01-01

Timely and accurate crop type distribution maps are an important inputs for crop yield estimation and production forecasting as multi-temporal images can observe phenological differences among crops. Therefore, time series remote sensing data are essential for crop type mapping, and image composition has commonly been used to improve the quality of the image time series. However, the optimal composition period is unclear as long composition periods (such as compositions lasting half a year) are less informative and short composition periods lead to information redundancy and missing pixels. In this study, we initially acquired daily 30 m Normalized Difference Vegetation Index (NDVI) time series by fusing MODIS, Landsat, Gaofen and Huanjing (HJ) NDVI, and then composited the NDVI time series using four strategies (daily, 8-day, 16-day, and 32-day). We used Random Forest to identify crop types and evaluated the classification performances of the NDVI time series generated from four composition strategies in two studies regions from Xinjiang, China. Results indicated that crop classification performance improved as crop separabilities and classification accuracies increased, and classification uncertainties dropped in the green-up stage of the crops. When using daily NDVI time series, overall accuracies saturated at 113-day and 116-day in Bole and Luntai, and the saturated overall accuracies (OAs) were 86.13% and 91.89%, respectively. Cotton could be identified 40∼60 days and 35∼45 days earlier than the harvest in Bole and Luntai when using daily, 8-day and 16-day composition NDVI time series since both producer's accuracies (PAs) and user's accuracies (UAs) were higher than 85%. Among the four compositions, the daily NDVI time series generated the highest classification accuracies. Although the 8-day, 16-day and 32-day compositions had similar saturated overall accuracies (around 85% in Bole and 83% in Luntai), the 8-day and 16-day compositions achieved these

ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

Mapping the change of Phragmites australis live biomass in the lower Mississippi River Delta marshes

Science.gov (United States)

Ramsey, Elijah W.; Rangoonwala, Amina

2017-07-28

Multiyear remote sensing mapping of the normalized difference vegetation index (NDVI) was carried out as an indicator of live biomass composition of the Phragmites australis (hereafter Phragmites) marsh in the lower Mississippi River Delta (hereafter delta) from 2014 to 2017. Maps of NDVI change showed that the Phragmites condition was fairly stable between May 2014 and July 2015. From July 2015 to April 2016 NDVI change indicated Phragmites suffered a widespread decline in the live biomass proportion.  Between April and September 2016, most marsh remained unchanged from the earlier period or showed improvement; although there were pockets of continued decline scattered throughout the lower delta. From September 2016 to May 2017 a pronounced and widely exhibited decline in the condition of Phragmites marsh again occurred throughout the lower delta. This final NDVI change mapping supported field observations of Phragmites decline during the same period.

Mapping the Progression of Phytophthora Ramorum

Science.gov (United States)

Banh, T.; Li, J.; El-Askary, H. M.

2013-12-01

There has been a plant pathogen, Phytophthora Ramorum that has been causing trouble for the plant species in the forests of California and Oregon. Phytophthora is essentially a water mold that infects oak species like California black oak, coast live oak as well as California bay laurel (Lamsal). What this project aims to accomplish is to observe any changes in NDVI values between the years of 2002 and 1994. What the project hopes to observe is a decline of NDVI values between the two years because the infection of Phytophtora Ramorum will cause stress to the plant or kill the plant, which will lower the values of NDVI. The project will utilizes satellite data to create NDVI images over the study area and two types of change detection methods to observe the differences between the NDVI values of the two years. Preliminary results for the project, data obtained from Landsat 7 ETM+ with a resolution of 240 meters, was not able to observe any significant changes. A finer resolution to differentiate the NDVI values would be needed. In addition the best way to keep the pathogen from getting out of control is with ground level management, or complete eradication of the pathogen. These eradication methods include burning the infected host plants and spreading herbicide (Alexander). With that in mind it would be ideal to have an early detection of the pathogen infestation. Therefore another goal of the project is to continue to research if remote sensing could play a role in an early detection method for the presence of Phytophtora Ramorum.

Utilizing NASA Earth Observations to Enhance Flood Impact Products and Mitigation in the Lower Mekong Water Basin

Science.gov (United States)

Doyle, C.; Gao, M.; Spruce, J.; Bolten, J. D.; Weber, S.

2014-12-01

This presentation discusses results of a project to develop a near real time flood monitoring capability for the Lower Mekong Water Basin (LMB), the largest river basin in Southeast Asia and home to more than sixty million people. The region has seen rapid population growth and socio-economic development, fueling unsustainable deforestation, agricultural expansion, and stream-flow regulation. The basin supports substantial rice farming and other agrarian activities, which heavily depend upon seasonal flooding. But, floods due to typhoons and other severe weather events can result in disasters that cost millions of dollars and cause hardships to millions of people. This study uses near real time and historical Aqua and Terra MODIS 250-m resolution Normalized Difference Vegetation Index (NDVI) products to map flood and drought impact within the LMB. In doing so, NDVI change products are derived by comparing from NDVI during the wet season to a baseline NDVI from the dry season. The method records flood events, which cause drastic decreases in NDVI compared to non-flooded conditions. NDVI change product computation was automated for updating a near real-time system, as part of the Committee on Earth Observing Satellites Disaster Risk Management Observation Strategy. The system is a web-based 'Flood Dashboard that will showcase MODIS flood monitoring products, along with other flood mapping and weather data products. This flood dashboard enables end-users to view and assess a variety of geospatial data to monitor floods and flood impacts in near real-time, as well provides a platform for further data aggregation for flood prediction modeling and post-event assessment.

Analysis of Seasonal and Annual Change of Vegetation in the Indian Thar Desert Using Modis Data

Science.gov (United States)

Santra, P.; Chkraborty, A.

2011-09-01

The western part of India, specifically the dry region, will play an important role in determining the Indian monsoon and even global climate patterns. Drastically change in land use pattern of the region has been observed during last few decades. In this paper, an effort was made to track the seasonal as well as annual changes of vegetation pattern in Jaisalmer district using MODIS normalized difference vegetation index (NDVI) products. Apart from this, ground data on vegetation were also collected under vegetation carbon pool assessment programme of ISRO-IGBP. It was found that during the hot summer month of May, the area under NDVI class 0-0.1 is reduced from 98% during 2003 to 95% during 2009 with a simultaneous increase in area under NDVI class 0.1-0.2 from 2 to 5%. During the month of September, area under NDVI class 0.2-0.3 increased from almost negligible during May to 34-39% during normal or surplus rainfall year but only to 3% during a deficit year. From the ground data on vegetation biomass, it was found that Prosopis juliflora and Acacia senegal are the most abundant trees in Jaisalmer region of the desert. The sites with NDVI value ≥ 0.2 were mostly found with Prosopis juliflora tree. Among shrubs, the most abundant species was Calotropis procera and Zizyphus numularia. From this study, it has been found that MODIS NDVI products may be used to quickly assess the vegetation changes in response to rainfall as well as due to anthroprogenic interventions in desert.

Potential and limitations of using digital repeat photography to track structural and physiological phenology in Mediterranean tree-grass ecosystems

Science.gov (United States)

Luo, Yunpeng; EI-Madany, Tarek; Filippa, Gianluca; Carrara, Arnaud; Cremonese, Edoardo; Galvagno, Marta; Hammer, Tiana; Pérez-Priego, Oscar; Reichstein, Markus; Martín Isabel, Pilar; González Cascón, Rosario; Migliavacca, Mirco

2017-04-01

Tree-Grass ecosystems are global widely distributed (16-35% of the land surface). However, its phenology (especially in water-limited areas) has not yet been well characterized and modeled. By using commercial digital cameras, continuous and relatively vast phenology data becomes available, which provides a good opportunity to monitor and develop a robust method used to extract the important phenological events (phenophases). Here we aimed to assess the usability of digital repeat photography for three Tree-Grass Mediterranean ecosystems over two different growing seasons (Majadas del Tietar, Spain) to extract critical phenophases for grass and evergreen broadleaved trees (autumn regreening of grass- Start of growing season; resprouting of tree leaves; senescence of grass - End of growing season), assess their uncertainty, and to correlate them with physiological phenology (i.e. phenology of ecosystem scale fluxes such as Gross Primary Productivity, GPP). We extracted green chromatic coordinates (GCC) and camera based normalized difference vegetation index (Camera-NDVI) from an infrared enabled digital camera using the "Phenopix" R package. Then we developed a novel method to retrieve important phenophases from GCC and Camera-NDVI from various region of interests (ROIs) of the imagery (tree areas, grass, and both - ecosystem) as well as from GPP, which was derived from Eddy Covariance tower in the same experimental site. The results show that, at ecosystem level, phenophases derived from GCC and Camera-NDVI are strongly correlated (R2 = 0.979). Remarkably, we observed that at the end of growing season phenophases derived from GCC were systematically advanced (ca. 8 days) than phenophase from Camera-NDVI. By using the radiative transfer model Soil Canopy Observation Photochemistry and Energy (SCOPE) we demonstrated that this delay is related to the different sensitivity of GCC and NDVI to the fraction of green/dry grass in the canopy, resulting in a systematic

Estimativa de imagens solares soho através de redes neurais artificiais

Science.gov (United States)

Andrade, M. C.; Fernandes, F. C. R.; Cecatto, J. R.; Rios Neto, A.; Rosa, R. R.; Sawant, H. S.

2003-08-01

A Rede Neural Artificial (RNA), no âmbito da teoria computacional, constitui uma teoria emergente que, por possuir habilidade em aprender a partir de dados de entrada, encontra diferentes aplicações em diferentes áreas. Um exemplo é a utilização de RNA na caracterização de padrões associados à dinâmica de processos espaço-temporais relacionados a fenômenos físicos não-lineares. Para obter informações sobre o comportamento destes fenômenos físicos utiliza-se, em diversos casos, seqüências de imagens digitalizadas, onde a caracterização de alguns fenômenos espaço-temporais é o procedimento mais viável para descrever a dinâmica das regiões ativas do Sol. Com base em imagens observadas por telescópios a bordo de satélites, estudos de previsão de eventos solares podem ser programados, permitindo prever possíveis efeitos posteriores nas regiões mais próximas da Terra (tempestades geomagnéticas e irregularidades ionosféricas). Neste trabalho avaliamos o desempenho da RNA para estimar padrões espaço-temporais, ou seja, imagens solares em ultravioleta, obtidas através do telescópio a bordo do satélite SOHO. Os resultados mostraram que as RNA conseguem generalizar os padrões de maneira satisfatória sem perder de forma significativa os principais aspectos da configuração global da atmosfera solar, comprovando a eficácia da RNA como ferramenta para esse tipo de aplicação. Portanto, este trabalho comprova a viabilidade de uso desta ferramenta em projetos voltados ao estudo do comportamento solar, em trabalhos do grupo de Física do Meio Interplanetário (FMI) na DAS e em programas desenvolvidos pelo Núcleo de Simulação e Análise de Sistemas Complexos (NUSASC) do Laboratório Associado de Computação e Matemática Aplicada (LAC) do INPE.

Avaliação da função muscular em usuários de prótese total dupla = Evaluation of muscular function in wearers of double complete denture

Directory of Open Access Journals (Sweden)

Ferreira, Daniel Filgueiras

2006-01-01

Full Text Available O objetivo deste estudo foi avaliar, através da eletromiografia, o comportamento da atividade muscular resultante do uso da técnica Convencional para obtenção de equilíbrio em prótese total dupla. Doze pacientes totalmente edêntulos, livres de sinais e sintomas de disfunção temporomandibular com no mínimo cinco anos de uso de próteses totais, foram selecionados. Os pacientes tiveram suas próteses substituídas por novas próteses e o equilíbrio articular obtido através do estabelecimento de contatos interferentes entre dentes artificiais. O padrão da atividade eletromiográfica (EMG foi mensurado com o eletromiógrafo Myosystem Iâ (Prosecon Ltda nos músculos temporais (porção anterior e masseteres nas posições de repouso (R e na contração isométrica em máxima intercuspidação (CIMI, em quatro tempos: T0 – instalação; T1 – 1° mês; T2 – 2° mês; T3 – 3° mês de uso das próteses. O sinal eletromiográfico foi condicionado por um filtro digital passa faixa e analisado em relação a sua amplitude através do RMS (Root Mean Square. Observou-se pequenas alterações nos valores da atividade EMG dos músculos temporais e masseteres na posição de R. Na posição de CIMI os músculos temporais apresentaram valores finais menores que os iniciais, e situação inversa foi observada para os masseteres, com valores finais maiores que os iniciais. A análise dos dados através do teste de Friedman não mostrou diferenças estatísticamente significantes (p < 0. 05 entre os tempos avaliados. Conclui-se que a técnica Convencional, no período avaliado, não proporcionou equilíbrio dos músculos mastigatórios estudados

Preditores espaço-temporais do andar para testes de capacidade funcional em pacientes com doença de Parkinson Gait spatial and temporal predictors for functional capacity tests in Parkinson's disease patients

Directory of Open Access Journals (Sweden)

MDR Sánchez-Arias

2008-10-01

Full Text Available OBJETIVOS: Determinar quais parâmetros espaço-temporais são preditores do andar de indivíduos com doença de Parkinson idiopática para os testes de resistência aeróbia e agilidade, propostos pela bateria de testes da American Alliance for Health, Physical Education, Recreation and Dance (AAHPERD. MATERIAIS E MÉTODOS: Foram selecionados seis homens e seis mulheres com comprometimento e estágio da doença em níveis leve e moderado, que realizaram os testes de agilidade e resistência aeróbia, conforme o protocolo da AAHPERD, e andaram 8m sobre uma passarela. Uma câmera digital registrou uma passada central. Marcadores foram fixados no quinto metatarso e na face lateral do calcâneo do membro inferior direito e no primeiro metatarso e na face medial do calcâneo do membro inferior esquerdo. As variáveis dependentes selecionadas foram: tempo nos testes de agilidade e resistência e as variáveis cinemáticas (comprimento da passada - CP, cadência - CAD, duração da passada - DP, duração da fase de duplo suporte - DDS, duração do suporte simples - SS, duração da fase de balanço - DB e velocidade da passada - VP. RESULTADOS: Para agilidade, o teste de Pearson apontou correlação estatisticamente significativa entre as variáveis CP (r=-0,70; pOBJECTIVE: To determine which spatial and temporal parameters are predictors of the gait pattern of individuals with idiopathic Parkinson's disease, for the aerobic endurance and agility tests included in the battery of tests of the AAHPERD protocol. METHODS: Six men and six women with mild and moderate impairment and disease stage were selected. They performed agility and aerobic endurance test in accordance with the AAHPERD protocol, and walked 8 m on a walkway. A digital video camera recorded one central stride. Markers were attached to the fifth metatarsal and lateral face of the calcaneus of the right leg and to the first metatarsal and medial face of the calcaneus of the left leg. The

Identification and application of the valid wavelength bands for burnt area detection and fire severity classification using Landsat/TM data

International Nuclear Information System (INIS)

Maki, M.; Tamura, M.

2003-01-01

Firstly, by using Landsat Thematic Mapper (TM) imagery before and after forest fire, the valid wavelength bands for detecting burnt areas were examined and compared to NDVI. Secondly, by using the valid wavelength bands, mapping of burnt area and classification of fire severity were examined. The results show that (a) channel 4 and 7 were more sensitive than other channels for detecting burnt area, (b) BAI (Burnt Area Index) [(ch. 4-ch. 7)/(ch. 4+ch. 7)] was more useful than NDVI for detecting burnt areas, and (c) BAI imagery was more useful for classification of burn severity than NDVI imagery

Detecting the Land-Cover Changes Induced by Large-Physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis

Directory of Open Access Journals (Sweden)

Hone-Jay Chu

2009-08-01

Full Text Available The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS, sequential Gaussian simulation (SGS and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran’I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE. Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management.

Variation of Vegetation Ecological Water Consumption and Its Response to Vegetation Coverage Changes in the Rocky Desertification Areas in South China.

Science.gov (United States)

Wan, Long; Tong, Jing; Zhou, Jinxing; Guo, Hongyan; Cui, Ming; Liu, Yuguo; Ning, Like; Tang, Fukai

2016-01-01

Over the past several decades, rocky desertification has led to severe ecological problems in karst areas in South China. After a rocky desertification treatment project was completed, the vegetation coverage changed greatly and, consequently, increased the ecology water consumption (approximately equal to the actual evapotranspiration) of the regional vegetation. Thus, it intensified the regional water stresses. This study explored the changes in the actual evapotranspiration (ETa) response to the vegetation coverage changes in the rocky desertification areas in South China based on the precipitation (P), potential evapotranspiration (ETp) and NDVI (the normalized difference vegetation index) datasets. The revised Bagrov model was used to simulate the actual evapotranspiration changes with the supposed increasing NDVI. The results indicated that the average NDVI value was lower when the rocky desertification was more severe. The ETa, evapotranspiration efficiency (ETa/ETp) and potential humidity (P/ETp) generally increased with the increasing NDVI. The sensitivity of the ETa response to vegetation coverage changes varied due to different precipitation conditions and different rocky desertification severities. The ETa was more sensitive under drought conditions. When a drought occurred, the ETa exhibited an average increase of 40~60 mm with the NDVI increasing of 0.1 in the rocky desertification areas. Among the 5 different severity categories of rocky desertification, the ETa values' responses to NDVI changes were less sensitive in the severe rocky desertification areas but more sensitive in the extremely and potential rocky desertification areas. For example, with the NDVI increasing of 0.025, 0.05, 0.075, and 0.1, the corresponding ETa changes increased by an average of 2.64 mm, 10.62 mm, 19.19 mm, and 27.58 mm, respectively, in severe rocky desertification areas but by 4.94 mm, 14.99 mm, 26.80, and 37.13 mm, respectively, in extremely severe rocky

Disaggregating and mapping crop statistics using hypertemporal remote sensing

Science.gov (United States)

Khan, M. R.; de Bie, C. A. J. M.; van Keulen, H.; Smaling, E. M. A.; Real, R.

2010-02-01

Governments compile their agricultural statistics in tabular form by administrative area, which gives no clue to the exact locations where specific crops are actually grown. Such data are poorly suited for early warning and assessment of crop production. 10-Daily satellite image time series of Andalucia, Spain, acquired since 1998 by the SPOT Vegetation Instrument in combination with reported crop area statistics were used to produce the required crop maps. Firstly, the 10-daily (1998-2006) 1-km resolution SPOT-Vegetation NDVI-images were used to stratify the study area in 45 map units through an iterative unsupervised classification process. Each unit represents an NDVI-profile showing changes in vegetation greenness over time which is assumed to relate to the types of land cover and land use present. Secondly, the areas of NDVI-units and the reported cropped areas by municipality were used to disaggregate the crop statistics. Adjusted R-squares were 98.8% for rainfed wheat, 97.5% for rainfed sunflower, and 76.5% for barley. Relating statistical data on areas cropped by municipality with the NDVI-based unit map showed that the selected crops were significantly related to specific NDVI-based map units. Other NDVI-profiles did not relate to the studied crops and represented other types of land use or land cover. The results were validated by using primary field data. These data were collected by the Spanish government from 2001 to 2005 through grid sampling within agricultural areas; each grid (block) contains three 700 m × 700 m segments. The validation showed 68%, 31% and 23% variability explained (adjusted R-squares) between the three produced maps and the thousands of segment data. Mainly variability within the delineated NDVI-units caused relatively low values; the units are internally heterogeneous. Variability between units is properly captured. The maps must accordingly be considered "small scale maps". These maps can be used to monitor crop performance of

Tomografia computadorizada no diagnóstico da otosclerose fenestral

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Vicente Andy de Oliveira

2004-01-01

Full Text Available OBJETIVO: Identificar os principais achados tomográficos da otosclerose fenestral e avaliar a utilidade da tomografia computadorizada de alta resolução (TCAR, como método diagnóstico dessa osteodistrofia. FORMA DE ESTUDO: Estudo prospectivo multicêntrico com tomografia computadorizada (TC de ossos temporais. MATERIAL E MÉTODO: 54 pacientes com diagnóstico clínico e cirúrgico de otosclerose. Foi realizada uma análise tomográfica, em que foi avaliada a sensibilidade da TC no diagnóstico radiológico da otosclerose fenestral, sendo verificados os principais sítios de lesões dessa doença, como também a sua bilateralidade e simetria. Foram incluídos neste estudo 22 pacientes submetidos à TC de ossos temporais para investigação de outras afecções otológicas, que constituíram o grupo controle. RESULTADOS: A TC foi positiva em 87% dos pacientes (77% das orelhas. Os achados tomográficos foram bilaterais na maioria dos casos (78,7%, e o foco fenestral mais prevalente foi o foco anterior à janela oval (FAJO. CONCLUSÕES: A TC apresentou um alto índice de positividade e o FAJO foi o foco mais prevalente nessa população, podendo ser considerado um achado tomográfico altamente sugestivo de otosclerose.

Optical Cloud Pixel Recovery via Machine Learning

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Subrina Tahsin

2017-05-01

Full Text Available Remote sensing derived Normalized Difference Vegetation Index (NDVI is a widely used index to monitor vegetation and land use change. NDVI can be retrieved from publicly available data repositories of optical sensors such as Landsat, Moderate Resolution Imaging Spectro-radiometer (MODIS and several commercial satellites. Studies that are heavily dependent on optical sensors are subject to data loss due to cloud coverage. Specifically, cloud contamination is a hindrance to long-term environmental assessment when using information from satellite imagery retrieved from visible and infrared spectral ranges. Landsat has an ongoing high-resolution NDVI record starting from 1984. Unfortunately, this long time series NDVI data suffers from the cloud contamination issue. Though both simple and complex computational methods for data interpolation have been applied to recover cloudy data, all the techniques have limitations. In this paper, a novel Optical Cloud Pixel Recovery (OCPR method is proposed to repair cloudy pixels from the time-space-spectrum continuum using a Random Forest (RF trained and tested with multi-parameter hydrologic data. The RF-based OCPR model is compared with a linear regression model to demonstrate the capability of OCPR. A case study in Apalachicola Bay is presented to evaluate the performance of OCPR to repair cloudy NDVI reflectance. The RF-based OCPR method achieves a root mean squared error of 0.016 between predicted and observed NDVI reflectance values. The linear regression model achieves a root mean squared error of 0.126. Our findings suggest that the RF-based OCPR method is effective to repair cloudy pixels and provides continuous and quantitatively reliable imagery for long-term environmental analysis.

As variações na comunidade de Odonata (Insecta) em córregos podem ser explicadas pelo Paradoxo do Plâncton? Explicando a riqueza de espécies pela variabilidade ambiental

OpenAIRE

Oliveira Junior, José Max Barbosa; Universidade do Estado de Mato Grosso; Cabette, Helena Soares Ramos; Universidade do Estado de Mato Grosso; Pinto, Nelson Silva; Universidade Federal de Goiás; Juen, Leandro; Universidade Federal do Pará

2013-01-01

A teoria do Paradoxo do Plâncton postula que ambientes que apresentam flutuações temporais periódicas apresentariam alta diversidade de espécie, uma vez que essas flutuações impediriam a ocorrência da exclusão competitiva. Este trabalho teve como objetivo avaliar a variação da comunidade de Odonata adulto na Bacia do Rio Suiá-Miçú, testando a hipótese de que locais que apresentam variá...

Ecological Structure of a Tropical Urban Forest in the Bang Kachao Peninsula, Bangkok

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Montathip Sommeechai

2018-01-01

Full Text Available Rapid urbanization has changed the structure and function of natural ecosystems, especially floodplain ecosystems in SE Asia. The ecological structure of vegetation stands and the usefulness of satellite images was investigated to characterize a disturbed tropical urban forest located in the Chao Phraya River lower floodplain, Thailand. Nine sample plots were established on the Bang Kachao Peninsula (BKP within 4 tropical forest types in an urban area: rehabilitation forest, home-garden agroforestry, mangrove and park. The tree habitats were beach forest, swamp forest, moist evergreen forest, dry evergreen forest, mangrove forest and abandoned orchard or home-garden. Normalized difference vegetation index (NDVI values obtained from Landsat 7 satellite images were correlated with plant structure from field surveys. NDVI had the highest relationship with stand factors for number of families, number of species, Shannon-Weiner index and total basal area. Linear regression predicted well the correlation between NDVI and stand factors for families and basal area. NDVI trends reflected urban tropical forest typing and biodiversity, being high in rehabilitation and mangrove forests, moderate in home-gardens and low in parks. We suggest that the application of NDVI for assessments can be useful for future planning, monitoring and management of the BKP and hence may contribute for increasing biodiversity and complexity of these urban forests.

Response of heterogeneous vegetation to aerosol radiative forcing over a northeast Indian station.

Science.gov (United States)

Latha, R; Vinayak, B; Murthy, B S

2018-01-15

Importance of atmospheric aerosols through direct and indirect effects on hydrological cycle is highlighted through multiple studies. This study tries to find how much the aerosols can affect evapo-transpiration (ET), a key component of the hydrological cycle over high NDVI (normalized difference vegetation index)/dense canopy, over Dibrugarh, known for vast tea plantation. The radiative effects of aerosols are calculated using satellite (Terra-MODIS) and reanalysis data on daily and monthly scales. Aerosol optical depth (AOD) obtained from satellite and ground observations compares well. Aerosol radiative forcing (ARF), calculated using MERRA data sets of 'clean-clear radiation' and 'clear-radiation' at the surface, shows a lower forcing efficiency, 35 Wm -zs , that is about half of that of ground observations. As vegetation controls ET over high NDVI area to the maximum and that gets modified through ARF, a regression equation is fitted between ET, AOD and NDVI for this station as ET = 0.25 + (-84.27) × AOD + (131.51) × NDVI that explains 82% of 'daily' ET variation using easily available satellite data. ET is found to follow net radiation closely and the direct relation between soil moisture and ET is weak on daily scale over this station as it may be acting through NDVI. Copyright © 2017 Elsevier Ltd. All rights reserved.

Observational Quantification of Climatic and Human Influences on Vegetation Greening in China

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Wenjian Hua

2017-04-01

Full Text Available This study attempts to quantify the relative contributions of vegetation greening in China due to climatic and human influences from multiple observational datasets. Satellite measured vegetation greenness, Normalized Difference Vegetation Index (NDVI, and relevant climate, land cover, and socioeconomic data since 1982 are analyzed using a multiple linear regression (MLR method. A statistically significant positive trend of average growing-season (April–October NDVI is found over more than 34% of the vegetated areas, mainly in North China, while significant decreases in NDVI are only seen in less than 5% of the areas. The relationships between vegetation and climate (temperature, precipitation, and radiation vary by geographical location and vegetation type. We estimate the NDVI changes in association with the non-climatic effects by removing the climatic effects from the original NDVI time series using the MLR analysis. Our results indicate that land use change is the dominant factor driving the long-term changes in vegetation greenness. The significant greening in North China is due to the increase in crops, grasslands, and forests. The socioeconomic datasets provide consistent and supportive results for the non-climatic effects at the provincial level that afforestation and reduced fire events generally have a major contribution. This study provides a basis for quantifying the non-climatic effects due to possible human influences on the vegetation greening in China.

Canopy reflectance indices and its relationship with yield in common bean plants (Phaseolus vulgaris L.) with phosphorus supply

International Nuclear Information System (INIS)

Rodriguez, M.G.; Escalante-Estrada, J.A.; Gonzalez, M.T.R.; Reynolds, M.P.

2006-01-01

Common bean plants (Phaseolus vulgaris L.) were grown under three phosphorous levels (0,100 & 200 kg ha-1) and under rain fed conditions with the objective to examine the association between vegetative indices (NDVI, normalized difference vegetation index; and GNDVI, green normalized difference vegetation index) and intercepted radiation, leaf area index, biomass and yield during the growing season. The maximum intercepted radiation, leaf area index (LAI) and biomass were reached during the pod filling stage {80 days after sowing (DAS)}, and the P treatment of 200 kg ha-1 showed the highest values. The high intercepted radiation was derived from an increase in LAI inducing a major biomass accumulation. Near to physiological maturity LAI decreased as a result of leaf abscission. NDVI and GNDVI were higher with P supply than without P at anthesis and pod filling stage (50 - 80 DAS). Near to physiological maturity, NDVI and GNDVI decreased in all the treatments . When the maximum intercepted radiation, LAI, and biomass production were reached during anthesis and pod filling stage, NDVI and GNDVI also had the highest values. The association between the vegetative indices and seed yield during the pod filling stage showed a linear relationship by the P supply. The relationship between GNDVI and seed yield was higher (r2 = 0.77) than the relationship between NDVI and seed yield (r2 = 0.61)

Tropical forest biomass and successional age class relationships to a vegetation index derived from Landsat TM data

Science.gov (United States)

Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, Armond T.

1989-01-01

Forest stand structure and biomass data were collected using conventional forest inventory techniques in tropical, subtropical, and warm temperate forest biomes. The feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated. The Normalized Difference Vegetation Index (NDVI) calculated from Landsat-TM data were not significantly correlated with forest regeneration age classes in the mountain terrain of the Luquillo Experimental Forest, Puerto Rico. The low sun angle and shadows cast on steep north and west facing slopes reduced spectral reflectance values recorded by TM orbital altitude. The NDVI, calculated from low altitude aircraft scanner data, was significatly correlated with forest age classes. However, analysis of variance suggested that NDVI differences were not detectable for successional forests older than approximately 15-20 years. Also, biomass differences in young successional tropical forest were not detectable using the NDVI. The vegetation index does not appear to be a good predictor of stand structure variables (e.g., height, diameter of main stem) or total biomass in uneven age, mixed broadleaf forest. Good correlation between the vegetation index and low biomass in even age pine plantations were achieved for a warm temperate study site. The implications of the study for the use of NDVI for forest structure and biomass estimation are discussed.

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA

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Boyte, Stephen; Wylie, Bruce K.; Rigge, Matthew B.; Dahal, Devendra

2018-01-01

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.

Important Value of Economic Potency Mangrove Using NDVI Satellite High Resolution Image To Support Eco Tourism Of Pamurbaya Area (Case Study: East Cost of Surabaya)

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Sukojo, B. M.; Hidayat, H.; Ratnasari, D.

2017-12-01

Indonesia is a vast maritime country; many mangrove conservations is found around coastal areas of Indonesia. Mangroves support the life of a large number of animal species by providing breeding, spawning and feeding. Mangrove forests as one of the unique ecosystems are potential natural resources, supporting the diversity of flora and fauna of terrestrial aquatic communities that directly or indirectly play an important role for human life in economic, social and environmental terms. East Coast Surabaya is an area with the most extensive and diverse mangrove ecosystems along the coast of Surabaya. Currently Pamurbaya used as a recreational object or nature tourism called eco tours. Utilization of mangrove ecosystem as a place of this eco tour bring positive impact on economic potency around pamurbaya area. So, to know the value of the economic potential of mangrove ecosystems for support of nature tourism Pamurbaya region needs to study mapping mangrove ecosystem conditions in the East Coast area of Surabaya. Mapping of mangrove conditions can use remote sensing technology by utilizing satellite image data with high resolution. Data used for mapping mangrove ecosystem conditions on the east coast of Surabaya are high resolution satellite image data of Pleiades 1A and field observation data such as Ground Control Point, soil spectral parameters and water quality. From satellite image data will be classification of mangrove vegetation canopy classification using NDVI vegetation index method using algorithm formula which then will be tested correlation with field observation data on reflectant value of field and water quality parameter. The purpose of this research is to know the condition of mangrove ecosystem to know the economic potential of mangrove ecosystem in supporting Pamurbaya nature tourism. The expected result of this research is the existence of basic geospatial information in the form of mangrove ecosystem condition map. So that can be used as decision

Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

Science.gov (United States)

Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

2014-03-01

In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

Upscaling from leaf to canopy chlorophyll/carotenoid pigment based vegetation indices reveal phenology of photosynthesis in temperate evergreen and deciduous trees

Science.gov (United States)

Wong, C. Y.; Bhathena, Y.; Arain, M. A.; Ensminger, I.

2017-12-01

Optically derived vegetation indices have been developed to provide information about plant status including photosynthetic activity. They reflect changes in leaf pigments, which vary seasonally in pigment composition, enabling them to be used as a proxy of photosynthetic phenology. Important pigments in photosynthetic activity are carotenoids and chlorophylls, which are associated with light harvesting and energy dissipation. In temperate forests, which consist of deciduous and evergreen trees, there are difficulties resolving evergreen phenology using the most widely used index, the normalized difference vegetation index (NDVI). NDVI works well in deciduous trees, which exhibit a "visible" phenological process of leaf growth in the spring, and leaf senescence and abscission in the autumn. Evergreen conifers stay green year-round and utilize "invisible" changes of overwintering pigment composition that NDVI cannot resolve, so carotenoid pigment sensitive vegetation indices have been suggested for evergreens. The aim of this study was to evaluate carotenoid based vegetation indices over the chlorophyll sensitive NDVI. For this purpose, we evaluated the greenness index, NDVI, and carotenoid pigment sensitive indices: photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI) in red maple, white oak and eastern white pine for two years. We also measured leaf gas exchange and pigment concentrations. We observed that NDVI correlated with photosynthetic activity in deciduous trees, whereas PRI and CCI correlated with photosynthesis across both evergreen and deciduous trees. This pattern was consistent, upscaling from leaf- to canopy-scales indicating that the mechanisms involved in winter acclimation can be resolved at larger spatial scales. PRI and CCI detected seasonal changes in carotenoids and chlorophylls linked to photoprotection and are suitable as a proxy of photosynthetic activity. These findings have implications to improve our use and

Regional urban area extraction using DMSP-OLS data and MODIS data

International Nuclear Information System (INIS)

Zhang, X Y; Cai, C; Li, P J

2014-01-01

Stable night lights data from Defense Meteorological Satellite Program (DMSP) Operational Line-scan System (OLS) provide a unique proxy for anthropogenic development. This paper proposed two new methods of extracting regional urban extents using DMSP-OLS data, MODIS NDVI data and Land Surface Temperature (LST) data. MODIS NDVI data were used to reduce the over-glow effect, since urban areas generally have lower vegetation index values than the surrounding areas (e.g. agricultural and forest areas). On the other hand, urban areas generally show higher surface temperatures than the surrounding areas. Since urban area is the only class of interest, a one-class classifier, the One-Class Support Vector Machine (OCSVM), was selected as the classifier. The first method is classification of different data combinations for mapping: (1) OLS data and NDVI data, (2) OLS data and LST data, and (3) OLS data, NDVI data and LST data combined. The second one is a morphological reconstruction based method which combines classification results from OLS plus NDVI data and from OLS plus LST data. In the morphological reconstruction based method, the classification result using OLS and NDVI data was used as a mask image, while the classification result using OLS and LST data was used as a marker image. The north China area covering 14 provinces was selected as study area. Classification results from Landsat TM/ETM+ data from selected areas with different development levels were used as reference data to validate the proposed methods. The results show that the proposed methods effectively reduced the over-glow effect caused by DSMP-OLS data and achieved better results compared to the results from the traditional thresholding technique. The combination of all three datasets produces more accurate results than those of using any two datasets. The proposed morphological reconstruction based method achieves the best result in urban extent mapping

Multi model and data analysis of terrestrial carbon cycle in Asia: From 2001 to 2006

Science.gov (United States)

Ichii, K.; Takahashi, K.; Suzuki, T.; Ueyama, M.; Sasai, T.; Hirata, R.; Saigusa, N.

2009-12-01

Accurate monitoring and modeling of the current status and their causes of interannual variations in terrestrial carbon cycle are important. Recently, many studies analyze using multiple methods (e.g. satellite data and ecosystem models) to clarify the underlain mechanisms and recent trend since each single methodology contains its own biases. The multi-model and data ensemble approach is a powerful method to clarify the current status and their underlain mechanisms. So far, many studies using multiple sources of data and models are conducted in North America, Europe, Africa, Amazon, and Japan, however, studies in monsoon Asia are lacking. In this study, we analyzed interannual variations in terrestrial carbon cycles in monsoon Asia, and evaluated current capability of remote sensing and ecosystem model to capture them based on multiple model and data sources; flux observations, remote sensing (e.g. MODIS, AVHRR, and VGT), and ecosystem models (e.g. SVM, BEAMS, CASA, Biome-BGC, LPJ, and TRIFFID). The satellite observation and ecosystem models show clear characteristics in interannual variabilities in satellite-based NDVI and model-based GPP. These are characterized by (1) spring NDVI and modeled GPP anomalies related to temperature anomaly in mid and high latitudinal areas (positive anomalies in 2002 and 2005 and negative one in 2006), (2) NDVI and GPP anomalies in southeastern and central Asia related to precipitation (e.g. India from 2003-2006), and (3) summer NDVI and GPP anomalies in 2003 related to strong anomalies in solar radiations. NDVI anomalies related to radiation ones (2003 summer) were not accurately captured by terrestrial ecosystem models. For example, LPJ model rather shows GPP positive anomalies in Far East Asia regions probably caused by positive precipitation anomalies. Further analysis requires improvement of models to reproduce more consistent spatial patterns in NDVI anomaly, and longer term analysis (e.g. after 1982).

Satellite Monitoring for Early Warning and Triggering Disaster Risk Financing in Uganda

Science.gov (United States)

Nakalembe, C. L.; Owor, M.

2016-12-01

Natural disasters typically occur with little warning and can have grave and long-lasting negative consequences especially for populations fully dependent on rainfed agriculture. Disaster risk financing (DRF) aims to scale up alternative livelihoods such as Labour Intensive Public Works (LIPW) when a disaster hits to minimize the likely impacts on communities. In data-rich regions triggering DRF or crop insurances payouts can be easily implemented e.g in the case of agriculture, yield losses due to drought can be measured directly. This is constrained in Uganda, because seasonal/annual production data are scarce due to the subsistence and smallholder nature of agriculture in addition to low capacity for data collection and analysis in the country. Satellite remote sensing based indices, in particular the Normalized Difference Vegetation Index (NDVI), provides an objective and dependable solution to this challenge. Using MODIS satellite imagery provided through the GLAM East-Africa portal (Global Agricultural Monitoring system adapted for East-Africa) for obtaining NDVI time-series in near real-time, the Office of the Prime Minister of Uganda (OPM) is designing an operational crop conditions monitoring system in support of its recently initiated DRF Project, under the Third Northern Uganda Social Action Fund (NUSAF 2). The basis for triggering the DRF mechanism under this project is the deviation from the long-term NDVI (NDVI Anomaly data) within the growing season beyond a defined threshold. The NDVI data that are preprocessed in the GLAM system offer spatially explicit information on vegetation and crop conditions forming an adequate base for assessing generalized growing season conditions and enabling the quick implementation of DRF using transparent and objective criteria. The system and criteria serve also as an early-warning mechanism as the NDVI anomaly approaches the triggering threshold allowing time for planning and implementing LIPW projects.

Vegetation Cover Analysis in Shaanxi Province of China Based on Grid Pixel Ternd Analysis and Stability Evaluation

Science.gov (United States)

Yue, H.; Liu, Y.

2018-04-01

As a key factor affecting the biogeochemical cycle of human existence, terrestrial vegetation is vulnerable to natural environment and human activities, with obvious temporal and spatial characteristics. The change of vegetation cover will affect the ecological balance and environmental quality to a great extent. Therefore, the research on the causes and influencing factors of vegetation cover has become the focus of attention of scholars at home and abroad. In the evolution of human activities and natural environment, the vegetation coverage in Shaanxi has changed accordingly. Using MODIS/NDVI 2000-2014 time series data, using the method of raster pixel trend analysis, stability evaluation, rescaled range analysis and correlation analysis, the climatic factors in Shaanxi province were studied in the near 15 years vegetation spatial and temporal variation and influence of vegetation NDVI changes. The results show that NDVI in Shaanxi province in the near 15 years increased by 0.081, the increase of NDVI in Northern Shaanxi was obvious, and negative growth was found in some areas of Guanzhong, southern Shaanxi NDVI overall still maintained at a high level; the trend of vegetation change in Shaanxi province has obvious spatial differences, most of the province is a slight tendency to improve vegetation, there are many obvious improvement areas in Northern Shaanxi Province. Guanzhong area vegetation area decreased, the small range of variation of vegetation in Shaanxi province; the most stable areas are mainly concentrated in the southern, southern Yanan, Yulin, Xi'an area of Weinan changed greatly; Shaanxi Province in recent 15 a, the temperature and precipitation have shown an increasing trend, and the vegetation NDVI is more closely related to the average annual rainfall, with increase of 0.48 °C/10 years and 69.5 mm per year.

Short-Term Impacts of the Air Temperature on Greening and Senescence in Alaskan Arctic Plant Tundra Habitats

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Jeremy L. May

2017-12-01

Full Text Available Climate change is warming the temperatures and lengthening the Arctic growing season with potentially important effects on plant phenology. The ability of plant species to acclimate to changing climatic conditions will dictate the level to which their spatial coverage and habitat-type dominance is different in the future. While the effect of changes in temperature on phenology and species composition have been observed at the plot and at the regional scale, a systematic assessment at medium spatial scales using new noninvasive sensor techniques has not been performed yet. At four sites across the North Slope of Alaska, changes in the Normalized Difference Vegetation Index (NDVI signal were observed by Mobile Instrumented Sensor Platforms (MISP that are suspended over 50 m transects spanning local moisture gradients. The rates of greening (measured in June and senescence (measured in August in response to the air temperature was estimated by changes in NDVI measured as the difference between the NDVI on a specific date and three days later. In June, graminoid- and shrub-dominated habitats showed the greatest rates of NDVI increase in response to the high air temperatures, while forb- and lichen-dominated habitats were less responsive. In August, the NDVI was more responsive to variations in the daily average temperature than spring greening at all sites. For graminoid- and shrub-dominated habitats, we observed a delayed decrease of the NDVI, reflecting a prolonged growing season, in response to high August temperatures. Consequently, the annual C assimilation capacity of these habitats is increased, which in turn may be partially responsible for shrub expansion and further increases in net summer CO2 fixation. Strong interannual differences highlight that long-term and noninvasive measurements of such complex feedback mechanisms in arctic ecosystems are critical to fully articulate the net effects of climate variability and climate change on

A comparison of multi-resource remote sensing data for vegetation indices

International Nuclear Information System (INIS)

Cao, Liqin; Wei, Lifei; Liu, Tingting

2014-01-01

With the development of the satellite sensor, multi-resource observation systems have become widely used. However, there is a huge difference between quantitative remote sensing products because of the different sensing observations and the quantitative retrieval algorithms. In this paper, the quantitative relationships between the normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) and the vegetation index based on the universal pattern decomposition method (VIUPD) of Landsat ETM+ and ASTER sensors are investigated. The difference in observations was examined between the two sensors, based on a pair of images. The results showed that: 1) There was a strong correlation between the different vegetation indices for the same sensor, with the coefficient of determination being greater than 0.9. 2) Whether for ASTER or Landsat, the information of VIUPD was richer than that of NDVI and SAVI. Furthermore, in dense vegetation areas, the values of NDVI and SAVI could easily reach saturation. 3) The values of SAVI were higher than NDVI in the areas of water or bare soil, while this was the opposite in areas of lush vegetation

Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

Science.gov (United States)

Boken, Vijendra K.; Easson, Gregory L.; Rowland, James

2010-01-01

The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R 2. The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

Sienogranitos leucocráticos do Domínio Macururé, Sistema Orogênico Sergipano, Nordeste do Brasil: Stock Glória Sul

Directory of Open Access Journals (Sweden)

Joane Almeida da Conceição

Full Text Available RESUMO: O Stock Glória Sul (SGS (41 km2 é arredondado e intrusivo na parte central do Domínio Macururé, no Sistema Orogênico Sergipano (SOS. Internamente o Stock é formado por vários tipos de sienogranitos leucocráticos (biotita sienogranito, sienogranito com muscovita e biotita e muscovita sienogranito. Os biotita sienogranitos apresentam abundância de enclaves máficos microgranulares que correspondem a sienitos e são ocasionais nos sienogranitos com muscovita e biotita. Os sienogranitos são metaluminosos, com termos mais evoluídos peraluminosos, posicionando-se no campo dos granitos do tipo I e exibem assinatura geoquímica cálcio-alcalino de alto K2O. Os enclaves sieníticos são metaluminosos e exibem assinatura shoshonítica. Os dados geoquímicos sugerem que as diferentes rochas presentes no SGS podem ser explicadas como produto da mistura entre um magma fortemente diferenciado e peraluminoso (≈ 73% SiO2 com outro máfico shoshonítico (≈ 56% SiO2, representado pelos enclaves. Os valores dos elementos traços são mais elevados nos enclaves do que nos granitos, tais como Ba (1.179 - 319 ppm, Rb (351 - 55,3 ppm, Y (16,7 - 1,6 ppm. Os padrões de elementos terras raras mostram variação de ∑38,58 - 299,21 ppm, LaN/YbN 12,57 - 137,22 e Eu/Eu* 0,72 - 1,94. O SGS, ante aos resultados obtidos neste estudo, evidencia que a granitogênese no Domínio Macururé (DM é complexa e que os sienogranitos leucocráticos que ocorrem bem distribuídos nesse domínio são pós-tectônicos e representam o produto de interação entre magmas riolíticos peraluminosos com magmas mantélicos shoshoníticos.

Biophysical remote sensing and terrestrial CO2 exchange at Cape Bounty, Melville Island

Science.gov (United States)

Gregory, Fiona Marianne

Cape Bounty, Melville Island is a partially vegetated High Arctic landscape with three main plant communities: polar semi-desert (47% of the study area), mesic tundra (31%) , and wet sedge meadows (7%). The objective of this research was to relate biophysical measurements of soil, vegetation, and CO2 exchange rates in each vegetation type to high resolution satellite data from IKONOS-2, extending plot level measurements to a landscape scale. Field data was collected through six weeks of the 2008 growing season. Two IKONOS images were acquired, one on July 4th and the other on August 2nd. Two products were generated from the satellite data: a land-cover classification and the Normalized Difference Vegetation Index (NDVI). The three vegetation types were found to have distinct soil and vegetation characteristics. Only the wet sedge meadows were a net sink for CO2; soil respiration tended to exceed photosynthesis in the sparsely vegetated mesic tundra and polar semi-desert. Scaling up the plot measurements by vegetation type area suggested that Cape Bounty was a small net carbon source (0.34 +/- 0.47 g C m-2 day-1) in the summer of 2008. NDVI was strongly correlated with percent vegetation cover, vegetation volume, soil moisture, and moderately with soil nitrogen, biomass, and leaf area index (LAI). Photosynthesis and respiration of CO2 both positively correlated with NDVI, most strongly when averaged over the season. NDVI increased over time in every vegetation type, but this change was not reflected in any significant measured changes in vegetation or CO2 flux rates. A simple spatial model was developed to estimate Net Ecosystem Exchange (NEE) at every pixel on the satellite images based on NDVI, temperature and incoming solar radiation. It was found that the rate of photosynthesis per unit NDVI was higher early in the growing season. The model estimated a mean flux to the atmosphere of 0.21 g C m-2 day-1 at the time of image acquisition on July 4th, and -0.07 g C m

Springs as hydrologic refugia in a changing climate? A remote sensing approach

Science.gov (United States)

Cartwright, Jennifer M.; Johnson, Henry M.

2018-01-01

Spring‐fed wetlands are ecologically important habitats in arid and semi‐arid regions. Springs have been suggested as possible hydrologic refugia from droughts and climate change; however, springs that depend on recent precipitation or snowmelt for recharge may be vulnerable to warming and drought intensification. Springs that are expected to maintain their ecohydrologic function in a warmer, drier climate may be priorities for conservation and restoration. Identifying such springs is difficult because many springs lack hydrologic records of adequate temporal extent and resolution to assess their resilience to water cycle changes. This study demonstrates proof‐of‐concept for the assessment of certain spring types (i.e., helocrene, hypocrene, and hillslope springs) in terms of hydrologic and ecological resilience to climatic water stress using freely available remote‐sensing and climate data. We used the Normalized Difference Vegetation Index (NDVI) from 1985 through 2011 to delineate surface‐moisture zones (SMZs) associated with 39 clusters of 172 springs in a montane sage‐steppe landscape in southeastern Oregon, USA. We developed and synthesized seven NDVI‐based indicators of SMZ resilience to interannual changes in water availability: (1) mean and (2) standard deviation of July NDVI; (3) mean difference in July NDVI and (4) difference in coefficient of variation for July NDVI between each SMZ and its surrounding watershed; (5) response of SMZ July NDVI to 90‐day antecedent precipitation; (6) response of SMZ July NDVI to the previous winter's snowpack; and (7) range of NDVI values from an exceptionally wet year followed by three dry years. Because all resilience indicators were highly inter‐correlated, we derived an overall metric of SMZ resilience using principal components analysis that accounted for 66% of total variance. This overall resilience score was positively correlated with SMZ elevation, slope, mean annual precipitation, and with

O direito à privacidade do trabalhador no ordenamento jurídico português

OpenAIRE

Mori, Amaury Haruo

2009-01-01

Tese de mestrado, Ciências Jurídicas, Faculdade de Direito, Universidade de Lisboa, 2010 O trabalho tem por objetivo analisar o direito à privacidade do trabalhador à luz do ordenamento jurídico português. A investigação está fundamentada em estudos doutrinários já realizados sobre o tema, a partir dos quais procura identificar o conceito de privacidade como bem juridicamente protegido pelo direito do trabalho em Portugal. Fatores culturais, sociais, temporais e pessoais dificultam a taref...

Normalized difference vegetation index for the South American continent used as a climatic variability indicator

International Nuclear Information System (INIS)

Liu, W.T.; Massambani, O.; Festa, M.

1992-01-01

The NOAA AVHRR GAC data set was used to produce Normalized Difference Vegetation Index (NDVI) maps for the South American Continent covering the period from August 1, 1981 to June 30, 1987. A 15-day maximum value composite procedure was used to partially eliminate the cloud contamination and atmospheric attenuation. Monthly evolution of NDVI for a dry and a wet year within the period studied was used to estimate the area covered by NDVI value less than 0.223, This value was used as an indicator of the drought area and the delineation of the Low rainfall areas in the continent. It was observed a well defined regional dependence of the drought area variability for the Northeast, Southwest and Northwest continent and also for the Amazon region. It is shown a relative estimation of the area coverage with NDVI less than 0.223 for the years 1982/83 and 1984/85. The dynamics of the drought area evolution in the continent is discussed. It is also presented a diagnosis of regional variability of the continental distribution of drought area from 1981 to 1987 for the months of May and September. This information is also used to discuss its relationship with the EL-Nino-Southern Oscillation (ENSO) and the South American Precipitation patterns during this period. It is suggested that the use of NDVI image to identify the dynamics of the drought induced by low rainfall may provide us valuable information to study the large scale climatic variation

Potential of VIIRS Data for Regional Monitoring of Gypsy Moth Defoliation: Implications for Forest Threat Early Warning System

Science.gov (United States)

Spruce, Joseph P.; Ryan, Robert E.; Smoot, James C.; Prados, Donald; McKellip, Rodney; Sader. Steven A.; Gasser, Jerry; May, George; Hargrove, William

2007-01-01

A NASA RPC (Rapid Prototyping Capability) experiment was conducted to assess the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) data for monitoring non-native gypsy moth (Lymantria dispar) defoliation of forests. This experiment compares defoliation detection products computed from simulated VIIRS and from MODIS (Moderate Resolution Imaging Spectroradiometer) time series products as potential inputs to a forest threat EWS (Early Warning System) being developed for the USFS (USDA Forest Service). Gypsy moth causes extensive defoliation of broadleaved forests in the United States and is specifically identified in the Healthy Forest Restoration Act (HFRA) of 2003. The HFRA mandates development of a national forest threat EWS. This system is being built by the USFS and NASA is aiding integration of needed satellite data products into this system, including MODIS products. This RPC experiment enabled the MODIS follow-on, VIIRS, to be evaluated as a data source for EWS forest monitoring products. The experiment included 1) assessment of MODIS-simulated VIIRS NDVI products, and 2) evaluation of gypsy moth defoliation mapping products from MODIS-simulated VIIRS and from MODIS NDVI time series data. This experiment employed MODIS data collected over the approximately 15 million acre mid-Appalachian Highlands during the annual peak defoliation time frame (approximately June 10 through July 27) during 2000-2006. NASA Stennis Application Research Toolbox software was used to produce MODIS-simulated VIIRS data and NASA Stennis Time Series Product Tool software was employed to process MODIS and MODIS-simulated VIIRS time series data scaled to planetary reflectance. MODIS-simulated VIIRS data was assessed through comparison to Hyperion-simulated VIIRS data using data collected during gypsy moth defoliation. Hyperion-simulated MODIS data showed a high correlation with actual MODIS data (NDVI R2 of 0.877 and RMSE of 0.023). MODIS-simulated VIIRS data for the same