[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.

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).

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

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

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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

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

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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.

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.

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

Using NDVI to measure precipitation in semi-arid landscapes

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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.

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

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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.

[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.

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

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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

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

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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.

Sensitivity of Climate to Changes in NDVI

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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

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

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

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

2014-10-01

associated with EOST; MAXN (Maximum NDVI) which corresponds to the maximum NDVI value; MAXT (Time of Maximum) which is the day associated with MAXN; DUR (Duration) defined as the number of days between SOST and EOST; and AMP (Amplitude) which is the difference between MAXN and SOSN. This application provides all these metrics in a single step. Initially, the data points are interpolated using a moving average graphic with five and three points. The eight metrics previously described are then obtained from the spline using numpy functions. In the present work, the developed toolbar was applied to MODerate resolution Imaging Spectroradiometer (MODIS) data covering a particular region of Portugal, which can be generally applied to other satellite data and study area. The code is open and can be modified according to the user requirements. Other advantage in publishing the plug-ins and the application code is the possibility of other users to improve this application.

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.

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.

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.

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.

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.

Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique

Directory of Open Access Journals (Sweden)

Daniel Maposa

2016-05-01

Full Text Available In this article we fit a time-dependent generalised extreme value (GEV distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1, annual 2-day maximum (AM2, annual 5-day maximum (AM5, annual 7-day maximum (AM7, annual 10-day maximum (AM10 and annual 30-day maximum (AM30. Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate. Keywords: nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value

Bayesian Method for Building Frequent Landsat-Like NDVI Datasets by Integrating MODIS and Landsat NDVI

OpenAIRE

Limin Liao; Jinling Song; Jindi Wang; Zhiqiang Xiao; Jian Wang

2016-01-01

Studies related to vegetation dynamics in heterogeneous landscapes often require Normalized Difference Vegetation Index (NDVI) datasets with both high spatial resolution and frequent coverage, which cannot be satisfied by a single sensor due to technical limitations. In this study, we propose a new method called NDVI-Bayesian Spatiotemporal Fusion Model (NDVI-BSFM) for accurately and effectively building frequent high spatial resolution Landsat-like NDVI datasets by integrating Moderate Resol...

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

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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.

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

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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). ...

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.

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

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

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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.

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

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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

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...

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

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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.

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

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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.

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

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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.

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

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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.

Explaining NDVI trends in northern Burkina Faso

DEFF Research Database (Denmark)

Rasmussen, Kjeld; Fensholt, Rasmus; Fog, Bjarne

2014-01-01

by a distinct spatial pattern and strongly dominated by negative trends in Normalized Difference Vegetation Index (NDVI). The aim of the paper is to explain this distinct pattern. When studied over the period 2000–2012, using NDVI data from the MODIS sensor the spatial pattern of NDVI trends indicates that non......-climatic factors are involved. By relating NDVI trends to landscape elements and land use change we demonstrate that NDVI trends in the north-western parts of the study area are mostly related to landscape elements, while this is not the case in the south-eastern parts, where rapidly changing land use, including....... expansion of irrigation, plays a major role. It is inferred that a process of increased redistribution of fine soil material, water and vegetation from plateaus and slopes to valleys, possibly related to higher grazing pressure, may provide an explanation of the observed pattern of NDVI trends. Further work...

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.

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

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Yuhan Rao

2015-06-01

Full Text Available 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 blending MODIS NDVI time-series data and multi-temporal Landsat TM/ETM+ images. This method firstly unmixes the NDVI temporal changes in MODIS time-series to different land cover types and then uses unmixed NDVI temporal changes to predict Landsat-like NDVI dataset. The test over a forest site shows high accuracy (average difference: −0.0070; average absolute difference: 0.0228; and average absolute relative difference: 4.02% and computation efficiency of NDVI-LMGM (31 seconds using a personal computer. Experiments over more complex landscape and long-term time-series demonstrated that NDVI-LMGM performs well in each stage of vegetation growing season and is robust in regions with contrasting spatial and spatial variations. Comparisons between NDVI-LMGM and current methods (i.e., Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM, Enhanced STARFM (ESTARFM and Weighted Linear Model (WLM show that NDVI-LMGM is more accurate and efficient than current methods. The proposed method will benefit land surface process research, which requires a dense NDVI time-series dataset with high spatial resolution.

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

MODIS NDVI Response Following Fires in Siberia

Science.gov (United States)

Ranson, K. Jon; Sun, G.; Kovacs, K.; Kharuk, V. I.

2003-01-01

The Siberian boreal forest is considered a carbon sink but may become an important source of carbon dioxide if climatic warming predictions are correct. The forest is continually changing through various disturbance mechanisms such as insects, logging, mineral exploitation, and especially fires. Patterns of disturbance and forest recovery processes are important factors regulating carbon flux in this area. NASA's Terra MODIS provides useful information for assessing location of fires and post fire changes in forests. MODIS fire (MOD14), and NDVI (MOD13) products were used to examine fire occurrence and post fire variability in vegetation cover as indicated by NDVI. Results were interpreted for various post fire outcomes, such as decreased NDVI after fire, no change in NDVI after fire and positive NDVI change after fire. The fire frequency data were also evaluated in terms of proximity to population centers, and transportation networks.

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.

At site and regional analysis of maximum annual and seasonal discharges and precipitation depths in the upper Hron region

International Nuclear Information System (INIS)

Kohnova, S.; Hlavcova, K.

2004-01-01

In this presentation authors deal with the regional analysis of maximum annual and seasonal discharges and precipitation depths in the upper Hron region (Slovak Republic). This work has two objectives: (1) At site and regional analysis of annual and seasonal maximum design discharges in the upper Hron region; (2) Analysis of annual and seasonal maximum design precipitations in the connection of extreme runoff condition in the upper Hron region

TREE AGE AS ADJUSTMENT FACTOR TO NDVI

OpenAIRE

Elias Fernando Berra; Denise Cybis Fontana; Tatiana Mora Kuplich

2018-01-01

ABSTRACT This study aimed to increase satellite-derived Normalized Difference Vegetation Index (NDVI) sensitivity to biophysical parameters changes with aid of a forest age-based adjustment factor. This factor is defined as a ratio between stand age and age of rotation, which value multiplied by Landsat-5/TM-derived NDVI generated the so-called adjusted index NDVI_a. Soil Adjusted Vegetation Index (SAVI) was also calculated. The relationship between these vegetation indices (VI) with Eucalypt...

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

Directory of Open Access Journals (Sweden)

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.

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).

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

2015-11-02

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.

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...

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.

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

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 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

Development and Application of an Annual Vegetation-Monitoring Tool in Gishwati Forest Reserve using MODIS NDVI product and Landsat-5 and 7

Science.gov (United States)

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.

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.

Maximum temperature accounts for annual soil CO2 efflux in temperate forests of Northern China

Science.gov (United States)

Zhou, Zhiyong; Xu, Meili; Kang, Fengfeng; Jianxin Sun, Osbert

2015-01-01

It will help understand the representation legality of soil temperature to explore the correlations of soil respiration with variant properties of soil temperature. Soil temperature at 10 cm depth was hourly logged through twelve months. Basing on the measured soil temperature, soil respiration at different temporal scales were calculated using empirical functions for temperate forests. On monthly scale, soil respiration significantly correlated with maximum, minimum, mean and accumulated effective soil temperatures. Annual soil respiration varied from 409 g C m−2 in coniferous forest to 570 g C m−2 in mixed forest and to 692 g C m−2 in broadleaved forest, and was markedly explained by mean soil temperatures of the warmest day, July and summer, separately. These three soil temperatures reflected the maximum values on diurnal, monthly and annual scales. In accordance with their higher temperatures, summer soil respiration accounted for 51% of annual soil respiration across forest types, and broadleaved forest also had higher soil organic carbon content (SOC) and soil microbial biomass carbon content (SMBC), but a lower contribution of SMBC to SOC. This added proof to the findings that maximum soil temperature may accelerate the transformation of SOC to CO2-C via stimulating activities of soil microorganisms. PMID:26179467

An analysis of annual maximum streamflows in Terengganu, Malaysia using TL-moments approach

Science.gov (United States)

Ahmad, Ummi Nadiah; Shabri, Ani; Zakaria, Zahrahtul Amani

2013-02-01

TL-moments approach has been used in an analysis to determine the best-fitting distributions to represent the annual series of maximum streamflow data over 12 stations in Terengganu, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: generalized pareto (GPA), generalized logistic, and generalized extreme value distribution. The influence of TL-moments on estimated probability distribution functions are examined by evaluating the relative root mean square error and relative bias of quantile estimates through Monte Carlo simulations. The boxplot is used to show the location of the median and the dispersion of the data, which helps in reaching the decisive conclusions. For most of the cases, the results show that TL-moments with one smallest value was trimmed from the conceptual sample (TL-moments (1,0)), of GPA distribution was the most appropriate in majority of the stations for describing the annual maximum streamflow series in Terengganu, Malaysia.

Research for annual travel-route changes of reindeer living around the Arctic Circle using satellite remote sensing

Science.gov (United States)

Suzuki, G.; Sakka, T.; Tashiro, T.; Kawamata, H.; Tatsuzawa, S.; Naruse, N.; Takahashi, Y.

2017-12-01

For a long time, nomads living in the Arctic Circle around Siberia have been making a living by hunting reindeer traditionally. Wild reindeer have a recurrent migration every year, however, the travel-route of reindeer has been changing recently, so the nomads cannot expect the route in their traditional experience. To support them, one of authors (Tatsuzawa) investigated the route by installing GPS transmitter to some reindeer. The reason of the changing route, however, remain unclear. Previous works indicated that the reason of changing the route must be a global warming, forest fires, thunders, and floods, but they only discuss only on the basis of measurements in specific area. The purpose of this study is to research why the arctic reindeer alter the travel route annually through 1) the annual change of vegetation (NDVI: normalized difference vegetation index) in reindeer ground, and through 2) the annual change of soil water content (mNDWI: modified normalized difference water index) which can be reflected precipitation near Lena river. First, we analyzed NDVI using MODIS images that can be observed over a wide area, filmed in July and August; the reindeer started to travel. We have compared the seasonal changes of the NDVI images with the trace obtained by GPS data from 2010 to 2012. Although NDVI images in July showed similar numerical values in every year, the satellite images taken at August 29 is annually different; NDVI values become lower (0.5 or less) when the reindeer travel to the north area in winter. This suggests that reindeer move to secure enough food in the end of summer. In contrast, mNDWI becomes high when the reindeer travel to the north area. The annual changes of the route may be related to the amount of rainfall.

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.

Modelling of extreme rainfall events in Peninsular Malaysia based on annual maximum and partial duration series

Science.gov (United States)

Zin, Wan Zawiah Wan; Shinyie, Wendy Ling; Jemain, Abdul Aziz

2015-02-01

In this study, two series of data for extreme rainfall events are generated based on Annual Maximum and Partial Duration Methods, derived from 102 rain-gauge stations in Peninsular from 1982-2012. To determine the optimal threshold for each station, several requirements must be satisfied and Adapted Hill estimator is employed for this purpose. A semi-parametric bootstrap is then used to estimate the mean square error (MSE) of the estimator at each threshold and the optimal threshold is selected based on the smallest MSE. The mean annual frequency is also checked to ensure that it lies in the range of one to five and the resulting data is also de-clustered to ensure independence. The two data series are then fitted to Generalized Extreme Value and Generalized Pareto distributions for annual maximum and partial duration series, respectively. The parameter estimation methods used are the Maximum Likelihood and the L-moment methods. Two goodness of fit tests are then used to evaluate the best-fitted distribution. The results showed that the Partial Duration series with Generalized Pareto distribution and Maximum Likelihood parameter estimation provides the best representation for extreme rainfall events in Peninsular Malaysia for majority of the stations studied. Based on these findings, several return values are also derived and spatial mapping are constructed to identify the distribution characteristic of extreme rainfall in Peninsular Malaysia.

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

Directory of Open Access Journals (Sweden)

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.

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.

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...

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.

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)

Trends in Mean Annual Minimum and Maximum Near Surface Temperature in Nairobi City, Kenya

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George Lukoye Makokha

2010-01-01

Full Text Available This paper examines the long-term urban modification of mean annual conditions of near surface temperature in Nairobi City. Data from four weather stations situated in Nairobi were collected from the Kenya Meteorological Department for the period from 1966 to 1999 inclusive. The data included mean annual maximum and minimum temperatures, and was first subjected to homogeneity test before analysis. Both linear regression and Mann-Kendall rank test were used to discern the mean annual trends. Results show that the change of temperature over the thirty-four years study period is higher for minimum temperature than maximum temperature. The warming trends began earlier and are more significant at the urban stations than is the case at the sub-urban stations, an indication of the spread of urbanisation from the built-up Central Business District (CBD to the suburbs. The established significant warming trends in minimum temperature, which are likely to reach higher proportions in future, pose serious challenges on climate and urban planning of the city. In particular the effect of increased minimum temperature on human physiological comfort, building and urban design, wind circulation and air pollution needs to be incorporated in future urban planning programmes of the city.

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

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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.

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 ...

Estimate of annual daily maximum rainfall and intense rain equation for the Formiga municipality, MG, Brazil

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Giovana Mara Rodrigues Borges

2016-11-01

Full Text Available Knowledge of the probabilistic behavior of rainfall is extremely important to the design of drainage systems, dam spillways, and other hydraulic projects. This study therefore examined statistical models to predict annual daily maximum rainfall as well as models of heavy rain for the city of Formiga - MG. To do this, annual maximum daily rainfall data were ranked in decreasing order that best describes the statistical distribution by exceedance probability. Daily rainfall disaggregation methodology was used for the intense rain model studies and adjusted with Intensity-Duration-Frequency (IDF and Exponential models. The study found that the Gumbel model better adhered to the data regarding observed frequency as indicated by the Chi-squared test, and that the exponential model best conforms to the observed data to predict intense rains.

Global-scale high-resolution ( 1 km) modelling of mean, maximum and minimum annual streamflow

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Barbarossa, Valerio; Huijbregts, Mark; Hendriks, Jan; Beusen, Arthur; Clavreul, Julie; King, Henry; Schipper, Aafke

2017-04-01

Quantifying mean, maximum and minimum annual flow (AF) of rivers at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. AF metrics can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict AF metrics based on climate and catchment characteristics. Yet, so far, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. We developed global-scale regression models that quantify mean, maximum and minimum AF as function of catchment area and catchment-averaged slope, elevation, and mean, maximum and minimum annual precipitation and air temperature. We then used these models to obtain global 30 arc-seconds (˜ 1 km) maps of mean, maximum and minimum AF for each year from 1960 through 2015, based on a newly developed hydrologically conditioned digital elevation model. We calibrated our regression models based on observations of discharge and catchment characteristics from about 4,000 catchments worldwide, ranging from 100 to 106 km2 in size, and validated them against independent measurements as well as the output of a number of process-based global hydrological models (GHMs). The variance explained by our regression models ranged up to 90% and the performance of the models compared well with the performance of existing GHMs. Yet, our AF maps provide a level of spatial detail that cannot yet be achieved by current GHMs.

Estimating agricultural yield gap in Africa using MODIS NDVI dataset

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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.

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

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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.

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.

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.

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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

On Selection of the Probability Distribution for Representing the Maximum Annual Wind Speed in East Cairo, Egypt

International Nuclear Information System (INIS)

El-Shanshoury, Gh. I.; El-Hemamy, S.T.

2013-01-01

The main objective of this paper is to identify an appropriate probability model and best plotting position formula which represent the maximum annual wind speed in east Cairo. This model can be used to estimate the extreme wind speed and return period at a particular site as well as to determine the radioactive release distribution in case of accident occurrence at a nuclear power plant. Wind speed probabilities can be estimated by using probability distributions. An accurate determination of probability distribution for maximum wind speed data is very important in expecting the extreme value . The probability plots of the maximum annual wind speed (MAWS) in east Cairo are fitted to six major statistical distributions namely: Gumbel, Weibull, Normal, Log-Normal, Logistic and Log- Logistic distribution, while eight plotting positions of Hosking and Wallis, Hazen, Gringorten, Cunnane, Blom, Filliben, Benard and Weibull are used for determining exceedance of their probabilities. A proper probability distribution for representing the MAWS is selected by the statistical test criteria in frequency analysis. Therefore, the best plotting position formula which can be used to select appropriate probability model representing the MAWS data must be determined. The statistical test criteria which represented in: the probability plot correlation coefficient (PPCC), the root mean square error (RMSE), the relative root mean square error (RRMSE) and the maximum absolute error (MAE) are used to select the appropriate probability position and distribution. The data obtained show that the maximum annual wind speed in east Cairo vary from 44.3 Km/h to 96.1 Km/h within duration of 39 years . Weibull plotting position combined with Normal distribution gave the highest fit, most reliable, accurate predictions and determination of the wind speed in the study area having the highest value of PPCC and lowest values of RMSE, RRMSE and MAE

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.

STATIONARITY OF ANNUAL MAXIMUM DAILY STREAMFLOW TIME SERIES IN SOUTH-EAST BRAZILIAN RIVERS

Directory of Open Access Journals (Sweden)

Jorge Machado Damázio

2015-08-01

Full Text Available DOI: 10.12957/cadest.2014.18302The paper presents a statistical analysis of annual maxima daily streamflow between 1931 and 2013 in South-East Brazil focused in detecting and modelling non-stationarity aspects. Flood protection for the large valleys in South-East Brazil is provided by multiple purpose reservoir systems built during 20th century, which design and operation plans has been done assuming stationarity of historical flood time series. Land cover changes and rapidly-increasing level of atmosphere greenhouse gases of the last century may be affecting flood regimes in these valleys so that it can be that nonstationary modelling should be applied to re-asses dam safety and flood control operation rules at the existent reservoir system. Six annual maximum daily streamflow time series are analysed. The time series were plotted together with fitted smooth loess functions and non-parametric statistical tests are performed to check the significance of apparent trends shown by the plots. Non-stationarity is modelled by fitting univariate extreme value distribution functions which location varies linearly with time. Stationarity and non-stationarity modelling are compared with the likelihood ratio statistic. In four of the six analyzed time series non-stationarity modelling outperformed stationarity modelling.Keywords: Stationarity; Extreme Value Distributions; Flood Frequency Analysis; Maximum Likelihood Method.

Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

Science.gov (United States)

Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

2018-05-01

Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km 2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization

Estimating distribution parameters of annual maximum streamflows in Johor, Malaysia using TL-moments approach

Science.gov (United States)

Mat Jan, Nur Amalina; Shabri, Ani

2017-01-01

TL-moments approach has been used in an analysis to identify the best-fitting distributions to represent the annual series of maximum streamflow data over seven stations in Johor, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: Three-parameter lognormal (LN3) and Pearson Type III (P3) distribution. The main objective of this study is to derive the TL-moments ( t 1,0), t 1 = 1,2,3,4 methods for LN3 and P3 distributions. The performance of TL-moments ( t 1,0), t 1 = 1,2,3,4 was compared with L-moments through Monte Carlo simulation and streamflow data over a station in Johor, Malaysia. The absolute error is used to test the influence of TL-moments methods on estimated probability distribution functions. From the cases in this study, the results show that TL-moments with four trimmed smallest values from the conceptual sample (TL-moments [4, 0]) of LN3 distribution was the most appropriate in most of the stations of the annual maximum streamflow series in Johor, Malaysia.

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.

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.

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.

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

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.

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

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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

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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.

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.

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

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

Science.gov (United States)

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)

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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-annual

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.

Diagnostic of annual cycle and effects of the ENSO about the maximum intensity of duration rains between 1 and 24 hours at the Andes of Colombia

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Poveda, German; Mesa, Oscar; Toro, Vladimir; Agudelo, Paula; Alvarez, Juan F; Arias, Paola; Moreno, Hernan; Salazar, Luis; Vieira, Sara

2002-01-01

We study the distribution of maximum rainfall events during the annual cycle, for storms ranging from 1 to 24-hour in duration; by using information over 51 rain gauges locate at the Colombian Andes. Also, the effects of both phases of ENSO (El Nino and La Nina) are quantified. We found that maximum rainfall intensity events occur during the rainy periods of march-may and September-November. There is a strong similarity between the annual cycle of mean total rainfall and that of the maximum intensities of rainfall over the tropical Andes. This result is quite consistent throughout the three ranges of the Colombian Andes. At inter annual timescales, we found that both phases of ENSO are associated with disturbances of maximum rainfall events; since during La Nina there are more intense precipitation events than during El Nino, overall, for durations longer than 3 hours, rainfall intensity gets reduced by one order of magnitude with respect to shorter durations (1-3 hours). The most extreme recorded rainfall events are apparently not associated with the annual and inter annual large scales forcing and appear to be randomly generated by the important role of the land surface atmosphere in the genesis and dynamics of intense storm over central Colombia

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

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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.

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

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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

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

, and to (b) decompose the NDVI signal into partial primary production components for herbaceous vegetation and shrubs across the study site. We further apply remote-sensed annual net primary production (ANPP) estimations and landscape type classification to explore the influence of inter-annual variations in seasonal precipitation on the production of herbaceous and shrub vegetation. Our results suggest that changes in the amount and temporal pattern of precipitation comprising reductions in monsoonal summer rainfall and/or increases in winter precipitation may enhance the shrub-encroachment process in desert grasslands of the American Southwest.

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

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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

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

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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

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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.

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.

Spatiotemporal extremes of temperature and precipitation during 1960-2015 in the Yangtze River Basin (China) and impacts on vegetation dynamics

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Cui, Lifang; Wang, Lunche; Qu, Sai; Singh, Ramesh P.; Lai, Zhongping; Yao, Rui

2018-05-01

Recently, extreme climate variation has been studied in different parts of the world, and the present study aims to study the impacts of climate extremes on vegetation. In this study, we analyzed the spatiotemporal variations of temperature and precipitation extremes during 1960-2015 in the Yangtze River Basin (YRB) using the Mann-Kendall (MK) test with Sen's slope estimator and kriging interpolation method based on daily precipitation (P), maximum temperature (T max), and minimum temperature (T min). We also analyzed the vegetation dynamics in the YRB during 1982-2015 using Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) datasets and investigated the relationship between temperature and precipitation extremes and NDVI using Pearson correlation coefficients. The results showed a pronounced increase in the annual mean maximum temperature (T nav) and mean minimum temperature (T xav) at the rate of 0.23 °C/10 years and 0.15 °C/10 years, respectively, during 1960-2015. In addition, the occurrence of warm days and warm nights shows increasing trends at the rate of 1.36 days/10 years and 1.70 days/10 years, respectively, while cold days and cold nights decreased at the rate of 1.09 days/10 years and 2.69 days/10 years, respectively, during 1960-2015. The precipitation extremes, such as very wet days (R95, the 95th percentile of daily precipitation events), very wet day precipitation (R95p, the number of days with rainfall above R95), rainstorm (R50, the number of days with rainfall above 50 mm), and maximum 1-day precipitation (RX1day), all show pronounced increasing trends during 1960-2015. In general, annual mean NDVI over the whole YRB increased at the rate of 0.01/10 years during 1982-2015, with an increasing transition around 1994. Spatially, annual mean NDVI increased in the northern, eastern, and parts of southwestern YRB, while it decreased in the YRD and parts of southern YRB during 1982-2015. The correlation

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

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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.

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

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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

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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.

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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.

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

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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...

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

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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.

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

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

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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

Environmental Drivers of NDVI-Based Vegetation Phenology in Central Asia

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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

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.

Regional analysis of annual maximum rainfall using TL-moments method

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Shabri, Ani Bin; Daud, Zalina Mohd; Ariff, Noratiqah Mohd

2011-06-01

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.

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.

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.

Spatial variability of maximum annual daily rain under different return periods at the Rio de Janeiro state, Brazil

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Roriz Luciano Machado

2010-01-01

Full Text Available Knowledge of maximum daily rain and its return period in a region is an important tool to soil conservation, hydraulic engineering and preservation of road projects. The objective of this work was to evaluate the spatial variability of maximum annual daily rain considering different return periods, at the Rio de Janeiro State. The data set was composed by historical series of 119 rain gauges, for 36 years of observation. The return periods, estimated by Gumbel distribution, were 2, 5, 10, 25, 50 and 100 years. The spatial variability of the return periods was evaluated by semivariograms. All the return periods presented spatial dependence, with exponential and spherical model fitted to the experimental semivariograms. The parameters of the fitted semivariogram model were very similar; however, it was observed the presence of higher nugget effects for semivariograms of longer return periods. The values of maximum annual daily average rain in all the return periods increased from north to south and from countryside to the coast. In the region between the Serra do Mar range and the coast, besides increasing in magnitude, an increase in the spatial variability of the studied values with increasing return periods was also noticed. This behavior is probably caused by the orographic effect. The interpolated maps were more erratic for higher return periods and at the North, Northeast and Coastal Plain regions, in which the installation of new pluviometric stations are recommended.

Analysis of Seasonal and Annual Change of Vegetation in the Indian Thar Desert Using Modis Data

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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.

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...

Change-Point and Trend Analysis on Annual Maximum Discharge in Continental United States

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Serinaldi, F.; Villarini, G.; Smith, J. A.; Krajewski, W. F.

2008-12-01

Annual maximum discharge records from 36 stations representing different hydro-climatic regimes in the continental United States with at least 100 years of records are used to investigate the presence of temporal trends and abrupt changes in mean and variance. Change point analysis is performed by means of two non- parametric (Pettitt and CUSUM), one semi-parametric (Guan), and two parametric (Rodionov and Bayesian Change Point) tests. Two non-parametric (Mann-Kendall and Spearman) and one parametric (Pearson) tests are applied to detect the presence of temporal trends. Generalized Additive Model for Location Scale and Shape (GAMLSS) models are also used to parametrically model the streamflow data exploiting their flexibility to account for changes and temporal trends in the parameters of distribution functions. Additionally, serial correlation is assessed in advance by computing the autocorrelation function (ACF), and the Hurst parameter is estimated using two estimators (aggregated variance and differenced variance methods) to investigate the presence of long range dependence. The results of this study indicate lack of long range dependence in the maximum streamflow series. At some stations the authors found a statistically significant change point in the mean and/or variance, while in general they detected no statistically significant temporal trends.

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.

Perfis temporais NDVI MODIS, na cana-soca, de maturação tardia NDVI MODIS temporal profiles, in sugarcane, late maturation

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Fernando L. P. Ramme

2010-06-01

Full Text Available Este artigo descreve o desenvolvimento de um banco de dados relacional e de uma ferramenta para a visualização de perfis temporais do NDVI MODIS, a partir dos dados do produto MOD09Q1, referente ao fator de refletância bidirecional de superfície relativa ao comprimento de onda do vermelho e do infravermelho-próximo, composição temporal em mosaicos de 8 dias, e a banda de controle de qualidade, dos talhões de cana-de-açúcar no Estado de São Paulo, para analisar a maturação da cana-soca Tardia. Das fazendas de cana-de-açúcar são obtidos os dados de históricos sobre produtividade, solo, variedade, localização de cada pixel para cada microrregião monitorada. Todos os dados são integrados em um banco de dados desenvolvido em PostgreSQL. O aplicativo foi implementado usando a linguagem Java e permitiu uma forma rápida e automática para analisar padrões fenológicos na cana-de-açúcar. Concluiu-se que o perfil temporal do NDVI MODIS obtido a partir do produto MOD09Q1 é capaz de subsidiar o monitoramento das mudanças fenológicas na cultura da cana-de-açúcar.This paper describes the development of a relational database and a tool for viewing MODIS NDVI temporal profile, using data from MOD09Q1 product, specifically the surface bidirectional reflectance factor relative to the RED and NIR wavelength, mosaic of 8-day temporal composition, and the quality band, in sugarcane fields in the state of São Paulo, for analysis of the late stubble-cane maturation. From sugarcane farms were obtained the historical data about yield, soil, variety, location of the each pixel for each subregion monitored. All data were integrated in a database developed in PostgreSQL. The tool was implemented using Java language and allowed a fast and automatic way of analyzing sugarcane phenological patterns. It concluded that the MODIS NDVI temporal profile using data from MOD09Q1 product is able to subsidize the monitoring of phenological changes in the

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

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

Directory of Open Access Journals (Sweden)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Science.gov (United States)

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

FLO1K, global maps of mean, maximum and minimum annual streamflow at 1 km resolution from 1960 through 2015

Science.gov (United States)

Barbarossa, Valerio; Huijbregts, Mark A. J.; Beusen, Arthur H. W.; Beck, Hylke E.; King, Henry; Schipper, Aafke M.

2018-03-01

Streamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K, a consistent streamflow dataset at a resolution of 30 arc seconds (~1 km) and global coverage. FLO1K comprises mean, maximum and minimum annual flow for each year in the period 1960-2015, provided as spatially continuous gridded layers. We mapped streamflow by means of artificial neural networks (ANNs) regression. An ensemble of ANNs were fitted on monthly streamflow observations from 6600 monitoring stations worldwide, i.e., minimum and maximum annual flows represent the lowest and highest mean monthly flows for a given year. As covariates we used the upstream-catchment physiography (area, surface slope, elevation) and year-specific climatic variables (precipitation, temperature, potential evapotranspiration, aridity index and seasonality indices). Confronting the maps with independent data indicated good agreement (R2 values up to 91%). FLO1K delivers essential data for freshwater ecology and water resources analyses at a global scale and yet high spatial resolution.

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

Science.gov (United States)

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

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.

Climate-simulated raceway pond culturing: quantifying the maximum achievable annual biomass productivity of Chlorella sorokiniana in the contiguous USA

Energy Technology Data Exchange (ETDEWEB)

Huesemann, M.; Chavis, A.; Edmundson, S.; Rye, D.; Hobbs, S.; Sun, N.; Wigmosta, M.

2017-09-13

Chlorella sorokiniana (DOE 1412) emerged as one of the most promising microalgae strains from the NAABB consortium project, with a remarkable doubling time under optimal conditions of 2.57 hr-1. However, its maximum achievable annual biomass productivity in outdoor ponds in the contiguous United States remained unknown. In order to address this knowledge gap, this alga was cultured in indoor LED-lighted and temperature-controlled raceways in nutrient replete freshwater (BG-11) medium at pH 7 under conditions simulating the daily sunlight intensity and water temperature fluctuations during three seasons in Southern Florida, an optimal outdoor pond culture location for this organism identified by biomass growth modeling. Prior strain characterization indicated that the average maximum specific growth rate (µmax) at 36 ºC declined continuously with pH, with µmax corresponding to 5.92, 5.83, 4.89, and 4.21 day-1 at pH 6, 7, 8, and 9, respectively. In addition, the maximum specific growth rate declined nearly linearly with increasing salinity until no growth was observed above 35 g/L NaCl. In the climate-simulated culturing studies, the volumetric ash-free dry weight-based biomass productivities during the linear growth phase were 57, 69, and 97 mg/L-day for 30-year average light and temperature simulations for January (winter), March (spring), and July (summer), respectively, which corresponds to average areal productivities of 11.6, 14.1, and 19.9 g/m2-day at a constant pond depth of 20.5 cm. The photosynthetic efficiencies (PAR) in the three climate-simulated pond culturing experiments ranged from 4.1 to 5.1%. The annual biomass productivity was estimated as ca. 15 g/m2-day, nearly double the U.S. Department of Energy (DOE) 2015 State of Technology annual cultivation productivity of 8.5 g/m2-day, but this is still significantly below the projected 2022 target of ca. 25 g/m2-day (U.S. DOE, 2016) for economic microalgal biofuel production, indicating the need for

Annual, semi-annual and ter-annual variations of gravity wave momentum flux in 13 years of SABER data

Science.gov (United States)

Chen, Dan; Preusse, Peter; Ern, Manfred; Strube, Cornelia

2017-04-01

In this study, the variations at different time scales such as the annual cycle, the semiannual oscillation (SAO), the ter-annual cycle (about four monthly) and the quasi-biennial oscillation (QBO) in zonal mean GW amplitudes and GW momentum flux (GWMF) have been investigated using satellite observations from 2002-2014 and combining ECMWF high resolution data with the GORGRAT model. The global distribution (patterns) of spectral amplitudes of GW momentum flux in stratosphere and mesosphere (from 30 km to 90 km) show that the annual cycle is the most predominant variation, and then are SAO, ter-annual cycle and QBO. For annual components, two relatively isolated amplitude maxima appear in each hemisphere: a subtropical maximum is associated with convective sources in summer, a mid and high latitude maximum is associated with the polar vortex in winter. In the subtropics, GWs propagate upward obliquely to the higher latitudes. The winter maximum in the southern hemisphere has larger momentum flux than that one in the northern hemisphere. While on the SH the phase (i.e. time corresponding to the maximum GWMF) continuously descends with the maximum in July in the upper mesosphere and in September in the lower stratosphere, on the northern hemisphere, the phase has no visible altitude dependence with a maximum in December. For semiannual variations, in the MLT (70-80 km) region, there is an obvious enhancement of spectral amplitude at equatorial latitudes which relate to the dissipation of convectively forced GWs. The SAO in absolute momentum flux and the annual cycle in zonal momentum flux indicated that the variations at mid-latitudes (about from 30°-40°) are not a SAO signals but rather an annual cycle when the direction of GWMF is considered. The ter-annual cycle may be related to the duration of active convection in subtropical latitudes (from June to Sep. in north hemisphere) Indications for QBO are found latitude extension to mid-latitudes in stratosphere of

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

Variation of Maximum Tree Height and Annual Shoot Growth of Smith Fir at Various Elevations in the Sygera Mountains, Southeastern Tibetan Plateau

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Wang, Yafeng; Čufar, Katarina; Eckstein, Dieter; Liang, Eryuan

2012-01-01

Little is known about tree height and height growth (as annual shoot elongation of the apical part of vertical stems) of coniferous trees growing at various altitudes on the Tibetan Plateau, which provides a high-elevation natural platform for assessing tree growth performance in relation to future climate change. We here investigated the variation of maximum tree height and annual height increment of Smith fir (Abies georgei var. smithii) in seven forest plots (30 m×40 m) along two altitudinal transects between 3,800 m and 4,200/4,390 m above sea level (a.s.l.) in the Sygera Mountains, southeastern Tibetan Plateau. Four plots were located on north-facing slopes and three plots on southeast-facing slopes. At each site, annual shoot growth was obtained by measuring the distance between successive terminal bud scars along the main stem of 25 trees that were between 2 and 4 m high. Maximum/mean tree height and mean annual height increment of Smith fir decreased with increasing altitude up to the tree line, indicative of a stress gradient (the dominant temperature gradient) along the altitudinal transect. Above-average mean minimum summer (particularly July) temperatures affected height increment positively, whereas precipitation had no significant effect on shoot growth. The time series of annual height increments of Smith fir can be used for the reconstruction of past climate on the southeastern Tibetan Plateau. In addition, it can be expected that the rising summer temperatures observed in the recent past and anticipated for the future will enhance Smith fir's growth throughout its altitudinal distribution range. PMID:22396738

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.

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)

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.

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.

Monitoring Start of Season in Alaska

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Robin, J.; Dubayah, R.; Sparrow, E.; Levine, E.

2006-12-01

In biomes that have distinct winter seasons, start of spring phenological events, specifically timing of budburst and green-up of leaves, coincides with transpiration. Seasons leave annual signatures that reflect the dynamic nature of the hydrologic cycle and link the different spheres of the Earth system. This paper evaluates whether continuity between AVHRR and MODIS normalized difference vegetation index (NDVI) is achievable for monitoring land surface phenology, specifically start of season (SOS), in Alaska. Additionally, two thresholds, one based on NDVI and the other on accumulated growing degree-days (GDD), are compared to determine which most accurately predicts SOS for Fairbanks. Ratio of maximum greenness at SOS was computed from biweekly AVHRR and MODIS composites for 2001 through 2004 for Anchorage and Fairbanks regions. SOS dates were determined from annual green-up observations made by GLOBE students. Results showed that different processing as well as spectral characteristics of each sensor restrict continuity between the two datasets. MODIS values were consistently higher and had less inter-annual variability during the height of the growing season than corresponding AVHRR values. Furthermore, a threshold of 131-175 accumulated GDD was a better predictor of SOS for Fairbanks than a NDVI threshold applied to AVHRR and MODIS datasets. The NDVI threshold was developed from biweekly AVHRR composites from 1982 through 2004 and corresponding annual green-up observations at University of Alaska-Fairbanks (UAF). The GDD threshold was developed from 20+ years of historic daily mean air temperature data and the same green-up observations. SOS dates computed with the GDD threshold most closely resembled actual green-up dates observed by GLOBE students and UAF researchers. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska.

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.

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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

Evaluating Annual Maximum and Partial Duration Series for Estimating Frequency of Small Magnitude Floods

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Fazlul Karim

2017-06-01

Full Text Available Understanding the nature of frequent floods is important for characterising channel morphology, riparian and aquatic habitat, and informing river restoration efforts. This paper presents results from an analysis on frequency estimates of low magnitude floods using the annual maximum and partial series data compared to actual flood series. Five frequency distribution models were fitted to data from 24 gauging stations in the Great Barrier Reef (GBR lagoon catchments in north-eastern Australia. Based on the goodness of fit test, Generalised Extreme Value, Generalised Pareto and Log Pearson Type 3 models were used to estimate flood frequencies across the study region. Results suggest frequency estimates based on a partial series are better, compared to an annual series, for small to medium floods, while both methods produce similar results for large floods. Although both methods converge at a higher recurrence interval, the convergence recurrence interval varies between catchments. Results also suggest frequency estimates vary slightly between two or more partial series, depending on flood threshold, and the differences are large for the catchments that experience less frequent floods. While a partial series produces better frequency estimates, it can underestimate or overestimate the frequency if the flood threshold differs largely compared to bankfull discharge. These results have significant implications in calculating the dependency of floodplain ecosystems on the frequency of flooding and their subsequent management.

Maximum power demand cost

International Nuclear Information System (INIS)

Biondi, L.

1998-01-01

The charging for a service is a supplier's remuneration for the expenses incurred in providing it. There are currently two charges for electricity: consumption and maximum demand. While no problem arises about the former, the issue is more complicated for the latter and the analysis in this article tends to show that the annual charge for maximum demand arbitrarily discriminates among consumer groups, to the disadvantage of some [it

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

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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

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).

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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.

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

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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.

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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.

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

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

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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

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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

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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.

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 ...

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.

Comparison of annual maximum series and partial duration series methods for modeling extreme hydrologic events

DEFF Research Database (Denmark)

Madsen, Henrik; Rasmussen, Peter F.; Rosbjerg, Dan

1997-01-01

Two different models for analyzing extreme hydrologic events, based on, respectively, partial duration series (PDS) and annual maximum series (AMS), are compared. The PDS model assumes a generalized Pareto distribution for modeling threshold exceedances corresponding to a generalized extreme value......). In the case of ML estimation, the PDS model provides the most efficient T-year event estimator. In the cases of MOM and PWM estimation, the PDS model is generally preferable for negative shape parameters, whereas the AMS model yields the most efficient estimator for positive shape parameters. A comparison...... of the considered methods reveals that in general, one should use the PDS model with MOM estimation for negative shape parameters, the PDS model with exponentially distributed exceedances if the shape parameter is close to zero, the AMS model with MOM estimation for moderately positive shape parameters, and the PDS...

Responses of Vegetation Growth to Climatic Factors in Shule River Basin in Northwest China: A Panel Analysis

Directory of Open Access Journals (Sweden)

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.

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.

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.

Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River.

Science.gov (United States)

Ouyang, Wei; Hao, Fanghua; Skidmore, Andrew K; Toxopeus, A G

2010-12-15

Soil erosion is a significant concern when considering regional environmental protection, especially in the Yellow River Basin in China. This study evaluated the temporal-spatial interaction of land cover status with soil erosion characteristics in the Longliu Catchment of China, using the Soil and Water Assessment Tool (SWAT) model. SWAT is a physical hydrological model which uses the RUSLE equation as a sediment algorithm. Considering the spatial and temporal scale of the relationship between soil erosion and sediment yield, simulations were undertaken at monthly and annual temporal scales and basin and sub-basin spatial scales. The corresponding temporal and spatial Normalized Difference Vegetation Index (NDVI) information was summarized from MODIS data, which can integrate regional land cover and climatic features. The SWAT simulation revealed that the annual soil erosion and sediment yield showed similar spatial distribution patterns, but the monthly variation fluctuated significantly. The monthly basin soil erosion varied from almost no erosion load to 3.92 t/ha and the maximum monthly sediment yield was 47,540 tones. The inter-annual simulation focused on the spatial difference and relationship with the corresponding vegetation NDVI value for every sub-basin. It is concluded that, for this continental monsoon climate basin, the higher NDVI vegetation zones prevented sediment transport, but at the same time they also contributed considerable soil erosion. The monthly basin soil erosion and sediment yield both correlated with NDVI, and the determination coefficients of their exponential correlation model were 0.446 and 0.426, respectively. The relationships between soil erosion and sediment yield with vegetation NDVI indicated that the vegetation status has a significant impact on sediment formation and transport. The findings can be used to develop soil erosion conservation programs for the study area. Copyright © 2010 Elsevier B.V. All rights reserved.

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

Directory of Open Access Journals (Sweden)

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.

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.

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

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Laura Ulsig

2017-01-01

Full Text Available Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI. This study investigates the potential of a Photochemical Reflectance Index (PRI, which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R2 = 0.36–0.8, which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R2 > 0.6 in all cases. The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

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

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

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...

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

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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.

Annual Gross Primary Production from Vegetation Indices: A Theoretically Sound Approach

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María Amparo Gilabert

2017-02-01

Full Text Available A linear relationship between the annual gross primary production (GPP and a PAR-weighted vegetation index is theoretically derived from the Monteith equation. A semi-empirical model is then proposed to estimate the annual GPP from commonly available vegetation indices images and a representative PAR, which does not require actual meteorological data. A cross validation procedure is used to calibrate and validate the model predictions against reference data. As the calibration/validation process depends on the reference GPP product, the higher the quality of the reference GPP, the better the performance of the semi-empirical model. The annual GPP has been estimated at 1-km scale from MODIS NDVI and EVI images for eight years. Two reference data sets have been used: an optimized GPP product for the study area previously obtained and the MOD17A3 product. Different statistics show a good agreement between the estimates and the reference GPP data, with correlation coefficient around 0.9 and relative RMSE around 20%. The annual GPP is overestimated in semiarid areas and slightly underestimated in dense forest areas. With the above limitations, the model provides an excellent compromise between simplicity and accuracy for the calculation of long time series of annual GPP.

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

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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

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

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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.

[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.

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.

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

Science.gov (United States)

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%.

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...

Estimating Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations

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Bradley C. Reed

2013-02-01

Full Text Available Winter annual plants in southwestern North America influence fire regimes, provide forage, and help prevent erosion. Exotic annuals may also threaten native species. Monitoring winter annuals is difficult because of their ephemeral nature, making the development of a satellite monitoring tool valuable. We mapped winter annual aboveground biomass in the Desert Southwest from satellite observations, evaluating 18 algorithms using time-series vegetation indices (VI. Field-based biomass estimates were used to calibrate and evaluate each algorithm. Winter annual biomass was best estimated by calculating a base VI across the period of record and subtracting it from the peak VI for each winter season (R2 = 0.92. The normalized difference vegetation index (NDVI derived from 8-day reflectance data provided the best estimate of winter annual biomass. It is important to account for the timing of peak vegetation when relating field-based estimates to satellite VI data, since post-peak field estimates may indicate senescent biomass which is inaccurately represented by VI-based estimates. Images generated from the best-performing algorithm show both spatial and temporal variation in winter annual biomass. Efforts to manage this variable resource would be enhanced by a tool that allows the monitoring of changes in winter annual resources over time.

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

Climatic driving forces in inter-annual variation of global FPAR

Science.gov (United States)

Peng, Dailiang; Liu, Liangyun; Yang, Xiaohua; Zhou, Bin

2012-09-01

Fraction of Absorbed Photosynthetically Active Radiation (FPAR) characterizes vegetation canopy functioning and its energy absorption capacity. In this paper, we focus on climatic driving forces in inter-annual variation of global FPAR from 1982 to 2006 by Global Historical Climatology Network (GHCN-Monthly) data. Using FPAR-Simple Ratio Vegetation Index (SR) relationship, Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used to estimate FPAR at the global scale. The correlation between inter-annual variation of FPAR and temperature, precipitation derived from GHCN-Monthly was examined, during the periods of March-May (MAM), June-August (JJA), September-November (SON), and December-February (DJF) over from 1982 to 2006. The analysis of climatic influence on global FPAR revealed the significant correlation with temperature and precipitation in some meteorological stations area, and a more significant correlation with precipitation was found than which with temperature. Some stations in the regions between 30° N and 60° N and around 30° S in South America, where the annual FPAR variation showed a significant positive correlation with temperature (P forest of Africa and Amazon during the dry season of JJA and SON.

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

Directory of Open Access Journals (Sweden)

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.

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.

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.

25 CFR 141.36 - Maximum finance charges on pawn transactions.

Science.gov (United States)

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false Maximum finance charges on pawn transactions. 141.36... PRACTICES ON THE NAVAJO, HOPI AND ZUNI RESERVATIONS Pawnbroker Practices § 141.36 Maximum finance charges on pawn transactions. No pawnbroker may impose an annual finance charge greater than twenty-four percent...

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

Inferências sobre o calendário agrícola a partir de perfis temporais de NDVI/MODIS

Directory of Open Access Journals (Sweden)

Denise Cybis Fontana

2015-01-01

Full Text Available Um dos maiores desafios para a modelagem de rendimentos de grãos, no contexto das estimativas de safras feitas de forma operacional para grandes áreas, está relacionado à identificação no tempo dos períodos em que as culturas anuais apresentam maior suscetibilidade a estresses ambientais. Para a cultura da soja, cultivada no período de primavera-verão no sul do Brasil, o principal fator de risco é a ocorrência de estresse hídrico no florescimento e enchimento de grãos. Esses subperíodos ocorrem em períodos distintos ao longo da região de produção como consequência de práticas de manejo diferenciadas dos produtores. Este trabalho teve como objetivo relacionar o calendário agrícola da cultura da soja a perfis temporais do índice de vegetação por diferença normalizada (NDVI/MODIS, com intuito de apresentar/validar uma tecnologia de baixo custo e adequada acurácia para fins de monitoramento e previsão de safras. Para tanto, foram analisados os dados de calendário agrícola (subperíodos de floração, enchimento de grãos e maturação da cultura da soja em regionais da EMATER (RS e imagens NDVI do sensor MODIS. Os resultados mostraram que os perfis temporais de NDVI permitem acompanhar a evolução temporal da biomassa da cultura da soja e determinar a ocorrência dos subperíodos do ciclo. As diferenças no valor do NDVI entre safras, regionais e subperíodos do ciclo da cultura demonstram a sensibilidade deste índice em detectar as respostas das plantas de soja às condições ambientais. Como consequência dos dados de NDVI serem gerados a partir das imagens MODIS, é possível a espacialização da informação acerca dos subperíodos para todas as safras e em todo o Estado, o que permite maior detalhamento temporal e espacial comparativamente à atual disponibilidade dos dados.

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.

Peak season plant activity shift towards spring is reflected by increasing carbon uptake by extratropical ecosystems.

Science.gov (United States)

Gonsamo, Alemu; Chen, Jing M; Ooi, Ying W

2018-05-01

Climate change is lengthening the growing season of the Northern Hemisphere extratropical terrestrial ecosystems, but little is known regarding the timing and dynamics of the peak season of plant activity. Here, we use 34-year satellite normalized difference vegetation index (NDVI) observations and atmospheric CO 2 concentration and δ 13 C isotope measurements at Point Barrow (Alaska, USA, 71°N) to study the dynamics of the peak of season (POS) of plant activity. Averaged across extratropical (>23°N) non-evergreen-dominated pixels, NDVI data show that the POS has advanced by 1.2 ± 0.6 days per decade in response to the spring-ward shifts of the start (1.0 ± 0.8 days per decade) and end (1.5 ± 1.0 days per decade) of peak activity, and the earlier onset of the start of growing season (1.4 ± 0.8 days per decade), while POS maximum NDVI value increased by 7.8 ± 1.8% for 1982-2015. Similarly, the peak day of carbon uptake, based on calculations from atmospheric CO 2 concentration and δ 13 C data, is advancing by 2.5 ± 2.6 and 4.3 ± 2.9 days per decade, respectively. POS maximum NDVI value shows strong negative relationships (p POS days. Given that the maximum solar irradiance and day length occur before the average POS day, the earlier occurrence of peak plant activity results in increased plant productivity. Both the advancing POS day and increasing POS vegetation greenness are consistent with the shifting peak productivity towards spring and the increasing annual maximum values of gross and net ecosystem productivity simulated by coupled Earth system models. Our results further indicate that the decline in autumn NDVI is contributing the most to the overall browning of the northern high latitudes (>50°N) since 2011. The spring-ward shift of peak season plant activity is expected to disrupt the synchrony of biotic interaction and exert strong biophysical feedbacks on climate by modifying the surface albedo and energy budget. © 2017

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

Science.gov (United States)

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...

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

Science.gov (United States)

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

Science.gov (United States)

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)

Science.gov (United States)

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

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.

[Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

Science.gov (United States)

Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

2016-01-01

To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

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

Directory of Open Access Journals (Sweden)

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

The impact of inter-annual variability of annual cycle on long-term persistence of surface air temperature in long historical records

Science.gov (United States)

Deng, Qimin; Nian, Da; Fu, Zuntao

2018-02-01

Previous studies in the literature show that the annual cycle of surface air temperature (SAT) is changing in both amplitude and phase, and the SAT departures from the annual cycle are long-term correlated. However, the classical definition of temperature anomalies is based on the assumption that the annual cycle is constant, which contradicts the fact of changing annual cycle. How to quantify the impact of the changing annual cycle on the long-term correlation of temperature anomaly variability still remains open. In this paper, a recently developed data adaptive analysis tool, the nonlinear mode decomposition (NMD), is used to extract and remove time-varying annual cycle to reach the new defined temperature anomalies in which time-dependent amplitude of annual cycle has been considered. By means of detrended fluctuation analysis, the impact induced by inter-annual variability from the time-dependent amplitude of annual cycle has been quantified on the estimation of long-term correlation of long historical temperature anomalies in Europe. The results show that the classical climatology annual cycle is supposed to lack inter-annual fluctuation which will lead to a maximum artificial deviation centering around 600 days. This maximum artificial deviation is crucial to defining the scaling range and estimating the long-term persistence exponent accurately. Selecting different scaling range could lead to an overestimation or underestimation of the long-term persistence exponent. By using NMD method to extract the inter-annual fluctuations of annual cycle, this artificial crossover can be weakened to extend a wider scaling range with fewer uncertainties.

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.

Vegetation dynamic characteristics and its responses to climate change in Jinghe River watershed of Loess Plateau, China

Science.gov (United States)

Chang, F.; Liu, W.; Zhou, H.; Ning, T.; Wang, Y.

2017-12-01

The Jinghe River is a second-order tributary of the Yellow River, and located in the middle-south part of the Loess Plateau. The watershed area is 45421km², with the mean annual precipitation (P) being about 508mm and aridity index 2.09. For a long time, soil and water loss in this watershed is severe, resulting in very fragile ecological environment. The GIMMS-normalized vegetation index NDVI is used to reflect condition of vegetation cover, and P and Penman potential evapotranspiration (ET) to represent climate water and heat conditions. The annual actual ET is estimated as the difference between P and runoff (ignoring the change of watershed water storage during each hydrological year, May to April of the following year). These concepts were introduced to discuss the dynamic characteristics of vegetation cover and its response to climate change. Results showed that the mean annual NDVI value was 0.51, showing a stable increasing trend from 2000 with an annual increasing rate of 8.7×10¯³. This result is consistent with the implementation of the project that converts farmland to forests and grassland and has achieved remarkable success in the Loess Plateau since 1999. It also indicates that the positive impact of human activity has been strengthened under the background of climate change. From 1982 to 2012, the annual actual ET was 464mm, accounting for 93.6% of annual P over the same period. The NDVI value of main growing season (5-9 months) is significantly correlated with annual P and annual humid index (ratio of annual P to annual potential ET). Vegetation water consumption is the main part of land surface ET, and the relationship between annual actual ET and NDVI value over the same period is also significant. The NDVI value, P and potential ET variation varied substantially within the Jinghe River watershed, and their relationships in different regions at an inter-annual scale are different. Currently, we are investigating the influence of the changes in

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)

Flood frequency analysis for nonstationary annual peak records in an urban drainage basin

Science.gov (United States)

Villarini, Gabriele; Smith, James A.; Serinaldi, Francesco; Bales, Jerad; Bates, Paul D.; Krajewski, Witold F.

2009-08-01

Flood frequency analysis in urban watersheds is complicated by nonstationarities of annual peak records associated with land use change and evolving urban stormwater infrastructure. In this study, a framework for flood frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary conditions. GAMLSS is applied to annual maximum peak discharge records for Little Sugar Creek, a highly urbanized watershed which drains the urban core of Charlotte, North Carolina. It is shown that GAMLSS is able to describe the variability in the mean and variance of the annual maximum peak discharge by modeling the parameters of the selected parametric distribution as a smooth function of time via cubic splines. Flood frequency analyses for Little Sugar Creek (at a drainage area of 110km) show that the maximum flow with a 0.01-annual probability (corresponding to 100-year flood peak under stationary conditions) over the 83-year record has ranged from a minimum unit discharge of 2.1mskm to a maximum of 5.1mskm. An alternative characterization can be made by examining the estimated return interval of the peak discharge that would have an annual exceedance probability of 0.01 under the assumption of stationarity (3.2mskm). Under nonstationary conditions, alternative definitions of return period should be adapted. Under the GAMLSS model, the return interval of an annual peak discharge of 3.2mskm ranges from a maximum value of more than 5000 years in 1957 to a minimum value of almost 8 years for the present time (2007). The GAMLSS framework is also used to examine the links between population trends and flood frequency, as well as trends in annual maximum rainfall. These analyses are used to examine evolving flood frequency over future decades.

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.

Seasonal relationship between normalized difference vegetation index and abundance of the Phlebotomus kala-azar vector in an endemic focus in Bihar, India

Directory of Open Access Journals (Sweden)

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.

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.

Semi-annual Sq-variation in solar activity cycle

Science.gov (United States)

Pogrebnoy, V.; Malosiev, T.

The peculiarities of semi-annual variation in solar activity cycle have been studied. The data from observatories having long observational series and located in different latitude zones were used. The following observatories were selected: Huancayo (magnetic equator), from 1922 to 1959; Apia (low latitudes), from 1912 to 1961; Moscow (middle latitudes), from 1947 to 1965. Based on the hourly values of H-components, the average monthly diurnal amplitudes (a difference between midday and midnight values), according to five international quiet days, were computed. Obtained results were compared with R (relative sunspot numbers) in the ranges of 0-30R, 40-100R, and 140-190R. It was shown, that the amplitude of semi-annual variation increases with R, from minimum to maximum values, on average by 45%. At equatorial Huancayo observatory, the semi-annual Sq(H)-variation appears especially clearly: its maximums take place at periods of equinoxes (March-April, September-October), and minimums -- at periods of solstices (June-July, December-January). At low (Apia observatory) and middle (Moscow observatory) latitudes, the character of semi-annual variation is somewhat different: it appears during the periods of equinoxes, but considerably less than at equator. Besides, with the growth of R, semi-annual variation appears against a background of annual variation, in the form of second peaks (maximum in June). At observatories located in low and middle latitudes, second peaks become more appreciable with an increase of R (March-April and September-October). During the periods of low solar activity, they are insignificant. This work has been carried out with the support from International Scientific and Technology Center (Project #KR-214).

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...

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.

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

Science.gov (United States)

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...

Flood frequency analysis for nonstationary annual peak records in an urban drainage basin

Science.gov (United States)

Villarini, G.; Smith, J.A.; Serinaldi, F.; Bales, J.; Bates, P.D.; Krajewski, W.F.

2009-01-01

Flood frequency analysis in urban watersheds is complicated by nonstationarities of annual peak records associated with land use change and evolving urban stormwater infrastructure. In this study, a framework for flood frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary conditions. GAMLSS is applied to annual maximum peak discharge records for Little Sugar Creek, a highly urbanized watershed which drains the urban core of Charlotte, North Carolina. It is shown that GAMLSS is able to describe the variability in the mean and variance of the annual maximum peak discharge by modeling the parameters of the selected parametric distribution as a smooth function of time via cubic splines. Flood frequency analyses for Little Sugar Creek (at a drainage area of 110 km2) show that the maximum flow with a 0.01-annual probability (corresponding to 100-year flood peak under stationary conditions) over the 83-year record has ranged from a minimum unit discharge of 2.1 m3 s- 1 km- 2 to a maximum of 5.1 m3 s- 1 km- 2. An alternative characterization can be made by examining the estimated return interval of the peak discharge that would have an annual exceedance probability of 0.01 under the assumption of stationarity (3.2 m3 s- 1 km- 2). Under nonstationary conditions, alternative definitions of return period should be adapted. Under the GAMLSS model, the return interval of an annual peak discharge of 3.2 m3 s- 1 km- 2 ranges from a maximum value of more than 5000 years in 1957 to a minimum value of almost 8 years for the present time (2007). The GAMLSS framework is also used to examine the links between population trends and flood frequency, as well as trends in annual maximum rainfall. These analyses are used to examine evolving flood frequency over future decades. ?? 2009 Elsevier Ltd.

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...

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...

Annual environmental monitoring report, January--December 1977

International Nuclear Information System (INIS)

1978-05-01

Environmental monitoring results continue to demonstrate that, except for penetrating radiation, environmental radiological impact due to SLAC operation is not distinguishable from natural environmantal sources. During 1977, the maximum neutron dose near the site boundary was 8.2 mrem. This represents about 8.2% of the annual dose from natural sources at this elevation, and 1.6% of the technical standard of 500 mrem per person annually

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.

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...

Assessing Land Degradation/Recovery in the African Sahel from Long-Term Earth Observation Based Primary Productivity and Precipitation Relationships

DEFF Research Database (Denmark)

Fensholt, Rasmus; Rasmussen, Kjeld; Kaspersen, Per Skougaard

2013-01-01

degradation. Consequently, RUE may be regarded as means of normalizing ANPP for the impact of annual precipitation, and as an indicator of non-precipitation related land degradation. Large scale and long term identification and monitoring of land degradation in drylands, such as the Sahel, can only......The ‘rain use efficiency’ (RUE) may be defined as the ratio of above-ground net primary productivity (ANPP) to annual precipitation, and it is claimed to be a conservative property of the vegetation cover in drylands, if the vegetation cover is not subject to non-precipitation related land...... useless as a means of normalizing for the impact of annual precipitation on ANPP. By replacing ΣNDVI by a ‘small NDVI integral’, covering only the rainy season and counting only the increase of NDVI relative to some reference level, this problem is solved. Using this approach, RUE is calculated...

Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

Science.gov (United States)

Mandal, S.; Choudhury, B. U.

2015-07-01

Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

Impacts of updated green vegetation fraction data on WRF simulations of the 2006 European heat wave

Science.gov (United States)

Refslund, J.; Dellwik, E.; Hahmann, A. N.; Barlage, M. J.; Boegh, E.

2012-12-01

Climate change studies suggest an increase in heat wave occurrences over Europe in the coming decades. Extreme events with excessive heat and associated drought will impact vegetation growth and health and lead to alterations in the partitioning of the surface energy. In this study, the atmospheric conditions during the heat wave year 2006 over Europe were simulated using the Weather Research and Forecasting (WRF) model. To account for the drought effects on the vegetation, new high-resolution green vegetation fraction (GVF) data were developed for the domain using NDVI data from MODIS satellite observations. Many empirical relationships exist to convert NDVI to GVF and both a linear and a quadratic formulation were evaluated. The new GVF product has a spatial resolution of 1 km2 and a temporal resolution of 8 days. To minimize impacts from low-quality satellite retrievals in the NDVI series, as well as for comparison with the default GVF climatology in WRF, a new background climatology using 10 recent years of observations was also developed. The annual time series of the new GVF climatology was compared to the default WRF GVF climatology at 18 km2 grid resolution for the most common land use classes in the European domain. The new climatology generally has higher GVF levels throughout the year, in particular an extended autumnal growth season. Comparison of 2006 GVF with the climatology clearly indicates vegetation stresses related to heat and drought. The GVF product based on a quadratic NDVI relationship shows the best agreement with the magnitude and annual range of the default input data, in addition to including updated seasonality for various land use classes. The new GVF products were tested in WRF and found to work well for the spring of 2006 where the difference between the default and new GVF products was small. The WRF 2006 heat wave simulations were verified by comparison with daily gridded observations of mean, minimum and maximum temperature and

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.

Changes in Vegetation Growth Dynamics and Relations with Climate over China’s Landmass from 1982 to 2011

Directory of Open Access Journals (Sweden)

Guang Xu

2014-04-01

Full Text Available Understanding how the dynamics of vegetation growth respond to climate change at different temporal and spatial scales is critical to projecting future ecosystem dynamics and the adaptation of ecosystems to global change. In this study, we investigated vegetated growth dynamics (annual productivity, seasonality and the minimum amount of vegetated cover in China and their relations with climatic factors during 1982–2011, using the updated Global Inventory Modeling and Mapping Studies (GIMMS third generation global satellite Advanced Very High Resolution Radiometer (AVHRR Normalized Difference Vegetation Index (NDVI dataset and climate data acquired from the National Centers for Environmental Prediction (NCEP. Major findings are as follows: (1 annual mean NDVI over China significantly increased by about 0.0006 per year from 1982 to 2011; (2 of the vegetated area in China, over 33% experienced a significant positive trend in vegetation growth, mostly located in central and southern China; about 21% experienced a significant positive trend in growth seasonality, most of which occurred in northern China (>35°N; (3 changes in vegetation growth dynamics were significantly correlated with air temperature and precipitation (p < 0.001 at a region scale; (4 at the country scale, changes in NDVI was significantly and positively correlated with annual air temperature (r = 0.52, p < 0.01 and not associated with annual precipitation (p > 0.1; (5 of the vegetated area, about 24% showed significant correlations between annual mean NDVI and air temperature (93% positive and remainder negative, and 12% showed significant correlations of annual mean NDVI with annual precipitation (65% positive and 35% negative. The spatiotemporal variations in vegetation growth dynamics were controlled primarily by temperature and secondly by precipitation. Vegetation growth was also affected by human activities; and (6 monthly NDVI was significantly correlated with the

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...

Probabilistic properties of the date of maximum river flow, an approach based on circular statistics in lowland, highland and mountainous catchment

Science.gov (United States)

Rutkowska, Agnieszka; Kohnová, Silvia; Banasik, Kazimierz

2018-04-01

Probabilistic properties of dates of winter, summer and annual maximum flows were studied using circular statistics in three catchments differing in topographic conditions; a lowland, highland and mountainous catchment. The circular measures of location and dispersion were used in the long-term samples of dates of maxima. The mixture of von Mises distributions was assumed as the theoretical distribution function of the date of winter, summer and annual maximum flow. The number of components was selected on the basis of the corrected Akaike Information Criterion and the parameters were estimated by means of the Maximum Likelihood method. The goodness of fit was assessed using both the correlation between quantiles and a version of the Kuiper's and Watson's test. Results show that the number of components varied between catchments and it was different for seasonal and annual maxima. Differences between catchments in circular characteristics were explained using climatic factors such as precipitation and temperature. Further studies may include circular grouping catchments based on similarity between distribution functions and the linkage between dates of maximum precipitation and maximum flow.

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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).

Science.gov (United States)

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

Science.gov (United States)

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

Science.gov (United States)

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.

Fodder Biomass Monitoring in Sahelian Rangelands Using Phenological Metrics from FAPAR Time Series

DEFF Research Database (Denmark)

Diouf, Abdoul Aziz; Brandt, Martin Stefan; Verger, Aleixandre

2015-01-01

Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI) and in situ biomass data....... This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and in situ biomass. A model with three variables—large seasonal integral (LINTG), length of growing season......, and end of season decreasing rate—performed best (MAE = 605 kg·DM/ha; R2 = 0.68) across Sahelian ecosystems in Senegal (data for the period 1999–2013). A model with annual maximum (PEAK) and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64), allowing a timely estimation...

Fodder Biomass Monitoring in Sahelian Rangelands Using Phenological Metrics from FAPAR Time Series

Directory of Open Access Journals (Sweden)

Abdoul Aziz Diouf

2015-07-01

Full Text Available Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI and in situ biomass data. This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR and in situ biomass. A model with three variables—large seasonal integral (LINTG, length of growing season, and end of season decreasing rate—performed best (MAE = 605 kg·DM/ha; R2 = 0.68 across Sahelian ecosystems in Senegal (data for the period 1999–2013. A model with annual maximum (PEAK and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64, allowing a timely estimation of forage availability. The subdivision of the study area in ecoregions increased overall accuracy (MAE = 489.21 kg·DM/ha; R2 = 0.77, indicating that a relation between metrics and ecosystem properties exists. LINTG was the main explanatory variable for woody rangelands with high leaf biomass, whereas for areas dominated by herbaceous vegetation, it was the PEAK metric. The proposed approach outperformed the established biomass NDVI-based product (MAE = 818 kg·DM/ha and R2 = 0.51 and should improve the operational monitoring of forage resources in Sahelian rangelands.

Latitudinal Change of Tropical Cyclone Maximum Intensity in the Western North Pacific

OpenAIRE

Choi, Jae-Won; Cha, Yumi; Kim, Hae-Dong; Kang, Sung-Dae

2016-01-01

This study obtained the latitude where tropical cyclones (TCs) show maximum intensity and applied statistical change-point analysis on the time series data of the average annual values. The analysis results found that the latitude of the TC maximum intensity increased from 1999. To investigate the reason behind this phenomenon, the difference of the average latitude between 1999 and 2013 and the average between 1977 and 1998 was analyzed. In a difference of 500 hPa streamline between the two ...

Trends and annual cycles in soundings of Arctic tropospheric ozone

Science.gov (United States)

Christiansen, Bo; Jepsen, Nis; Kivi, Rigel; Hansen, Georg; Larsen, Niels; Smith Korsholm, Ulrik

2017-08-01

Ozone soundings from nine Nordic stations have been homogenized and interpolated to standard pressure levels. The different stations have very different data coverage; the longest period with data is from the end of the 1980s to 2014. At each pressure level the homogenized ozone time series have been analysed with a model that includes both low-frequency variability in the form of a polynomial, an annual cycle with harmonics, the possibility for low-frequency variability in the annual amplitude and phasing, and either white noise or noise given by a first-order autoregressive process. The fitting of the parameters is performed with a Bayesian approach not only giving the mean values but also confidence intervals. The results show that all stations agree on a well-defined annual cycle in the free troposphere with a relatively confined maximum in the early summer. Regarding the low-frequency variability, it is found that Scoresbysund, Ny Ålesund, Sodankylä, Eureka, and Ørland show similar, significant signals with a maximum near 2005 followed by a decrease. This change is characteristic for all pressure levels in the free troposphere. A significant change in the annual cycle was found for Ny Ålesund, Scoresbysund, and Sodankylä. The changes at these stations are in agreement with the interpretation that the early summer maximum is appearing earlier in the year. The results are shown to be robust to the different settings of the model parameters such as the order of the polynomial, number of harmonics in the annual cycle, and the type of noise.

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

Directory of Open Access Journals (Sweden)

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.

Annual environmental monitoring report, January--December 1976

International Nuclear Information System (INIS)

1977-05-01

Environmental monitoring results continue to demonstrate that, except for penetrating radiation, environmental radiological impact due to SLAC operation is not distinguishable from natural environmental sources. During 1976 the maximum neutron dose near the site boundary was 3.4 mrem. This represents about 3.4% of the annual dose from natural sources at this elevation and 0.68% of the technical standard of 500 mrem per person annually. There have been no measurable increases in radioactivity in ground water attributable to SLAC operations. Airborne radioactivity released from SLAC also continues to make only a negligible environmental impact and result in a site boundary annual dose of less than 0.01 mrem, which represents less than 0.01% of the annual dose from the natural radiation environment and about 0.002% of the technical standard

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)

Science.gov (United States)

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).

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

Directory of Open Access Journals (Sweden)

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

Trends and annual cycles in soundings of Arctic tropospheric ozone

Directory of Open Access Journals (Sweden)

B. Christiansen

2017-08-01

Full Text Available Ozone soundings from nine Nordic stations have been homogenized and interpolated to standard pressure levels. The different stations have very different data coverage; the longest period with data is from the end of the 1980s to 2014. At each pressure level the homogenized ozone time series have been analysed with a model that includes both low-frequency variability in the form of a polynomial, an annual cycle with harmonics, the possibility for low-frequency variability in the annual amplitude and phasing, and either white noise or noise given by a first-order autoregressive process. The fitting of the parameters is performed with a Bayesian approach not only giving the mean values but also confidence intervals. The results show that all stations agree on a well-defined annual cycle in the free troposphere with a relatively confined maximum in the early summer. Regarding the low-frequency variability, it is found that Scoresbysund, Ny Ålesund, Sodankylä, Eureka, and Ørland show similar, significant signals with a maximum near 2005 followed by a decrease. This change is characteristic for all pressure levels in the free troposphere. A significant change in the annual cycle was found for Ny Ålesund, Scoresbysund, and Sodankylä. The changes at these stations are in agreement with the interpretation that the early summer maximum is appearing earlier in the year. The results are shown to be robust to the different settings of the model parameters such as the order of the polynomial, number of harmonics in the annual cycle, and the type of noise.

Annual environmental monitoring report, January--December 1975

International Nuclear Information System (INIS)

1976-04-01

Environmental monitoring results continue to demonstrate that, except for penetrating radiation, environmental radiological impact due to SLAC operation is not distinguishable from natural environmental sources. During 1975 the maximum neutron dose near the site boundary was 15.8 mrem. This represents about 16 percent of the annual dose from natural sources at this elevation and 3.2 percent of the technical standard of 500 mrem per person annually. There have been no measurable increases in radioactivity in ground water attributable to SLAC operations. Airborne radioactivity released from SLAC also continues to make only a negligible environmental impact and results in a site boundary annual dose of less than 2.4 mrem, which represents less than 2.4 percent of the annual dose from the natural radiation environment and about 0.5 percent of the technical standard

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...

Modeling mangrove biomass using remote sensing based age and growth estimates

Science.gov (United States)

Lagomasino, D.; Fatoyinbo, T. E.; Feliciano, E. A.; Lee, S. K.; Trettin, C.; Mangora, M.; Rahman, M.

2016-12-01

Mangroves are highly regarded coastal forests because of their ecosystem services and high carbon storage potential. In addition, these forests can develop rapidly in locations where congenial environmental conditions and sediment supply are available. Monitoring the growth and age of developing mangrove forests is crucial for sustainable management and estimating carbon stocks. Combining imagery from radar and optical satellites (e.g., TanDEM-X and Landsat), we can estimate young mangrove growth and age at regional and continental scales. We used TanDEM-X radar interferometry for modeling canopy height in 2013 and Landsat to measure land cover change from 1990 to 2013. Annual NDVI composites were determined for each calendar year between 1990 and 2013. New land areas gained from the transition of water to vegetation were determined by the differences in annual NDVI composites and the reference year 2013. The year of the greatest NDVI difference that met the threshold criteria was used as the initial tree height (0 m). Annual canopy height growth rates were estimated by the duration between land generation times and 2013 canopy height models derived from TanDEM-X and very-high resolution optical data. In this presentation, we compare growth rates and biomass accumulation in mangrove forests at four river deltas; the Zambezi (Mozambique), Rufiji (Tanzania), Ganges (Bangladesh), and Mekong (Vietnam). The spatial patterns of growth rates coincided with characteristic successional paradigms and stream morphology, where the maximum growth rates typically occurred along prograding creek banks. Initial comparisons between height-only and growth-age biomass indicate that the latter tend to overestimate biomass for younger forest stands of similar height. Both the vertical (e.g., canopy height) and horizontal (e.g., expansion) growth rates measured from remote sensing can garner important information regarding mangrove succession and primary productivity. Continued research

Annual plan, December 1999

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-07-01

This annual plan is being provided as required under Section 'D' of the Alberta Energy and Utilities Board Information Letter IL 90-8. The objective is to provide the Board, NOVA Gas Transmission (NGTL) customers and other interested parties with a comprehensive overview of NOVA Gas Transmission's pipeline system expansion plans for the gas year 2000/ 2001, and the winter season of the 2001/2002 gas year. The plan includes descriptions of NGTL's design assumptions and criteria, as well as long term outlook for field deliverability, productive capability, gas deliveries, proposed facility additions, capital expenditures, revenue requirements and firm service demand rates. Major factors affecting the facility requirements for the period under consideration are a decrease in the maximum day delivery volume at the Empress border point, an increase in intra-Alberta maximum day delivery volumes and associated decline in productive capability. Chapter One of the Plan describes the the Annual Plan process itself; Chapter Two is devoted to a discussion of facilities design methodology; Chapter Three deals with economic assumptions; Chapter Four describes design flow, while Chapters Five and Six outline the mainline , meter stations, laterals, and lateral loops facility requirements. Chapter Seven provides and overview of the capital and financial forecasts. tabs., figs.

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

Science.gov (United States)

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.

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.

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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

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.

Modelling maximum river flow by using Bayesian Markov Chain Monte Carlo

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Cheong, R. Y.; Gabda, D.

2017-09-01

Analysis of flood trends is vital since flooding threatens human living in terms of financial, environment and security. The data of annual maximum river flows in Sabah were fitted into generalized extreme value (GEV) distribution. Maximum likelihood estimator (MLE) raised naturally when working with GEV distribution. However, previous researches showed that MLE provide unstable results especially in small sample size. In this study, we used different Bayesian Markov Chain Monte Carlo (MCMC) based on Metropolis-Hastings algorithm to estimate GEV parameters. Bayesian MCMC method is a statistical inference which studies the parameter estimation by using posterior distribution based on Bayes’ theorem. Metropolis-Hastings algorithm is used to overcome the high dimensional state space faced in Monte Carlo method. This approach also considers more uncertainty in parameter estimation which then presents a better prediction on maximum river flow in Sabah.

The estimation of probable maximum precipitation: the case of Catalonia.

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Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel

2008-12-01

A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.

Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

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Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

2001-08-01

An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

Vegetation Activity Trend and Its Relationship with Climate Change in the Three Gorges Area, China

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Guifeng Han

2013-01-01

Full Text Available Based on SPOT/VGT NDVI time series images from 1999 to 2009 in the Three Gorges Area (TGA, we detected vegetation activity and trends using two methods, the Mann-Kendall and Slope tests. The relationships between vegetation activity trends and annual average temperature and annual total precipitation were analyzed using observational data in seven typical meteorological stations. Vegetation activity presents a distinctive uptrend during the study period, especially in Fengjie, Yunyang, Wushan, Wuxi, and Badong counties located in the midstream of the Three Gorges Reservoir. However, in the Chongqing major area (CMA and its surrounding areas and Fuling, Yichang, and part of Wanzhou, vegetation activity shows a decreasing trend as a result of urban expansion. The NDVI has two fluctuation troughs in 2004 and 2006. The annual mean temperature presents a slight overall upward trend, but the annual total precipitation does not present a significant trend. And they almost have no significant correlations with the NDVI. Therefore, temperature and precipitation are not major influences on vegetation activity change. Instead, increasing vegetation cover benefits from a number of environment protection policies and management, and ecological construction is a major factor resulting in the upward trend. In addition, resettlement schemes mitigate the impact of human activity on vegetation activity.

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)

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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.

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

Analyzing temporal changes in maximum runoff volume series of the Danube River

International Nuclear Information System (INIS)

Halmova, Dana; Pekarova, Pavla; Onderka, Milan; Pekar, Jan

2008-01-01

Several hypotheses claim that more extremes in climatic and hydrologic phenomena are anticipated. In order to verify such hypotheses it is inevitable to examine the past periods by thoroughly analyzing historical data. In the present study, the annual maximum runoff volumes with t-day durations were calculated for a 130-year series of mean daily discharge of Danube River at Bratislava gauge (Slovakia). Statistical methods were used to clarify how the maximum runoff volumes of the Danube River changed over two historical periods (1876-1940 and 1941-2005). The conclusion is that the runoff volume regime during floods has not changed significantly during the last 130 years.

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.

Modeling the impacts of phenological and inter-annual changes in landscape metrics on local biodiversity of agricultural lands of Eastern Ontario using multi-spatial and multi-temporal remote sensing data

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Alavi-Shoushtari, N.; King, D.

2017-12-01

Agricultural landscapes are highly variable ecosystems and are home to many local farmland species. Seasonal, phenological and inter-annual agricultural landscape dynamics have potential to affect the richness and abundance of farmland species. Remote sensing provides data and techniques which enable monitoring landscape changes in multiple temporal and spatial scales. MODIS high temporal resolution remote sensing images enable detection of seasonal and phenological trends, while Landsat higher spatial resolution images, with its long term archive enables inter-annual trend analysis over several decades. The objective of this study to use multi-spatial and multi-temporal remote sensing data to model the response of farmland species to landscape metrics. The study area is the predominantly agricultural region of eastern Ontario. 92 sample landscapes were selected within this region using a protocol designed to maximize variance in composition and configuration heterogeneity while controlling for amount of forest and spatial autocorrelation. Two sample landscape extents (1×1km and 3×3km) were selected to analyze the impacts of spatial scale on biodiversity response. Gamma diversity index data for four taxa groups (birds, butterflies, plants, and beetles) were collected during the summers of 2011 and 2012 within the cropped area of each landscape. To extract the seasonal and phenological metrics a 2000-2012 MODIS NDVI time-series was used, while a 1985-2012 Landsat time-series was used to model the inter-annual trends of change in the sample landscapes. The results of statistical modeling showed significant relationships between farmland biodiversity for several taxa and the phenological and inter-annual variables. The following general results were obtained: 1) Among the taxa groups, plant and beetles diversity was most significantly correlated with the phenological variables; 2) Those phenological variables which are associated with the variability in the start of

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.

Applying ARIMA model for annual volume time series of the Magdalena River

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Gloria Amaris

2017-04-01

Conclusions: The simulated results obtained with the ARIMA model compared to the observed data showed a fairly good adjustment of the minimum and maximum magnitudes. This allows concluding that it is a good tool for estimating minimum and maximum volumes, even though this model is not capable of simulating the exact behaviour of an annual volume time series.

Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland.

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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

Annual environmental monitoring report, January-December 1982

International Nuclear Information System (INIS)

1983-03-01

Environmental monitoring results continue to demonstrate that environmental radiological impact due to SLAC operation is not distinguishable from natural environmental sources. During 1982, the maximum measured neutron dose near the site boundary was not distinguishable from the cosmic ray neutron background. There have been no measurable increases in radioactivity in ground water attributable to SLAC operations since operation began in 1966. Airborne radioactivity released from SLAC continues to make only a negligible environmental impact, and results in a site boundary annual dose of less than 0.3 mrem; this represents less than 0.3% of the annual dose from the natural radiation environment, and about 0.06% of the technical standard

Annual environmental monitoring report, January--December 1978

International Nuclear Information System (INIS)

1979-04-01

Environmental monitoring results continue to demonstrate that, except for penetrating radiation, environmental radiological impact due to SLAC operation is not distinguishable from natural environmental sources. During 1978, the maximum neutron dose near the site boundary was 6.6 mrem. This represents about 6.6% of the annual dose from natural sources at this elevation, and 1.3% of the technical standard of 500 mrem per person annually. There have been no measurable increases in radioactivity in ground water attributable to SLAC operations since 1966. Because of major new construction, well water samples were not collected and analyzed during 1978. Construction activities have also temporarily placed our sampling stations for the sanitary and storm sewers out of service. They will be re-established as soon as construction activities permit. Airborne radioactivity released from SLAC continues to make only a negligible environmental impact, and results in a site boundary annual dose of less than 0.01 mrem; this represents less than 0.01% of the annual dose from the natural radiation environment, and about 0.002% of the technical standard

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

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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.

Mapping Annual Precipitation across Mainland China in the Period 2001–2010 from TRMM3B43 Product Using Spatial Downscaling Approach

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Yuli Shi

2015-05-01

Full Text Available Spatially explicit precipitation data is often responsible for the prediction accuracy of hydrological and ecological models. Several statistical downscaling approaches have been developed to map precipitation at a high spatial resolution, which are mainly based on the valid conjugations between satellite-driven precipitation data and geospatial predictors. Performance of the existing approaches should be first evaluated before applying them to larger spatial extents with a complex terrain across different climate zones. In this paper, we investigate the statistical downscaling algorithms to derive the high spatial resolution maps of precipitation over continental China using satellite datasets, including the Normalized Distribution Vegetation Index (NDVI from the Moderate Resolution Imaging Spectroradiometer (MODIS, the Global Digital Elevation Model (GDEM from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, and the rainfall product from the Tropical Rainfall Monitoring Mission (TRMM. We compare three statistical techniques (multiple linear regression, exponential regression, and Random Forest regression trees for modeling precipitation to better understand how the selected model types affect the prediction accuracy. Then, those models are implemented to downscale the original TRMM product (3B43; 0.25° resolution onto the finer grids (1 × 1 km2 of precipitation. Finally we validate the downscaled annual precipitation (a wet year 2001 and a dry year 2010 against the ground rainfall observations from 596 rain gauge stations over continental China. The result indicates that the downscaling algorithm based on the Random Forest regression outperforms, when compared to the linear regression and the exponential regression. It also shows that the addition of the residual terms does not significantly improve the accuracy of results for the RF model. The analysis of the variable importance reveals the NDVI related predictors

Variation in Phenometric Lapse Rates in Pasture Resources across Four Rayons in Kyrgyzstan

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Henebry, G. M.; Tomaszewska, M. A.; Kelgenbaeva, K.

2017-12-01

High elevation pasture resources form the foundation of agro-pastoralist livelihoods in Kyrgyzstan and elsewhere in montane Central Asia. We explore the temporal and the topographical variation in phenometric lapse rates (PLRs: the change in a phenometric as a function of elevation) across four rayons in two oblasts of the Kyrgyz Republic—Alay, At-Bashy, Chong Alay, and Naryn—with the aim of identifying and quantifying robust generic patterns in the PLRs. We evaluate two fundamental phenometrics derived from the downward convex quadratic model of land surface phenology that links the NDVI to accumulated growing degree-day (AGDD). The peak height (PH) is the maximum NDVI value obtained from the fitted model. The thermal time to peak (TTP) is the amount of AGDD required to reach the PH. We fitted sixteen years of Landsat NDVI data at 30 m spatial resolution to annual AGDD progressions derived from MODIS land surface temperature time series at 1 km spatial resolution, yielding maps for each phenometric. If the coefficient of determination was less than 0.5, then the model fit was deemed a failure. We classified the reliability of pasture resources into five classes based on the number of years of successful model fit: very persistent (14-16 y); persistent (11-13 y); marginal (7-10 y); occasional (4-6); and rare (1-3). We explore the interactive roles of elevation, slope, aspect, latitude, and rayon on the PLRs and pasture resource persistence to identify critical areas for resource management.

Close relationship between spectral vegetation indices and Vcmax in deciduous and mixed forests

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Yanlian Zhou

2014-04-01

Full Text Available Seasonal variations of photosynthetic capacity parameters, notably the maximum carboxylation rate, Vcmax, play an important role in accurate estimation of CO2 assimilation in gas-exchange models. Satellite-derived normalised difference vegetation index (NDVI, enhanced vegetation index (EVI and model-data fusion can provide means to predict seasonal variation in Vcmax. In this study, Vcmax was obtained from a process-based model inversion, based on an ensemble Kalman filter (EnKF, and gross primary productivity, and sensible and latent heat fluxes measured using eddy covariance technique at two deciduous broadleaf forest sites and a mixed forest site. Optimised Vcmax showed considerable seasonal and inter-annual variations in both mixed and deciduous forest ecosystems. There was noticeable seasonal hysteresis in Vcmax in relation to EVI and NDVI from 8 d composites of satellite data during the growing period. When the growing period was phenologically divided into two phases (increasing VIs and decreasing VIs phases, significant seasonal correlations were found between Vcmax and VIs, mostly showing R2>0.95. Vcmax varied exponentially with increasing VIs during the first phase (increasing VIs, but second and third-order polynomials provided the best fits of Vcmax to VIs in the second phase (decreasing VIs. The relationships between NDVI and EVI with Vcmax were different. Further efforts are needed to investigate Vcmax–VIs relationships at more ecosystem sites to the use of satellite-based VIs for estimating Vcmax.

Assessing satellite-based start-of-season trends in the US High Plains

International Nuclear Information System (INIS)

Lin, X; Sassenrath, G F; Hubbard, K G; Mahmood, R

2014-01-01

To adequately assess the effects of global warming it is necessary to address trends and impacts at the local level. This study examines phenological changes in the start-of-season (SOS) derived from satellite observations from 1982–2008 in the US High Plains region. The surface climate-based SOS was also evaluated. The averaged profiles of SOS from 37° to 49°N latitude by satellite- and climate-based methods were in reasonable agreement, especially for areas where croplands were masked out and an additional frost date threshold was adopted. The statistically significant trends of satellite-based SOS show a later spring arrival ranging from 0.1 to 4.9 days decade −1 over nine Level III ecoregions. We found the croplands generally exhibited larger trends (later arrival) than the non-croplands. The area-averaged satellite-based SOS for non-croplands (i.e. mostly grasslands) showed no significant trends. We examined the trends of temperatures, precipitation, and standardized precipitation index (SPI), as well as the strength of correlation between the satellite-based SOS and these climatic drivers. Our results indicate that satellite-based SOS trends are spatially and primarily related to annual maximum normalized difference vegetation index (NDVI, mostly in summertime) and/or annual minimum NDVI (mostly in wintertime) and these trends showed the best correlation with six-month SPI over the period 1982–2008 in the US High Plains region. (letter)

Use of Current 2010 Forest Disturbance Monitoring Products for the Conterminous United States in Aiding a National Forest Threat Early Warning System

Science.gov (United States)

Spruce, Joseph P.; Hargrove, William; Gasser, J.; Smoot, J.; Kuper, P.

2010-01-01

This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009,. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

Dynamic variability of the heading-flowering stages of single rice in China based on field observations and NDVI estimations.

Science.gov (United States)

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.

Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois

Science.gov (United States)

Over, Thomas M.; Saito, Riki J.; Veilleux, Andrea G.; Sharpe, Jennifer B.; Soong, David T.; Ishii, Audrey L.

2016-06-28

This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged

Annual and inter-annual variations of 6.5-day-planetary-waves in MLT observed by TIMED/SABER

Science.gov (United States)

Huang, Yingying; Li, Huijun; Li, Chongyin; Zhang, Shaodong

2017-04-01

Annual and inter-annual variations of 6.5DWs in 20-110 km, 52°S-52°N, 2002-2016 are studied by using v2.0 TIMED/SABER kinetic temperature data. Firstly, global annual variations of 6.5DW's spectral power and amplitudes are obtained. Strong wave amplitudes emerge in 30°S/N-50°S/N, and peaks in altitude separate in stratosphere (40-50 km), mesosphere (80-90 km) and the lower thermosphere (100-110 km), respectively. Their annual variations are similar in both hemispheres, but different in altitude. In 40-50 km, the annual maximums emerge mostly in winters: Dec.-Jan. in the NH and Jul.-Aug. in the SH. In MLT, annual peaks arise twice in each half of year. In 80-90 km, they're mainly in equinoctial seasons and winters: May, Aug.-Sep. and Jan. in the NH and Feb., Nov. and May in the SH. In 100-110 km, they emerge mainly in equinoctial seasons: Apr.-May and Aug.-Sep. in the NH and Feb.-Mar. and Oct.-Nov. in the SH. Then, inter-annual variations of 6.5DW amplitudes during the 14-year period are studied. Frequency spectra of monthly-mean amplitudes show that, main dynamics in long-term variations of 6.5DWs are AO and SAO in both hemispheres. Besides, QBO are visible in both hemispheres and 4-month period signals are noticed in the NH in MLT. Amplitudes of SAO, AO and QBO are obtained by bandpass filter. Their amplitudes are comparable in stratosphere and mesosphere, and QBO signals are weaker than the others in the LT. Vertical variations both of SAO and AO amplitudes are very stable. AO structures have little inter-annual changes, while inter-annual variations of SAO are significant and are related with 6.5DW. It means that annual and inter-annual variations of 6.5DW are mainly controlled by AO and SAO, respectively. Although QBO signals are weaker and their variations are less regular than AO and SAO, their phases seems to relate with inter-annual variations of 6.5DW as well.

Beyond Precipitation: Physiographic Gradients Dictate the Relative Importance of Environmental Drivers on Savanna Vegetation

Science.gov (United States)

Campo-Bescós, Miguel A.; Muñoz-Carpena, Rafael; Kaplan, David A.; Southworth, Jane; Zhu, Likai; Waylen, Peter R.

2013-01-01

Background Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. Methodology/Principal Findings We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation950 mm). Conclusions/Significance We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for

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

Annual and semiannual variations of the cosmic radiation

International Nuclear Information System (INIS)

Khor, H.P.; Kwok, W.K.; Owens, A.J.

1979-01-01

We determine the annual and semiannual harmonics in the Deep River Neutron Monitor counting rate for the years 1960--1975. A new Fourier analysis technique is used to eliminate solar cycle variations, an we discuss the statistical errors in the determination of the harmonics. The annual and semiannual waves changed markedly from year to year. The yearly harmonic has an average amplitude approx.0.6% with a maximum in early March, corresponding to a southward anisotropy of approx.5%/AU perpendicular to the solar equatorial plane. The semiannual harmonic shows no phase coherence and its average amplitude is only marginally significant, < or approx. =0.2%

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.

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

Science.gov (United States)

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

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Directory of Open Access Journals (Sweden)

César da Silva Chagas

2013-04-01

Full Text Available Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI, derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs was greater than of the classic Maximum Likelihood Classifier (MLC. Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 % was superior to the MLC map (57.94 %. The main errors when using the two classifiers were caused by: a the geological heterogeneity of the area coupled with problems related to the geological map; b the depth of lithic contact and/or rock exposure, and c problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

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.

MONITORAMENTO DE SECAS NA BRETANHA reconstituição histórica e abordagem por teledetecção

Directory of Open Access Journals (Sweden)

Vincent Dubreuil

2010-01-01

Full Text Available Brittany, as many French territories, experiences sometimes drought issues which can vary in intensity and duration. The aim of this study is to determine the impacts of droughts on soil water resources since the early XIXth century. Thus, a soil water balance suited to regional scales was used and applied to different cities of Brittany and surroundings such as Rennes, Plougonvelin and Nantes. The evaporation defi ciency obtained at a monthly scale revealed droughts intensity and inter-annual variability. At a yearly scale a positive tendency of the defi ciency was noticed. At a monthly scale the inter-annual variability was clearly shown and revealed a 4-year period rhythm with soils lacking of water for one summer month. Finally, we used the NDVI calculated from SPOT-Vegetation images for monitoring the spatial extent of drought in Brittany. For 2003 (the last great drought observed in western France, we found a good relationship between the NDVI and the evapotranspiration but bidirectional refl ectance effects, angular values and compositing's procedures may also have a great impact on observed values of NDVI.

Maximum skin dose assessment in interventional cardiology: large area detectors and calculation methods

International Nuclear Information System (INIS)

Quail, E.; Petersol, A.

2002-01-01

Advances in imaging technology have facilitated the development of increasingly complex radiological procedures for interventional radiology. Such interventional procedures can involve significant patient exposure, although often represent alternatives to more hazardous surgery or are the sole method for treatment. Interventional radiology is already an established part of mainstream medicine and is likely to expand further with the continuing development and adoption of new procedures. Between all medical exposures, interventional radiology is first of the list of the more expansive radiological practice in terms of effective dose per examination with a mean value of 20 mSv. Currently interventional radiology contribute 4% to the annual collective dose, in spite of contributing to total annual frequency only 0.3% but considering the perspectives of this method can be expected a large expansion of this value. In IR procedures the potential for deterministic effects on the skin is a risk to be taken into account together with stochastic long term risk. Indeed, the International Commission on Radiological Protection (ICRP) in its publication No 85, affirms that the patient dose of priority concern is the absorbed dose in the area of skin that receives the maximum dose during an interventional procedure. For the mentioned reasons, in IR it is important to give to practitioners information on the dose received by the skin of the patient during the procedure. In this paper maximum local skin dose (MSD) is called the absorbed dose in the area of skin receiving the maximum dose during an interventional procedure

Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates

Directory of Open Access Journals (Sweden)

M. Ardyna

2013-06-01

Full Text Available Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC. In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs that significantly contribute to primary production (PP are often observed. These are neither detected by ocean color sensors nor accounted for in the primary production models applied to the Arctic Ocean. Here, we assemble a large database of pan-Arctic observations (i.e., 5206 stations and develop an empirical model to estimate vertical chlorophyll a (Chl a according to (1 the shelf–offshore gradient delimited by the 50 m isobath, (2 seasonal variability along pre-bloom, post-bloom, and winter periods, and (3 regional differences across ten sub-Arctic and Arctic seas. Our detailed analysis of the dataset shows that, for the pre-bloom and winter periods, as well as for high surface Chl a concentration (Chl asurf; 0.7–30 mg m−3 throughout the open water period, the Chl a maximum is mainly located at or near the surface. Deep SCMs occur chiefly during the post-bloom period when Chl asurf is low (0–0.5 mg m−3. By applying our empirical model to annual Chl asurf time series, instead of the conventional method assuming vertically homogenous Chl a, we produce novel pan-Arctic PP estimates and associated uncertainties. Our results show that vertical variations in Chl a have a limited impact on annual depth-integrated PP. Small overestimates found when SCMs are shallow (i.e., pre-bloom, post-bloom > 0.7 mg m−3, and the winter period somehow compensate for the underestimates found when SCMs are deep (i.e., post-bloom −3. SCMs are, however, important seasonal features with a substantial impact on depth-integrated PP estimates, especially when surface nitrate is exhausted in the Arctic Ocean and where highly stratified and oligotrophic conditions prevail.

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

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)

[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.

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

Directory of Open Access Journals (Sweden)

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 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

Application of maximum values for radiation exposure and principles for the calculation of radiation dose

International Nuclear Information System (INIS)

2000-01-01

The guide sets out the mathematical definitions and principles involved in the calculation of the equivalent dose and the effective dose, and the instructions concerning the application of the maximum values of these quantities. further, for monitoring the dose caused by internal radiation, the guide defines the limits derived from annual dose limits (the Annual Limit on Intake and the Derived Air Concentration). Finally, the guide defines the operational quantities to be used in estimating the equivalent dose and the effective dose, and also sets out the definitions of some other quantities and concepts to be used in monitoring radiation exposure. The guide does not include the calculation of patient doses carried out for the purposes of quality assurance

Application of maximum values for radiation exposure and principles for the calculation of radiation dose

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-07-01

The guide sets out the mathematical definitions and principles involved in the calculation of the equivalent dose and the effective dose, and the instructions concerning the application of the maximum values of these quantities. further, for monitoring the dose caused by internal radiation, the guide defines the limits derived from annual dose limits (the Annual Limit on Intake and the Derived Air Concentration). Finally, the guide defines the operational quantities to be used in estimating the equivalent dose and the effective dose, and also sets out the definitions of some other quantities and concepts to be used in monitoring radiation exposure. The guide does not include the calculation of patient doses carried out for the purposes of quality assurance.

Mapping Water Level Dynamics over Central Congo River Using PALSAR Images, Envisat Altimetry, and Landsat NDVI Data

Science.gov (United States)

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

5 CFR 630.1111 - Limitation on the amount of donated annual leave received by an emergency leave recipient.

Science.gov (United States)

2010-01-01

... needs of individual emergency leave recipients, an employing agency may allow an employee to receive... annual leave received by an emergency leave recipient. 630.1111 Section 630.1111 Administrative Personnel... recipient. An emergency leave recipient may receive a maximum of 240 hours of donated annual leave at any...

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

Directory of Open Access Journals (Sweden)

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

The Annual Cycle of Water Vapor on Mars as Observed by the Thermal Emission Spectrometer

Science.gov (United States)

Smith, Michael D.; Vondrak, Richard R. (Technical Monitor)

2001-01-01

Spectra taken by the Mars Global Surveyor Thermal Emission Spectrometer (TES) have been used to monitor the latitude, longitude, and seasonal dependence of water vapor for over one full Martian year (March 1999-March 2001). A maximum in water vapor abundance is observed at high latitudes during mid-summer in both hemispheres, reaching a maximum value of approximately 100 pr-micrometer in the north and approximately 50 pr-micrometer in the south. Low water vapor abundance (water vapor. The latitudinal and seasonal dependence of the decay of the northern summer water vapor maximum implies cross-equatorial transport of water to the southern hemisphere, while there is little or no corresponding transport during the decay of the southern hemisphere summer maximum. The latitude-longitude dependence of annually-averaged water vapor (corrected for topography) has a significant positive correlation with albedo and significant negative correlations with thermal inertia and surface pressure. Comparison of TES results with those retrieved from the Viking Orbiter Mars Atmospheric Water Detectors (MAWD) experiments shows some similar features, but also many significant differences. The southern hemisphere maximum observed by TES was not observed by MAWD and the large latitudinal gradient in annually-averaged water vapor observed by MAWD does not appear in the TES results.

Analysis of Grassland Ecosystem Physiology at Multiple Scales Using Eddy Covariance, Stable Isotope and Remote Sensing Techniques

Science.gov (United States)

Flanagan, L. B.; Geske, N.; Emrick, C.; Johnson, B. G.

2006-12-01

Grassland ecosystems typically exhibit very large annual fluctuations in above-ground biomass production and net ecosystem productivity (NEP). Eddy covariance flux measurements, plant stable isotope analyses, and canopy spectral reflectance techniques have been applied to study environmental constraints on grassland ecosystem productivity and the acclimation responses of the ecosystem at a site near Lethbridge, Alberta, Canada. We have observed substantial interannual variation in grassland productivity during 1999-2005. In addition, there was a strong correlation between peak above-ground biomass production and NEP calculated from eddy covariance measurements. Interannual variation in NEP was strongly controlled by the total amount of precipitation received during the growing season (April-August). We also observed significant positive correlations between a multivariate ENSO index and total growing season precipitation, and between the ENSO index and annual NEP values. This suggested that a significant fraction of the annual variability in grassland productivity was associated with ENSO during 1999-2005. Grassland productivity varies asymmetrically in response to changes in precipitation with increases in productivity during wet years being much more pronounced than reductions during dry years. Strong increases in plant water-use efficiency, based on carbon and oxygen stable isotope analyses, contribute to the resilience of productivity during times of drought. Within a growing season increased stomatal limitation of photosynthesis, associated with improved water-use efficiency, resulted in apparent shifts in leaf xanthophyll cycle pigments and changes to the Photochemical Reflectance Index (PRI) calculated from hyper-spectral reflectance measurements conducted at the canopy-scale. These shifts in PRI were apparent before seasonal drought caused significant reductions in leaf area index (LAI) and changes to canopy-scale "greenness" based on NDVI values. With

Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data

Directory of Open Access Journals (Sweden)

Willem J. D. van Leeuwen

2008-03-01

Full Text Available This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR and examine burn severity at the selected sites. The phenological metrics (pheno-metrics included the timing and greenness (i.e. NDVI for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation

The Urban Heat Island Effect and the Role of Vegetation to Address the Negative Impacts of Local Climate Changes in a Small Brazilian City

Directory of Open Access Journals (Sweden)

Elis Dener Lima Alves

2017-02-01

Full Text Available This study analyzes the influence of urban-geographical variables on determining heat islands and proposes a model to estimate and spatialize the maximum intensity of urban heat islands (UHI. Simulations of the UHI based on the increase of normalized difference vegetation index (NDVI, using multiple linear regression, in Iporá (Brazil are also presented. The results showed that the UHI intensity of this small city tended to be lower than that of bigger cities. Urban geometry and vegetation (UI and NDVI were the variables that contributed the most to explain the variability of the maximum UHI intensity. It was observed that areas located in valleys had lower thermal values, suggesting a cool island effect. With the increase in NDVI in the central area of a maximum UHI, there was a significant decrease in its intensity and size (a 45% area reduction. It is noteworthy that it was possible to spatialize the UHI to the whole urban area by using multiple linear regression, providing an analysis of the urban set from urban-geographical variables and thus performing prognostic simulations that can be adapted to other small tropical cities.

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.

Modeling the distribution of Schistosoma mansoni and host snails in Uganda using satellite sensor data and Geographical Information Systems

DEFF Research Database (Denmark)

Stensgaard, Anna-Sofie; Jørgensen, A; Kabatereine, N B

2005-01-01

The potential value of MODIS satellite sensor data on Normalized Difference Vegetation Index (NDVI) and land surface temperatures (LST) for describing the distribution of the Schistosoma mansoni-"Biomphalaria pfeifferi"/Biomphalaria sudanica parasite-snail system in inland Uganda, were tested...... by developing annual and seasonal composite models, and iteratively analysing for their relationship with parasite and snail distribution. The dry season composite model predicted an endemic area that produced the best fit with the distribution of schools with > or =5% prevalence. NDVI values of 151-174, day...

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...

Weldon Spring, Missouri: Annual environmental monitoring report, calendar year 1987

International Nuclear Information System (INIS)

1987-01-01

Radiological monitoring at the WSS during 1987 measured uranium, Radium-226, and Thorium-230 concentrations in surface water, groundwater, and sediment; radon gas concentrations in air; all long-lived natural series isotopes in air particulates; and external gamma radiation exposure rates. Potential radiation doses to the public were calculated based on assumed exposure periods and the above measurements. Radon concentrations, external gamma exposure rates, and radionuclide concentrations in groundwater and surface water at the site were generally equivalent to previous years' levels. The maximum calculated annual radiation dose to a hypothetically exposed individual at the WSRP and WSCP area was 1 mrem, or 1 percent of the DOE radiation protection standard of 100 mrem. The maximum calculated annual radiation dose to a hypothetically exposed individual at the WSQ was 14 mrem, or about 14 percent of the standard. Thus the WSS currently complies with DOE Off-site Dose Standards. Chemical contamination monitoring at the WSS during 1987 measured nitroaromatics, total organic carbon and the inorganic anions chloride, nitrate, fluoride and sulfate in surface water, groundwater and sediment. 22 refs., 26 figs., 21 tabs

Integrated Spatial Models of Non Native Plant Invasion, Fire Risk, and Wildlife Habitat to Support Conservation of Military and Adjacent Lands in the Arid Southwest

Science.gov (United States)

2015-12-01

Schwalbe 2002). The result is a vastly altered fire regime for desert regions. As a consequence of human activities and the prevalence of invasive...the most prevalent predictors for Brassica presence (6 of 12 variables), with three models associated with mean fall NDVI, one with maximum fall NDVI...plant diversity assessment using a pixel nested plot design: a case study in Beaver Meadows, Rocky Mountain National Park, Colorado, USA. Diversity

Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

Directory of Open Access Journals (Sweden)

Qiutong Jin

2016-06-01

Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

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

Science.gov (United States)

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.

50 CFR 259.34 - Minimum and maximum deposits; maximum time to deposit.

Science.gov (United States)

2010-10-01

... B objective. A time longer than 10 years, either by original scheduling or by subsequent extension... OCEANIC AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE AID TO FISHERIES CAPITAL CONSTRUCTION FUND...) Minimum annual deposit. The minimum annual (based on each party's taxable year) deposit required by the...

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

Directory of Open Access Journals (Sweden)

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.

Annual environmental monitoring report, January-December 1983

International Nuclear Information System (INIS)

1984-03-01

Environmental monitoring results continue to demonstrate that environmental radiological impact due to SLAC operation is not easily distinguishable from natural environmental sources. During 1983, the maximum approximated neutron dose near the site boundary was 5 mrem. There have been no measurable increases in radioactivity in ground water attributable to SLAC operations since operation began in 1966. We have never found any evidence of radioactivity in ground water in excess of natural background radioactivity from uranium and thorium decay chains and potassium-40. Airborne radioactivity released from SLAC continues to make only a negligible environmental impact, and results in a site-boundary annual dose of less than 0.3 mrem; this represents less than 0.3% of the annual dose from the natural radiation environment, and about 0.06% of the technical standard. 8 references, 5 figures, 4 tables

Linking phenology and biomass productivity in South Dakota mixed-grass prairie

Science.gov (United States)

Rigge, Matthew; Smart, Alexander; Wylie, Bruce; Gilmanov, Tagir; Johnson, Patricia

2013-01-01

Assessing the health of rangeland ecosystems based solely on annual biomass production does not fully describe plant community condition; the phenology of production can provide inferences on species composition, successional stage, and grazing impacts. We evaluate the productivity and phenology of western South Dakota mixed-grass prairie using 2000 to 2008 Moderate Resolution Imaging Spectrometer (MODIS) normalized difference vegetation index (NDVI) satellite imagery at 250 m spatial resolution. Growing season NDVI images were integrated weekly to produce time-integrated NDVI (TIN), a proxy of total annual biomass production, and integrated seasonally to represent annual production by cool (C3) and warm (C4) season species. Additionally, a variety of phenological indicators including cool season percentage of TIN were derived from the seasonal profiles of NDVI. Cool season percentage and TIN were combined to generate vegetation classes, which served as proxies of plant community condition. TIN decreased with precipitation from east to west across the study area. Alternatively, cool season percentage increased from east to west, following patterns related to the reliability (interannual coefficient of variation [CV]) and quantity of mid-summer precipitation. Cool season TIN averaged 76.8% of total. Seasonal accumulation of TIN corresponded closely (R2 > 0.90) to that of gross photosynthesis data from a carbon flux tower. Field-collected biomass and community composition data were strongly related to the TIN and cool season percentage products. The patterns of vegetation classes were responsive to topographic, edaphic, and land management influences on plant communities. Accurate maps of biomass production, cool/warm season composition, and vegetation classes can improve the efficiency of land management by adjusting stocking rates and season of use to maximize rangeland productivity and achieve conservation objectives. Further, our results clarify the spatial and

Identifying the Relationships between Water Quality and Land Cover Changes in the Tseng-Wen Reservoir Watershed of Taiwan

Directory of Open Access Journals (Sweden)

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.

Maximum known stages and discharges of New York streams and their annual exceedance probabilities through September 2011

Science.gov (United States)

Wall, Gary R.; Murray, Patricia M.; Lumia, Richard; Suro, Thomas P.

2014-01-01

Maximum known stages and discharges at 1,400 sites on 796 streams within New York are tabulated. Stage data are reported in feet. Discharges are reported as cubic feet per second and in cubic feet per second per square mile. Drainage areas range from 0.03 to 298,800 square miles; excluding the three sites with larger drainage areas on the St. Lawrence and Niagara Rivers, which drain the Great Lakes, the maximum drainage area is 8,288 square miles (Hudson River at Albany). Most data were obtained from U.S. Geological Survey (USGS) compilations and records, but some were provided by State, local, and other Federal agencies and by private organizations. The stage and discharge information is grouped by major drainage basins and U.S. Geological Survey site number, in downstream order. Site locations and their associated drainage area, period(s) of record, stage and discharge data, and flood-frequency statistics are compiled in a Microsoft Excel spreadsheet. Flood frequencies were derived for 1,238 sites by using methods described in Bulletin 17B (Interagency Advisory Committee on Water Data, 1982), Ries and Crouse (2002), and Lumia and others (2006). Curves that “envelope” maximum discharges within their range of drainage areas were developed for each of six flood-frequency hydrologic regions and for sites on Long Island, as well as for the State of New York; the New York curve was compared with a curve derived from a plot of maximum known discharges throughout the United States. Discharges represented by the national curve range from at least 2.7 to 4.9 times greater than those represented by the New York curve for drainage areas of 1.0 and 1,000 square miles. The relative magnitudes of discharge and runoff in the six hydrologic regions of New York and Long Island suggest the largest known discharges per square mile are in the southern part of western New York and the Catskill Mountain area, and the smallest are on Long Island.

Impact of Precipitation Fluctuation on Desert-Grassland ANPP

Directory of Open Access Journals (Sweden)

Liangxu Liu

2016-11-01

Full Text Available Precipitation change has significantly influenced annual net primary productivity (ANPP at either annual or seasonal scales in desert steppes in arid and semi-arid regions. In order to reveal the process of precipitation driving ANPP at different time scales, responses of different ANPP levels to the inter-annual and intra-annual precipitation fluctuations were analyzed. ANPP was reversed by building a ground reflectance spectrum model, from 2000 to 2015, using the normalized differential vegetation index of the Moderate-Resolution Imaging Spectroradiometer (MODIS-NDVI data at 250 m × 250 m spatial resolution. Since the description of the differently expressing forms of precipitation are not sufficient in former studies in order to overcome the deficiency of former studies, in this study, intra-annual precipitation fluctuations were analyzed not only with precipitation of May–August, June–August, July–August, and August, respectively, which have direct influence on vegetation productivity within the year, but quantitative description, vector precipitation (R, concentration ratio (Cd, and concentration period (D, were also used to describe the overall characteristics of intra-annual precipitation fluctuations. The concentration ratio and the maximum precipitation period of the intra-annual precipitation were represented by using monthly precipitation. The results showed that: (1 in the period from 1971 to 2015, the maximum annual precipitation is 3.76 times that of the minimum in the Urat desert steppe; (2 vector precipitation is more significantly related to ANPP (r = 0.7724, p = 0.000 compared to meteorological annual precipitation and real annual precipitation influence; and (3 annual precipitation is almost concentrated in 5–8 months and monthly precipitation accumulation has significantly effected ANPP, especially in the period of June–August, since the vegetation composition in the study area was mainly sub-shrubs and perennial

Annual report on JEN-1 reactor

International Nuclear Information System (INIS)

Montes, J.

1972-01-01

In the annual report on the JEN-1 reactor the main features of the reactor operations and maintenance are described. The reactor has been critical for 1831 hours, what means 65,8% of the total working time. Maintenance and pool water contamination have occupied the rest of the time. The maintenance schedule is shown in detail according to three subjects. The main failures and reactor scrams are also described. The daily maximum values of the water activity are given so as the activity of the air in the reactor hall. (Author)

Latitudinal Change of Tropical Cyclone Maximum Intensity in the Western North Pacific

Directory of Open Access Journals (Sweden)

Jae-Won Choi

2016-01-01

Full Text Available This study obtained the latitude where tropical cyclones (TCs show maximum intensity and applied statistical change-point analysis on the time series data of the average annual values. The analysis results found that the latitude of the TC maximum intensity increased from 1999. To investigate the reason behind this phenomenon, the difference of the average latitude between 1999 and 2013 and the average between 1977 and 1998 was analyzed. In a difference of 500 hPa streamline between the two periods, anomalous anticyclonic circulations were strong in 30°–50°N, while anomalous monsoon trough was located in the north of South China Sea. This anomalous monsoon trough was extended eastward to 145°E. Middle-latitude region in East Asia is affected by the anomalous southeasterlies due to these anomalous anticyclonic circulations and anomalous monsoon trough. These anomalous southeasterlies play a role of anomalous steering flows that make the TCs heading toward region in East Asia middle latitude. As a result, TCs during 1999–2013 had higher latitude of the maximum intensity compared to the TCs during 1977–1998.

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

Science.gov (United States)

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.

Assessment of annual effective dose from 238U and 226Ra due to consumption of foodstuffs by inhabitants of Tehran city (IR)

International Nuclear Information System (INIS)

Hosseini, T.; Fathivand, A. A.; Abbasisiar, F.; Karimi, M.; Barati, H.

2006-01-01

The concentrations of 238 U and 226 Ra were determined in different foodstuffs purchased from markets in Tehran. Determinations of the radionuclides have been carried out using alpha spectrometry technique, on samples of egg, lentil, potato, rice, soya, spinach, tea and wheat. Average concentrations of natural radionuclides and foodstuff consumption rate were used to assess annual intake and based on intake values, the annual effective ingestion dose has been estimated for Tehran city residents. The measurement results show that soya has the maximum concentration of 238 U equal to 15.6 ± 2.6 mBq kg -1 and tea has the maximum concentration of 226 Ra equal to 1153.3 ± 265.3 mBq kg -1 . Besides, the maximum annual effective dose from 238 U and 226 Ra were assessed to be 2.88 x 10 -2 ±7.20 x 10 -3 and 2.15 ± 0.54 μSv, respectively, from wheat samples. (authors)

Activity and migratory flights of individual free-flying songbirds throughout the annual cycle

DEFF Research Database (Denmark)

Bäckman, Johan; Andersson, Arne; Alerstam, Thomas

2017-01-01

the sampling events. Activity levels were stored on an hourly basis throughout the annual cycle, allowing periods of resting/sleep, continuous flight and intermediate activity (foraging, breeding) to be distinguished. Measurements from a light sensor were stored from preprogrammed key stationary periods during...... the year to provide control information about geographic location. Successful results, including annual actogram, were obtained for a red-backed shrike Lanius collurio carrying out its annual loop migration between northern Europe and southern Africa. The shrike completed its annual migration by performing...... > 66 (max. 73) nocturnal migratory flights (29 flights in autumn and > 37, max. 44, in spring) adding up to a total of > 434 (max. 495) flight hours. Migratory flights lasted on average 6.6 h with maximum 15.9 h. These flights were aggregated into eight travel episodes (periods of 4-11 nights when...

Radon continuous monitoring in Altamira Cave (northern Spain) to assess user's annual effective dose

International Nuclear Information System (INIS)

Lario, J.; Sanchez-Moral, S.; Canaveras, J.C.; Cuezva, S.; Soler, V.

2005-01-01

In this work, we present the values of radon concentration, measured by continuous monitoring during a complete annual cycle in the Polychromes Hall of Altamira Cave in order to undertake more precise calculations of annual effective dose for guides and visitors in tourist caves. The 222 Rn levels monitored inside the cave ranges from 186 Bq m -3 to 7120 Bq m -3 , with an annual average of 3562 Bq m -3 . In order to more accurately estimate effective dose we use three scenarios with different equilibrium factors (F=0.5, 0.7 and 1.0) together with different dose conversion factors proposed in the literature. Neither effective dose exceeds international recommendations. Moreover, with an automatic radon monitoring system the time remaining to reach the maximum annual dose recommended could be automatically updated

Effectance, committed effective dose equivalent and annual limits on intake: what are the changes?

International Nuclear Information System (INIS)

Kendall, G.M.; Stather, J.W.; Phipps, A.W.

1990-01-01

This paper outlines the concept of effectance, compares committed effectance with the old committed effective dose equivalent and goes on to discuss changes in the annual limits on intakes and the maximum organ doses which would result from an intake of an ALI (Annual Limit of Intake). It is shown that committed effectance is usually, but not always, higher than committed effective dose equivalent. ALIS are usually well below those resulting from the ICRP Publication 30 scheme. However, if the ALI were based only on a limit on effectance it would imply a high dose to specific organs for certain nuclides. In order to control maximum organ doses an explicit limit could be introduced. However, this would destroy some of the attractive features of the new scheme. An alternative would be a slight modification to some of the weighting factors. (author)

41st Annual Meeting of the Spanish Nuclear Society

Energy Technology Data Exchange (ETDEWEB)

NONE

2015-07-01

The Spanish Nuclear Society (SNE) is a non-profit association, made up of professionals and institutions, in order to promote awareness and dissemination of nuclear science and technology. The 41 Annual Meeting of the Spanish Nuclear Society was held in A Coruña from 23 to 25 September 2015. This Annual Meeting allows professionals and companies in the sector to analyze the current state of nuclear energy and its future challenges, covering different topics from engineering to R & D, nuclear safety, also impact on health and the environment, climate change, nuclear facilities, experience spanish companies in the management of knowledge in the nuclear sector. This congress has involved some 600 experts who have dealt with current issues and maximum interest.

Integrating Statistical and Expert Knowledge to Develop Phenoregions for the Continental United States

Science.gov (United States)

Betancourt, J. L.; Biondi, F.; Bradford, J. B.; Foster, J. R.; Betancourt, J. L.; Foster, J. R.; Biondi, F.; Bradford, J. B.; Henebry, G. M.; Post, E.; Koenig, W.; Hoffman, F. M.; de Beurs, K.; Hoffman, F. M.; Kumar, J.; Hargrove, W. W.; Norman, S. P.; Brooks, B. G.

2016-12-01

Vegetated ecosystems exhibit unique phenological behavior over the course of a year, suggesting that remotely sensed land surface phenology may be useful for characterizing land cover and ecoregions. However, phenology is also strongly influenced by temperature and water stress; insect, fire, and weather disturbances; and climate change over seasonal, interannual, decadal and longer time scales. Normalized difference vegetation index (NDVI), a remotely sensed measure of greenness, provides a useful proxy for land surface phenology. We used NDVI for the conterminous United States (CONUS) derived from the Moderate Resolution Spectroradiometer (MODIS) every eight days at 250 m resolution for the period 2000-2015 to develop phenological signatures of emergent ecological regimes called phenoregions. We employed a "Big Data" classification approach on a supercomputer, specifically applying an unsupervised data mining technique, to this large collection of NDVI measurements to develop annual maps of phenoregions. This technique produces a prescribed number of prototypical phenological states to which every location belongs in any year. To reduce the impact of short-term disturbances, we derived a single map of the mode of annual phenological states for the CONUS, assigning each map cell to the state with the largest integrated NDVI in cases where multiple states tie for the highest frequency of occurrence. Since the data mining technique is unsupervised, individual phenoregions are not associated with an ecologically understandable label. To add automated supervision to the process, we applied the method of Mapcurves, developed by Hargrove and Hoffman, to associate individual phenoregions with labeled polygons in expert-derived maps of biomes, land cover, and ecoregions. We will present the phenoregions methodology and resulting maps for the CONUS, describe the "label-stealing" technique for ascribing biome characteristics to phenoregions, and introduce a new polar

Approximate maximum parsimony and ancestral maximum likelihood.

Science.gov (United States)

Alon, Noga; Chor, Benny; Pardi, Fabio; Rapoport, Anat

2010-01-01

We explore the maximum parsimony (MP) and ancestral maximum likelihood (AML) criteria in phylogenetic tree reconstruction. Both problems are NP-hard, so we seek approximate solutions. We formulate the two problems as Steiner tree problems under appropriate distances. The gist of our approach is the succinct characterization of Steiner trees for a small number of leaves for the two distances. This enables the use of known Steiner tree approximation algorithms. The approach leads to a 16/9 approximation ratio for AML and asymptotically to a 1.55 approximation ratio for MP.

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.

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

Science.gov (United States)

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

Stochastic Evaluation of Maximum Wind Installation in a Radial Distribution Network

DEFF Research Database (Denmark)

Chen, Peiyuan; Bak-Jensen, Birgitte; Chen, Zhe

2011-01-01

This paper proposes an optimization algorithm to find the maximum wind installation in a radial distribution network. The algorithm imposes a limit on the amount of wind energy that can be curtailed annually. The algorithm implements the wind turbine reactive power control and wind energy...... curtailment using sensitivity factors. The optimization is integrated with Monte Carlo simulation to account for the stochastic behavior of load demand and wind power generation. The proposed algorithm is tested on a real 20 kV Danish distribution system in Støvring. It is demonstrated that the algorithm...... executes reactive compensation and energy curtailment sequentially in an effective and efficient manner....

Change of annual collective dose equivalent of radiation workers at KURRI

International Nuclear Information System (INIS)

Okamoto, Kenichi

1994-01-01

The change of exposure dose equivalent of radiation workers at KURRI (Kyoto University Research Reactor Institute) in the past 30 years is reported together with the operational accomplishments. The reactor achieved criticality on June 24, 1964 and reached the normal power of 1000 kW on August 17 of the same year, and the normal power was elevated to 5000 kW on July 16, 1968 until today. The change of the annual effective dose equivalent, the collective dose equivalent, the average annual dose equivalent and the maximum dose equivalent are indicated in the table and the figure. The chronological table on the activities of the reactor is added. (T.H.)

Estimate of Annual Ultraviolet-A Exposures in Cars in Australia

International Nuclear Information System (INIS)

Parisi, A.V.; Kimlin, M.G.

2000-01-01

The annual solar UVA exposures in four cars were estimated by measuring the UVA irradiances in the vehicles in each of the four seasons and in the morning, noon and afternoon. For the cars with untinted windows the maximum UVA irradiances in cars do not necessarily occur at noon when the outside irradiances are at their highest. Additionally, they do not occur in summer. The range of annual UVA exposures between 9:00 and 15:00 EST is 1918 to 6177 J.cm -2 for the cars without the after-market window tint. These correspond to 5% to 17% of the ambient UVA on a horizontal plane over the same period outside the cars. The range is for the different sites in the car. For the car with the after-market window tint, the range of the annual UVA exposures was 489 to 2969 J.cm -2 or 1% to 8% of the ambient UVA. (author)

Satellite Global and Hemispheric Lower Tropospheric Temperature Annual Temperature Cycle

Directory of Open Access Journals (Sweden)

Michael A. Brunke

2010-11-01

Full Text Available Previous analyses of the Earth’s annual cycle and its trends have utilized surface temperature data sets. Here we introduce a new analysis of the global and hemispheric annual cycle using a satellite remote sensing derived data set during the period 1979–2009, as determined from the lower tropospheric (LT channel of the MSU satellite. While the surface annual cycle is tied directly to the heating and cooling of the land areas, the tropospheric annual cycle involves additionally the gain or loss of heat between the surface and atmosphere. The peak in the global tropospheric temperature in the 30 year period occurs on 10 July and the minimum on 9 February in response to the larger land mass in the Northern Hemisphere. The actual dates of the hemispheric maxima and minima are a complex function of many variables which can change from year to year thereby altering these dates.Here we examine the time of occurrence of the global and hemispheric maxima and minima lower tropospheric temperatures, the values of the annual maxima and minima, and the slopes and significance of the changes in these metrics.  The statistically significant trends are all relatively small. The values of the global annual maximum and minimum showed a small, but significant trend. Northern and Southern Hemisphere maxima and minima show a slight trend toward occurring later in the year. Most recent analyses of trends in the global annual cycle using observed surface data have indicated a trend toward earlier maxima and minima.

Predicting the Maximum Earthquake Magnitude from Seismic Data in Israel and Its Neighboring Countries.

Science.gov (United States)

Last, Mark; Rabinowitz, Nitzan; Leonard, Gideon

2016-01-01

This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006-2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year.

Application of maximum values for radiation exposure and principles for the calculation of radiation doses

International Nuclear Information System (INIS)

2007-08-01

The guide presents the definitions of equivalent dose and effective dose, the principles for calculating these doses, and instructions for applying their maximum values. The limits (Annual Limit on Intake and Derived Air Concentration) derived from dose limits are also presented for the purpose of monitoring exposure to internal radiation. The calculation of radiation doses caused to a patient from medical research and treatment involving exposure to ionizing radiation is beyond the scope of this ST Guide

Spatial-temporal changes of maximum and minimum temperatures in the Wei River Basin, China: Changing patterns, causes and implications

Science.gov (United States)

Liu, Saiyan; Huang, Shengzhi; Xie, Yangyang; Huang, Qiang; Leng, Guoyong; Hou, Beibei; Zhang, Ying; Wei, Xiu

2018-05-01

Due to the important role of temperature in the global climate system and energy cycles, it is important to investigate the spatial-temporal change patterns, causes and implications of annual maximum (Tmax) and minimum (Tmin) temperatures. In this study, the Cloud model were adopted to fully and accurately analyze the changing patterns of annual Tmax and Tmin from 1958 to 2008 by quantifying their mean, uniformity, and stability in the Wei River Basin (WRB), a typical arid and semi-arid region in China. Additionally, the cross wavelet analysis was applied to explore the correlations among annual Tmax and Tmin and the yearly sunspots number, Arctic Oscillation, Pacific Decadal Oscillation, and soil moisture with an aim to determine possible causes of annual Tmax and Tmin variations. Furthermore, temperature-related impacts on vegetation cover and precipitation extremes were also examined. Results indicated that: (1) the WRB is characterized by increasing trends in annual Tmax and Tmin, with a more evident increasing trend in annual Tmin, which has a higher dispersion degree and is less uniform and stable than annual Tmax; (2) the asymmetric variations of Tmax and Tmin can be generally explained by the stronger effects of solar activity (primarily), large-scale atmospheric circulation patterns, and soil moisture on annual Tmin than on annual Tmax; and (3) increasing annual Tmax and Tmin have exerted strong influences on local precipitation extremes, in terms of their duration, intensity, and frequency in the WRB. This study presents new analyses of Tmax and Tmin in the WRB, and the findings may help guide regional agricultural production and water resources management.

Estimation of Mangrove Net Primary Production and Carbon Sequestration service using Light Use Efficiency model in the Sunderban Biosphere region, India

Science.gov (United States)

Sannigrahi, Srikanta; Sen, Somnath; Paul, Saikat

2016-04-01

-LUE and VPM models has explained the maximum variances (>80%) in comparison to the other model. Study result has also showed that the BPP has explained the maximum model variances (>93%) followed by BCP (>65%) and ELP (>50%). Scaled WS, iWS, LST, VPD, NDVI was performed better in a minimum ELP condition whereas surface moisture and wetness was highly correlated with the AGB and NPP (R2 = 0.86 RMSE = 1.83). During this study period (2000-2013), it was found that there was a significantly declining trend (R2 = 0.32 P = 0.05) of annual NPP and the maximum decrease was found in the eastern part where built-up area was mainly accounted for reduction of NPP. BCP are explained higher variances (>80%) in the optimum climatic condition exist along the coastal stretches in comparison to the landward extent (>45%).

Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5

Directory of Open Access Journals (Sweden)

Daniel Fonseca de Carvalho

2014-03-01

Full Text Available The objective of this work was to evaluate the seasonal variation of soil cover and rainfall erosivity, and their influences on the revised universal soil loss equation (Rusle, in order to estimate watershed soil losses in a temporal scale. Twenty-two TM Landsat 5 images from 1986 to 2009 were used to estimate soil use and management factor (C factor. A corresponding rainfall erosivity factor (R factor was considered for each image, and the other factors were obtained using the standard Rusle method. Estimated soil losses were grouped into classes and ranged from 0.13 Mg ha-1 on May 24, 2009 (dry season to 62.0 Mg ha-1 on March 11, 2007 (rainy season. In these dates, maximum losses in the watershed were 2.2 and 781.5 Mg ha-1 , respectively. Mean annual soil loss in the watershed was 109.5 Mg ha-1 , but the central area, with a loss of nearly 300.0 Mg ha-1 , was characterized as a site of high water-erosion risk. The use of C factor obtained from remote sensing data, associated to corresponding R factor, was fundamental to evaluate the soil erosion estimated by the Rusle in different seasons, unlike of other studies which keep these factors constant throughout time.

Annual environmental monitoring report, January-December 1979

International Nuclear Information System (INIS)

1980-05-01

Environmental monitoring results continue to demonstrate that, except for penetrating radiation, environmental radiological impact due to SLAC operation is not distinguishable from natural environmental sources. During 1979, the maximum measured neutron dose near the site boundary was not distinguishable from the cosmic ray neutron background. There have been no measurable increases in radioactivity in ground water attributable to SLAC operations since 1966. Because of major new construction, well water samples were not collected and analyzed during 1979. Construction activities have also temporarily placed our sampling stations for the sanitary and storm sewers out of service. They will be reestablished as soon as construction activities permit (mid 1980). Airborne radioactivity released from SLAC continues to make only a negligible environmental impact, and results in a site boundary annual dose of less than 0.3 mrem; this represents less than 0.3% of the annual dose from the natural radiation environment, and about 0.06% of the technical standard

Trends in global vegetation activity and climatic drivers indicate a decoupled response to climate change

DEFF Research Database (Denmark)

Schut, Antonius G T; Ivits, Eva; Conijn, Jacob G.

2015-01-01

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 TBWper 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...

Responses of Vegetation Cover to Environmental Change in Large Cities of China

Directory of Open Access Journals (Sweden)

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.

Identifying Forest Impacted by Development in the Commonwealth of Virginia through the Use of Landsat and Known Change Indicators

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Matthew N. House

2018-01-01

Full Text Available This study examines the effectiveness of using the Normalized Difference Vegetation Index (NDVI derived from 1326 different Landsat Thematic Mapper and Enhanced Thematic Mapper images in finding low density development within the Commonwealth of Virginia’s forests. Individual NDVI images were stacked by year for the years 1995–2011 and the yearly maximum for each pixel was extracted, resulting in a 17-year image stack of all yearly maxima (a 98.7% data reduction. Using location data from housing starts and well permits, known previously forested housing starts were isolated from all other forest disturbance types. Samples from development disturbances and other forest disturbances, as well as from undisturbed forest, were used to derive vegetation index thresholds enabling separation of disturbed forest from undisturbed forest. Disturbances, once identified, could be separated into Development Disturbances and Non-Development Disturbances using a classification tree and only two variables from the Disturbance Detection and Diagnostics (D3 algorithm: the maximum NDVI in the available recovery period and the slope between the NDVI value at the time of the disturbance and the maximum NDVI in the available recovery period. Low density development disturbances of previous forest land cover had an F-measure, combining precision and recall into a single class-specific accuracy (β = 1, of 0.663. We compared our results to the NLCD 2001–2011 land cover changes from any forest (classes 41, 42, 43, and 90 to any developed (classes 21, 22, 23, and 24, resulting in an F-measure of 0.00 for the same validation points. Landsat time series stacks thus show promise for identifying even the small changes associated with low density development that have been historically overlooked/underestimated by prior mapping efforts. However, further research is needed to ensure that (1 the approach will work in other forest biomes and (2 enabling detection of these

Average monthly and annual climate maps for Bolivia

KAUST Repository

Vicente-Serrano, Sergio M.

2015-02-24

This study presents monthly and annual climate maps for relevant hydroclimatic variables in Bolivia. We used the most complete network of precipitation and temperature stations available in Bolivia, which passed a careful quality control and temporal homogenization procedure. Monthly average maps at the spatial resolution of 1 km were modeled by means of a regression-based approach using topographic and geographic variables as predictors. The monthly average maximum and minimum temperatures, precipitation and potential exoatmospheric solar radiation under clear sky conditions are used to estimate the monthly average atmospheric evaporative demand by means of the Hargreaves model. Finally, the average water balance is estimated on a monthly and annual scale for each 1 km cell by means of the difference between precipitation and atmospheric evaporative demand. The digital layers used to create the maps are available in the digital repository of the Spanish National Research Council.

Maximum permissible dose

International Nuclear Information System (INIS)

Anon.

1979-01-01

This chapter presents a historic overview of the establishment of radiation guidelines by various national and international agencies. The use of maximum permissible dose and maximum permissible body burden limits to derive working standards is discussed

Séries temporais de NDVI do sensor SPOT Vegetation e algoritmo SAM aplicados ao mapeamento de cana‑de‑açúcar

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Luiz Eduardo Vicente

2012-09-01

Full Text Available O objetivo deste trabalho foi avaliar o mapeamento de área de cana‑de‑açúcar por meio de série temporal, de seis anos de dados do índice de vegetação por diferença normalizada (NDVI, oriundos do sensor Vegetation, a bordo do satélite "système pour l'observation de la Terre" (SPOT. Três classes de cobertura do solo (cana‑de‑açúcar, pasto e floresta, do Estado de São Paulo, foram selecionadas como assinaturas espectro‑temporais de referência, que serviram como membros extremos ("endmembers" para classificação com o algoritmo "spectral angle mapper" (SAM. A partir desta classificação, o mapeamento da área de cana‑de‑açúcar foi realizado com uso de limiares na imagem-regra do SAM, gerados a partir dos valores dos espectros de referência. Os resultados mostram que o algoritmo SAM pode ser aplicado a séries de dados multitemporais de resolução moderada, o que permite eficiente mapeamento de alvo agrícola em escala mesorregional. Dados oficiais de áreas de cana‑de‑açúcar, para as microrregiões paulistas, apresentam boa correlação (r² = 0,8 com os dados obtidos pelo método avaliado. A aplicação do algoritmo SAM mostrou ser útil em análises temporais. As séries temporais de NDVI do sensor SPOT Vegetation podem ser utilizadas para mapeamento da área de cana‑de‑açúcar em baixa resolução.

Hydrological differentiation and spatial distribution of high altitude wetlands in a semi-arid Andean region derived from satellite data

Science.gov (United States)

Otto, M.; Scherer, D.; Richters, J.

2011-05-01

High Altitude Wetlands of the Andes (HAWA) belong to a unique type of wetland within the semi-arid high Andean region. Knowledge about HAWA has been derived mainly from studies at single sites within different parts of the Andes at only small time scales. On the one hand, HAWA depend on water provided by glacier streams, snow melt or precipitation. On the other hand, they are suspected to influence hydrology through water retention and vegetation growth altering stream flow velocity. We derived HAWA land cover from satellite data at regional scale and analysed changes in connection with precipitation over the last decade. Perennial and temporal HAWA subtypes can be distinguished by seasonal changes of photosynthetically active vegetation (PAV) indicating the perennial or temporal availability of water during the year. HAWA have been delineated within a region of 12 800 km2 situated in the Northwest of Lake Titicaca. The multi-temporal classification method used Normalized Differenced Vegetation Index (NDVI) and Normalized Differenced Infrared Index (NDII) data derived from two Landsat ETM+ scenes at the end of austral winter (September 2000) and at the end of austral summer (May 2001). The mapping result indicates an unexpected high abundance of HAWA covering about 800 km2 of the study region (6 %). Annual HAWA mapping was computed using NDVI 16-day composites of Moderate Resolution Imaging Spectroradiometer (MODIS). Analyses on the relation between HAWA and precipitation was based on monthly precipitation data of the Tropical Rain Measurement Mission (TRMM 3B43) and MODIS Eight Day Maximum Snow Extent data (MOD10A2) from 2000 to 2010. We found HAWA subtype specific dependencies on precipitation conditions. A strong relation exists between perennial HAWA and snow fall (r2: 0.82) in dry austral winter months (June to August) and between temporal HAWA and precipitation (r2: 0.75) during austral summer (March to May). Annual changes in spatial extend of perennial HAWA

Development of relative thermal stress index (RTSI) for Monitoring and Management of Dry Deciduous Ecosystem

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Gupta, R. K.; Vijayan, D.

Gir wildlife sanctuary located between 20 r 57 to 21 r 20 N and 70 r 28 to 71 r 13 E is the last home of Asiatic lions Its biodiversity comprises of 450 recorded flowering plant species 32 species of mammals 26 species of reptiles about 300 species of birds and more than 2000 species of insects As per 1995 census it has 304 lions and 268 leopards The movement of wildlife to thermally comfortable zones to reduce stress conditions forces the changes in management plan with reference to change in localized water demand This necessitates the use of space based thermal data available from AVHRR MODIS etc to monitor temperature of Gir-ecosystem for meso-scale level operational utility As the time scale of the variability of NDVI parameter is much higher than that for lower boundary temperature LBT the dense patch in riverine forest having highest NDVI value would not experience change in its vigour with the change in the season NDVI value of such patch would be near invariant over the year and temperature of this pixel could serve as reference temperature for developing the concept of relative thermal stress index RTSI which is defined as RTSI T p -T r T max -T r wherein T r T max and T p refer to LBT over the maximum NDVI reference point maximum LBT observed in the Gir ecosystem and the temperature of the pixel in the image respectively RTSI images were computed from AVHRR images for post-monsoon leaf-shedded and summer seasons Scatter plot between RTSI and NDVI for summer seasons

A study on the intra-annual variation and the spatial distribution of precipitation amount and duration over Greece on a 10 day basis

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Bartzokas, A.; Lolis, C. J.; Metaxas, D. A.

2003-02-01

The intra-annual variation of precipitation amount and duration and their spatial distribution during the year are studied on a 10 day basis for the Greek region, using S-mode and T-mode factor analysis. (i) For the intra-annual variation of precipitation amount, two modes were revealed: the first shows one broad maximum during the conventional winter in stations affected by the sea; the second presents two maxima, the first during late autumn-early winter and the second during late spring, corresponding to the northern mainland stations. (ii) For the spatial distribution of precipitation, three main patterns were revealed: the first one is the winter pattern, with the maximum over the west windward area; the second is the summer pattern, with a maximum over the north inland region; and the third is the autumn pattern, with the maximum over northwestern Greece. (iii) For precipitation duration, two types of intra-annual variation were revealed. The first one is similar to the first of the analysis for precipitation amount; the second presents two maxima, the first during the beginning of December and the second during the middle of February, corresponding to the areas of northwestern and northeastern Greece. (iv) For the spatial distribution of precipitation duration, three main patterns were revealed: the first is the summer pattern, which is similar to the second of the analysis for precipitation amount; the second is the winter pattern, with the spatial maximum located over the eastern mainland and western Crete; finally, the third one is the autumn pattern, with the maximum in northwestern Greece. During the third 10 day period of October and the second 10 day period of February, precipitation seems to present singularities, possibly due to fluctuations in atmospheric circulation. The above intra-annual variations and spatial distribution patterns are connected to the seasonal variations of the depression trajectories, the atmospheric instability, the influence

A Two-Stage Information-Theoretic Approach to Modeling Landscape-Level Attributes and Maximum Recruitment of Chinook Salmon in the Columbia River Basin.

Energy Technology Data Exchange (ETDEWEB)

Thompson, William L.; Lee, Danny C.

2000-11-01

Many anadromous salmonid stocks in the Pacific Northwest are at their lowest recorded levels, which has raised questions regarding their long-term persistence under current conditions. There are a number of factors, such as freshwater spawning and rearing habitat, that could potentially influence their numbers. Therefore, we used the latest advances in information-theoretic methods in a two-stage modeling process to investigate relationships between landscape-level habitat attributes and maximum recruitment of 25 index stocks of chinook salmon (Oncorhynchus tshawytscha) in the Columbia River basin. Our first-stage model selection results indicated that the Ricker-type, stock recruitment model with a constant Ricker a (i.e., recruits-per-spawner at low numbers of fish) across stocks was the only plausible one given these data, which contrasted with previous unpublished findings. Our second-stage results revealed that maximum recruitment of chinook salmon had a strongly negative relationship with percentage of surrounding subwatersheds categorized as predominantly containing U.S. Forest Service and private moderate-high impact managed forest. That is, our model predicted that average maximum recruitment of chinook salmon would decrease by at least 247 fish for every increase of 33% in surrounding subwatersheds categorized as predominantly containing U.S. Forest Service and privately managed forest. Conversely, mean annual air temperature had a positive relationship with salmon maximum recruitment, with an average increase of at least 179 fish for every increase in 2 C mean annual air temperature.

Identifying the Impact of Natural Hazards on Food Security in Africa: Crop Monitoring Using MODIS NDVI Time-Series

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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

Design guidelines for H-Darrieus wind turbines: Optimization of the annual energy yield

International Nuclear Information System (INIS)

Bianchini, Alessandro; Ferrara, Giovanni; Ferrari, Lorenzo

2015-01-01

Highlights: • Proposal for a new design criterion for H-Darrieus turbines based on the energy-yield maximization. • 21,600 design cases analyzed to identify the best solutions for each installation site (i.e. average wind speed). • Critical analysis of the best design choices in terms of turbine shape, dimensions, airfoils and constraints. • Notable energy increase provided by the new design approach. • Each site requires a specific turbine concept to optimize the energy yield. - Abstract: H-Darrieus wind turbines are gaining popularity in the wind energy market, particularly as they are thought to represent a suitable solution even in unconventional installation areas. To promote the diffusion of this technology, industrial manufacturers are continuously proposing new and appealing exterior solutions, coupled with tempting rated-power offers. The actual operating conditions of a rotor over a year can be, however, very different from the nominal one and strictly dependent on the features of the installation site. Based on these considerations, a turbine optimization oriented to maximize the annual energy yield, instead of the maximum power, is thought to represent a more interesting solution. With this goal in mind, 21,600 test cases of H-Darrieus rotors were compared on the basis of their energy-yield capabilities for different annual wind distributions in terms of average speed. The wind distributions were combined with the predicted performance maps of the rotors obtained with a specifically developed numerical code based on a Blade Element Momentum (BEM) approach. The influence on turbine performance of the cut-in speed was accounted for, as well as the limitations due to structural loads (i.e. maximum rotational speed and maximum wind velocity). The analysis, carried out in terms of dimensionless parameters, highlighted the aerodynamic configurations able to ensure the largest annual energy yield for each wind distribution and set of aerodynamic

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.

Quarterly, Bi-annual and Annual Reports

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Quarterly, Bi-annual and Annual Reports are periodic reports issued for public release. For the deep set fishery these reports are issued quarterly and anually....

[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.

A Comparative Frequency Analysis of Maximum Daily Rainfall for a SE Asian Region under Current and Future Climate Conditions

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Velautham Daksiya

2017-01-01

Full Text Available The impact of changing climate on the frequency of daily rainfall extremes in Jakarta, Indonesia, is analysed and quantified. The study used three different models to assess the changes in rainfall characteristics. The first method involves the use of the weather generator LARS-WG to quantify changes between historical and future daily rainfall maxima. The second approach consists of statistically downscaling general circulation model (GCM output based on historical empirical relationships between GCM output and station rainfall. Lastly, the study employed recent statistically downscaled global gridded rainfall projections to characterize climate change impact rainfall structure. Both annual and seasonal rainfall extremes are studied. The results show significant changes in annual maximum daily rainfall, with an average increase as high as 20% in the 100-year return period daily rainfall. The uncertainty arising from the use of different GCMs was found to be much larger than the uncertainty from the emission scenarios. Furthermore, the annual and wet seasonal analyses exhibit similar behaviors with increased future rainfall, but the dry season is not consistent across the models. The GCM uncertainty is larger in the dry season compared to annual and wet season.

Transcription through the eye of a needle: daily and annual cyclic gene expression variation in Douglas-fir needles.

Science.gov (United States)

Cronn, Richard; Dolan, Peter C; Jogdeo, Sanjuro; Wegrzyn, Jill L; Neale, David B; St Clair, J Bradley; Denver, Dee R

2017-07-24

Perennial growth in plants is the product of interdependent cycles of daily and annual stimuli that induce cycles of growth and dormancy. In conifers, needles are the key perennial organ that integrates daily and seasonal signals from light, temperature, and water availability. To understand the relationship between seasonal cycles and seasonal gene expression responses in conifers, we examined diurnal and circannual needle mRNA accumulation in Douglas-fir (Pseudotsuga menziesii) needles at diurnal and circannual scales. Using mRNA sequencing, we sampled 6.1 × 10 9 reads from 19 trees and constructed a de novo pan-transcriptome reference that includes 173,882 tree-derived transcripts. Using this reference, we mapped RNA-Seq reads from 179 samples that capture daily and annual variation. We identified 12,042 diurnally-cyclic transcripts, 9299 of which showed homology to annotated genes from other plant genomes, including angiosperm core clock genes. Annual analysis revealed 21,225 circannual transcripts, 17,335 of which showed homology to annotated genes from other plant genomes. The timing of maximum gene expression is associated with light intensity at diurnal scales and photoperiod at annual scales, with approximately half of transcripts reaching maximum expression +/- 2 h from sunrise and sunset, and +/- 20 days from winter and summer solstices. Comparisons with published studies from other conifers shows congruent behavior in clock genes with Japanese cedar (Cryptomeria), and a significant preservation of gene expression patterns for 2278 putative orthologs from Douglas-fir during the summer growing season, and 760 putative orthologs from spruce (Picea) during the transition from fall to winter. Our study highlight the extensive diurnal and circannual transcriptome variability demonstrated in conifer needles. At these temporal scales, 29% of expressed transcripts show a significant diurnal cycle, and 58.7% show a significant circannual cycle. Remarkably

The application of a Grey Markov Model to forecasting annual maximum water levels at hydrological stations

Science.gov (United States)

Dong, Sheng; Chi, Kun; Zhang, Qiyi; Zhang, Xiangdong

2012-03-01

Compared with traditional real-time forecasting, this paper proposes a Grey Markov Model (GMM) to forecast the maximum water levels at hydrological stations in the estuary area. The GMM combines the Grey System and Markov theory into a higher precision model. The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values, and thus gives forecast results involving two aspects of information. The procedure for forecasting annul maximum water levels with the GMM contains five main steps: 1) establish the GM (1, 1) model based on the data series; 2) estimate the trend values; 3) establish a Markov Model based on relative error series; 4) modify the relative errors caused in step 2, and then obtain the relative errors of the second order estimation; 5) compare the results with measured data and estimate the accuracy. The historical water level records (from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin, China are utilized to calibrate and verify the proposed model according to the above steps. Every 25 years' data are regarded as a hydro-sequence. Eight groups of simulated results show reasonable agreement between the predicted values and the measured data. The GMM is also applied to the 10 other hydrological stations in the same estuary. The forecast results for all of the hydrological stations are good or acceptable. The feasibility and effectiveness of this new forecasting model have been proved in this paper.

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.

Conifers in cold environments synchronize maximum growth rate of tree-ring formation with day length.

Science.gov (United States)

Rossi, Sergio; Deslauriers, Annie; Anfodillo, Tommaso; Morin, Hubert; Saracino, Antonio; Motta, Renzo; Borghetti, Marco

2006-01-01

Intra-annual radial growth rates and durations in trees are reported to differ greatly in relation to species, site and environmental conditions. However, very similar dynamics of cambial activity and wood formation are observed in temperate and boreal zones. Here, we compared weekly xylem cell production and variation in stem circumference in the main northern hemisphere conifer species (genera Picea, Pinus, Abies and Larix) from 1996 to 2003. Dynamics of radial growth were modeled with a Gompertz function, defining the upper asymptote (A), x-axis placement (beta) and rate of change (kappa). A strong linear relationship was found between the constants beta and kappa for both types of analysis. The slope of the linear regression, which corresponds to the time at which maximum growth rate occurred, appeared to converge towards the summer solstice. The maximum growth rate occurred around the time of maximum day length, and not during the warmest period of the year as previously suggested. The achievements of photoperiod could act as a growth constraint or a limit after which the rate of tree-ring formation tends to decrease, thus allowing plants to safely complete secondary cell wall lignification before winter.

Climate Change and Its Impact on the Eco-Environment of the Three-Rivers Headwater Region on the Tibetan Plateau, China

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Chong Jiang

2015-09-01

Full Text Available This study analyzes the impact of climate change on the eco-environment of the Three-Rivers Headwater Region (TRHR, Tibetan Plateau, China. Temperature and precipitation experienced sharp increases in this region during the past 57 years. A dramatic increase in winter temperatures contributed to a rise in average annual temperatures. Moreover, annual runoff in the Lancang (LRB and Yangtze (YARB river basins showed an increasing trend, compared to a slight decrease in the Yellow River Basin (YRB. Runoff is predominantly influenced by rainfall, which is controlled by several monsoon systems. The water temperature in the YRB and YARB increased significantly from 1958 to 2007 (p < 0.001, driven by air temperature changes. Additionally, owing to warming and wetting trends in the TRHR, the net primary productivity (NPP and normalized difference vegetation index (NDVI showed significant increasing trends during the past half-century. Furthermore, although an increase in water erosion due to rainfall erosivity was observed, wind speeds declined significantly, causing a decline in wind erosion, as well as the frequency and duration of sandstorms. A clear regional warming trend caused an obvious increasing trend in glacier runoff, with a maximum value observed in the 2000s.

Climate Change and Its Impact on the Eco-Environment of the Three-Rivers Headwater Region on the Tibetan Plateau, China.

Science.gov (United States)

Jiang, Chong; Zhang, Linbo

2015-09-25

This study analyzes the impact of climate change on the eco-environment of the Three-Rivers Headwater Region (TRHR), Tibetan Plateau, China. Temperature and precipitation experienced sharp increases in this region during the past 57 years. A dramatic increase in winter temperatures contributed to a rise in average annual temperatures. Moreover, annual runoff in the Lancang (LRB) and Yangtze (YARB) river basins showed an increasing trend, compared to a slight decrease in the Yellow River Basin (YRB). Runoff is predominantly influenced by rainfall, which is controlled by several monsoon systems. The water temperature in the YRB and YARB increased significantly from 1958 to 2007 (p changes. Additionally, owing to warming and wetting trends in the TRHR, the net primary productivity (NPP) and normalized difference vegetation index (NDVI) showed significant increasing trends during the past half-century. Furthermore, although an increase in water erosion due to rainfall erosivity was observed, wind speeds declined significantly, causing a decline in wind erosion, as well as the frequency and duration of sandstorms. A clear regional warming trend caused an obvious increasing trend in glacier runoff, with a maximum value observed in the 2000s.

ENHANCED MODELING OF REMOTELY SENSED ANNUAL LAND SURFACE TEMPERATURE CYCLE

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Z. Zou

2017-09-01

Full Text Available Satellite thermal remote sensing provides access to acquire large-scale Land surface temperature (LST data, but also generates missing and abnormal values resulting from non-clear-sky conditions. Given this limitation, Annual Temperature Cycle (ATC model was employed to reconstruct the continuous daily LST data over a year. The original model ATCO used harmonic functions, but the dramatic changes of the real LST caused by the weather changes remained unclear due to the smooth sine curve. Using Aqua/MODIS LST products, NDVI and meteorological data, we proposed enhanced model ATCE based on ATCO to describe the fluctuation and compared their performances for the Yangtze River Delta region of China. The results demonstrated that, the overall root mean square errors (RMSEs of the ATCE was lower than ATCO, and the improved accuracy of daytime was better than that of night, with the errors decreased by 0.64 K and 0.36 K, respectively. The improvements of accuracies varied with different land cover types: the forest, grassland and built-up areas improved larger than water. And the spatial heterogeneity was observed for performance of ATC model: the RMSEs of built-up area, forest and grassland were around 3.0 K in the daytime, while the water attained 2.27 K; at night, the accuracies of all types significantly increased to similar RMSEs level about 2 K. By comparing the differences between LSTs simulated by two models in different seasons, it was found that the differences were smaller in the spring and autumn, while larger in the summer and winter.