Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

Energy Technology Data Exchange (ETDEWEB)

Nikolov, Ned [Natural Resource Research Center, 2150 Centre Avenue, Building A, Room 368, Fort Collins, CO 80526 (United States)]. E-mail: nnikolov@fs.fed.us; Zeller, Karl [USDA FS Rocky Mountain Research Station, 240 W. Prospect Road, Fort Collins, CO 80526 (United States)]. E-mail: kzeller@fs.fed.us

2006-06-15

Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. - The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale.

Pattern Decomposition Method and a New Vegetation Index for Hyper-Multispectral Satellite Data Analysis

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Muramatsu, K.; Furumi, S.; Hayashi, A.; Shiono, Y.; Ono, A.; Fujiwara, N.; Daigo, M.; Ochiai, F.

We have developed the ``pattern decomposition method'' based on linear spectral mixing of ground objects for n-dimensional satellite data. In this method, spectral response patterns for each pixel in an image are decomposed into three components using three standard spectral shape patterns determined from the image data. Applying this method to AMSS (Airborne Multi-Spectral Scanner) data, eighteen-dimensional data are successfully transformed into three-dimensional data. Using the three components, we have developed a new vegetation index in which all the multispectral data are reflected. We consider that the index should be linear to the amount of vegetation and vegetation vigor. To validate the index, its relations to vegetation types, vegetation cover ratio, and chlorophyll contents of a leaf were studied using spectral reflectance data measured in the field with a spectrometer. The index was sensitive to vegetation types and vegetation vigor. This method and index are very useful for assessment of vegetation vigor, classifying land cover types and monitoring vegetation changes

Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data

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Lhermitte, S.; Tips, M.; Verbesselt, J.; Jonckheere, I.; Van Aardt, J.; Coppin, Pol

2005-10-01

Large-scale wild fires have direct impacts on natural ecosystems and play a major role in the vegetation ecology and carbon budget. Accurate methods for describing post-fire development of vegetation are therefore essential for the understanding and monitoring of terrestrial ecosystems. Time series analysis of satellite imagery offers the potential to quantify these parameters with spatial and temporal accuracy. Current research focuses on the potential of time series analysis of SPOT Vegetation S10 data (1999-2001) to quantify the vegetation recovery of large-scale burns detected in the framework of GBA2000. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of vegetation recovery based on remote sensing indicators. Southern Africa was used as a pilot study area, given the availability of ground and satellite data. An automated technique was developed to extract consistent indicators of vegetation recovery from the SPOT-VGT time series. Reference areas were used to quantify the vegetation regrowth by means of Regeneration Indices (RI). Two kinds of recovery indicators (time and value- based) were tested for RI's of NDVI, SR, SAVI, NDWI, and pure band information. The effects of vegetation structure and temporal fire regime features on the recovery indicators were subsequently analyzed. Statistical analyses were conducted to assess whether the recovery indicators were different for different vegetation types and dependent on timing of the burning season. Results highlighted the importance of appropriate reference areas and the importance of correct normalization of the SPOT-VGT data.

Health benefit of vegetable/fruit juice-based diet: Role of microbiome

OpenAIRE

Henning, Susanne M.; Yang, Jieping; Shao, Paul; Lee, Ru-Po; Huang, Jianjun; Ly, Austin; Hsu, Mark; Lu, Qing-Yi; Thames, Gail; Heber, David; Li, Zhaoping

2017-01-01

The gut microbiota is an important contributor to human health. Vegetable/fruit juices provide polyphenols, oligosaccharides, fiber and nitrate (beet juice), which may induce a prebiotic-like effect. Juice-based diets are becoming popular. However, there is a lack of scientific evidence of their health benefits. It was our hypothesis that changes in the intestinal microbiota induced by a juice-based diet play an important role in their health benefits. Twenty healthy adults consumed only vege...

Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series MODIS and LANDSAT satellite images

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Georgopoulou, Danai; Koutsias, Nikos

2015-04-01

Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS and LANDSAT satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. Satellite remote sensing data from MODIS and LANDSAT satellites in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the satellite data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we

Study of Wetland Ecosystem Vegetation Using Satellite Data

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Dyukarev, E. A.; Alekseeva, M. N.; Golovatskaya, E. A.

2017-12-01

The normalized difference vegetation index (NDVI) is used to estimate the aboveground net production (ANP) of wetland ecosystems for the key area at the South Taiga zone of West Siberia. The vegetation index and aboveground production are related by linear dependence and are specific for each wetland ecosystem. The NDVI grows with an increase in the ANP at wooded oligotrophic ecosystems. Open oligotrophic bogs and eutrophic wetlands are characterized by an opposite relation. Maps of aboveground production for wetland ecosystems are constructed for each study year and for the whole period of studies. The average aboveground production for all wetland ecosystems of the key area, which was estimated with consideration for the area they occupy and using the data of satellite measurements of the vegetation index, is 305 g C/m2/yr. The total annual carbon accumulation in aboveground wetland vegetation in the key area is 794600 t.

Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

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Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

2016-09-01

Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

Climatic Changes Effects On Spectral Vegetation Indices For Forested Areas Analysis From Satellite Data

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Zoran, M.; Stefan, S.

2007-01-01

Climate-induced changes at the land surface may in turn feed back on the climate itself through changes in soil moisture, vegetation, radiative characteristics, and surface-atmosphere exchanges of water vapor. Thresholding based on biophysical variables derived from time trajectories of satellite data is a new approach to classifying forest land cover via remote . sensing .The input data are composite values of the Normalized Difference Vegetation Index (NDVI). Classification accuracies are function of the class, comparison method and season of the year. The aim of the paper is forest biomass assessment and land-cover changes analysis due to climatic effects

Long-term change analysis of satellite-based evapotranspiration over Indian vegetated surface

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Gupta, Shweta; Bhattacharya, Bimal K.; Krishna, Akhouri P.

2016-05-01

In the present study, trend of satellite based annual evapotranspiration (ET) and natural forcing factors responsible for this were analyzed. Thirty years (1981-2010) of ET data at 0.08° grid resolution, generated over Indian region from opticalthermal observations from NOAA PAL and MODIS AQUA satellites, were used. Long-term data on gridded (0.5° x 0.5°) annual rainfall (RF), annual mean surface soil moisture (SSM) ERS scatterometer at 25 km resolution and annual mean incoming shortwave radiation from MERRA-2D reanalysis were also analyzed. Mann-Kendall tests were performed with time series data for trend analysis. Mean annual ET loss from Indian ago-ecosystem was found to be almost double (1100 Cubic Km) than Indian forest ecosystem (550 Cubic Km). Rainfed vegetation systems such as forest, rainfed cropland, grassland showed declining ET trend @ - 4.8, -0.6 &-0.4 Cubic Kmyr-1, respectively during 30 years. Irrigated cropland initially showed ET decline upto 1995 @ -0.8 cubic Kmyr-1 which could possibly be due to solar dimming followed by increasing ET @ 0.9 cubic Kmyr-1 after 1995. A cross-over point was detected between forest ET decline and ET increase in irrigated cropland during 2008. During 2001-2010, the four agriculturally important Indian states eastern, central, western and southern showed significantly increasing ET trend with S-score of 15-25 and Z-score of 1.09-2.9. Increasing ET in western and southern states was found to be coupled with increase in annual rainfall and SSM. But in eastern and central states no significant trend in rainfall was observed though significant increase in ET was noticed. The study recommended to investigate the influence of anthropogenic factors such as increase in area under irrigation, increased use of water for irrigation through ground water pumping, change in cropping pattern and cultivars on increasing ET.

Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

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Tao Yu

2018-02-01

Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

Post-fire vegetation recovery in Portugal based on spot/vegetation data

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Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

2010-04-01

A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

Vegetation mapping with satellite data of the Forsmark and Tierp regions

Energy Technology Data Exchange (ETDEWEB)

Boresjoe-Bronge, Laine; Wester, Kjell [SwedPower, Stockholm (Sweden)

2002-04-01

SKB (Swedish Nuclear Fuel and Waste Management Co) performs a siting program for deep repository of spent nuclear fuel that includes survey of three potential sites. The SKB siting process has now reached the site investigation phase. There are several fields of investigations performed in this phase. One of them is description of the surface ecosystems. The surface ecosystems are mapped both on a regional (50-100 km{sup 2} ) and a local level (1 km{sup 2} ). Two inventory methods are used, remote sensing (satellite data/aerial photographs) for the regional level, and field inventory for the detailed level. As a part of the surface ecosystem characterisation on the regional level vegetation mapping using satellite data has been performed over the three potential deep depository sites, Forsmark, Tierp and Oskarshamn. The user requirements for the vegetation mapping of the potential sites are the following: Dominated species in the tree layer, shrub layer, field layer and ground layer shall be described both on regional and local level; Dominated species in all layers shall be quantified regarding share and percentage of ground cover, or absence of cover (vegetation free ground); The regional and the local inventory shall have identical or comparable classification systems; The classification system and the method used shall make it possible to scale the results from local to regional level and vice versa; The produced layers shall be presented in digital form and make it possible to model biomass and turnover of organic matter (carbon, nutrients, water); The produced information shall in a first phase be of use for planning and for making nature and environmental considerations. Data sources used in the study include geo-referenced SPOT4 XI data (20 m ground resolution), geo-referenced Landsat TM data (30 m ground resolution), soil type data, topographic map data and colour infrared aerial photographs. The production of vegetation layers has been carried out in two

Vegetation mapping with satellite data of the Forsmark and Tierp regions

International Nuclear Information System (INIS)

Boresjoe-Bronge, Laine; Wester, Kjell

2002-04-01

SKB (Swedish Nuclear Fuel and Waste Management Co) performs a siting program for deep repository of spent nuclear fuel that includes survey of three potential sites. The SKB siting process has now reached the site investigation phase. There are several fields of investigations performed in this phase. One of them is description of the surface ecosystems. The surface ecosystems are mapped both on a regional (50-100 km 2 ) and a local level (1 km 2 ). Two inventory methods are used, remote sensing (satellite data/aerial photographs) for the regional level, and field inventory for the detailed level. As a part of the surface ecosystem characterisation on the regional level vegetation mapping using satellite data has been performed over the three potential deep depository sites, Forsmark, Tierp and Oskarshamn. The user requirements for the vegetation mapping of the potential sites are the following: Dominated species in the tree layer, shrub layer, field layer and ground layer shall be described both on regional and local level; Dominated species in all layers shall be quantified regarding share and percentage of ground cover, or absence of cover (vegetation free ground); The regional and the local inventory shall have identical or comparable classification systems; The classification system and the method used shall make it possible to scale the results from local to regional level and vice versa; The produced layers shall be presented in digital form and make it possible to model biomass and turnover of organic matter (carbon, nutrients, water); The produced information shall in a first phase be of use for planning and for making nature and environmental considerations. Data sources used in the study include geo-referenced SPOT4 XI data (20 m ground resolution), geo-referenced Landsat TM data (30 m ground resolution), soil type data, topographic map data and colour infrared aerial photographs. The production of vegetation layers has been carried out in two steps. In

Accumulation and health risk of heavy metals in vegetables from harmless and organic vegetable production systems of China.

Science.gov (United States)

Chen, Yong; Hu, Wenyou; Huang, Biao; Weindorf, David C; Rajan, Nithya; Liu, Xiaoxiao; Niedermann, Silvana

2013-12-01

Heavy metal accumulation in vegetables is a growing concern for public health. Limited studies have elucidated the heavy metal accumulation characteristics and health risk of different vegetables produced in different facilities such as greenhouses and open-air fields and under different management modes such as harmless and organic. Given the concern over the aforementioned factors related to heavy metal accumulation, this study selected four typical greenhouse vegetable production bases, short-term harmless greenhouse vegetable base (SHGVB), middle-term harmless greenhouse vegetable base (MHGVB), long-term harmless greenhouse vegetable base (LHGVB), and organic greenhouse vegetable base (OGVB), in Nanjing City, China to study heavy metal accumulation in different vegetables and their associated health risks. Results showed that soils and vegetables from SHGVB and OGVB apparently accumulated fewer certain heavy metals than those from other bases, probably due to fewer planting years and special management, respectively. Greenhouse conditions significantly increased certain soil heavy metal concentrations relative to open-air conditions. However, greenhouse conditions did not significantly increase concentrations of As, Cd, Cu, Hg, and Zn in leaf vegetables. In fact, under greenhouse conditions, Pb accumulation was effectively reduced. The main source of soil heavy metals was the application of large amounts of low-grade fertilizer. There was larger health risk for producers' children to consume vegetables from the three harmless vegetable bases than those of residents' children. The hazard index (HI) over a large area exceeded 1 for these two kinds of children in the MHGVB and LHGVB. There was also a slight risk in the SHGVB for producers' children solely. However, the HI of the whole area of the OGVB for two kinds of children was below 1, suggesting low risk of heavy metal exposure through the food chain. Notably, the contribution rate of Cu and Zn to the HI were

Health benefit of vegetable/fruit juice-based diet: Role of microbiome.

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Henning, Susanne M; Yang, Jieping; Shao, Paul; Lee, Ru-Po; Huang, Jianjun; Ly, Austin; Hsu, Mark; Lu, Qing-Yi; Thames, Gail; Heber, David; Li, Zhaoping

2017-05-19

The gut microbiota is an important contributor to human health. Vegetable/fruit juices provide polyphenols, oligosaccharides, fiber and nitrate (beet juice), which may induce a prebiotic-like effect. Juice-based diets are becoming popular. However, there is a lack of scientific evidence of their health benefits. It was our hypothesis that changes in the intestinal microbiota induced by a juice-based diet play an important role in their health benefits. Twenty healthy adults consumed only vegetable/fruit juices for 3 days followed by 14 days of customary diet. On day 4 we observed a significant decrease in weight and body mass index (p = 2.0E -05 ), which was maintained until day 17 (p = 3.0E -04 ). On day 4 the proportion of the phylum Firmicutes and Proteobacteria in stool was significantly decreased and Bacteroidetes and Cyanobacteria was increased compared to baseline and was partially reversed on day 17. On day 4 plasma and urine nitric oxide was increased by 244 ± 89% and 450 ± 360%, respectively, and urinary lipid peroxidation marker malondialdehyde was decreased by 32 ± 21% compared to baseline. General well-being score was increased at the end of the study. In summary a 3-day juice-based diet altered the intestinal microbiota associated with weight loss, increase in the vasodilator NO, and decrease in lipid oxidation.

Extending a field-based Sonoran desert vegetation classification to a regional scale using optical and microwave satellite imagery

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Shupe, Scott Marshall

2000-10-01

Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers

Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

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Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

2010-05-01

The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

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Fisher, Jeremy Isaac

Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat

Detecting long-term changes to vegetation in northern Canada using the Landsat satellite image archive

International Nuclear Information System (INIS)

Fraser, R H; Olthof, I; Carrière, M; Deschamps, A; Pouliot, D

2011-01-01

Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM + satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1–25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.

Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

Science.gov (United States)

Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

2017-04-01

vegetation cover (taken for vegetation temperature) Ta and efficient radiation temperature Ts.eff, as well as land surface emissivity E, normalized difference vegetation index NDVI, vegetation cover fraction B, and leaf area index LAI. The SEVIRI-based retrievals have included precipitation, LST Tls and Ta, E at daylight and nighttime, LAI (daily), and B. From the MSU-MR data there have been retrieved values of all the same characteristics as from the AVHRR data. The MSU-MR-based daily and monthly sums of precipitation have been calculated using the developed earlier and modified Multi Threshold Method (MTM) intended for the cloud detection and identification of its types around the clock as well as allocation of precipitation zones and determination of instantaneous maximum rainfall intensities for each pixel at that the transition from assessing rainfall intensity to estimating their daily values is a key element of the MTM. Measurement data from 3 IR MSU-MR channels (3.8, 11 i 12 μm) as well as their differences have been used in the MTM as predictors. Controlling the correctness of the MSU-MR-derived rainfall estimates has been carried out when comparing with analogous AVHRR- and SEVIRI-based retrievals and with precipitation amounts measured at the agricultural meteorological station of the study region. Probability of rainfall zones determination from the MSU-MR data, to match against the actual ones, has been 75-85% as well as for the AVHRR and SEVIRI data. The time behaviors of satellite-derived and ground-measured daily and monthly precipitation sums for vegetation season and yeaŗ correspondingly, have been in good agreement with each other although the first ones have been smoother than the latter. Discrepancies have existed for a number of local maxima for which satellite-derived precipitation estimates have been less than ground-measured values. It may be due to the different spatial scales of areal satellite-derived and point ground-based estimates. Some

CHARACTERISING VEGETATED SURFACES USING MODIS MULTIANGULAR SATELLITE DATA

Directory of Open Access Journals (Sweden)

G. McCamley

2012-07-01

Full Text Available Bidirectional Reflectance Distribution Functions (BRDF seek to represent variations in surface reflectance resulting from changes in a satellite's view and solar illumination angles. BRDF representations have been widely used to assist in the characterisation of vegetation. However BRDF effects are often noisy, difficult to interpret and are the spatial integral of all the individual surface features present in a pixel. This paper describes the results of an approach to understanding how BRDF effects can be used to characterise vegetation. The implementation of the Ross Thick Li Sparse BRDF model using MODIS is a stable, mature data product with a 10 year history and is a ready data source. Using this dataset, a geometric optical model is proposed that seeks to interpret the BRDF effects in terms of Normalised Difference Vegetation Index (NDVI and a height-to-width ratio of the vegetation components. The height-to-width ratio derived from this model seeks to represent the dependence of NDVI to changes in view zenith angle as a single numeric value. The model proposed within this paper has been applied to MODIS pixels in central Australia for areas in excess of 18,000 km2. The study area is predominantly arid and sparsely vegetated which provides a level of temporal and spatial homogeneity. The selected study area also minimises the effects associated with mutual obscuration of vegetation which is not considered by the model. The results are represented as a map and compared to NDVI derived from MODIS and NDVI derived from Landsat mosaics developed for Australia's National Carbon Accounting System (NCAS. The model reveals additional information not obvious in reflectance data. For example, the height-to-width ratio is able to reveal vegetation features in arid areas that do not have an accompanying significant increase in NDVI derived from MODIS, i.e. the height-to-width ratio reveals vegetation which is otherwise only apparent in NDVI derived

Vegetation mapping from high-resolution satellite images in the heterogeneous arid environments of Socotra Island (Yemen)

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Malatesta, Luca; Attorre, Fabio; Altobelli, Alfredo; Adeeb, Ahmed; De Sanctis, Michele; Taleb, Nadim M.; Scholte, Paul T.; Vitale, Marcello

2013-01-01

Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geomorphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum likelihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.

Post-fire vegetation recovery in Portugal based ewline on spot/vegetation data

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C. Gouveia

2010-04-01

Full Text Available A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI, with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation

A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE for Satellite-Based Actual Evapotranspiration Estimation

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Hua Zhang

2016-09-01

Full Text Available The estimation of spatially-variable actual evapotranspiration (AET is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE, to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges. Compared to traditional triangle methods, TAVE introduces three unique features: (i the discretization of the domain as overlapping elevation zones; (ii a variable wet edge that is a function of elevation zone; and (iii variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA and a global AET product (MOD16 over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%, in contrast to substantial overestimation by TA (+234% and underestimation by MOD16 (−50%. In forested (non-irrigated, water consuming regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange

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Joiner, J.; Yoshida, Y.; Vasilkov, A. P.; Schaefer, K.; Jung, M.; Guanter, L.; Zhang, Y; Garrity, S.; Middleton, E. M.; Huemmrich, K. F.;

Detecting robust signals of interannual variability of gross primary productivity in Asia from multiple terrestrial carbon cycle models and long-term satellite-based vegetation data

Science.gov (United States)

Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.

2014-12-01

Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently

Satellite monitoring of different vegetation types by differential optical absorption spectroscopy (DOAS in the red spectral range

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T. Wagner

2007-01-01

Full Text Available A new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms relying on the strong change of the reflectivity in the red and near infrared spectral region, our method analyses weak narrow-band (few nm reflectance structures (i.e. "fingerprint" structures of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS, which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric absorptions are automatically corrected (in contrast to other algorithms. The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the results illustrate the seasonal cycles of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future.

Validation of an Innovative Satellite-Based UV Dosimeter

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Morelli, Marco; Masini, Andrea; Simeone, Emilio; Khazova, Marina

2016-08-01

We present an innovative satellite-based UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in-vivo assessment of the erythemal effects on some volunteers having a controlled exposure to solar radiation.Both validations showed that the satellite-based UV dosimeter has a good accuracy and reliability needed for health-related applications.The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. This app will be launched on the global market by siHealth Ltd in May 2016 under the name of "HappySun" and available both for Android and for iOS devices (more info on http://www.happysun.co.uk).Extensive R&D activities are on-going for further improvement of the satellite-based UV dosimeter's accuracy.

Global changes in dryland vegetation dynamics (1988–2008 assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data

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N. Andela

2013-10-01

Full Text Available Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008 vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI and the recently developed passive-microwave-based Vegetation Optical Depth (VOD. The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.

Consumer clusters in Denmark based on coarse vegetable intake frequency, explained by hedonics, socio-demographic, health and food lifestyle factors

DEFF Research Database (Denmark)

Beck, Tove Kjær; Jensen, Sidsel; Simmelsgaard, H.

2015-01-01

for the reported vegetable intake, as these differed across the clusters. Each cluster had distinct socio-demographic, health and food lifestyle profiles. 'Low frequency' was characterized by uninvolved consumers with lack of interest in food, 'carrot eaters' vegetable intake was driven by health aspects....... The present study drew upon a large Danish survey (n = 1079) to study the intake of coarse vegetables among Danish consumers. Four population clusters were identified based on their intake of 17 different coarse vegetables, and profiled according to hedonics, socio-demographic, health, and food lifestyle...... ('beetroot eaters'), and a high intake frequency of all coarse vegetables ('high frequency'). There was a relationship between reported liking and reported intake frequency for all tested vegetables. Preference for foods with a sweet, salty or bitter taste, in general, was also identified to be decisive...

Identification of High-Variation Fields based on Open Satellite Imagery

DEFF Research Database (Denmark)

Jeppesen, Jacob Høxbroe; Jacobsen, Rune Hylsberg; Nyholm Jørgensen, Rasmus

2017-01-01

. The categorization is based on vegetation indices derived from Sentinel-2 satellite imagery. A case study on 7678 winter wheat fields is presented, which employs open data and open source software to analyze the satellite imagery. Furthermore, the method can be automated to deliver categorizations at every update......This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective...

Health Benefits of Fruits and Vegetables1

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Slavin, Joanne L.; Lloyd, Beate

2012-01-01

Fruits and vegetables are universally promoted as healthy. The Dietary Guidelines for Americans 2010 recommend you make one-half of your plate fruits and vegetables. Myplate.gov also supports that one-half the plate should be fruits and vegetables. Fruits and vegetables include a diverse group of plant foods that vary greatly in content of energy and nutrients. Additionally, fruits and vegetables supply dietary fiber, and fiber intake is linked to lower incidence of cardiovascular disease and obesity. Fruits and vegetables also supply vitamins and minerals to the diet and are sources of phytochemicals that function as antioxidants, phytoestrogens, and antiinflammatory agents and through other protective mechanisms. In this review, we describe the existing dietary guidance on intake of fruits and vegetables. We also review attempts to characterize fruits and vegetables into groups based on similar chemical structures and functions. Differences among fruits and vegetables in nutrient composition are detailed. We summarize the epidemiological and clinical studies on the health benefits of fruits and vegetables. Finally, we discuss the role of fiber in fruits and vegetables in disease prevention. PMID:22797986

Modeling water and heat balance components of large territory for vegetation season using information from polar-orbital and geostationary meteorological satellites

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Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

2015-04-01

-2013 vegetation seasons. To provide the retrieval of Ts.eff, E, Ta, NDVI, B, and LAI the previously developed technologies of AVHRR data processing have been refined and adapted to the region of interest. The updated linear regression estimators for Ts.eff and Tà have been built using representative training samples compiled for above vegetation seasons. The updated software package has been applied for AVHRR data processing to generate estimates of named values. To verify the accuracy of these estimates the error statistics of Ts.eff and Ta derivation has been investigated for various days of named seasons using comparison with in-situ ground-based measurements. On the base of special technology and Internet resources the remote sensing products Tls, E, NDVI, LAI derived from MODIS data and covering the study area have been extracted from LP DAAC web-site for the same vegetation seasons. The reliability of the MODIS-derived Tls estimates has been confirmed via comparison with analogous and collocated ground-, AVHRR-, and SEVIRI-based ones. The prepared remote sensing dataset has also included the SEVIRI-derived estimates of Tls, E, NDVI, Ta at daylight and night-time and daily estimates of LAI. The Tls estimates has been built utilizing the method and technology developed for the retrieval of Tls and E from 15 minutes time interval SEVIRI data in IR channels 10.8 and 12.0 µm (classified as 100% cloud-free and covering the area of interest) at three successive times without accurate a priori knowledge of E. Comparison of the SEVIRI-based Tls retrievals with independent collocated Tls estimates generated at the Land Surface Analysis Satellite Applications Facility (LSA SAF, Lisbon, Portugal) has given daily- or monthly-averaged values of RMS deviation in the range of 2°C for various dates and months during the mentioned vegetation seasons which is quite acceptable result. The reliability of the SEVIRI-based Tls estimates for the study area has been also confirmed by comparing

Satellite -Based Networks for U-Health & U-Learning

Science.gov (United States)

Graschew, G.; Roelofs, T. A.; Rakowsky, S.; Schlag, P. M.

2008-08-01

The use of modern Information and Communication Technologies (ICT) as enabling tools for healthcare services (eHealth) introduces new ways of creating ubiquitous access to high-level medical care for all, anytime and anywhere (uHealth). Satellite communication constitutes one of the most flexible methods of broadband communication offering high reliability and cost-effectiveness of connections meeting telemedicine communication requirements. Global networks and the use of computers for educational purposes stimulate and support the development of virtual universities for e-learning. Especially real-time interactive applications can play an important role in tailored and personalised services.

Improving satellite-based post-fire evapotranspiration estimates in semi-arid regions

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Poon, P.; Kinoshita, A. M.

2017-12-01

Climate change and anthropogenic factors contribute to the increased frequency, duration, and size of wildfires, which can alter ecosystem and hydrological processes. The loss of vegetation canopy and ground cover reduces interception and alters evapotranspiration (ET) dynamics in riparian areas, which can impact rainfall-runoff partitioning. Previous research evaluated the spatial and temporal trends of ET based on burn severity and observed an annual decrease of 120 mm on average for three years after fire. Building upon these results, this research focuses on the Coyote Fire in San Diego, California (USA), which burned a total of 76 km2 in 2003 to calibrate and improve satellite-based ET estimates in semi-arid regions affected by wildfire. The current work utilizes satellite-based products and techniques such as the Google Earth Engine Application programming interface (API). Various ET models (ie. Operational Simplified Surface Energy Balance Model (SSEBop)) are compared to the latent heat flux from two AmeriFlux eddy covariance towers, Sky Oaks Young (US-SO3), and Old Stand (US-SO2), from 2000 - 2015. The Old Stand tower has a low burn severity and the Young Stand tower has a moderate to high burn severity. Both towers are used to validate spatial ET estimates. Furthermore, variables and indices, such as Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and the Normalized Burn Ratio (NBR) are utilized to evaluate satellite-based ET through a multivariate statistical analysis at both sites. This point-scale study will able to improve ET estimates in spatially diverse regions. Results from this research will contribute to the development of a post-wildfire ET model for semi-arid regions. Accurate estimates of post-fire ET will provide a better representation of vegetation and hydrologic recovery, which can be used to improve hydrologic models and predictions.

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.

A MODIS-based vegetation index climatology

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Our motivation here is to provide information for the NASA Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval algorithms (launch in 2014). Vegetation attenuates the signal and the algorithms must correct for this effect. One approach is to use data that describes the canopy water ...

Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

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MARIA IOANA VLAD

2011-01-01

Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

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Boken, Vijendra K.; Easson, Gregory L.; Rowland, James

2010-01-01

The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R 2. The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel.

Science.gov (United States)

Brandt, Martin; Mbow, Cheikh; Diouf, Abdoul A; Verger, Aleixandre; Samimi, Cyrus; Fensholt, Rasmus

2015-04-01

After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal. © 2014 John Wiley & Sons Ltd.

Satellite-based detection of global urban heat-island temperature influence

Science.gov (United States)

Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

2002-01-01

This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

Towards a more objective evaluation of modelled land-carbon trends using atmospheric CO2 and satellite-based vegetation activity observations

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D. Dalmonech

2013-06-01

Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular the net land–atmosphere carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to better understand the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely sensed vegetation activity to provide a novel set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits specifically considers the robustness of information given that the uncertainty of both data and evaluation methodology is largely unknown or difficult to quantify. Based on these considerations, we introduce a baseline benchmark – a minimum test that any model has to pass – to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI Earth System Model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite-based vegetation activity data allows pinpointing of specific model deficiencies that would not be possible by the sole use of atmospheric CO2 observations.

Validation and in vivo assessment of an innovative satellite-based solar UV dosimeter for a mobile app dedicated to skin health.

Science.gov (United States)

Morelli, M; Masini, A; Simeone, E; Khazova, M

2016-08-31

We present an innovative satellite-based solar UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in vivo assessment of the erythemal effects on some volunteers having controlled exposure to solar radiation. The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. Both validations showed that the system has a good accuracy and reliability needed for health-related applications. This app will be launched on the market by siHealth Ltd in May 2016 under the name of "HappySun" and is available for both Android and iOS devices (more info on ). Extensive R&D activities are on-going for the further improvement of the satellite-based UV dosimeter's accuracy.

Australian consumer awareness of health benefits associated with vegetable consumption.

Science.gov (United States)

Rekhy, Reetica; Khan, Aila; Eason, Jocelyn; Mactavish-West, Hazel; Lister, Carolyn; Mcconchie, Robyn

2017-04-01

The present study investigated the perceived health benefits of specific vegetable consumption to guide the use of nutrition and health claims on vegetable marketing collateral. Free elicitation and consumer ranking data were collected through an online survey of 1000 adults from across Australia and analysed for the perceived importance of vegetables in the daily diet, number of serves consumed per day, knowledge about health-related benefits of specific vegetables and perceived health benefits of vegetable consumption. The importance of vegetables in the diet and daily vegetable consumption was higher in people from an English-speaking background, females, people aged 45 years and over and people living in non-metropolitan areas. Digestion was selected as the major health benefit from consumption of specific vegetables. However, understanding of the health benefits of specific vegetable consumption was relatively low among consumers. Half of the respondents were not sure of the health benefits associated with specific vegetables, except for carrots and spinach. Some respondents volunteered nutrient content or other information. There was no clear indication that consumers understand the specific health benefits conferred by consumption of vegetables. Nutrient and health benefit labelling therefore has the capacity to enhance knowledge of vegetable consumers. It is recommended that health benefit labelling be tailored to promote greater consumption of vegetables in those demographic groups where vegetable consumption was lower. The present study assists the Australian vegetable industry in helping consumers make more informed consumption choices. © 2016 Dietitians Association of Australia.

An Intercomparison of Vegetation Products from Satellite-based Observations used for Soil Moisture Retrievals

Science.gov (United States)

Vreugdenhil, Mariette; de Jeu, Richard; Wagner, Wolfgang; Dorigo, Wouter; Hahn, Sebastian; Bloeschl, Guenter

2013-04-01

Vegetation and its water content affect active and passive microwave soil moisture retrievals and need to be taken into account in such retrieval methodologies. This study compares the vegetation parameterisation that is used in the TU-Wien soil moisture retrieval algorithm to other vegetation products, such as the Vegetation Optical Depth (VOD), Net Primary Production (NPP) and Leaf Area Index (LAI). When only considering the retrieval algorithm for active microwaves, which was developed by the TU-Wien, the effect of vegetation on the backscattering coefficient is described by the so-called slope [1]. The slope is the first derivative of the backscattering coefficient in relation to the incidence angle. Soil surface backscatter normally decreases quite rapidly with the incidence angle over bare or sparsely vegetated soils, whereas the contribution of dense vegetation is fairly uniform over a large range of incidence angles. Consequently, the slope becomes less steep with increasing vegetation. Because the slope is a derivate of noisy backscatter measurements, it is characterised by an even higher level of noise. Therefore, it is averaged over several years assuming that the state of the vegetation doesn't change inter-annually. The slope is compared to three dynamic vegetation products over Australia, the VOD, NPP and LAI. The VOD was retrieved from AMSR-E passive microwave data using the VUA-NASA retrieval algorithm and provides information on vegetation with a global coverage of approximately every two days [2]. LAI is defined as half the developed area of photosynthetically active elements of the vegetation per unit horizontal ground area. In this study LAI is used from the Geoland2 products derived from SPOT Vegetation*. The NPP is the net rate at which plants build up carbon through photosynthesis and is a model-based estimate from the BiosEquil model [3, 4]. Results show that VOD and slope correspond reasonably well over vegetated areas, whereas in arid

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)

THE ANALYSIS OF MOISTURE DEFICIT BASED ON MODIS AND LANDSAT SATELLITE IMAGES. CASE STUDY: THE OLTENIA PLAIN

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ONȚEL IRINA

2014-03-01

Full Text Available Satellite images are an important source of information to identify and analyse some hazardous climatic phenomena such as the dryness and drought. These phenomena are characterized by scarce rainfall, increased evapotranspiration and high soil moisture deficit. The soil water reserve depletes to the wilting coefficient, soon followed by the pedological drought which has negative effects on vegetation and agricultural productivity. The MODIS satellite images (Moderate Resolution Imaging Spectroradiometer allow the monitoring of the vegetation throughout the entire vegetative period, with a frequency of 1-2 days and with a spatial resolution of 250 m, 500 m and 1 km away. Another useful source of information is the LANDSAT satellite images, with a spatial resolution of 30 m. Based on MODIS and Landsat satellite images, were calculated moisture monitoring index such as SIWSI (Shortwave Infrared Water Stress Index. Consequently, some years with low moisture such as 2000, 2002, 2007 and 2012 could be identified. Spatially, the areas with moisture deficit varied from one year to another all over the whole analised period (2000-2012. The remote sensing results was corelated with Standard Precipitation Anomaly, which gives a measure of the severity of a wet or dry event.

Advances in monitoring vegetation and land use dynamics in the Sahel

DEFF Research Database (Denmark)

Mbow, Cheikh; Fensholt, Rasmus; Nielsen, Thomas Theis

2014-01-01

of CO2 in the atmosphere, grazing pressure, bush fires and agricultural expansion or contraction. The use of satellite data in combination with field data played a major role in the monitoring of vegetation dynamics and land use in the Sahel, since the mega drought of the 1970s and the 1980s. This paper...... briefly reviews the advance of satellite-based monitoring of vegetation dynamics over these 40 years. We discuss the promises of current and likely future data sources and analysis tools, as well as the need to strengthen in situ data collection to support and validate satellite-based vegetation and land...

An Exploitation of Satellite-based Observation for Health Information: The UFOS Project

Energy Technology Data Exchange (ETDEWEB)

Mangin, A.; Morel, M.; Fanton d' Andon, O

2000-07-01

Short, medium and long-term trends of UV intensity levels are of crucial importance for either assessing effective biological impacts on human population, or implementing adequate preventive behaviours. Better information on a large spatial scale and increased public awareness of the short-term variations in UV values will help to support health agencies' goals of educating the public on UV risks. The Ultraviolet Forecast Operational Service Project (UFAS), financed in part by the European Commission/DG Information Society (TEN-TELECOM programme), aims to exploit satellite-based observations and to supply a set of UV products directly useful to health care. The short-term objective is to demonstrate the technical and economical feasibility and benefits that could be brought by such a system. UFOS is carried out by ACRI, with the support of an Advisory Group chaired by WHO and involving representation from the sectors of Health (WHO, INTERSUN collaborating centres, ZAMBON), Environment (WMO, IASB), and Telecommunications (EURECOM, IMET). (author)

An Exploitation of Satellite-based Observation for Health Information: The UFOS Project

International Nuclear Information System (INIS)

Mangin, A.; Morel, M.; Fanton d'Andon, O.

2000-01-01

Short, medium and long-term trends of UV intensity levels are of crucial importance for either assessing effective biological impacts on human population, or implementing adequate preventive behaviours. Better information on a large spatial scale and increased public awareness of the short-term variations in UV values will help to support health agencies' goals of educating the public on UV risks. The Ultraviolet Forecast Operational Service Project (UFAS), financed in part by the European Commission/DG Information Society (TEN-TELECOM programme), aims to exploit satellite-based observations and to supply a set of UV products directly useful to health care. The short-term objective is to demonstrate the technical and economical feasibility and benefits that could be brought by such a system. UFOS is carried out by ACRI, with the support of an Advisory Group chaired by WHO and involving representation from the sectors of Health (WHO, INTERSUN collaborating centres, ZAMBON), Environment (WMO, IASB), and Telecommunications (EURECOM, IMET). (author)

Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method

Science.gov (United States)

Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian

2017-06-01

Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.

Global Crop Monitoring: A Satellite-Based Hierarchical Approach

Directory of Open Access Journals (Sweden)

Bingfang Wu

2015-04-01

Full Text Available Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China and “sub-countries” (for the nine largest countries. The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI, Vegetation Condition Index (VCI, Cropped Arable Land Fraction (CALF as well as Cropping Intensity (CI. Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI, cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion. Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly “CropWatch bulletin” which

Modeling Agricultural Crop Production in China using AVHRR-based Vegetation Health Indices

Science.gov (United States)

Yang, B.; Kogan, F.; Guo, W.; Zhiyuan, P.; Xianfeng, J.

Weather related crop losses have always been a concern for farmers On a wider scale it has always influenced decision of Governments traders and other policy makers for the purpose of balanced food supplies trade and distribution of aid to the nations in need Therefore national policy and decision makers are giving increasing importance to early assessment of crop losses in response to weather fluctuations This presentation emphasizes utility of AVHRR-based Vegetation health index VHI for early warning of drought-related losses of agricultural production in China The VHI is a three-channel index characterizing greenness vigor and temperature of land surface which can be used as proxy for estimation of how healthy and potentially productive could be vegetation China is the largest in the world producer of grain including wheat and rice and cotton In the major agricultural areas China s crop production is very dependent on weather The VHI being a proxy indicator of weather impact on vegetation showed some correlation with productivity of agricultural crops during the critical period of their development The periods of the strongest correlation were investigated and used to build regression models where crop yield deviation from technological trend was accepted as a dependent and VHI as independent variables The models were developed for several major crops including wheat corn and soybeans

Canopy Modeling of Aquatic Vegetation: Construction of Submerged Vegetation Index

Science.gov (United States)

Ma, Z.; Zhou, G.

2018-04-01

The unique spectral characteristics of submerged vegetation in wetlands determine that the conventional terrestrial vegetation index cannot be directly employed to species identification and parameter inversion of submerged vegetation. Based on the Aquatic Vegetation Radiative Transfer model (AVRT), this paper attempts to construct an index suitable for submerged vegetation, the model simulated data and a scene of Sentinel-2A image in Taihu Lake, China are utilized for assessing the performance of the newly constructed indices and the existent vegetation indices. The results show that the angle index composed by 525 nm, 555 nm and 670 nm can resist the effects of water columns and is more sensitive to vegetation parameters such as LAI. Furthermore, it makes a well discrimination between submerged vegetation and water bodies in the satellite data. We hope that the new index will provide a theoretical basis for future research.

Vegetable-based dietary pattern and liver cancer risk: results from the Shanghai women's and men's health studies.

Science.gov (United States)

Zhang, Wei; Xiang, Yong-Bing; Li, Hong-Lan; Yang, Gong; Cai, Hui; Ji, Bu-Tian; Gao, Yu-Tang; Zheng, Wei; Shu, Xiao-Ou

2013-10-01

Although dietary patterns, specific foods, and their constituents have been linked to cancer risk, the role of dietary patterns and specific food groups in liver cancer risk has not been investigated. In the Shanghai Women's Health Study (SWHS) and Shanghai Men's Health Study (SMHS), two cohort studies of 132 837 Chinese women and men, we evaluated the relationship between dietary patterns, food groups, and liver cancer risk. Through in-person interviews, dietary information intake over the preceding year was collected by using a validated food-frequency questionnaire. Cox regression model was used to estimate hazard ratios and 95% confidence intervals with adjustment for potential confounders. During an average follow-up of 10.9 (SWHS) or 5.5 (SMHS) years, 267 incident liver cancer cases were identified after the first 2 years of study enrolment. Three dietary patterns were derived by factor analysis. A vegetable-based dietary pattern was inversely associated with liver cancer; hazard ratios (95% confidence intervals) for the lowest to highest quartiles were: 1.00; 0.98 (0.71-1.35); 0.93 (0.67-1.29); and 0.58 (0.40-0.84); P(trend) = 0.01. The association was stronger among participants with a history of chronic liver disease. Further analyses showed high intakes of celery, mushrooms, allium vegetables, composite vegetables (including asparagus lettuce and garland chrysanthemum), legumes and legume products were associated with reduced liver cancer risk (all P(trend) < 0.05). Fruit- and meat-based dietary patterns were not associated with liver cancer risk. Our study suggests that a vegetable-based dietary pattern is associated with reduced liver cancer risk. © 2013 Japanese Cancer Association.

A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

Science.gov (United States)

Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

2017-12-01

The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

International Nuclear Information System (INIS)

Hashim, M; Pour, A B; Onn, C H

2014-01-01

Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate

Satellite Based Cropland Carbon Monitoring System

Science.gov (United States)

Bandaru, V.; Jones, C. D.; Sedano, F.; Sahajpal, R.; Jin, H.; Skakun, S.; Pnvr, K.; Kommareddy, A.; Reddy, A.; Hurtt, G. C.; Izaurralde, R. C.

2017-12-01

Agricultural croplands act as both sources and sinks of atmospheric carbon dioxide (CO2); absorbing CO2 through photosynthesis, releasing CO2 through autotrophic and heterotrophic respiration, and sequestering CO2 in vegetation and soils. Part of the carbon captured in vegetation can be transported and utilized elsewhere through the activities of food, fiber, and energy production. As well, a portion of carbon in soils can be exported somewhere else by wind, water, and tillage erosion. Thus, it is important to quantify how land use and land management practices affect the net carbon balance of croplands. To monitor the impacts of various agricultural activities on carbon balance and to develop management strategies to make croplands to behave as net carbon sinks, it is of paramount importance to develop consistent and high resolution cropland carbon flux estimates. Croplands are typically characterized by fine scale heterogeneity; therefore, for accurate carbon flux estimates, it is necessary to account for the contribution of each crop type and their spatial distribution. As part of NASA CMS funded project, a satellite based Cropland Carbon Monitoring System (CCMS) was developed to estimate spatially resolved crop specific carbon fluxes over large regions. This modeling framework uses remote sensing version of Environmental Policy Integrated Climate Model and satellite derived crop parameters (e.g. leaf area index (LAI)) to determine vertical and lateral carbon fluxes. The crop type LAI product was developed based on the inversion of PRO-SAIL radiative transfer model and downscaled MODIS reflectance. The crop emergence and harvesting dates were estimated based on MODIS NDVI and crop growing degree days. To evaluate the performance of CCMS framework, it was implemented over croplands of Nebraska, and estimated carbon fluxes for major crops (i.e. corn, soybean, winter wheat, grain sorghum, alfalfa) grown in 2015. Key findings of the CCMS framework will be presented

A change detection strategy for monitoring vegetative and land-use cover types using remotely-sensed, satellite-based data

International Nuclear Information System (INIS)

Hallum, C.

1993-01-01

Changes to the environment are of critical concern in the world today; consequently, monitoring such changes and assessing their impacts are tasks demanding considerably higher priority. The ecological impacts of the natural global cycles of gases and particulates in the earth's atmosphere are highly influenced by the extent of changes to vegetative canopy characteristics which dictates the need for capability to detect and assess the magnitude of such changes. The primary emphasis of this paper is on the determination of the size and configuration of the sampling unit that maximizes the probability of its intersection with a 'change' area. Assessment of the significance of the 'change' in a given locality is also addressed and relies on a statistical approach that compares the number of elemental units exceeding a reflectance threshold when compared to a previous point in time. Consideration is also given to a technical framework that supports quantifying the magnitude of the 'change' over large areas (i.e., the estimated area changing from forest to agricultural land-use). The latter entails a multistage approach which utilizes satellite-based and other related data sources

Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

Science.gov (United States)

Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

2015-04-01

Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

Use of satellite imagery to identify vegetation cover changes following the Waldo Canyon Fire event, Colorado, 2012-2013

Science.gov (United States)

Cole, Christopher J.; Friesen, Beverly A.; Wilson, Earl M.

2014-01-01

The Waldo Canyon Fire of 2012 was one of the most destructive wildfire events in Colorado history. The fire burned a total of 18,247 acres, claimed 2 lives, and destroyed 347 homes. The Waldo Canyon Fire continues to pose challenges to nearby communities. In a preliminary emergency assessment conducted in 2012, the U.S. Geological Survey (USGS) concluded that drainage basins within and near the area affected by the Waldo Canyon Fire pose a risk for future debris flow events. Rainfall over burned, formerly vegetated surfaces resulted in multiple flood and debris flow events that affected the cities of Colorado Springs and Manitou Springs in 2013. One fatality resulted from a mudslide near Manitou Springs in August 2013. Federal, State, and local governments continue to monitor these hazards and other post-fire effects, along with the region’s ecological recovery. At the request of the Colorado Springs Office of Emergency Management, the USGS Special Applications Science Center developed a geospatial product to identify vegetation cover changes following the 2012 Waldo Canyon Fire event. Vegetation cover was derived from July 2012 WorldView-2 and September 2013 QuickBird multispectral imagery at a spatial resolution of two meters. The 2012 image was collected after the fire had reached its maximum extent. Per-pixel increases and decreases in vegetation cover were identified by measuring spectral changes that occurred between the 2012 and 2013 image dates. A Normalized Difference Vegetation Index (NDVI), and Green-Near Infrared Index (GRNIR) were computed from each image. These spectral indices are commonly used to characterize vegetation cover and health condition, due to their sensitivity to detect foliar chlorophyll content. Vector polygons identifying surface-cover feature boundaries were derived from the 2013 imagery using image segmentation software. This geographic software groups similar image pixels into vector objects based upon their spatial and spectral

Monitoring and modeling crop health and water use via in-situ, airborne and space-based platforms

KAUST Repository

McCabe, M. F.

2014-12-01

The accurate retrieval of plant water use, health and function together with soil state and condition, represent key objectives in the management and monitoring of large-scale agricultural production. In regions of water shortage or stress, understanding the sustainable use of available water supplies is critical. Unfortunately, this need is all too often limited by a lack of reliable observations. Techniques that balance the demand for reliable ground-based data with the rapid retrieval of spatially distributed crop characteristics represent a needed line of research. Data from in-situ monitoring coupled with advances in satellite retrievals of key land surface variables, provide the information necessary to characterize many crop health and water use features, including evaporation, leaf-chlorophyll and other common vegetation indices. With developments in UAV and quadcopter solutions, the opportunity to bridge the spatio-temporal gap between satellite and ground based sensing now exists, along with the capacity for customized retrievals of crop information. While there remain challenges in the routine application of autonomous airborne systems, the state of current technology and sensor developments provide the capacity to explore the operational potential. While this presentation will focus on the multi-scale estimation of crop-water use and crop-health characteristics from satellite-based sensors, the retrieval of high resolution spatially distributed information from near-surface airborne and ground-based systems will also be examined.

Monitoring and Modeling Crop Health and Water Use via in-situ, Airborne and Space-based Platforms

Science.gov (United States)

McCabe, M. F.

2014-12-01

The accurate retrieval of plant water use, health and function together with soil state and condition, represent key objectives in the management and monitoring of large-scale agricultural production. In regions of water shortage or stress, understanding the sustainable use of available water supplies is critical. Unfortunately, this need is all too often limited by a lack of reliable observations. Techniques that balance the demand for reliable ground-based data with the rapid retrieval of spatially distributed crop characteristics represent a needed line of research. Data from in-situ monitoring coupled with advances in satellite retrievals of key land surface variables, provide the information necessary to characterize many crop health and water use features, including evaporation, leaf-chlorophyll and other common vegetation indices. With developments in UAV and quadcopter solutions, the opportunity to bridge the spatio-temporal gap between satellite and ground based sensing now exists, along with the capacity for customized retrievals of crop information. While there remain challenges in the routine application of autonomous airborne systems, the state of current technology and sensor developments provide the capacity to explore the operational potential. While this presentation will focus on the multi-scale estimation of crop-water use and crop-health characteristics from satellite-based sensors, the retrieval of high resolution spatially distributed information from near-surface airborne and ground-based systems will also be examined.

Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

Science.gov (United States)

Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

2018-04-01

Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0

A simple model for yield prediction of rice based on vegetation index derived from satellite and AMeDAS data during ripening period

International Nuclear Information System (INIS)

Wakiyama, Y.; Inoue, K.; Nakazono, K.

2003-01-01

The present study was conducted to show a simple model for rice yield predicting by using a vegetation index (NDVI) derived from satellite and meteorological data. In a field experiment, the relationship between the vegetation index and radiation absorbed by the rice canopy was investigated from transplanting to maturity. Their correlation held. This result revealed that the vegetation index could be used as a measure of absorptance of solar radiation by rice canopy. NDVI multiplied by solar radiation (SR) every day was accumulated (Σ(SR·NDVI)) from the field experiment. Σ(SR·NDVI) was plotted against above ground dry matter. It was obvious that they had a strong relationship. Rice yield largely depends on solar radiation and air temperature during the ripening period. Air temperature affects dry matter production. Relationships between Y SR -1 (Y: rice yield, SR: solar radiation) and mean air temperature were investigated from meteorological data and statistical data on rice yield. There was an optimum air temperature, 21.3°C, for ripening. When it was near 21.3°C in the ripening period, the rice yield was higher. We proposed a simple model for yield prediction of rice based on these results. The model is composed with SR·NDVI and the optimum air temperature. Vegetation index was derived from 3 years, LANDSAT TM data in Toyama, Ishikawa, Fukui and Nagano prefectures at heading. The meteorological data was used from AMeDAS data. The model was described as follows: Y = 0.728 SR·NDVI−2.04(T−21.3) 2 + 282 (r 2 = 0.65, n = 43) where Y is rice yield (kg 10a -1 ), SR is solar radiation (MJ m -2 ) during the ripening period (from 10 days before heading to 30 days after heading), T is mean air temperature (°C) during the ripening period. RMSE was 33.7kg 10a -1 . The model revealed good precision. (author)

Northern Everglades, Florida, satellite image map

Science.gov (United States)

Thomas, Jean-Claude; Jones, John W.

2002-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Integration of satellite-induced fluorescence and vegetation optical depth to improve the retrieval of land evaporation

Science.gov (United States)

Pagán, B. R.; Martens, B.; Maes, W. H.; Miralles, D. G.

2017-12-01

Global satellite-based data sets of land evaporation overcome limitations in coverage of in situ measurements while retaining some observational nature. Although their potential for real world applications are promising, their value during dry conditions is still poorly understood. Most evaporation retrieval algorithms are not directly sensitive to soil moisture. An exception is the Global Land Evaporation Amsterdam Model (GLEAM), which uses satellite surface soil moisture and precipitation to account for land water availability. The existing methodology may greatly benefit from the optimal integration of novel observations of the land surface. Microwave vegetation optical depth (VOD) and near-infrared solar-induced fluorescence (SIF) are expected to reflect different aspects of evaporative stress. While the former is considered to be a proxy of vegetation water content, the latter is indicative of the activity of photosynthetic machinery. As stomata regulate both photosynthesis and transpiration, we expect a relationship between SIF and transpiration. An important motivation to incorporate observations in land evaporation calculations is that plant transpiration - usually the largest component of the flux - is extremely challenging to model due to species-dependent responses to drought. Here we present an innovative integration of VOD and SIF into the GLEAM evaporative stress function. VOD is utilized as a measurement of isohydricity to improve the representation of species specific drought responses. SIF is used for transpiration modelling, a novel application, and standardized by incoming solar radiation to better account for radiation-limited periods. Results are validated with global FLUXNET and International Soil Moisture Network data and demonstrate that the incorporation of VOD and SIF can yield accurate estimates of transpiration over large-scales, which are essential to further understand ecosystem-atmosphere feedbacks and the response of terrestrial

Satellite-Based Sunshine Duration for Europe

Directory of Open Access Journals (Sweden)

Bodo Ahrens

2013-06-01

Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

Vegetation classification and quatification by satellite image processing. A case study in north Portugal

Energy Technology Data Exchange (ETDEWEB)

Aranha, J.T. [Dept. Florestal, UTAD, 5001-801 Vila Real (Portugal); Viana, H.F. [Instituto Politecnico de Viseu, Escola Superior Agraria, Viseu (Portugal); Rodrigues, R. [Bioflag - Consulting - Santo Tirso (Portugal)

2008-07-01

The expected increase in Forest Biomass demand for energy production leads to derive expeditious and non-expensive techniques in order to classify vegetal land cover and evaluate the available biomass like to be harvested. Satellite image processing and classification, combined to field work, is a suitable tool to achieve these aims. A vegetation index (NDVI) was created by means of a Landsat TM image, from 2006, manipulation, in order to create a general vegetation map. Then, the same image was submitted to a supervised classification process in order to produce a land cover map (overall accuracy of 85%). In a second stage, they were collected NDVI values for each sampling plot, in order to update the database previous developed with data collected within forestry stands and shrubland. This data merging enabled to transform general vegetation map into available biomass within forestry stands and shrubland. The results showed a range of values from 0.25 up to 6.00 dry ton./ha for recent and former burnt areas recovered by Pinus pinaster (maritime pine) young trees and from 2.00 up to 9.00 dry ton./ha for recent and former burnt areas recovered by shrubs (e.g. genista or broom).

Mapping Aquatic Vegetation in a Large, Shallow Eutrophic Lake: A Frequency-Based Approach Using Multiple Years of MODIS Data

Directory of Open Access Journals (Sweden)

Xiaohan Liu

2015-08-01

Full Text Available Aquatic vegetation serves many important ecological and socioeconomic functions in lake ecosystems. The presence of floating algae poses difficulties for accurately estimating the distribution of aquatic vegetation in eutrophic lakes. We present an approach to map the distribution of aquatic vegetation in Lake Taihu (a large, shallow eutrophic lake in China and reduce the influence of floating algae on aquatic vegetation mapping. Our approach involved a frequency analysis over a 2003–2013 time series of the floating algal index (FAI based on moderate-resolution imaging spectroradiometer (MODIS data. Three phenological periods were defined based on the vegetation presence frequency (VPF and the growth of algae and aquatic vegetation: December and January composed the period of wintering aquatic vegetation; February and March composed the period of prolonged coexistence of algal blooms and wintering aquatic vegetation; and June to October was the peak period of the coexistence of algal blooms and aquatic vegetation. By comparing and analyzing the satellite-derived aquatic vegetation distribution and 244 in situ measurements made in 2013, we established a FAI threshold of −0.025 and VPF thresholds of 0.55, 0.45 and 0.85 for the three phenological periods. We validated the accuracy of our approach by comparing the results between the satellite-derived maps and the in situ results obtained from 2008–2012. The overall classification accuracy was 87%, 81%, 77%, 88% and 73% in the five years from 2008–2012, respectively. We then applied the approach to the MODIS images from 2003–2013 and obtained the total area of the aquatic vegetation, which varied from 265.94 km2 in 2007 to 503.38 km2 in 2008, with an average area of 359.62 ± 69.20 km2 over the 11 years. Our findings suggest that (1 the proposed approach can be used to map the distribution of aquatic vegetation in eutrophic algae-rich waters and (2 dramatic changes occurred in the

Consumer evaluation of 'Veggycation®', a website promoting the health benefits of vegetables.

Science.gov (United States)

Rekhy, Reetica; Khan, Aila; van Ogtrop, Floris; McConchie, Robyn

2017-03-01

Issue addressed Whether the website Veggycation ® appeals to particular groups of consumers significantly more than other groups. Methods Australian adults aged ≥18 years (n = 1000) completed an online survey. The website evaluation instrument used was tested for validity and reliability. Associations between demographic variables and website evaluation dimensions of attractiveness, content, user-friendliness and loyalty intentions were examined using a general linear model (GLM). The appraisal of the website was further investigated based on the respondents' daily consumption level of vegetables and the importance they attach to vegetable consumption in their diet, using GLM and a Tukey's all-pair comparison. Results Veggycation ® has a high level of acceptance among the Australian community with certain groups evaluating the website more favourably. These include women, people aged≤29 years, higher income respondents, non-metro respondents and those who viewed vegetables as extremely important in their daily diet. Conclusions Customisation of the website for consumer groups with low vegetable consumption is recommended. Designing tailored communication tools will assist in enhancing the knowledge base of vegetable-related health benefits and may promote vegetable consumption among the Australian population. So what? The promotion of higher vegetable consumption is aided by tailored, well-designed web communication. This study adds to the existing body of knowledge for the education of organisations developing e-tools for promoting health education and literacy.

Case study of atmospheric correction on CCD data of HJ-1 satellite based on 6S model

International Nuclear Information System (INIS)

Xue, Xiaoiuan; Meng, Oingyan; Xie, Yong; Sun, Zhangli; Wang, Chang; Zhao, Hang

2014-01-01

In this study, atmospheric radiative transfer model 6S was used to simulate the radioactive transfer process in the surface-atmosphere-sensor. An algorithm based on the look-up table (LUT) founded by 6S model was used to correct (HJ-1) CCD image pixel by pixel. Then, the effect of atmospheric correction on CCD data of HJ-1 satellite was analyzed in terms of the spectral curves and evaluated against the measured reflectance acquired during HJ-1B satellite overpass, finally, the normalized difference vegetation index (NDVI) before and after atmospheric correction were compared. The results showed: (1) Atmospheric correction on CCD data of HJ-1 satellite can reduce the ''increase'' effect of the atmosphere. (2) Apparent reflectance are higher than those of surface reflectance corrected by 6S model in band1∼band3, but they are lower in the near-infrared band; the surface reflectance values corrected agree with the measured reflectance values well. (3)The NDVI increases significantly after atmospheric correction, which indicates the atmospheric correction can highlight the vegetation information

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

International Nuclear Information System (INIS)

Boresjoe Bronge, Laine

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

Energy Technology Data Exchange (ETDEWEB)

Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

Science.gov (United States)

Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

2016-01-01

We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

14 CFR 141.91 - Satellite bases.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... assistant chief instructor is designated for each satellite base, and that assistant chief instructor is...

Feasibility Study of Land Cover Classification Based on Normalized Difference Vegetation Index for Landslide Risk Assessment

Directory of Open Access Journals (Sweden)

Thilanki Dahigamuwa

2016-10-01

Full Text Available Unfavorable land cover leads to excessive damage from landslides and other natural hazards, whereas the presence of vegetation is expected to mitigate rainfall-induced landslide potential. Hence, unexpected and rapid changes in land cover due to deforestation would be detrimental in landslide-prone areas. Also, vegetation cover is subject to phenological variations and therefore, timely classification of land cover is an essential step in effective evaluation of landslide hazard potential. The work presented here investigates methods that can be used for land cover classification based on the Normalized Difference Vegetation Index (NDVI, derived from up-to-date satellite images, and the feasibility of application in landslide risk prediction. A major benefit of this method would be the eventual ability to employ NDVI as a stand-alone parameter for accurate assessment of the impact of land cover in landslide hazard evaluation. An added benefit would be the timely detection of undesirable practices such as deforestation using satellite imagery. A landslide-prone region in Oregon, USA is used as a model for the application of the classification method. Five selected classification techniques—k-nearest neighbor, Gaussian support vector machine (GSVM, artificial neural network, decision tree and quadratic discriminant analysis support the viability of the NDVI-based land cover classification. Finally, its application in landslide risk evaluation is demonstrated.

Pollution characteristics and health risk assessment of heavy metals in the vegetable bases of northwest China.

Science.gov (United States)

Sawut, Rukeya; Kasim, Nijat; Maihemuti, Balati; Hu, Li; Abliz, Abdugheni; Abdujappar, Abdusalam; Kurban, Miradil

2018-06-17

The objective of this study was to investigate heavy metal contamination in four major vegetable bases and determine the health risks of residents in the vicinity of the highly urbanized city Urumqi in Xinjiang, China. In this paper, we determined the contents of six heavy metals (i.e., As, Zn, Cd, Cr, Hg, and Pb) in surface soil and groundwater to evaluate the levels of heavy metal pollution and human health risks using the pollution index (PI), the Nemerow integrated pollution index (NIPI), the ecological risk factor (E i r ), risk index (RI) and the health risk assessment model. The results showed that (1) The PI, NIPI, the ecological risk factor and risk index indicated that Cd and Hg were the primary pollutants in Sishihu village. These indices suggested moderate to slightly heavy potential ecological risks. In Anningqu town, Hg and Cd led to high levels of pollution and posed slightly heavy potential ecological risks. In Qinggedahu village, it was concluded that the metals Zn, Cr, Cd, Hg, and Pb caused moderate to heavy pollution. In Liushihu village, the pollution trends in the area were low. The results of the pollution level of the irrigation well water (i.e., groundwater) indicated that the well water was considerably safer than the soil, but Cr posed a slight pollution risk. (2) The non-carcinogenic risks for adults based on the HI values of these four vegetable bases were  Sishihu village > Anningqu town. For children, the carcinogenic risks posed by As through trough inhalation and ingestion were the main exposure pathways. From the TCR results, it can be seen that in Sishihu village, Anningqu town, and Qinggedahu village, the TCR values for adults and children were >1 × 10 -4 (unitless), and this degree of carcinogenic risk is unacceptable. (3) The identification of risk sources determined the main pollution sources affecting the vegetable bases were human activities and natural sources. Anthropogenic activities were most often related to

Satellite Leaf Area Index: Global Scale Analysis of the Tendencies Per Vegetation Type Over the Last 17 Years

Directory of Open Access Journals (Sweden)

Simon Munier

2018-03-01

Full Text Available The main objective of this study is to detect and quantify changes in the vegetation dynamics of each vegetation type at the global scale over the last 17 years. With recent advances in remote sensing techniques, it is now possible to study the Leaf Area Index (LAI seasonal and interannual variability at the global scale and in a consistent way over the last decades. However, the coarse spatial resolution of these satellite-derived products does not permit distinguishing vegetation types within mixed pixels. Considering only the dominant type per pixel has two main drawbacks: the LAI of the dominant vegetation type is contaminated by spurious signal from other vegetation types and at the global scale, significant areas of individual vegetation types are neglected. In this study, we first developed a Kalman Filtering (KF approach to disaggregate the satellite-derived LAI from GEOV1 over nine main vegetation types, including grasslands and crops as well as evergreen, broadleaf and coniferous forests. The KF approach permits the separation of distinct LAI values for individual vegetation types that coexist within a pixel. The disaggregated LAI product, called LAI-MC (Multi-Cover, consists of world-wide LAI maps provided every 10 days for each vegetation type over the 1999–2015 period. A trend analysis of the original GEOV1 LAI product and of the disaggregated LAI time series was conducted using the Mann-Kendall test. Resulting trends of the GEOV1 LAI (which accounts for all vegetation types compare well with previous regional or global studies, showing a greening over a large part of the globe. When considering each vegetation type individually, the largest global trend from LAI-MC is found for coniferous forests (0.0419 m 2 m − 2 yr − 1 followed by summer crops (0.0394 m 2 m − 2 yr − 1 , while winter crops and grasslands show the smallest global trends (0.0261 m 2 m − 2 yr − 1 and 0.0279 m 2 m − 2 yr − 1 , respectively. The LAI

A Drone-based Tropical Forest Experiment to Estimate Vegetation Properties

Science.gov (United States)

Henke, D.

2017-12-01

In mid-latitudes, remote sensing technology is intensively used to monitor vegetation properties. However, in the tropics, high cloud-cover and saturation effects of vegetation indices (VI) hamper the reliability of vegetation parameters derived from satellite data. A drone experiment over the Barro Colorado Island (BCI), Panama, with high temporal repetition rates was conducted in spring 2017 to investigate the robustness and stability of remotely sensed vegetation parameters in tropical environments. For this purpose, three 10-day flight windows in February, March and April were selected and drone flights were repeated on daily intervals when weather conditions and equipment allowed it. In total, 18 days were recorded with two different optical cameras on sensefly's eBee drone: one red, green, blue (RGB) camera and one camera with near infra-red (NIR), green and blue channels. When possible, the data were acquired at the same time of day. Pix4D and Agisoft software were used to calculate the Normalized Difference VI (NDVI) and forest structure. In addition, leave samples were collected ones per month from 16 different plant species and the relative water content was measured as ground reference. Further data sources for the analysis are phenocam images (RGB & NIR) on BCI and satellite images of MODIS (NDVI; Enhanced VI EVI) and Sentinel-1 (radar backscatter). The attached figure illustrates the main data collected on BCI. Initial results suggest that the coefficient of determination (R2) is relatively high between ground samples and drone data, Sentinel-1 backscatter and MODIS EVI with R2 values ranging from 0.4 to 0.6; on the contrary, R2 values between ground measurements and MODIS NDVI or phenocam images are below 0.2. As the experiment took place mainly during dry season on BCI, cloud-cover rates are less dominate than during wet season. Under these conditions, MODIS EVI, which is less vulnerable to saturation effects, seems to be more reliable than MODIS

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.

South Florida Everglades: satellite image map

Science.gov (United States)

Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

2001-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Farmers' Perception towards Organic-based Vegetable Produc-tion ...

African Journals Online (AJOL)

It is well established that organic farming is a production system that sustain the health of the soils, ecosystems and people. This study assessed the small-scale farmers' perception towards organic based vegetable production in Ilaro agricultural zone of Ogun state, Nigeria. A multi-stage sampling procedure was used in the ...

Consumer clusters in Denmark based on coarse vegetable intake frequency, explained by hedonics, socio-demographic, health and food lifestyle factors. A cross-sectional national survey.

Science.gov (United States)

Beck, Tove K; Jensen, Sidsel; Simmelsgaard, Sonni Hansen; Kjeldsen, Chris; Kidmose, Ulla

2015-08-01

Vegetable intake seems to play a protective role against major lifestyle diseases. Despite this, the Danish population usually eats far less than the recommended daily intake. The present study focused on the intake of 17 coarse vegetables and the potential barriers limiting their intake. The present study drew upon a large Danish survey (n = 1079) to study the intake of coarse vegetables among Danish consumers. Four population clusters were identified based on their intake of 17 different coarse vegetables, and profiled according to hedonics, socio-demographic, health, and food lifestyle factors. The four clusters were characterized by a very low intake frequency of coarse vegetables ('low frequency'), a low intake frequency of coarse vegetables; but high intake frequency of carrots ('carrot eaters'), a moderate coarse vegetable intake frequency and high intake frequency of beetroot ('beetroot eaters'), and a high intake frequency of all coarse vegetables ('high frequency'). There was a relationship between reported liking and reported intake frequency for all tested vegetables. Preference for foods with a sweet, salty or bitter taste, in general, was also identified to be decisive for the reported vegetable intake, as these differed across the clusters. Each cluster had distinct socio-demographic, health and food lifestyle profiles. 'Low frequency' was characterized by uninvolved consumers with lack of interest in food, 'carrot eaters' vegetable intake was driven by health aspects, 'beetroot eaters' were characterized as traditional food consumers, and 'high frequency' were individuals with a strong food engagement and high vegetable liking. 'Low frequency' identified more barriers than other consumer clusters and specifically regarded low availability of pre-cut/prepared coarse vegetables on the market as a barrier. Across all clusters a low culinary knowledge was identified as the main barrier. Copyright © 2015 Elsevier Ltd. All rights reserved.

Occurrence and source analysis of typical veterinary antibiotics in manure, soil, vegetables and groundwater from organic vegetable bases, northern China

International Nuclear Information System (INIS)

Hu Xiangang; Zhou Qixing; Luo Yi

2010-01-01

The residue of antibiotics is becoming an intractable environmental problem in many organic vegetable bases. However, their residual levels and distribution are still obscure. This work systematically analyzed the occurrence and migration of typical veterinary antibiotics in organic vegetable bases, northern China. The results showed that there was no obvious geographical difference in antibiotic distribution between soil and manure. A simple migration model can be easy and quick to predict the accumulation of antibiotics in soil. Antibiotics were mainly taken up through water transport and passive absorption in vegetables. The distribution of antibiotics in a plant was in the sequence leaf > stem > root, and performed biological accumulation. The residues of antibiotics in all samples in winter were significantly higher than those in summer. Overall, this work can lay the foundation for understanding ecological risk of antibiotics and their potential adverse effects on human health by food chain. - The residues of typical veterinary antibiotics from manure were detected and migrated in soil, vegetables and groundwater of organic vegetable bases.

Assessing and monitoring of urban vegetation using multiple endmember spectral mixture analysis

Science.gov (United States)

Zoran, M. A.; Savastru, R. S.; Savastru, D. M.

2013-08-01

During last years urban vegetation with significant health, biological and economical values had experienced dramatic changes due to urbanization and human activities in the metropolitan area of Bucharest in Romania. We investigated the utility of remote sensing approaches of multiple endmember spectral mixture analysis (MESMA) applied to IKONOS and Landsat TM/ETM satellite data for estimating fractional cover of urban/periurban forest, parks, agricultural vegetation areas. Because of the spectral heterogeneity of same physical features of urban vegetation increases with the increase of image resolution, the traditional spectral information-based statistical method may not be useful to classify land cover dynamics from high resolution imageries like IKONOS. So we used hierarchy tree classification method in classification and MESMA for vegetation land cover dynamics assessment based on available IKONOS high-resolution imagery of Bucharest town. This study employs thirty two endmembers and six hundred and sixty spectral models to identify all Earth's features (vegetation, water, soil, impervious) and shade in the Bucharest area. The mean RMS error for the selected vegetation land cover classes range from 0.0027 to 0.018. The Pearson correlation between the fraction outputs from MESMA and reference data from all IKONOS images 1m panchromatic resolution data for urban/periurban vegetation were ranging in the domain 0.7048 - 0.8287. The framework in this study can be applied to other urban vegetation areas in Romania.

A morphometric analysis of vegetation patterns in dryland ecosystems

Science.gov (United States)

Mander, Luke; Dekker, Stefan C.; Li, Mao; Mio, Washington; Punyasena, Surangi W.; Lenton, Timothy M.

2017-02-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.

Ground-and satellite-based evidence of the biophysical mechanisms behind the greening Sahel

DEFF Research Database (Denmark)

Brandt, Martin Stefan; Mbow, Cheikh; Diouf, Abdoul A.

2015-01-01

After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness...... over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass...... remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass...

[Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

Science.gov (United States)

Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

2015-11-01

Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution

Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling

Science.gov (United States)

Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.

2015-01-01

Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless

Monitoring Corals and Submerged Aquatic Vegetation in Western Pacific Using Satellite Remote Sensing Integrated with Field Data

Science.gov (United States)

Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.

2013-12-01

Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to

A vegetation height classification approach based on texture analysis of a single VHR image

International Nuclear Information System (INIS)

Petrou, Z I; Manakos, I; Stathaki, T; Tarantino, C; Adamo, M; Blonda, P

2014-01-01

Vegetation height is a crucial feature in various applications related to ecological mapping, enhancing the discrimination among different land cover or habitat categories and facilitating a series of environmental tasks, ranging from biodiversity monitoring and assessment to landscape characterization, disaster management and conservation planning. Primary sources of information on vegetation height include in situ measurements and data from active satellite or airborne sensors, which, however, may often be non-affordable or unavailable for certain regions. Alternative approaches on extracting height information from very high resolution (VHR) satellite imagery based on texture analysis, have recently been presented, with promising results. Following the notion that multispectral image bands may often be highly correlated, data transformation and dimensionality reduction techniques are expected to reduce redundant information, and thus, the computational cost of the approaches, without significantly compromising their accuracy. In this paper, dimensionality reduction is performed on a VHR image and textural characteristics are calculated on its reconstructed approximations, to show that their discriminatory capabilities are maintained up to a large degree. Texture analysis is also performed on the projected data to investigate whether the different height categories can be distinguished in a similar way

Intake of Raw Fruits and Vegetables Is Associated With Better Mental Health Than Intake of Processed Fruits and Vegetables

Science.gov (United States)

Brookie, Kate L.; Best, Georgia I.; Conner, Tamlin S.

2018-01-01

Background: Higher intakes of fruits and vegetables, rich in micronutrients, have been associated with better mental health. However, cooking or processing may reduce the availability of these important micronutrients. This study investigated the differential associations between intake of raw fruits and vegetables, compared to processed (cooked or canned) fruits and vegetables, and mental health in young adults. Methods: In a cross-sectional survey design, 422 young adults ages 18–25 (66.1% female) living in New Zealand and the United States completed an online survey that assessed typical consumption of raw vs. cooked/canned/processed fruits and vegetables, negative and positive mental health (depressive symptoms, anxiety, negative mood, positive mood, life satisfaction, and flourishing), and covariates (including socio-economic status, body mass index, sleep, physical activity, smoking, and alcohol use). Results: Controlling for covariates, raw fruit and vegetable intake (FVI) predicted reduced depressive symptoms and higher positive mood, life satisfaction, and flourishing; processed FVI only predicted higher positive mood. The top 10 raw foods related to better mental health were carrots, bananas, apples, dark leafy greens like spinach, grapefruit, lettuce, citrus fruits, fresh berries, cucumber, and kiwifruit. Conclusions: Raw FVI, but not processed FVI, significantly predicted higher mental health outcomes when controlling for the covariates. Applications include recommending the consumption of raw fruits and vegetables to maximize mental health benefits. PMID:29692750

Intake of Raw Fruits and Vegetables Is Associated With Better Mental Health Than Intake of Processed Fruits and Vegetables

Directory of Open Access Journals (Sweden)

Kate L. Brookie

2018-04-01

Full Text Available Background: Higher intakes of fruits and vegetables, rich in micronutrients, have been associated with better mental health. However, cooking or processing may reduce the availability of these important micronutrients. This study investigated the differential associations between intake of raw fruits and vegetables, compared to processed (cooked or canned fruits and vegetables, and mental health in young adults.Methods: In a cross-sectional survey design, 422 young adults ages 18–25 (66.1% female living in New Zealand and the United States completed an online survey that assessed typical consumption of raw vs. cooked/canned/processed fruits and vegetables, negative and positive mental health (depressive symptoms, anxiety, negative mood, positive mood, life satisfaction, and flourishing, and covariates (including socio-economic status, body mass index, sleep, physical activity, smoking, and alcohol use.Results: Controlling for covariates, raw fruit and vegetable intake (FVI predicted reduced depressive symptoms and higher positive mood, life satisfaction, and flourishing; processed FVI only predicted higher positive mood. The top 10 raw foods related to better mental health were carrots, bananas, apples, dark leafy greens like spinach, grapefruit, lettuce, citrus fruits, fresh berries, cucumber, and kiwifruit.Conclusions: Raw FVI, but not processed FVI, significantly predicted higher mental health outcomes when controlling for the covariates. Applications include recommending the consumption of raw fruits and vegetables to maximize mental health benefits.

Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health

Science.gov (United States)

Luvall, Jeffrey C.; Sprigg, W. A.; Huete, A.; Nickovic, S.; Pejanovic, G.; Levetin, E.; Van de water, P.; Myers, O.; Budge, A. M.; Krapfl, H.;

Health benefits of kimchi (Korean fermented vegetables) as a probiotic food.

Science.gov (United States)

Park, Kun-Young; Jeong, Ji-Kang; Lee, Young-Eun; Daily, James W

2014-01-01

Kimchi is a traditional Korean food manufactured by fermenting vegetables with probiotic lactic acid bacteria (LAB). Many bacteria are involved in the fermentation of kimchi, but LAB become dominant while the putrefactive bacteria are suppressed during salting of baechu cabbage and the fermentation. The addition of other subingredients and formation of fermentation byproducts of LAB promote the fermentation process of LAB to eventually lead to eradication of putrefactive- and pathogenic bacteria, and also increase the functionalities of kimchi. Accordingly, kimchi can be considered a vegetable probiotic food that contributes health benefits in a similar manner as yogurt as a dairy probiotic food. Further, the major ingredients of kimchi are cruciferous vegetables; and other healthy functional foods such as garlic, ginger, red pepper powder, and so on are added to kimchi as subingredients. As all of these ingredients undergo fermentation by LAB, kimchi is regarded as a source of LAB; and the fermentative byproducts from the functional ingredients significantly boost its functionality. Because kimchi is both tasty and highly functional, it is typically served with steamed rice at every Korean meal. Health functionality of kimchi, based upon our research and that of other, includes anticancer, antiobesity, anticonstipation, colorectal health promotion, probiotic properties, cholesterol reduction, fibrolytic effect, antioxidative and antiaging properties, brain health promotion, immune promotion, and skin health promotion. In this review we describe the method of kimchi manufacture, fermentation, health functionalities of kimchi and the probiotic properties of its LAB.

Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Biao Wang

2017-08-01

Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

Automated Recognition of Vegetation and Water Bodies on the Territory of Megacities in Satellite Images of Visible and IR Bands

Science.gov (United States)

Mozgovoy, Dmitry k.; Hnatushenko, Volodymyr V.; Vasyliev, Volodymyr V.

2018-04-01

Vegetation and water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. A methodology of automated recognition of vegetation and water bodies on the territory of megacities in satellite images of sub-meter spatial resolution of the visible and IR bands is proposed. By processing multispectral images from the satellite SuperView-1A, vector layers of recognized plant and water objects were obtained. Analysis of the results of image processing showed a sufficiently high accuracy of the delineation of the boundaries of recognized objects and a good separation of classes. The developed methodology provides a significant increase of the efficiency and reliability of updating maps of large cities while reducing financial costs. Due to the high degree of automation, the proposed methodology can be implemented in the form of a geo-information web service functioning in the interests of a wide range of public services and commercial institutions.

Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

Science.gov (United States)

Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

2016-06-01

The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

A satellite and model based flood inundation climatology of Australia

Science.gov (United States)

Schumann, G.; Andreadis, K.; Castillo, C. J.

2013-12-01

To date there is no coherent and consistent database on observed or simulated flood event inundation and magnitude at large scales (continental to global). The only compiled data set showing a consistent history of flood inundation area and extent at a near global scale is provided by the MODIS-based Dartmouth Flood Observatory. However, MODIS satellite imagery is only available from 2000 and is hampered by a number of issues associated with flood mapping using optical images (e.g. classification algorithms, cloud cover, vegetation). Here, we present for the first time a proof-of-concept study in which we employ a computationally efficient 2-D hydrodynamic model (LISFLOOD-FP) complemented with a sub-grid channel formulation to generate a complete flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent. The model was built completely from freely available SRTM-derived data, including channel widths, bank heights and floodplain topography, which was corrected for vegetation canopy height using a global ICESat canopy dataset. Channel hydraulics were resolved using actual channel data and bathymetry was estimated within the model using hydraulic geometry. On the floodplain, the model simulated the flow paths and inundation variables at a 1 km resolution. The developed model was run over a period of 40 years and a floodplain inundation climatology was generated and compared to satellite flood event observations. Our proof-of-concept study demonstrates that this type of model can reliably simulate past flood events with reasonable accuracies both in time and space. The Australian model was forced with both observed flow climatology and VIC-simulated flows in order to assess the feasibility of a model-based flood inundation climatology at the global scale.

Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

Science.gov (United States)

Anderson, Martha C.; Zolin, Cornelio A.; Hain, Christopher R.; Semmens, Kathryn; Tugrul Yilmaz, M.; Gao, Feng

2015-07-01

Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and functioning have been attributed to cloud and aerosol contamination of shortwave reflectance composites, particularly over the rainforested regions of the Amazon basin which are subject to prolonged periods of cloud cover and episodes of intense biomass burning. This study compares timeseries of satellite-derived maps of LAI from the Moderate Resolution Imaging Spectroradiometer (MODIS) and precipitation from the Tropical Rainfall Mapping Mission (TRMM) with a diagnostic Evaporative Stress Index (ESI) retrieved using thermal infrared remote sensing over South America for the period 2003-2013. This period includes several severe droughts and floods that occurred both over the Amazon and over unforested savanna and agricultural areas in Brazil. Cross-correlations between absolute values and standardized anomalies in monthly LAI and precipitation composites as well as the actual-to-reference evapotranspiration (ET) ratio used in the ESI were computed for representative forested and agricultural regions. The correlation analyses reveal strong apparent anticorrelation between MODIS LAI and TRMM precipitation anomalies over the Amazon, but better coupling over regions vegetated with shorter grass and crop canopies. The ESI was more consistently correlated with precipitation patterns over both landcover types. Temporal comparisons between ESI and TRMM anomalies suggest longer moisture buffering timescales in the deeper rooted rainforest systems. Diagnostic thermal-based retrievals of ET and ET anomalies, such as used in the ESI, provide independent information on the impacts of extreme hydrologic events on vegetation health in comparison with VI and precipitation-based drought

Satellite derived phenology of southern Africa for 1985-2000 and functional classification of vegetation based on phenometrics

CSIR Research Space (South Africa)

Steenkamp, K

2009-05-01

Full Text Available analyzed vegetation phenometrics across South Africa (SA) in order to characterize phenological patterns and their inter-annual variability. A second objective is to distinguish biomes and sub-biome “bioregions” based on functional patterns. The long term...

Concentration and potential health risk of heavy metals in market vegetables in Chongqing, China.

Science.gov (United States)

Yang, Qing-Wei; Xu, Yuan; Liu, Shou-Jiang; He, Jin-Feng; Long, Fang-Yan

2011-09-01

Concentration and daily intake (DI) of heavy metals (Pb, Zn, Mn, Cu, Cd and Cr) in market vegetables in Chongqing of China are investigated and their potential health risk for local consumers is simultaneously evaluated by calculating the target hazard quotient (THQ). The results showed that the measured Pb and Cd concentrations exceeded the safety limits given by FAO/WHO and Chinese regulations, indicating serious contamination of market vegetables by these metals. As respective DI values for Pb, Mn and Cd were also above the international guideline bases, health risk to the consumers is obvious. The individual THQ for Pb and Cd in pakchoi and Cd in mustard, and the combined THQ for all metals in each vegetable species excluding cos lettuce were above the threshold 1.0, implying the obviously adverse effect on health. Therefore, attention should be paid particularly to the potential hazardous exposure to vegetable heavy metals, especially for Pb and Cd, over a lifetime for people in Chongqing. Copyright © 2011 Elsevier Inc. All rights reserved.

Health Risk Assessment of Vegetables Grown on the Contaminated Soils in Daye City of Hubei Province, China

Directory of Open Access Journals (Sweden)

Jun Yang

2017-11-01

Full Text Available China is an agriculturally-producing country and the safety of its vegetables will have an extensive attention at home and abroad. Recently, contamination of soils and vegetables caused by mining activities is of great social concern because of the potential risk to human health, especially to the residents whom live near metal or metalloid mines. In this study, 18 topsoil and 141 vegetable samples were collected from the contaminated areas in Daye City Hubei Province, China and the concentrations of copper (Cu, zinc (Zn, arsenic (As, cadmium (Cd and lead (Pb were analyzed. A self-designed questionnaire was assigned to obtain the exposure scenario and the USEPA health risk assessment model was adopted to assess two type of risks (non-carcinogenic risks and carcinogenic risks of vegetables to humans. The results showed that the average contents of metal(loids in soils exceeded the background value of Daye City. The average contents of metal(loids, especially As, Cd, Pb, in three kinds of vegetables were significantly higher than the permissible values based on Chinese national standard. Leafy vegetables had relatively higher concentrations and the transfer factors of As (0.015, Cd (0.080 and Pb (0.003 were comparable to leguminous and fruit vegetables. Leguminous vegetables had relatively higher concentrations and transfer factors of Cu (0.032 and Zn (0.094 than leafy and fruit vegetables. The transfer factors from soil to plants follows a decreasing order as Cd (0.068, Zn (0.047 > Cu (0.023 > As (0.006, Pb (0.002. Furthermore, health risk assessment revealed the following results: the non-carcinogenic risk decreased in the order of children, adult, adolescent, while the carcinogenic risk followed a decreasing order of adult, adolescent, children; the calculated carcinogenic and non-carcinogenic risk of the metal(loids by vegetable consumption decreased in the order of leafy vegetables > fruit vegetables > leguminous vegetables. The relatively

Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006

DEFF Research Database (Denmark)

Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.

2014-01-01

A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of veg...

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

Science.gov (United States)

McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

2008-01-01

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify

Mangrove forests submitted to depositional processes and salinity variation investigated using satellite images and vegetation structure surveys

OpenAIRE

Cunha-Lignon, M.; Kampel, M.; Menghini, R.P.; Schaeffer-Novelli, Y.; Cintrón, G.; Dahdouh-Guebas, F.

2011-01-01

The current paper examines the growth and spatio-temporal variation of mangrove forests in response to depositional processes and different salinity conditions. Data from mangrove vegetation structure collected at permanent plots and satellite images were used. In the northern sector important environmental changes occurred due to an artificial channel producing modifications in salinity. The southern sector is considered the best conserved mangrove area along the coast of São Paulo State, Br...

Trend shifts in satellite-derived vegetation growth in Central Eurasia, 1982-2013.

Science.gov (United States)

Xu, Hao-Jie; Wang, Xin-Ping; Yang, Tai-Bao

2017-02-01

Central Eurasian vegetation is critical for the regional ecological security and the global carbon cycle. However, climatic impacts on vegetation growth in Central Eurasia are uncertain. The reason for this uncertainty lies in the fact that the response of vegetation to climate change showed nonlinearity, seasonality and differences among plant functional types. Based on remotely sensed vegetation index and in-situ meteorological data for the years 1982-2013, in conjunction with the latest land cover type product, we analyzed how vegetation growth trend varied across different seasons and evaluated vegetation response to climate variables at regional, biome and pixel scales. We found a persistent increase in the growing season NDVI over Central Eurasia during 1982-1994, whereas this greening trend has stalled since the mid-1990s in response to increased water deficit. The stalled trend in the growing season NDVI was largely attributed by summer and autumn NDVI changes. Enhanced spring vegetation growth after 2002 was caused by rapid spring warming. The response of vegetation to climatic factors varied in different seasons. Precipitation was the main climate driver for the growing season and summer vegetation growth. Changes in temperature and precipitation during winter and spring controlled the spring vegetation growth. Autumn vegetation growth was mainly dependent on the vegetation growth in summer. We found diverse responses of different vegetation types to climate drivers in Central Eurasia. Forests were more responsive to temperature than to precipitation. Grassland and desert vegetation responded more strongly to precipitation than to temperature in summer but more strongly to temperature than to precipitation in spring. In addition, the growth of desert vegetation was more dependent on winter precipitation than that of grasslands. This study has important implications for improving the performance of terrestrial ecosystem models to predict future vegetation

A tiered approach for the human health risk assessment for consumption of vegetables from with cadmium-contaminated land in urban areas

International Nuclear Information System (INIS)

Swartjes, Frank A.; Versluijs, Kees W.; Otte, Piet F.

2013-01-01

Consumption of vegetables that are grown in urban areas takes place worldwide. In developing countries, vegetables are traditionally grown in urban areas for cheap food supply. In developing and developed countries, urban gardening is gaining momentum. A problem that arises with urban gardening is the presence of contaminants in soil, which can be taken up by vegetables. In this study, a scientifically-based and practical procedure has been developed for assessing the human health risks from the consumption of vegetables from cadmium-contaminated land. Starting from a contaminated site, the procedure follows a tiered approach which is laid out as follows. In Tier 0, the plausibility of growing vegetables is investigated. In Tier 1 soil concentrations are compared with the human health-based Critical soil concentration. Tier 2 offers the possibility for a detailed site-specific human health risk assessment in which calculated exposure is compared to the toxicological reference dose. In Tier 3, vegetable concentrations are measured and tested following a standardized measurement protocol. To underpin the derivation of the Critical soil concentrations and to develop a tool for site-specific assessment the determination of the representative concentration in vegetables has been evaluated for a range of vegetables. The core of the procedure is based on Freundlich-type plant–soil relations, with the total soil concentration and the soil properties as variables. When a significant plant–soil relation is lacking for a specific vegetable a geometric mean of BioConcentrationFactors (BCF) is used, which is normalized according to soil properties. Subsequently, a ‘conservative’ vegetable-group-consumption-rate-weighted BioConcentrationFactor is calculated as basis for the Critical soil concentration (Tier 1). The tool to perform site-specific human health risk assessment (Tier 2) includes the calculation of a ‘realistic worst case’ site-specific vegetable

A tiered approach for the human health risk assessment for consumption of vegetables from with cadmium-contaminated land in urban areas

Energy Technology Data Exchange (ETDEWEB)

Swartjes, Frank A., E-mail: frank.swartjes@rivm.nl; Versluijs, Kees W.; Otte, Piet F.

2013-10-15

Consumption of vegetables that are grown in urban areas takes place worldwide. In developing countries, vegetables are traditionally grown in urban areas for cheap food supply. In developing and developed countries, urban gardening is gaining momentum. A problem that arises with urban gardening is the presence of contaminants in soil, which can be taken up by vegetables. In this study, a scientifically-based and practical procedure has been developed for assessing the human health risks from the consumption of vegetables from cadmium-contaminated land. Starting from a contaminated site, the procedure follows a tiered approach which is laid out as follows. In Tier 0, the plausibility of growing vegetables is investigated. In Tier 1 soil concentrations are compared with the human health-based Critical soil concentration. Tier 2 offers the possibility for a detailed site-specific human health risk assessment in which calculated exposure is compared to the toxicological reference dose. In Tier 3, vegetable concentrations are measured and tested following a standardized measurement protocol. To underpin the derivation of the Critical soil concentrations and to develop a tool for site-specific assessment the determination of the representative concentration in vegetables has been evaluated for a range of vegetables. The core of the procedure is based on Freundlich-type plant–soil relations, with the total soil concentration and the soil properties as variables. When a significant plant–soil relation is lacking for a specific vegetable a geometric mean of BioConcentrationFactors (BCF) is used, which is normalized according to soil properties. Subsequently, a ‘conservative’ vegetable-group-consumption-rate-weighted BioConcentrationFactor is calculated as basis for the Critical soil concentration (Tier 1). The tool to perform site-specific human health risk assessment (Tier 2) includes the calculation of a ‘realistic worst case’ site-specific vegetable

Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images

International Nuclear Information System (INIS)

Arellano, Paul; Tansey, Kevin; Balzter, Heiko; Boyd, Doreen S.

2015-01-01

The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI 705 ) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. - Highlights: • Leaf biochemical alterations in the rainforest are caused by petroleum pollution. • Lower levels of chlorophyll content are symptom of vegetation stress in polluted sites. • Increased foliar water content was found in vegetation near polluted sites. • Vegetation stress was detected by using vegetation indices from satellite images. • Polluted sites and hydrocarbon seepages in rainforest can be identified from space. - Hydrocarbon pollution in the Amazon forest is observed for first time from satellite data

Human health risk assessment: heavy metal contamination of vegetables in Bahawalpur, Pakistan

Directory of Open Access Journals (Sweden)

Hafiza Hira Iqbal

2016-01-01

Full Text Available Dietary exposure of toxic metals is a vital concern for human health through vegetable consumption, especially in developing countries. Aim of the current study was to determine the health risk related to vegetables contamination of heavy metals by irrigated with sewage and turbine water. Irrigation water sources, soils and vegetables were analyzed for selected metals viz: Pb, Cd, Cr and Ni. Heavy metals in water samples were within the permissible limits except Cd in sewage water. The concentration of heavy metals in soil and vegetables irrigated with turbine water were lower than the safe limits. In case of vegetables irrigated with sewage water, Cd was higher in soil while Pb, Cd and Cr were higher in most of the vegetables. Daily intake of metals, health risk index and Bio-concentration factor was also determined. Health risk index values for Cd, Pb and Ni were exceeded the permissible limits (European Union, 2002. Bio-concentration factor (BCF found to be maximum (16.4 mg/kg in Coriandrum sativum cultivated with sewage water. Raphanus caudatus, Coriandrum sativum, Daucus carota, Allium sativum and Solanum tuberosum showed Health Risk Index of Cd > 1 in adults and children. Allium sativum also showed HRI of Pb > 1 in children. We conclude that the quality of vegetables irrigated with sewage water is poor and not fit for human health, evident from the high concentration of Pb, Cd and Cr. Urgent measures are required to prevent consumption and production vegetables irrigated with of sewage water in the study area.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

Science.gov (United States)

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-08-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia's cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

Patchiness in semi-arid dwarf shrublands: evidence from satellite ...

African Journals Online (AJOL)

... Plants; Remote sensing; Rhigozum obovatum Burch; Satellite-derived vegetation indices; Woody species; patchiness; semi-arid; dwarf shrubland; shrublands; co2; assimilation; karoo; south africa; ndvi; satellite imagery; geochemical mound; rhigozum obovatum; eriocephalus ericoides; pentzia incana; vegetation; botany

Quantifying vegetation distribution and structure using high resolution drone-based structure-from-motion photogrammetry

Science.gov (United States)

Zhang, J.; Okin, G.

2017-12-01

Vegetation is one of the most important driving factors of different ecosystem processes in drylands. The structure of vegetation controls the spatial distribution of moisture and heat in the canopy and the surrounding area. Also, the structure of vegetation influences both airflow and boundary layer resistance above the land surface. Multispectral satellite remote sensing has been widely used to monitor vegetation coverage and its change; however, it can only capture 2D images, which do not contain the vertical information of vegetation. In situ observation uses different methods to measure the structure of vegetation, and their results are accurate; however, these methods are laborious and time-consuming, and susceptible to undersampling in spatial heterogeneity. Drylands are sparsely covered by short plants, which allows the drone fly at a relatively low height to obtain ultra-high resolution images. Structure-from-motion (SfM) is a photogrammetric method that was proved to produce 3D model based on 2D images. Drone-based remote sensing can obtain the multiangle images for one object, which can be used to constructed 3D models of vegetation in drylands. Using these images detected by the drone, the orthomosaics and digital surface model (DSM) can be built. In this study, the drone-based remote sensing was conducted in Jornada Basin, New Mexico, in the spring of 2016 and 2017, and three derived vegetation parameters (i.e., canopy size, bare soil gap size, and plant height) were compared with those obtained with field measurement. The correlation coefficient of canopy size, bare soil gap size, and plant height between drone images and field data are 0.91, 0.96, and 0.84, respectively. The two-year averaged root-mean-square error (RMSE) of canopy size, bare soil gap size, and plant height between drone images and field data are 0.61 m, 1.21 m, and 0.25 cm, respectively. The two-year averaged measure error (ME) of canopy size, bare soil gap size, and plant height

Satellite-based ET estimation using Landsat 8 images and SEBAL model

Directory of Open Access Journals (Sweden)

Bruno Bonemberger da Silva

Full Text Available ABSTRACT Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Paraná, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.

Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

Science.gov (United States)

Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna

2016-01-01

This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

Coupling Analysis of Heat Island Effects, Vegetation Coverage and Urban Flood in Wuhan

Science.gov (United States)

Liu, Y.; Liu, Q.; Fan, W.; Wang, G.

2018-04-01

In this paper, satellite image, remote sensing technique and geographic information system technique are main technical bases. Spectral and other factors comprehensive analysis and visual interpretation are main methods. We use GF-1 and Landsat8 remote sensing satellite image of Wuhan as data source, and from which we extract vegetation distribution, urban heat island relative intensity distribution map and urban flood submergence range. Based on the extracted information, through spatial analysis and regression analysis, we find correlations among heat island effect, vegetation coverage and urban flood. The results show that there is a high degree of overlap between of urban heat island and urban flood. The area of urban heat island has buildings with little vegetation cover, which may be one of the reasons for the local heavy rainstorms. Furthermore, the urban heat island has a negative correlation with vegetation coverage, and the heat island effect can be alleviated by the vegetation to a certain extent. So it is easy to understand that the new industrial zones and commercial areas which under constructions distribute in the city, these land surfaces becoming bare or have low vegetation coverage, can form new heat islands easily.

Assessment of Land Use-Cover Changes and Successional Stages of Vegetation in the Natural Protected Area Altas Cumbres, Northeastern Mexico, Using Landsat Satellite Imagery

Directory of Open Access Journals (Sweden)

Uriel Jeshua Sánchez-Reyes

2017-07-01

Full Text Available Loss of vegetation cover is a major factor that endangers biodiversity. Therefore, the use of geographic information systems and the analysis of satellite images are important for monitoring these changes in Natural Protected Areas (NPAs. In northeastern Mexico, the Natural Protected Area Altas Cumbres (NPAAC represents a relevant floristic and faunistic patch on which the impact of loss of vegetation cover has not been assessed. This work aimed to analyze changes of land use and coverage (LULCC over the last 42 years on the interior and around the exterior of the area, and also to propose the time of succession for the most important types of vegetation. For the analysis, LANDSAT satellite images from 1973, 1986, 2000, 2005 and 2015 were used, they were classified in seven categories through a segmentation and maximum likelihood analysis. A cross-tabulation analysis was performed to determine the succession gradient. Towards the interior of the area, a significant reduction of tropical vegetation and, to a lesser extent, temperate forests was found, as well as an increase in scrub cover from 1973 to 2015. In addition, urban and vegetation-free areas, as well as modified vegetation, increased to the exterior. Towards the interior of the NPA, the processes of perturbation and recovery were mostly not linear, while in the exterior adjacent area, the presence of secondary vegetation with distinct definite time of succession was evident. The analysis carried out is the first contribution that evaluates LULCC in this important NPA of northeastern Mexico. Results suggest the need to evaluate the effects of these modifications on species.

Satellite-Based Precipitation Datasets

Science.gov (United States)

Munchak, S. J.; Huffman, G. J.

2017-12-01

Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

Satellite-based laser windsounder

International Nuclear Information System (INIS)

Schultz, J.F.; Czuchlewski, S.J.; Quick, C.R.

1997-01-01

This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project''s primary objective is to determine the technical feasibility of using satellite-based laser wind sensing systems for detailed study of winds, aerosols, and particulates around and downstream of suspected proliferation facilities. Extensive interactions with the relevant operational organization resulted in enthusiastic support and useful guidance with respect to measurement requirements and priorities. Four candidate wind sensing techniques were evaluated, and the incoherent Doppler technique was selected. A small satellite concept design study was completed to identify the technical issues inherent in a proof-of-concept small satellite mission. Use of a Mach-Zehnder interferometer instead of a Fabry-Perot would significantly simplify the optical train and could reduce weight, and possibly power, requirements with no loss of performance. A breadboard Mach-Zehnder interferometer-based system has been built to verify these predictions. Detailed plans were made for resolving other issues through construction and testing of a ground-based lidar system in collaboration with the University of Wisconsin, and through numerical lidar wind data assimilation studies

A Forward GPS Multipath Simulator Based on the Vegetation Radiative Transfer Equation Model.

Science.gov (United States)

Wu, Xuerui; Jin, Shuanggen; Xia, Junming

2017-06-05

Global Navigation Satellite Systems (GNSS) have been widely used in navigation, positioning and timing. Nowadays, the multipath errors may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), i.e., GPS-Multipath Reflectometry (GPS-MR). However, bistatic scattering properties and the relation between GPS observables and geophysical parameters are not clear, e.g., vegetation. In this paper, a new element on bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that the wheat will decrease the amplitudes of GPS multipath observables (SNR, phase and code), if we increase the vegetation moisture contents or the scatters sizes (stem or leaf). Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with previous results for environmental parameter detections by GPS-MR.

New Approaches to Irrigation Scheduling of Vegetables

Directory of Open Access Journals (Sweden)

Michael D. Cahn

2017-04-01

Full Text Available Using evapotranspiration (ET data for scheduling irrigations on vegetable farms is challenging due to imprecise crop coefficients, time consuming computations, and the need to simultaneously manage many fields. Meanwhile, the adoption of soil moisture monitoring in vegetables has historically been limited by sensor accuracy and cost, as well as labor required for installation, removal, and collection of readings. With recent improvements in sensor technology, public weather-station networks, satellite and aerial imaging, wireless communications, and cloud computing, many of the difficulties in using ET data and soil moisture sensors for irrigation scheduling of vegetables can now be addressed. Web and smartphone applications have been developed that automate many of the calculations involved in ET-based irrigation scheduling. Soil moisture sensor data can be collected through wireless networks and accessed using web browser or smartphone apps. Energy balance methods of crop ET estimation, such as eddy covariance and Bowen ratio, provide research options for further developing and evaluating crop coefficient guidelines of vegetables, while recent advancements in surface renewal instrumentation have led to a relatively low-cost tool for monitoring crop water requirement in commercial farms. Remote sensing of crops using satellite, manned aircraft, and UAV platforms may also provide useful tools for vegetable growers to evaluate crop development, plant stress, water consumption, and irrigation system performance.

Health-promoting components of fruits and vegetables in the diet.

Science.gov (United States)

Liu, Rui Hai

2013-05-01

Regular consumption of fruits, vegetables, whole grains, and other plant foods has been negatively correlated with the risk of the development of chronic diseases. There is a huge gap between the average consumption of fruits and vegetables in Americans and the amount recommended by the 2010 Dietary Guidelines for Americans. The key is to encourage consumers to increase the total amount to 9 to 13 servings of fruits and vegetables in all forms available. Fresh, processed fruits and vegetables including frozen and canned, cooked, 100% fruit juices and 100% vegetable juices, as well as dry fruits are all considered as servings of fruits and vegetables per day. A wide variety of fruits, vegetables, whole grains, and other plant foods provide a range of nutrients and different bioactive compounds including phytochemicals, vitamins, minerals, and fibers. Potatoes serve as one of the low-fat foods with unique nutrients and phytochemical profiles, particularly rich in vitamin C, vitamin B-6, potassium, manganese, and dietary fibers. Potatoes provide 25% of vegetable phenolics in the American diet, the largest contributors among the 27 vegetables commonly consumed in the United States, including flavonoids (quercetin and kaempferol), phenolic acids (chlorogenic acid and caffeic acid), and carotenoids (lutein and zeaxanthin). More and more evidence suggests that the health benefits of fruits, vegetables, whole grains, and other plant foods are attributed to the synergy or interactions of bioactive compounds and other nutrients in whole foods. Therefore, consumers should obtain their nutrients, antioxidants, bioactive compounds, and phytochemicals from a balanced diet with a wide variety of fruits, vegetables, whole grains, and other plant foods for optimal nutrition, health, and well-being, not from dietary supplements.

Global trends in satellite-based emergency mapping

Science.gov (United States)

Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

2016-01-01

Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

Ecological restoration of groundwater-dependent vegetation in the arid Ejina Delta: evidences from satellite evapotranspiration

Science.gov (United States)

Kai, Lu; Garcia, Monica; Yu, Jingjie; Zhang, Yichi; Wang, Ping; Wang, Sheng; Liu, Xiao

2017-04-01

The ecological water conveyance project (EWCP) in the Ejina delta, a typical hyper-arid area of China, aimed to restore degraded phreatophytic ecosystems. We assessed the degree of ecosystem recovery using as an ecohydrological indicator a ratio between actual and potential evapotranspiration derived from MODIS since the beginning of the project in 2001. The selected indicator was the Temperature Vegetation Dryness Index (TVDI) which was validated with Eddy covariance (EC) data confirming its applicability to monitor groundwater dependent vegetation. The spatial analyses of the evapotranspiration ratio show drying trends (2000-2015) which are stronger and also cover larger extensions than the wetting trends. Thus, the condition of key riparian areas relying mostly on surface water improved since the project began. However, groundwater dependent ecosystems located in lower river Xihe reaches present drying trends. It seems that despite of the runoff supplemented by the EWCP project, there is nowadays more inequality in the access to water by groundwater dependent ecosystems in the Ejina Delta. The study shows that energy-evaporation indices, relying on radiometric satellite temperature like the TVDI, can detect degradation signals that otherwise might go undetected by NDVI analyses especially in arid regions, where vegetation indices are greatly affected by the soil background signals. Additionally, they can provide timely information to water managers on how much water to allocate for a sustainable restoration program.

Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

KAUST Repository

Houborg, Rasmus

2013-07-01

In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

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).

Physics teaching by infrared remote sensing of vegetation

Science.gov (United States)

Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund

2018-05-01

Context- and project-based teaching has proven to foster different affective and cognitive aspects of learning. As a versatile and multidisciplinary scientific research area with diverse applications for everyday life, satellite remote sensing is an interesting context for physics education. In this paper we give a brief overview of satellite remote sensing of vegetation and how to obtain your own, individual infrared remote sensing data with affordable converted digital cameras. This novel technique provides the opportunity to conduct individual remote sensing measurement projects with students in their respective environment. The data can be compared to real satellite data and is of sufficient accuracy for educational purposes.

Characterization of subarctic vegetation using ground based remote sensing methods

Science.gov (United States)

Finnell, D.; Garnello, A.; Palace, M. W.; Sullivan, F.; Herrick, C.; Anderson, S. M.; Crill, P. M.; Varner, R. K.

2014-12-01

well as WorldView-2 satellite imagery collected during the years 2012-2014. Identification of methane flux regions will later be analyzed based on vegetation coverage to aid classification of increased emission zones within the mire.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

Science.gov (United States)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Health promoting compounds in vegetables and fruits:

DEFF Research Database (Denmark)

Brandt, K.; Christensen, L.P.; Hansen-Møller, J.

2004-01-01

Vegetables contain unknown compounds with important health promoting effect. The described project defined and tested a two-step screening procedure for identification of such compounds. Step 1 is initial screening according to three criteria: 1.1, chemically reactive functional groups; 1...

SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

A. Sharma

2015-03-01

Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

Using VEGETATION satellite data and the crop model STICS-Prairie to estimate pasture production at the national level in France

Science.gov (United States)

Di Bella, C.; Faivre, R.; Ruget, F.; Seguin, B.

In France, pastures constitute an important land cover type, sustaining principally husbandry production. The absence of low-cost methods applicable to large regions has conducted to the use of simulation models, as in the ISOP system. Remote sensing data may be considered as a potential tool to improve a correct diagnosis in a real time framework. Thirteen forage regions (FR) of France, differing in their soil, climatic and productive characteristics were selected for this purpose. SPOT4-VEGETATION images have been used to provide, using subpixel estimation models, the spectral signature corresponding to pure pasture conditions. This information has been related with some growth variables estimated by STICS-Prairie model (inside ISOP system). Beyond the good general agreement between the two types of data, we found that the best relations were observed between NDVI middle infrared based index (SWVI) and leaf area index. The results confirm the capacities of the satellite data to provide complementary productive variables and help to identify the spatial and temporal differences between satellite and model information, mainly during the harvesting periods. This could contribute to improve the evaluations of the model on a regional scale.

Will European agricultural policy for school fruit and vegetables improve public health? A review of school fruit and vegetable programmes.

Science.gov (United States)

de Sa, Joia; Lock, Karen

2008-12-01

For the first time, public health, particularly obesity, is being seen as a driver of EU agricultural policy. In 2007, European Ministers of Agriculture were asked to back new proposals for school fruit and vegetable programmes as part of agricultural reforms. In 2008, the European Commission conducted an impact assessment to assess the potential impact of this new proposal on health, agricultural markets, social equality and regional cohesion. A systematic review of the effectiveness of interventions to promote fruit and/or vegetable consumption in children in schools, to inform the EC policy development process. School schemes are effective at increasing both intake and knowledge. Of the 30 studies included, 70% increased fruits and vegetables (FV) intake, with none decreasing intake. Twenty-three studies had follow-up periods >1 year and provide some evidence that FV schemes can have long-term impacts on consumption. Only one study led to both increased fruit and vegetable intake and reduction in weight. One study showed that school fruit and vegetable schemes can also help to reduce inequalities in diet. Effective school programmes have used a range of approaches and been organized in ways which vary nationally depending on differences in food supply chain and education systems. EU agriculture policy for school fruits and vegetables schemes should be an effective approach with both public health and agricultural benefits. Aiming to increase FV intake amongst a new generation of consumers, it will support a range of EU policies including obesity and health inequalities.

Estimation of vegetation cover resilience from satellite time series

Directory of Open Access Journals (Sweden)

T. Simoniello

2008-07-01

Full Text Available Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity.

In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis

Development of a Dynamic Web Mapping Service for Vegetation Productivity Using Earth Observation and in situ Sensors in a Sensor Web Based Approach

Directory of Open Access Journals (Sweden)

Sytze de Bruin

2009-03-01

Full Text Available This paper describes the development of a sensor web based approach which combines earth observation and in situ sensor data to derive typical information offered by a dynamic web mapping service (WMS. A prototype has been developed which provides daily maps of vegetation productivity for the Netherlands with a spatial resolution of 250 m. Daily available MODIS surface reflectance products and meteorological parameters obtained through a Sensor Observation Service (SOS were used as input for a vegetation productivity model. This paper presents the vegetation productivity model, the sensor data sources and the implementation of the automated processing facility. Finally, an evaluation is made of the opportunities and limitations of sensor web based approaches for the development of web services which combine both satellite and in situ sensor sources.

Seasonal analysis of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data

International Nuclear Information System (INIS)

Darmawan, S; Takeuchi, W; Shofiyati, R; Sari, D K; Wikantika, K

2014-01-01

Paddy field is important agriculture crop in Indonesia. Rice is a food staple for 237,6 million Indonesian people. Paddy field growth is strongly influenced by water, but the amount of precipitation is unpredictable. Annual and interannual climate variability in Indonesia is unusual. In recent years remote sensing data has been used for measurement and monitoring of precipitation, drought and Vegetation index such as Global Satellite Mapping of Precipitation (GSMaP), Multi-purpose Transmission SATellite (MTSAT) and Moderate Resolution Imaging Spectroradiometer (MODIS). The objective of this research is to investigate seasonal variability of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data. The methodology consists of collecting of enhanced vegetation index (EVI) from MODIS data, mosaicking of image, collecting of region of interest of paddy field, collecting of precipitation and drought index based on Keetch Bryam Drought Index (KBDI) from GSMaP and MTSAT, and seasonal analysis. The result of this research has showed seasonal variability of precipitation, KBDI and EVI on Indonesia paddy field from 2007 until 2012. Precipitation begins from January until May and October until December, and KBDI begins to increase from June and peak in September only in South Sumatera precipitation almost in all month. Seasonal analysis has showed precipitation and KBDI affect on EVI that can indicate variety phenology of Indonesian paddy field. Peak of EVI occurs before peak of KBDI occurs and increasing of KBDI followed by decreasing of EVI. In 2010 all province got higher precipitation and smaller KBDI so EVI has three peaks such as in West Java that can indicated increasing of rice production

Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery

Science.gov (United States)

Mitri, George H.; Gitas, Ioannis Z.

2013-02-01

Careful evaluation of forest regeneration and vegetation recovery after a fire event provides vital information useful in land management. The use of remotely sensed data is considered to be especially suitable for monitoring ecosystem dynamics after fire. The aim of this work was to map post-fire forest regeneration and vegetation recovery on the Mediterranean island of Thasos by using a combination of very high spatial (VHS) resolution (QuickBird) and hyperspectral (EO-1 Hyperion) imagery and by employing object-based image analysis. More specifically, the work focused on (1) the separation and mapping of three major post-fire classes (forest regeneration, other vegetation recovery, unburned vegetation) existing within the fire perimeter, and (2) the differentiation and mapping of the two main forest regeneration classes, namely, Pinus brutia regeneration, and Pinus nigra regeneration. The data used in this study consisted of satellite images and field observations of homogeneous regenerated and revegetated areas. The methodology followed two main steps: a three-level image segmentation, and, a classification of the segmented images. The process resulted in the separation of classes related to the aforementioned objectives. The overall accuracy assessment revealed very promising results (approximately 83.7% overall accuracy, with a Kappa Index of Agreement of 0.79). The achieved accuracy was 8% higher when compared to the results reported in a previous work in which only the EO-1 Hyperion image was employed in order to map the same classes. Some classification confusions involving the classes of P. brutia regeneration and P. nigra regeneration were observed. This could be attributed to the absence of large and dense homogeneous areas of regenerated pine trees in the study area.

Concentration and health risk evaluation of heavy metals in market-sold vegetables and fishes based on questionnaires in Beijing, China.

Science.gov (United States)

Fang, Yanyan; Nie, Zhiqiang; Liu, Feng; Die, Qingqi; He, Jie; Huang, Qifei

2014-10-01

Concentrations of heavy metals (As, Cd, Pb, Cu, Ni, Fe, Mn, and Zn) in market vegetables and fishes in Beijing, China, are investigated, and their health risk to local consumers is evaluated by calculating the target hazard quotient (THQ). The heavy metal concentrations in vegetables and fishes ranged from not detectable (ND) to 0.21 mg/kg fresh weight (f.w.) (As), ND to 0.10 mg/kg f.w. (Cd), and n.d to 0.57 mg/kg f.w. (Pb), with average concentrations of 0.17, 0.04, and 0.24 mg/kg f.w., respectively. The measured concentrations of As, Cd, Pb, Cu, Ni, Fe, Mn, and Zn are generally lower than the safety limits given by the Chinese regulation safety and quality standards of agriculture products (GB2762-2012). As, Cd, and Pb contaminations are found in vegetables and fishes. The exceeding standard rates are 19 % for As, 3 % for Cd, and 25 % for Pb. Pb contaminations are found quite focused on the fish samples from traditional agri-product markets. The paper further analyzed the health risk of heavy metals in vegetables and fishes respectively from supermarkets and traditional agri-product markets; the results showed that the fishes of traditional agri-product markets have higher health risk, while the supermarkets have vegetables of higher heavy metal risk, and the supervision should be strengthened in the fish supply channels in traditional agri-product markets.

Analytical Diagnostics of Non-Optimal Use of Pesticides and Health Hazards for Vegetable Pickers

International Nuclear Information System (INIS)

Zafar, M.; Mehmood, T.; Baig, I. A.; Saboor, A.; Sadiq, S.; Mahmood, K.

2016-01-01

Economically pesticides are meant to control pests in the fields. Up to certain optimal use of a typical pesticide, it enhances the yield of crops and vegetables. But, eventually amplified use of pesticides results in contamination of environment (water, soil, and air) and increase the health cost of vegetable pickers. The purpose of this study is to estimate the excessive use of pesticides and economic cost of health hazards for the vegetable pickers in district Vehari. Data from 90 respondents were collected and analyzed. The most common health problems identified during the survey were headache, eye irritation, skin infection, cough and shortness of breath. Health cost consists of costs related to precautionary measure, medication, traveling, the opportunity cost of attended persons and productivity loss. The mean health cost of vegetable pickers in the study area was about Rs. 385 per picker per year. Health cost model was used to measure the health cost of vegetable pickers. The regression results showed that pesticides were being applied non-optimally in the study area i.e., number of pesticide applications for vegetables (7-31) were substantially higher than the recommended dose. Health cost function was significantly different from zero as indicated by F-stat (32.18) and it is also supported by R/sup 2/ that about 70 percent variation in health cost is explained by medication accompanied by productivity loss (Rs. 223), precautionary measure (Rs. 134), attended person cost (Rs. 14) and traveling expenditures (Rs. 16). Hence, strict legislation is required to overcome the availability of hazardous pesticides and to keep the vegetable pickers aware of the optimal use of pesticides through appropriate extension services. (author)

Tree Canopy Light Interception Estimates in Almond and a Walnut Orchards Using Ground, Low Flying Aircraft, and Satellite Based Methods to Improve Irrigation Scheduling Programs

Science.gov (United States)

Rosecrance, Richard C.; Johnson, Lee; Soderstrom, Dominic

2016-01-01

Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

OpenAIRE

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991...

Health-Promoting Components of Fruits and Vegetables in the Diet12

Science.gov (United States)

Liu, Rui Hai

2013-01-01

Regular consumption of fruits, vegetables, whole grains, and other plant foods has been negatively correlated with the risk of the development of chronic diseases. There is a huge gap between the average consumption of fruits and vegetables in Americans and the amount recommended by the 2010 Dietary Guidelines for Americans. The key is to encourage consumers to increase the total amount to 9 to 13 servings of fruits and vegetables in all forms available. Fresh, processed fruits and vegetables including frozen and canned, cooked, 100% fruit juices and 100% vegetable juices, as well as dry fruits are all considered as servings of fruits and vegetables per day. A wide variety of fruits, vegetables, whole grains, and other plant foods provide a range of nutrients and different bioactive compounds including phytochemicals, vitamins, minerals, and fibers. Potatoes serve as one of the low-fat foods with unique nutrients and phytochemical profiles, particularly rich in vitamin C, vitamin B-6, potassium, manganese, and dietary fibers. Potatoes provide 25% of vegetable phenolics in the American diet, the largest contributors among the 27 vegetables commonly consumed in the United States, including flavonoids (quercetin and kaempferol), phenolic acids (chlorogenic acid and caffeic acid), and carotenoids (lutein and zeaxanthin). More and more evidence suggests that the health benefits of fruits, vegetables, whole grains, and other plant foods are attributed to the synergy or interactions of bioactive compounds and other nutrients in whole foods. Therefore, consumers should obtain their nutrients, antioxidants, bioactive compounds, and phytochemicals from a balanced diet with a wide variety of fruits, vegetables, whole grains, and other plant foods for optimal nutrition, health, and well-being, not from dietary supplements. PMID:23674808

Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

Directory of Open Access Journals (Sweden)

Athos Agapiou

2017-06-01

Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

Ground test of satellite constellation based quantum communication

OpenAIRE

Liao, Sheng-Kai; Yong, Hai-Lin; Liu, Chang; Shentu, Guo-Liang; Li, Dong-Dong; Lin, Jin; Dai, Hui; Zhao, Shuang-Qiang; Li, Bo; Guan, Jian-Yu; Chen, Wei; Gong, Yun-Hong; Li, Yang; Lin, Ze-Hong; Pan, Ge-Sheng

2016-01-01

Satellite based quantum communication has been proven as a feasible way to achieve global scale quantum communication network. Very recently, a low-Earth-orbit (LEO) satellite has been launched for this purpose. However, with a single satellite, it takes an inefficient 3-day period to provide the worldwide connectivity. On the other hand, similar to how the Iridium system functions in classic communication, satellite constellation (SC) composed of many quantum satellites, could provide global...

A Satellite-Based Multi-Pollutant Index of Global Air Quality

Science.gov (United States)

Cooper, Mathew J.; Martin, Randall V.; vanDonkelaar, Aaron; Lamsal, Lok; Brauer, Michael; Brook, Jeffrey R.

2012-01-01

Air pollution is a major health hazard that is responsible formillions of annual excess deaths worldwide. Simpleindicators are useful for comparative studies and to asses strends over time. The development of global indicators hasbeen impeded by the lack of ground-based observations in vast regions of the world. Recognition is growing of the need for amultipollutant approach to air quality to better represent human exposure. Here we introduce the prospect of amultipollutant air quality indicator based on observations from satellite remote sensing.

Satellite remote sensing in epidemiological studies.

Science.gov (United States)

Sorek-Hamer, Meytar; Just, Allan C; Kloog, Itai

2016-04-01

Particulate matter air pollution is a ubiquitous exposure linked with multiple adverse health outcomes for children and across the life course. The recent development of satellite-based remote-sensing models for air pollution enables the quantification of these risks and addresses many limitations of previous air pollution research strategies. We review the recent literature on the applications of satellite remote sensing in air quality research, with a focus on their use in epidemiological studies. Aerosol optical depth (AOD) is a focus of this review and a significant number of studies show that ground-level particulate matter can be estimated from columnar AOD. Satellite measurements have been found to be an important source of data for particulate matter model-based exposure estimates, and recently have been used in health studies to increase the spatial breadth and temporal resolution of these estimates. It is suggested that satellite-based models improve our understanding of the spatial characteristics of air quality. Although the adoption of satellite-based measures of air quality in health studies is in its infancy, it is rapidly growing. Nevertheless, further investigation is still needed in order to have a better understanding of the AOD contribution to these prediction models in order to use them with higher accuracy in epidemiological studies.

Detecting Historical Vegetation Changes in the Dunhuang Oasis Protected Area Using Landsat Images

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Xiuxia Zhang

2017-09-01

Full Text Available Abstract: Given its proximity to an artificial oasis, the Donghu Nature Reserve in the Dunhuang Oasis has faced environmental pressure and vegetation disturbances in recent decades. Satellite vegetation indices (VIs can be used to detect such changes in vegetation if the satellite images are calibrated to surface reflectance (SR values. The aim of this study was to select a suitable VI based on the Landsat Climate Data Record (CDR products and the absolute radiation-corrected results of Landsat L1T images to detect the spatio-temporal changes in vegetation for the Donghu Reserve during 1986–2015. The results showed that the VI difference (ΔVI images effectively reduced the changes in the source images. Compared with the other VIs, the soil-adjusted vegetation index (SAVI displayed greater robustness to atmospheric effects in the two types of SR images and was more responsive to vegetation changes caused by human factors. From 1986 to 2015, the positive changes in vegetation dominated the overall change trend, with changes in vegetation in the reserve decreasing during 1990–1995, increasing until 2005–2010, and then decreasing again. The vegetation changes were mainly distributed at the edge of the artificial oasis outside the reserve. The detected changes in vegetation in the reserve highlight the increased human pressure on the reserve.

Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

Energy Technology Data Exchange (ETDEWEB)

Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.; Cook, David R.; Matamala, Roser; Fischer, Marc L.; Jin, Cui; Dong, Jinwei; Biradar, Chandrashekhar

2014-09-01

Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared with the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.

Investigation on the Patterns of Global Vegetation Change Using a Satellite-Sensed Vegetation Index

Directory of Open Access Journals (Sweden)

Ainong Li

2010-06-01

Full Text Available The pattern of vegetation change in response to global change still remains a controversial issue. A Normalized Difference Vegetation Index (NDVI dataset compiled by the Global Inventory Modeling and Mapping Studies (GIMMS was used for analysis. For the period 1982–2006, GIMMS-NDVI analysis indicated that monthly NDVI changes show homogenous trends in middle and high latitude areas in the northern hemisphere and within, or near, the Tropic of Cancer and Capricorn; with obvious spatio-temporal heterogeneity on a global scale over the past two decades. The former areas featured increasing vegetation activity during growth seasons, and the latter areas experienced an even greater amplitude in places where precipitation is adequate. The discussion suggests that one should be cautious of using the NDVI time-series to analyze local vegetation dynamics because of its coarse resolution and uncertainties.

Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

Science.gov (United States)

Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

2014-12-01

The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are

Seasonally asymmetric enhancement of northern vegetation productivity

Science.gov (United States)

Park, T.; Myneni, R.

2017-12-01

Multiple evidences of widespread greening and increasing terrestrial carbon uptake have been documented. In particular, enhanced gross productivity of northern vegetation has been a critical role leading to observed carbon uptake trend. However, seasonal photosynthetic activity and its contribution to observed annual carbon uptake trend and interannual variability are not well understood. Here, we introduce a multiple-source of datasets including ground, atmospheric and satellite observations, and multiple process-based global vegetation models to understand how seasonal variation of land surface vegetation controls a large-scale carbon exchange. Our analysis clearly shows a seasonally asymmetric enhancement of northern vegetation productivity in growing season during last decades. Particularly, increasing gross productivity in late spring and early summer is obvious and dominant driver explaining observed trend and variability. We observe more asymmetric productivity enhancement in warmer region and this spatially varying asymmetricity in northern vegetation are likely explained by canopy development rate, thermal and light availability. These results imply that continued warming may facilitate amplifying asymmetric vegetation activity and cause these trends to become more pervasive, in turn warming induced regime shift in northern land.

Method for validating cloud mask obtained from satellite measurements using ground-based sky camera.

Science.gov (United States)

Letu, Husi; Nagao, Takashi M; Nakajima, Takashi Y; Matsumae, Yoshiaki

2014-11-01

Error propagation in Earth's atmospheric, oceanic, and land surface parameters of the satellite products caused by misclassification of the cloud mask is a critical issue for improving the accuracy of satellite products. Thus, characterizing the accuracy of the cloud mask is important for investigating the influence of the cloud mask on satellite products. In this study, we proposed a method for validating multiwavelength satellite data derived cloud masks using ground-based sky camera (GSC) data. First, a cloud cover algorithm for GSC data has been developed using sky index and bright index. Then, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived cloud masks by two cloud-screening algorithms (i.e., MOD35 and CLAUDIA) were validated using the GSC cloud mask. The results indicate that MOD35 is likely to classify ambiguous pixels as "cloudy," whereas CLAUDIA is likely to classify them as "clear." Furthermore, the influence of error propagations caused by misclassification of the MOD35 and CLAUDIA cloud masks on MODIS derived reflectance, brightness temperature, and normalized difference vegetation index (NDVI) in clear and cloudy pixels was investigated using sky camera data. It shows that the influence of the error propagation by the MOD35 cloud mask on the MODIS derived monthly mean reflectance, brightness temperature, and NDVI for clear pixels is significantly smaller than for the CLAUDIA cloud mask; the influence of the error propagation by the CLAUDIA cloud mask on MODIS derived monthly mean cloud products for cloudy pixels is significantly smaller than that by the MOD35 cloud mask.

Satellites as Sentinels for Environment & Health

Science.gov (United States)

Maynard, Nancy G.

2002-01-01

Satellites as Sentinels for Environment & Health Remotely-sensed data and observations are providing powerful new tools for addressing human and ecosystem health by enabling improved understanding of the relationships and linkages between health-related environmental parameters and society as well as techniques for early warning of potential health problems. NASA Office of Earth Science Applications Program has established a new initiative to utilize its data, expertise, and observations of the Earth for public health applications. In this initiative, lead by Goddard Space Flight Center, remote sensing, geographic information systems, improved computational capabilities, and interdisciplinary research between the Earth and health science communities are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global health issues. This presentation provides a number of recent examples of applications of advanced remote sensing and other technologies to health.and security issues related to the following: infectious and vector-borne diseases; urban, regional and global air pollution; African and Asian airborne dust; heat stress; UV radiation; water-borne disease; extreme weather; contaminant pathways (ocean, atmosphere, ice)

Satellite Image Time Series Decomposition Based on EEMD

Directory of Open Access Journals (Sweden)

Yun-long Kong

2015-11-01

Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.

Satellite stories: capturing professional experiences of academic health sciences librarians working in delocalized health sciences programs.

Science.gov (United States)

Phinney, Jackie; Horsman, Amanda Rose

2018-01-01

Health sciences training programs have progressively expanded onto satellite campuses, allowing students the opportunity to learn in communities away from an academic institution's main campus. This expansion has encouraged a new role for librarians to assume, in that a subset of health sciences librarians identify as "satellite librarians" who are permanently located at a distance from the main campus. Due to the unique nature of this role and lack of existing data on the topic, the authors investigated the experiences and perceptions of this unique group of information professionals. An electronic survey was distributed to health sciences librarians via two prominent North American email discussion lists. Questions addressed the librarians' demographics, feelings of social inclusion, technological support, autonomy, professional support, and more. Eighteen surveys were analyzed. While several respondents stated that they had positive working relationships with colleagues, many cited issues with technology, scheduling, and lack of consideration as barriers to feeling socially included at both the parent and local campuses. Social inclusion, policy creation, and collection management issues were subject to their unique situations and their colleagues' perceptions of their roles as satellite librarians. The results from this survey suggest that the role of the academic health sciences librarian at the satellite campus needs to be clearly communicated and defined. This, in turn, will enhance the experience for the librarian and provide better service to the client.

Climatic drivers of vegetation based on wavelet analysis

Science.gov (United States)

Claessen, Jeroen; Martens, Brecht; Verhoest, Niko E. C.; Molini, Annalisa; Miralles, Diego

2017-04-01

Vegetation dynamics are driven by climate, and at the same time they play a key role in forcing the different bio-geochemical cycles. As climate change leads to an increase in frequency and intensity of hydro-meteorological extremes, vegetation is expected to respond to these changes, and subsequently feed back on their occurrence. This response can be analysed using time series of different vegetation diagnostics observed from space, in the optical (e.g. Normalised Difference Vegetation Index (NDVI), Solar Induced Fluorescence (SIF)) and microwave (Vegetation Optical Depth (VOD)) domains. In this contribution, we compare the climatic drivers of different vegetation diagnostics, based on a monthly global data-cube of 24 years at a 0.25° resolution. To do so, we calculate the wavelet coherence between each vegetation-related observation and observations of air temperature, precipitation and incoming radiation. The use of wavelet coherence allows unveiling the scale-by-scale response and sensitivity of the diverse vegetation indices to their climatic drivers. Our preliminary results show that the wavelet-based statistics prove to be a suitable tool for extracting information from different vegetation indices. Going beyond traditional methods based on linear correlations, the application of wavelet coherence provides information about: (a) the specific periods at which the correspondence between climate and vegetation dynamics is larger, (b) the frequencies at which this correspondence occurs (e.g. monthly or seasonal scales), and (c) the time lag in the response of vegetation to their climate drivers, and vice versa. As expected, areas of high rainfall volumes are characterised by a strong control of radiation and temperature over vegetation. Furthermore, precipitation is the most important driver of vegetation variability over short terms in most regions of the world - which can be explained by the rapid response of leaf development towards available water content

Water availability forecasting for Naryn River using ground-based and satellite snow cover data

Directory of Open Access Journals (Sweden)

O. Y. Kalashnikova

2017-01-01

Full Text Available The main source of river nourishment in arid regions of Central Asia is the melting of seasonal snow accu‑ mulated in mountains during the cold period. In this study, we analyzed data on seasonal snow cover by ground‑based observations from Kyrgyzhydromet network, as well as from MODIS satellite imagery for the period of 2000–2015. This information was used to compile the forecast methods of water availability of snow‑ice and ice‑snow fed rivers for the vegetation period. The Naryn river basin was chosen as a study area which is the main tributary of Syrdarya River and belongs to the Aral Sea basin. The representative mete‑ orological stations with ground‑based observations of snow cover were identified and regression analysis between mean discharge for the vegetation period and number of snow covered days, maximum snow depth based on in‑situ data as well as snow cover area based on MODIS images was conducted. Based on this infor‑ mation, equations are derived for seasonal water availability forecasting using multiple linear regression anal‑ ysis. Proposed equations have high correlation coefficients (R = 0.89÷0.92 and  and fore‑ casting accuracy. The methodology was implemented in Kyrgyzhydromet and is used for forecasting of water availability in Naryn basin and water inflow into Toktogul Reservoir.

Health risk assessment of heavy metals in vegetables grown around battery production area

Directory of Open Access Journals (Sweden)

Ying Chen

2014-04-01

Full Text Available Battery production is one of the main sources of heavy metals that present great harm to human health even in low concentrations. Chromium (Cr, Cadmium (Cd and Lead (Pb were measured in edible portions of vegetables and soils around a battery production area in China, and the potential health risk of heavy metal contamination to the local population via vegetable consumption was evaluated. Their concentrations in edible portions of vegetables were 2.354 (0.078-14.878, 0.035 (0.003-0.230 and 0.039 (0.003-0.178 mg kg-1, respectively. Approximately 3 % of the Cd in the vegetable samples exceeded the maximum concentration allowable by national food safety criteria, although Pb content in all samples were within the criteria. Transfer factors (TF from soils to vegetables were dependent on vegetable species. Leguminous vegetables were more likely to accumulate Cr, while leaf vegetables tended to show higher levels of concentration of Cd and Pb. Melon vegetables demonstrated a relatively low capacity for accumulating the heavy metals studied. TF were positively correlated with soil organic matter and negatively correlated with soil pH. The mean estimated daily intake of Cr, Cd and Pb via dietary consumption of vegetables was 0.011, 1.65 × 10-4 and 1.84 × 10-4 mg kg-1 of body weight per day, respectively, levels that were much lower than the reference doses recommended by USEPA (U.S. Environmental Protection Agency and JECFA (Joint FAO/WHO Expert Committee on Food Additives, indicating that the potential health risk of Cr, Cd and Pb exposure via vegetable consumption to the local population around this battery production area could be negligible.

A Space Based Solar Power Satellite System

Science.gov (United States)

Engel, J. M.; Polling, D.; Ustamujic, F.; Yaldiz, R.; et al.

2002-01-01

(SPoTS) supplying other satellites with energy. SPoTS is due to be commercially viable and operative in 2020. of Technology designed the SPoTS during a full-time design period of six weeks as a third year final project. The team, organized according to the principles of systems engineering, first conducted a literature study on space wireless energy transfer to select the most suitable candidates for use on the SPoTS. After that, several different system concepts have been generated and evaluated, the most promising concept being worked out in greater detail. km altitude. Each SPoTS satellite has a 50m diameter inflatable solar collector that focuses all received sunlight. Then, the received sunlight is further redirected by means of four pointing mirrors toward four individual customer satellites. A market-analysis study showed, that providing power to geo-stationary communication satellites during their eclipse would be most beneficial. At arrival at geo-stationary orbit, the focused beam has expended to such an extent that its density equals one solar flux. This means that customer satellites can continue to use their regular solar arrays during their eclipse for power generation, resulting in a satellite battery mass reduction. the customer satellites in geo-stationary orbit, the transmitted energy beams needs to be pointed with very high accuracy. Computations showed that for this degree of accuracy, sensors are needed, which are not mainstream nowadays. Therefore further research must be conducted in this area in order to make these high-accuracy-pointing systems commercially attractive for use on the SPoTS satellites around 2020. Total 20-year system lifetime cost for 18 SPoT satellites are estimated at approximately USD 6 billion [FY2001]. In order to compete with traditional battery-based satellite power systems or possible ground based wireless power transfer systems the price per kWh for the customer must be significantly lower than the present one

Food environment of fruits and vegetables in the territory of the Health Academy Program.

Science.gov (United States)

Costa, Bruna Vieira de Lima; Oliveira, Cláudia Di Lorenzo; Lopes, Aline Cristine Souza

2015-11-01

This study provides a spatial analysis of distribution and access to commercial fruit and vegetable establishments within the territory of a representative sample of public fitness facilities known as the Health Academy Program (HAP) in Belo Horizonte, Minas Gerais State, Brazil. The study evaluated commercial food establishments within a buffer area based on a radius of 1,600 meters around each of 18 randomly selected fitness facilities. Quality of access to fruits and vegetables was assessed by the Healthy Food Store Index (HFSI), consisting of the variables availability, variety, and advertising of fruits, vegetables and ultra-processed foods. The analysis was based on calculation of the Kernel intensity estimator, nearest neighbor method, and Ripley K-function. Of the 336 food establishments, 61.3% were green grocers and open-air markets, with a median HFSI of 11 (5 to 16). In only 17% of the territories, the majority of the "hot area" establishments displayed better access to healthy foods, and only three areas showed a clustering pattern. The study showed limited access to commercial establishments supplying healthy fruits and vegetables within the territory of the public fitness program.

[Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].

Science.gov (United States)

Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han

2014-11-01

Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.

The 2005 and 2012 major drought events in Iberia: monitoring vegetation dynamics and crop yields using satellite data.

Science.gov (United States)

Gouveia, Célia M.; Trigo, Ricardo M.

2014-05-01

The Iberian Peninsula is recurrently affected by drought episodes and therefore by the adverse effects associated that range from severe water shortages to economic losses and related social impacts. During the hydrological years of 2004/2005 and 2011/2012, Iberia was hit by two of the worst drought episodes ever recording in this semi-arid region (Garcia-Herrera at al., 2007; Trigo et al., 2013). These two drought episodes were extreme in both its magnitude and spatial extent. A tendency towards a drier Mediterranean for the period 1970-2010 in comparison with 1901-70 has been identified (Hoerling et al., 2012), reinforcing the need for a continuous monitoring of vegetation stress and reliable estimates of the drought impacts. The strong effect of water scarcity on vegetation dynamics is well documented in Mediterranean and other semi-arid regions. Despite the usual link established between the decrease of vegetation greenness and the lack of precipitation during a considerably long period, the impact on vegetation activity may be amplified by other climatic anomalies, such as high temperature, high wind, and low relative humidity. The recent availability of consistent satellite imagery covering large regions over long periods of time has progressively reinforced the role of remote sensing in environmental studies, in particular in those related to drought episodes (e.g. Gouveia et al., 2009). The aim of the present work is to assess and monitor the cumulative impact over time of drought conditions on vegetation over Iberian Peninsula. For this purpose we have used the regional fields of the Normalized Difference Vegetation Index (NDVI) as obtained from the VEGETATION-SPOT5 instrument, from 1999 to 2013. The entire 15-yr long period was analysed, but particular attention was devoted to the two extreme drought episodes of 2004-2005 and 2011-2012. During the hydrological years of 2004-2005 and 2011-2012 drought episodes negative anomalies of NDVI were observed over

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

Directory of Open Access Journals (Sweden)

Greg Easson

2007-12-01

Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

Leo satellite-based telecommunication network concepts

Science.gov (United States)

Aiken, John G.; Swan, Peter A.; Leopold, Ray J.

1991-01-01

Design considerations are discussed for Low Earth Orbit (LEO) satellite based telecommunications networks. The satellites are assumed to be connected to each other via intersatellite links. They are connected to the end user either directly or through gateways to other networks. Frequency reuse, circuit switching, packet switching, call handoff, and routing for these systems are discussed by analogy with terrestrial cellular (mobile radio) telecommunication systems.

Fine-tuning satellite-based rainfall estimates

Science.gov (United States)

Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

2018-05-01

Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

Mapping Aquatic Vegetation in a Tropical Wetland Using High Spatial Resolution Multispectral Satellite Imagery

Directory of Open Access Journals (Sweden)

Timothy G. Whiteside

2015-09-01

Full Text Available Vegetation plays a key role in the environmental function of wetlands. The Ramsar-listed wetlands of the Magela Creek floodplain in Northern Australia are identified as being at risk from weeds, fire and climate change. In addition, the floodplain is a downstream receiving environment for the Ranger Uranium Mine. Accurate methods for mapping wetland vegetation are required to provide contemporary baselines of annual vegetation dynamics on the floodplain to assist with analysing any potential change during and after minesite rehabilitation. The aim of this study was to develop and test the applicability of geographic object-based image analysis including decision tree classification to classify WorldView-2 imagery and LiDAR-derived ancillary data to map the aquatic vegetation communities of the Magela Creek floodplain. Results of the decision tree classification were compared against a Random Forests classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010. The decision tree classification method provided an overall accuracy of 78% which was significantly higher than the overall accuracy of the Random Forests classification (67%. Most of the error in both classifications was associated with confusion between spectrally similar classes dominated by grasses, such as Hymenachne and Pseudoraphis. In addition, the extent of the sedge Eleocharis was under-estimated in both cases. This suggests the method could be useful for mapping wetlands where statistical-based supervised classifications have achieved less than satisfactory results. Based upon the results, the decision tree method will form part of an ongoing operational monitoring program.

Fruits and vegetables consumption and depressive symptoms: A population-based study in Peru.

Science.gov (United States)

Wolniczak, Isabella; Cáceres-DelAguila, José A; Maguiña, Jorge L; Bernabe-Ortiz, Antonio

2017-01-01

Among different factors, diet patterns seem to be related to depression. The aim of this study was to evaluate the association between the consumption of fruits and/or vegetables and depressive symptoms. A secondary data analysis was conducted using information from a population-based survey from 25 regions from Peru. The outcome was the presence of depressive symptoms according to the Patient Health Questionnaire (cutoff ≥15 to define major depressive syndrome); whereas the exposure was the self-reported consumption of fruits and/or vegetables (in tertiles and using WHO recommendation ≥5 servings/day). The association of interest was evaluated using Poisson regression models controlling for the complex-sample survey design and potential confounders. Data from 25,901 participants were analyzed, mean age 44.2 (SD: 17.7) and 13,944 (54.0%) women. Only 910 (3.8%; 95%CI: 3.5%-4.2%) individuals reported consuming ≥5 servings of fruits and/or vegetables/day; whereas 819 (2.8%; 95%CI: 2.5%-3.1%) had depressive symptoms. Those in the lowest tertile of fruits and/or vegetables consumption had greater prevalence of depressive symptoms (PR = 1.88; 95%CI: 1.39-2.55) than those in the highest tertile. This association was stronger with fruits (PR = 1.92; 95%CI: 1.46-2.53) than vegetables (PR = 1.42; 95%CI: 1.05-1.93) alone. An inverse relationship between consumption of fruits and/or vegetables and depressive symptoms is reported. Less than 5% of subjects reported consuming the amount of fruits and vegetables recommended by the WHO. There is a need to implement strategies to promote better diet patterns with potential impact on mental health.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport

Science.gov (United States)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; Van de Water, P. K.; Myers, O. B.; Budge, A. M.;

Greenhouse cultivation mitigates metal-ingestion-associated health risks from vegetables in wastewater-irrigated agroecosystems

Energy Technology Data Exchange (ETDEWEB)

Cao, Chun [College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, Gansu (China); College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, Gansu (China); Chen, Xing-Peng; Ma, Zhen-Bang [College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, Gansu (China); Jia, Hui-Hui [State High-Tech Industrial Innovation Center, Shenzhen 518057, Guangdong (China); Wang, Jun-Jian, E-mail: junjian.wang@utoronto.ca [Department of Physical and Environmental Sciences, University of Toronto, Toronto M1C 1A4 (Canada)

2016-08-01

Wastewater irrigation can elevate metal concentrations in soils and crops and increase the metal-associated health risks via vegetable ingestion in arid and semiarid northwestern China. Here, we investigated the As, Cd, Cr, Cu, Ni, Pb, and Zn concentrations in four vegetable species from Dongdagou and Xidagou farmlands in Baiyin, Gansu, China. We evaluated the effects of irrigation type (Dongdagou: industrial wastewater; Xidagou: domestic wastewater) and cultivation mode (open field and greenhouse) on the vegetable metal concentration, metal partitioning, soil-to-plant bioconcentration factor (BCF), and the health risk index. All stream waters, soils, and vegetables were found most severely polluted by As and Cd, with higher severity in the industrial-wastewater-irrigated Dongdagou than the domestic-wastewater-irrigated Xidagou. All vegetables had higher or, at least, comparable metal mass allocated in the shoot than in the root. Greenhouse cultivation could reduce metal-ingestion-associated health risks from edible vegetable biomass by decreasing the soil to plant bioaccumulation (BCF) and the metal concentration. This effect was always significant for all vegetables within Xidagou, and for carrot within Dongdagou. This mitigation effect of greenhouse cultivation could be attributed to the metal sorption by a higher level of soil organic matter and faster growth rate over metal uptake rate in greenhouses compared to open fields. Such mitigation effect was, however, insignificant for leafy vegetables within Dongdagou, when much more severely polluted water for irrigation was applied in greenhouses compared to open fields within Dongdagou. The present study highlights greenhouse cultivation as a potential mitigating approach to providing less-polluted vegetables for residents in the severely polluted area in addition to the source pollution control. - Highlights: • Vegetable farmlands in Baiyin, Gansu, China were severely polluted by As and Cd. • Greenhouses had

Greenhouse cultivation mitigates metal-ingestion-associated health risks from vegetables in wastewater-irrigated agroecosystems

International Nuclear Information System (INIS)

Cao, Chun; Chen, Xing-Peng; Ma, Zhen-Bang; Jia, Hui-Hui; Wang, Jun-Jian

2016-01-01

Wastewater irrigation can elevate metal concentrations in soils and crops and increase the metal-associated health risks via vegetable ingestion in arid and semiarid northwestern China. Here, we investigated the As, Cd, Cr, Cu, Ni, Pb, and Zn concentrations in four vegetable species from Dongdagou and Xidagou farmlands in Baiyin, Gansu, China. We evaluated the effects of irrigation type (Dongdagou: industrial wastewater; Xidagou: domestic wastewater) and cultivation mode (open field and greenhouse) on the vegetable metal concentration, metal partitioning, soil-to-plant bioconcentration factor (BCF), and the health risk index. All stream waters, soils, and vegetables were found most severely polluted by As and Cd, with higher severity in the industrial-wastewater-irrigated Dongdagou than the domestic-wastewater-irrigated Xidagou. All vegetables had higher or, at least, comparable metal mass allocated in the shoot than in the root. Greenhouse cultivation could reduce metal-ingestion-associated health risks from edible vegetable biomass by decreasing the soil to plant bioaccumulation (BCF) and the metal concentration. This effect was always significant for all vegetables within Xidagou, and for carrot within Dongdagou. This mitigation effect of greenhouse cultivation could be attributed to the metal sorption by a higher level of soil organic matter and faster growth rate over metal uptake rate in greenhouses compared to open fields. Such mitigation effect was, however, insignificant for leafy vegetables within Dongdagou, when much more severely polluted water for irrigation was applied in greenhouses compared to open fields within Dongdagou. The present study highlights greenhouse cultivation as a potential mitigating approach to providing less-polluted vegetables for residents in the severely polluted area in addition to the source pollution control. - Highlights: • Vegetable farmlands in Baiyin, Gansu, China were severely polluted by As and Cd. • Greenhouses had

Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

Science.gov (United States)

Suepa, Tanita

The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability

Assessing Wildlife Habitat And Range Utilization in Arizona Using Satellite Data

Science.gov (United States)

Hutchinson, C. F.; Marsh, S. E.; Krausman, P. R.; Enns, R. M.; Howery, L. D.; Trobia, E.; Wallace, C. S.; Walker, J. J.; Mauz, K.; Boyd, H.; Salazar, H.

2001-05-01

Since their reintroduction in 1914, elk (Cervus elaphus) have grown to be a major issue in the western United States. Most land is controlled by federal or state agencies, but individual ranchers have agreements that permit them to graze cattle on much of this land. Elk often compete with cattle for forage, and damage infrastructure (i.e. fences, watering points, and crops). Conversely, environmentalists and hunters also have an interest in the management of elk populations. As a result, consequence of these conflicting interests, there is little agreement about the size of the elk population or the nature, location, and timing of conflicts that elk might cause. This study was intended to provide information that might help managers understand the distribution of elk in Arizona as a consequence of seasonal variation and in response to extreme climatic events (i.e. El Niño and La Niña). The first task involved modeling elk populations over time. There are no long term or large-scale studies of elk movements through continuous observation (i.e. radiocollars). A technique for modeling elk population has been developed that is based on harvest data, gender ratios, and estimates of male mortality. This provided estimates of elk populations for individual game management units (areas for which harvest is reported and within which elk are managed by the Arizona Game and Fish Department). The second task involved the use of satellite data to characterize vegetation responses to seasonal and interannual climate variation among vegetation associations within game management units. This involved the use of NOAA Advanced Very High Resolution Radiometer (AVHRR) time series data to describe temporal vegetation behavior, Landsat and Ikonos data to describe spatial vegetation distribution in conjunction with U.S. Forest Service vegetation maps. Elk population estimates were correlated with satellite-derived vegetation measures by vegetation association through time. The patterns

Analysis of consumption frequencies of vegetables and fruits in Korean adolescents based on Korea youth risk behavior web-based survey (2006, 2011).

Science.gov (United States)

Kim, Yangsuk; Kwon, Yong-Suk; Park, Young-Hee; Choe, Jeong-Sook; Lee, Jin-Young

2015-08-01

This study analyzed factors affecting consumption frequencies of vegetables and fruits in Korean adolescents. Consumption frequencies of vegetables and fruits, general characteristics, meal, health, and other variables were analyzed for a total of 147,047 adolescents who participated in the KYRBWS (Korea Youth Risk Behavior Web-based Survey) conducted in 2006 and 2011 by the Korea Centers for Disease Control and Prevention. Consumption frequencies of vegetables and fruits more than once a day significantly decreased in 2011 compared to 2006 based on Chi-square test conducted for every factor employed in the study. Analysis of factors showed that consumption frequencies of vegetables and fruits were reduced in both study years as subjective income decreased, whereas intake frequencies increased with mother's education level and reduction of adolescent stress level. In general, consumption frequencies of vegetables and fruits decreased in 2011 compared to those in 2006. Thus, future research needs to improve dietary guidelines for nutrition education in order for students to recognize the importance of food consumption and necessity of increasing daily serving sizes of vegetables and fruits for their balanced consumption.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

Science.gov (United States)

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-01-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia’s cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal

Long-term decrease in satellite vegetation indices in response to environmental variables in an iconic desert riparian ecosystem: the Upper San Pedro, Arizona, United States

Science.gov (United States)

Nguyen, Uyen; Glenn, Edward P.; Nagler, Pamela L.; Scott, Russell L.

2015-01-01

The Upper San Pedro River is one of the few remaining undammed rivers that maintain a vibrant riparian ecosystem in the southwest United States. However, its riparian forest is threatened by diminishing groundwater and surface water inputs, due to either changes in watershed characteristics such as changes in riparian and upland vegetation, or human activities such as regional groundwater pumping. We used satellite vegetation indices to quantify the green leaf density of the groundwater-dependent riparian forest from 1984 to 2012. The river was divided into a southern, upstream (mainly perennial flow) reach and a northern, downstream (mainly intermittent and ephemeral flow) reach. Pre-monsoon (June) Landsat normalized difference vegetation index (NDVI) values showed a 20% drop for the northern reach (P  0·05). NDVI and enhanced vegetation index values were positively correlated (P deterioration of the riparian forest in the northern reach.

Plant-based diets and cardiovascular health.

Science.gov (United States)

Satija, Ambika; Hu, Frank B

2018-02-13

Plant-based diets, defined in terms of low frequency of animal food consumption, have been increasingly recommended for their health benefits. Numerous studies have found plant-based diets, especially when rich in high quality plant foods such as whole grains, fruits, vegetables, and nuts, to be associated with lower risk of cardiovascular outcomes and intermediate risk factors. This review summarizes the current evidence base examining the associations of plant-based diets with cardiovascular endpoints, and discusses the potential biological mechanisms underlying their health effects, practical recommendations and applications of this research, and directions for future research. Healthful plant-based diets should be recommended as an environmentally sustainable dietary option for improved cardiovascular health. Copyright © 2018 Elsevier Inc. All rights reserved.

Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

Science.gov (United States)

García-Haro, Francisco Javier; Campos-Taberner, Manuel; Muñoz-Marí, Jordi; Laparra, Valero; Camacho, Fernando; Sánchez-Zapero, Jorge; Camps-Valls, Gustau

2018-05-01

This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key parameters for a wide range of land-biosphere applications. The algorithm is based on a hybrid approach that blends the generalization capabilities offered by physical radiative transfer models with the accuracy and computational efficiency of machine learning methods. One major feature is the implementation of multi-output retrieval methods able to jointly and more consistently estimate all the biophysical parameters at the same time. We propose a multi-output Gaussian process regression (GPRmulti), which outperforms other considered methods over PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrary Inclined Leaves) radiative transfer models) EPS simulations. The global EPS products include uncertainty estimates taking into account the uncertainty captured by the retrieval method and input errors propagation. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. The paper discusses initial validation studies and provides details about the characteristics and overall quality of the products, which can be of interest to assist the successful use of the data by a broad user's community. The consistent generation and distribution of the EPS vegetation products will

Study of a Vegetation Index Based on HJ CCD Data's top-of-atmosphere reflectance and FPAR Inversion

International Nuclear Information System (INIS)

Dong, Taifeng; Wu, Bingfang; Meng, Jihua

2014-01-01

The Fraction of Photosynthetically Active Radiation (FPAR)absorbed by plant canopies is a key parameter for monitoring crop condition and estimating crop yield. In general, it is necessary to obtain Top of Canopy (TOC) reflectance from optical remote sensing data in digital number through atmospheric correction procedures before retrieving FPAR. However, there are a few of uncertainties that existe in the process of atmosphere correction and reduced the quality of TOC. This paper presents a vegetation index based on Top-of-Atmosphere (TOA) reflectance derived from HJ-1 CCD satellite for estimating direct crop FPAR. The vegetation index (HJVI) was designed based on the simulated results of a canopy-atmosphere radiative transfer model, including TOA reflectance and corresponded FPAR. The HJVI had taken the advantages of information in the green, the red and the near-infrared spectral domainswith with a aim of reducing the atmospheric effect and enhancing the sensitive to green vegetation. The HJVI was used to estimate soybean FPAR directly and validated using field measurements. The result indicated that the inversion algorithm produced a good relationship between the prediction and measurement (R 2 = 0.546, RMSE = 0.083) and the HJVI showed high potential for estimating FPAR based on the HJ-1 TOA reflectance directly

Fruit and vegetable intake of Korean children and adolescents according to cooking location and daily meal: study based on 2010 and 2011 Korea National Health and Nutrition Examination Survey data.

Science.gov (United States)

Kwon, Yong-Suk; Kim, Yangsuk

2018-01-01

This study analyzed the intake of fruits and vegetables by cooking location and daily meals for Korean children and adolescents. For this study, 2,538 Korean children and adolescents aged 7-18 years, who participated in the 2010 and 2011 Korea National Health and Nutrition Examination Survey dietary intake survey (24-hour recall methods), were sampled. The total unsalted fruit and vegetable intake for all subjects was 300 g (aged 7-12 years, 280 g; aged 13-18 years, 316 g). Regarding meal serving location, the combined unsalted fruit and vegetable intake was 159 g at home, 206 g at commercial locations, and 104 g at institutions. The combined unsalted fruit and vegetable intake in snack form was 128 g, which was higher than that during daily meals. In total, 24.9% of subjects satisfied the recommended fruit and vegetable intake (>=400 g), according to the guidelines created by the World Health Organization/World Cancer Research Fund. Logistic regression analysis results revealed that the fruit and vegetable intake of girls was 1.4 times higher than that of boys, and the number of people who ate more than 400 g of fruits and vegetables was 1.7 times higher in the group with higher education. Based on the above results, in-depth measures to continuously increase intake of fruits and vegetables in children and adolescents are needed. This study can be used as basic data for the development of educational programs for dietary improvements.

Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

Directory of Open Access Journals (Sweden)

Jane Southworth

2010-12-01

Full Text Available Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.

Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

Science.gov (United States)

Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

2014-08-01

The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

A comparison of multi-resource remote sensing data for vegetation indices

International Nuclear Information System (INIS)

Cao, Liqin; Wei, Lifei; Liu, Tingting

2014-01-01

With the development of the satellite sensor, multi-resource observation systems have become widely used. However, there is a huge difference between quantitative remote sensing products because of the different sensing observations and the quantitative retrieval algorithms. In this paper, the quantitative relationships between the normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) and the vegetation index based on the universal pattern decomposition method (VIUPD) of Landsat ETM+ and ASTER sensors are investigated. The difference in observations was examined between the two sensors, based on a pair of images. The results showed that: 1) There was a strong correlation between the different vegetation indices for the same sensor, with the coefficient of determination being greater than 0.9. 2) Whether for ASTER or Landsat, the information of VIUPD was richer than that of NDVI and SAVI. Furthermore, in dense vegetation areas, the values of NDVI and SAVI could easily reach saturation. 3) The values of SAVI were higher than NDVI in the areas of water or bare soil, while this was the opposite in areas of lush vegetation

The European Common Agricultural Policy on fruits and vegetables: exploring potential health gain from reform.

Science.gov (United States)

Veerman, J Lennert; Barendregt, Jan J; Mackenbach, Johan P

2006-02-01

Consumption of fruits and vegetables is associated with a reduced risk of cardiovascular disease and cancer. The European Union Common Agricultural Policy keeps prices high by limiting the availability of fruits and vegetables. This policy is at odds with public health interests. We assess the potential health gain for the Dutch population of discontinuing EU withdrawal support for fruits and vegetables. The maximum effect of the reform was estimated by assuming that a quantity equivalent to the amount of produce withdrawn in recent years would be brought onto the market. For the calculation of the effect of consumption change on health we constructed a multi-state life table model in which consumption of fruits and vegetables is linked to ischaemic heart disease, stroke, and cancer of the oesophagus, stomach, colorectum, lung and breast. Uncertainty is quantified using Monte Carlo simulation. The reform would maximally increase the average consumption of fruits and vegetables by 1.80% (95% uncertainty interval 1.12-2.73), with an ensuing increase in life expectancy of 3.8 (2.2-5.9) days for men and 2.6 (1.5-4.2) days for women. The reform is also likely to decrease socio-economic inequalities in health. Ending EU withdrawal support for fruits and vegetables could result in a modest health gain for the Dutch population, though uncertainty in the estimates is high. A more comprehensive examination of the health effects of the EU agricultural policy could help to ensure health is duly considered in decision-making.

Carbohydrates, Dietary Fiber, and Resistant Starch in White Vegetables: Links to Health Outcomes12

OpenAIRE

Slavin, Joanne L.

2013-01-01

Vegetables are universally promoted as healthy. Dietary Guidelines for Americans 2010 recommend that you make half of your plate fruits and vegetables. Vegetables are diverse plants that vary greatly in energy content and nutrients. Vegetables supply carbohydrates, dietary fiber, and resistant starch in the diet, all of which have been linked to positive health outcomes. Fiber lowers the incidence of cardiovascular disease and obesity. In this paper, the important role of white vegetables in ...

Analysis of consumption frequencies of vegetables and fruits in Korean adolescents based on Korea youth risk behavior web-based survey (2006, 2011)

OpenAIRE

Kim, Yangsuk; Kwon, Yong-Suk; Park, Young-Hee; Choe, Jeong-Sook; Lee, Jin-Young

2015-01-01

BACKGROUND/OBJECTIVES This study analyzed factors affecting consumption frequencies of vegetables and fruits in Korean adolescents. SUBJECTS/METHODS Consumption frequencies of vegetables and fruits, general characteristics, meal, health, and other variables were analyzed for a total of 147,047 adolescents who participated in the KYRBWS (Korea Youth Risk Behavior Web-based Survey) conducted in 2006 and 2011 by the Korea Centers for Disease Control and Prevention. RESULTS Consumption frequencie...

Combustion of animal or vegetable based liquid waste products

International Nuclear Information System (INIS)

Wikman, Karin; Berg, Magnus

2002-04-01

In this project experiences from combustion of animal and vegetable based liquid waste products have been compiled. Legal aspects have also been taken into consideration and the potential for this type of fuel on the Swedish energy market has been evaluated. Today the supply of animal and vegetable based liquid waste products for energy production in Sweden is limited. The total production of animal based liquid fat is about 10,000 tonnes annually. The animal based liquid waste products origin mainly from the manufacturing of meat and bone meal. Since meat and bone meal has been banned from use in animal feeds it is possible that the amount of animal based liquid fat will decrease. The vegetable based liquid waste products that are produced in the processing of vegetable fats are today used mainly for internal energy production. This result in limited availability on the commercial market. The potential for import of animal and vegetable based liquid waste products is estimated to be relatively large since the production of this type of waste products is larger in many other countries compared to Sweden. Vegetable oils that are used as food or raw material in industries could also be imported for combustion, but this is not reasonable today since the energy prices are relatively low. Restrictions allow import of SRM exclusively from Denmark. This is today the only limit for increased imports of animal based liquid fat. The restrictions for handle and combustion of animal and vegetable based liquid waste products are partly unclear since this is covered in several regulations that are not easy to interpret. The new directive for combustion of waste (2000/76/EG) is valid for animal based waste products but not for cadaver or vegetable based waste products from provisions industries. This study has shown that more than 27,400 tonnes of animal based liquid waste products and about 6,000 tonnes of vegetable based liquid waste products were used for combustion in Sweden

ALPINE VEGETATION ECOTONE DYNAMICS IN GANGOTRI CATCHMENT USING REMOTE SENSING TECHNIQUES

Directory of Open Access Journals (Sweden)

C. P. Singh

2012-09-01

Full Text Available Analysis of the satellite imagery reveals two different perspectives of the vegetation ecotone dynamics in Gangotri catchment. On one hand, there is evidence of upward shift in the alpine tree and vegetation ecotone over three decades. On the other hand, there has been densification happening at the past treeline. The time series fAPAR data of two decades from NOAA-AVHRR confirms the greening trend in the area. The density of trees in Chirbasa has gone up whereas in Bhojbasa there is no significant change in NDVI but the number of groves has increased. Near Gaumukh the vegetal activity has not shown any significant change. We found that the treeline extracted from satellite imagery has moved up about 327±80m and other vegetation line has moved up about 401±77m in three decades. The vertical rate of treeline shift is found to be 11m/yr with reference to 1976 treeline; however, this can be 5m/yr if past toposheet records (1924 – 45 are considered as reliable reference. However, the future IPCC scenario based bioclimatic fundamental niche modelling of the Betula utilis (a surrogate to alpine treeline suggests that treeline could be moving upward with an average rate of 3m/yr. This study not only confirms that there is an upward shift of vegetation in the alpine zone of Himalayas, but also indicate that old vegetation ecotones have grown denser

Soil Erosion Risk Map based on irregularity of the vegetative activity

Science.gov (United States)

Saa-Requejo, Antonio; Tarquis, Ana Maria; Martín-Sotoca, Juan J.; Valencia, Jose L.; Gobin, Anne; Rodriguez-Sinobas, Leonor

2016-04-01

Because of the difficulties to build on both daily rainfall and base shorter time, we explored the possibilities of building indexes based on land cover, which also provide us the opportunity to evaluate their evolution over time. We consider the Fournier index (Fournier, 1960) which is used to assess the rainfall erosivity based on monthly rainfall, alternatively to use of the rainfall intensity in time bases under one hour (eg., van der Knijff et al., 1999; Shamshad et al, 2008). This index can also be interpreted as an index of irregularity and representing a ratio between maximum monthly precipitation and annual rainfall. We propose to calculate this irregularity in terms of irregularity of the vegetative activity. This activity is related to precipitation, but also with the availability of water in the soil reservoir and land use. Therefore, we propose a kind of Fournier index on the effective use of water, which is also closely related to variations in infiltration. Higher is the presence of vegetation higher is the effective use of water. For this "modified Fourier index" we used the NDVI (Normalized Difference Vegetation Index) as index of available vegetative activity, which is widely reported in the literature (Jensen, 2000). Initial calculations have been done with MODIS 500 x 500 m satellite data. The selected area was Cega-Eresma-Adaja subbasin during the period from 2009 to 2012. We selected 8 days composite images product. The calculation of the valid values to eliminate areas with clouds or snow is performed according to the criteria of Martinez Sotoca (2014), ie with a Saturation (based on HSL color model) greater or equal to 0.15. Then, an average of these values was estimated to represent each month of the year. The results are very interesting when we compare Modified Fournier Index on NDVIs with the map of potential soil loss. We have found surprisingly similar patterns and practical equivalence between several classes. Therefore, the Modified

Satellite Imagery Analysis for Automated Global Food Security Forecasting

Science.gov (United States)

Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

2017-12-01

The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

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Tang, G.; Bartlein, P. J.

2012-08-01

Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH

Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island

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Julien Morel

2014-07-01

Full Text Available Estimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1 an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2 the Kumar-Monteith efficiency model, and (3 a forced-coupling method with a sugarcane crop model (MOSICAS and satellite-derived fraction of absorbed photosynthetically active radiation. These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t∙ha−1. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. The main limitation is the acquisition of a minimum of five satellite images. The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.

Effects of tailoring ingredients in auditory persuasive health messages on fruit and vegetable intake.

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Elbert, Sarah P; Dijkstra, Arie; Rozema, Andrea D

2017-07-01

Health messages can be tailored by applying different tailoring ingredients, among which personalisation, feedback and adaptation. This experiment investigated the separate effects of these tailoring ingredients on behaviour in auditory health persuasion. Furthermore, the moderating effect of self-efficacy was assessed. The between-participants design consisted of four conditions. A generic health message served as a control condition; personalisation was applied using the recipient's first name, feedback was given on the personal state, or the message was adapted to the recipient's value. The study consisted of a pre-test questionnaire (measuring fruit and vegetable intake and perceived difficulty of performing these behaviours, indicating self-efficacy), exposure to the auditory message and a follow-up questionnaire measuring fruit and vegetable intake two weeks after message exposure (n = 112). ANCOVAs showed no main effect of condition on either fruit or vegetable intake, but a moderation was found on vegetable intake: When self-efficacy was low, vegetable intake was higher after listening to the personalisation message. No significant differences between the conditions were found when self-efficacy was high. Individuals with low self-efficacy seemed to benefit from incorporating personalisation, but only regarding vegetable consumption. This finding warrants further investigation in tailoring research.

A Mobile Phone App Intervention Targeting Fruit and Vegetable Consumption: The Efficacy of Textual and Auditory Tailored Health Information Tested in a Randomized Controlled Trial.

Science.gov (United States)

Elbert, Sarah Pietertje; Dijkstra, Arie; Oenema, Anke

2016-06-10

Mobile phone apps are increasingly used to deliver health interventions, which provide the opportunity to present health information via different communication modes. However, scientific evidence regarding the effects of such health apps is scarce. In a randomized controlled trial, we tested the efficacy of a 6-month intervention delivered via a mobile phone app that communicated either textual or auditory tailored health information aimed at stimulating fruit and vegetable intake. A control condition in which no health information was given was added. Perceived own health and health literacy were included as moderators to assess for which groups the interventions could possibly lead to health behavior change. After downloading the mobile phone app, respondents were exposed monthly to either text-based or audio-based tailored health information and feedback over a period of 6 months via the mobile phone app. In addition, respondents in the control condition only completed the baseline and posttest measures. Within a community sample (online recruitment), self-reported fruit and vegetable intake at 6-month follow-up was our primary outcome measure. In total, 146 respondents (ranging from 40 to 58 per condition) completed the study (attrition rate 55%). A significant main effect of condition was found on fruit intake (P=.049, partial η(2)=0.04). A higher fruit intake was found after exposure to the auditory information, especially in recipients with a poor perceived own health (P=.003, partial η(2)=0.08). In addition, health literacy moderated the effect of condition on vegetable intake 6 months later (Pmobile health app. The app seems to have the potential to change fruit and vegetable intake up to 6 months later, at least for specific groups. We found different effects for fruit and vegetable intake, respectively, suggesting that different underlying psychological mechanisms are associated with these specific behaviors. Based on our results, it seems worthwhile

Heavy metals in vegetables and potential risk for human health

Directory of Open Access Journals (Sweden)

Fernando Guerra

2012-02-01

Full Text Available Ingestion of vegetables containing heavy metals is one of the main ways in which these elements enter the human body. Once entered, heavy metals are deposited in bone and fat tissues, overlapping noble minerals. Slowly released into the body, heavy metals can cause an array of diseases. This study aimed to investigate the concentrations of cadmium, nickel, lead, cobalt and chromium in the most frequently consumed foodstuff in the São Paulo State, Brazil and to compare the heavy metal contents with the permissible limits established by the Brazilian legislation. A value of intake of heavy metals in human diets was also calculated to estimate the risk to human health. Vegetable samples were collected at the São Paulo General Warehousing and Centers Company, and the heavy metal content was determined by atomic absorption spectrophotometry. All sampled vegetables presented average concentrations of Cd and Ni lower than the permissible limits established by the Brazilian legislation. Pb and Cr exceeded the limits in 44 % of the analyzed samples. The Brazilian legislation does not establish a permissible limit for Co contents. Regarding the consumption habit of the population in the São Paulo State, the daily ingestion of heavy metals was below the oral dose of reference, therefore, consumption of these vegetables can be considered safe and without risk to human health.

SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

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Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

2016-04-01

Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

Spoilage of vegetable crops by bacteria and fungi and related health hazards.

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Tournas, V H

2005-01-01

After harvest, vegetables are often spoiled by a wide variety of microorganisms including many bacterial and fungal species. The most common bacterial agents are Erwinia carotovora, Pseudomonas spp., Corynebacterium, Xanthomonas campestris, and lactic acid bacteria with E. carotovora being the most common, attacking virtually every vegetable type. Fungi commonly causing spoilage of fresh vegetables are Botrytis cinerea, various species of the genera Alternaria, Aspergillus, Cladosporium, Colletotrichum, Phomopsis, Fusarium, Penicillium, Phoma, Phytophthora, Pythium and Rhizopus spp., Botrytis cinerea, Ceratocystis fimbriata, Rhizoctonia solani, Sclerotinia sclerotiorum, and some mildews. A few of these organisms show a substrate preference whereas others such as Botrytis cinerea, Colletotrichum, Alternaria, Cladosporium, Phytophthora, and Rhizopus spp., affect a wide variety of vegetables causing devastating losses. Many of these agents enter the plant tissue through mechanical or chilling injuries, or after the skin barrier has been broken down by other organisms. Besides causing huge economic losses, some fungal species could produce toxic metabolites in the affected sites, constituting a potential health hazard for humans. Additionally, vegetables have often served as vehicles for pathogenic bacteria, viruses, and parasites and were implicated in many food borne illness outbreaks. In order to slow down vegetable spoilage and minimize the associated adverse health effects, great caution should be taken to follow strict hygiene, good agricultural practices (GAPs) and good manufacturing practices (GMPs) during cultivation, harvest, storage, transport, and marketing.

Optical burst switching based satellite backbone network

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Li, Tingting; Guo, Hongxiang; Wang, Cen; Wu, Jian

2018-02-01

We propose a novel time slot based optical burst switching (OBS) architecture for GEO/LEO based satellite backbone network. This architecture can provide high speed data transmission rate and high switching capacity . Furthermore, we design the control plane of this optical satellite backbone network. The software defined network (SDN) and network slice (NS) technologies are introduced. Under the properly designed control mechanism, this backbone network is flexible to support various services with diverse transmission requirements. Additionally, the LEO access and handoff management in this network is also discussed.

NASA Satellite Observations: A Unique Asset for the Study of the Environment and Implications for Public Health

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Estes Sue M.

2010-01-01

This slide presentation highlights how satellite observation systems are assets for studying the environment in relation to public health. It includes information on current and future satellite observation systems, NASA's public health and safety research, surveillance projects, and NASA's public health partners.

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

Science.gov (United States)

Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

2013-04-01

The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

Role of fruits and vegetables in adolescent cardiovascular health: a systematic review.

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Collese, Tatiana Sadalla; Nascimento-Ferreira, Marcus Vinicius; de Moraes, Augusto César Ferreira; Rendo-Urteaga, Tara; Bel-Serrat, Silvia; Moreno, Luis A; Carvalho, Heráclito Barbosa

2017-05-01

Levels of fruit and vegetable consumption are low among adolescents, and the possible effect of this on cardiovascular health in this age group is undefined. The aim of this systematic review was to investigate the potential role of fruit and vegetable consumption in adolescent cardiovascular health. Six electronic databases (BioMed Central, MEDLINE, Web of Science, CINAHL, Scopus, PsycINFO) were searched from database inception to December 2015. The search strategy used the following sets of descriptors: adolescents; fruits and vegetables; cardiovascular risk indicators; cross-sectional and cohort studies. Potentially eligible articles were selected independently by 2 reviewers. Eleven articles meeting the inclusion criteria were included (10 cross-sectional, 1 cohort). The main reasons for study exclusion (n = 71) were misclassification of individuals as adolescents, an unspecified outcome that was incongruent with the definitions provided, and assessment of fruits and vegetables as part of a food pattern. Articles evaluated fruit and vegetable intake (separately, together, only vegetables, or with fruit juice) in diverse units, using food frequency questionnaires, 24-hour dietary recalls, and food records. One-third of the studies showed significant inverse associations of fruit and vegetable intake with systolic blood pressure, abdominal obesity, triglycerides, high-density lipoprotein cholesterol, and metabolic syndrome. The associations between fruit and vegetable consumption and indicators of cardiovascular risk in adolescents are inconsistent, likely because of heterogeneity in the methods used to assess and classify consumption and to define cardiovascular risk in adolescents. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Spatial and temporal interpolation of satellite-based aerosol optical depth measurements over North America using B-splines

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Pfister, Nicolas; O'Neill, Norman T.; Aube, Martin; Nguyen, Minh-Nghia; Bechamp-Laganiere, Xavier; Besnier, Albert; Corriveau, Louis; Gasse, Geremie; Levert, Etienne; Plante, Danick

2005-08-01

Satellite-based measurements of aerosol optical depth (AOD) over land are obtained from an inversion procedure applied to dense dark vegetation pixels of remotely sensed images. The limited number of pixels over which the inversion procedure can be applied leaves many areas with little or no AOD data. Moreover, satellite coverage by sensors such as MODIS yields only daily images of a given region with four sequential overpasses required to straddle mid-latitude North America. Ground based AOD data from AERONET sun photometers are available on a more continuous basis but only at approximately fifty locations throughout North America. The object of this work is to produce a complete and coherent mapping of AOD over North America with a spatial resolution of 0.1 degree and a frequency of three hours by interpolating MODIS satellite-based data together with available AERONET ground based measurements. Before being interpolated, the MODIS AOD data extracted from different passes are synchronized to the mapping time using analyzed wind fields from the Global Multiscale Model (Meteorological Service of Canada). This approach amounts to a trajectory type of simplified atmospheric dynamics correction method. The spatial interpolation is performed using a weighted least squares method applied to bicubic B-spline functions defined on a rectangular grid. The least squares method enables one to weight the data accordingly to the measurement errors while the B-splines properties of local support and C2 continuity offer a good approximation of AOD behaviour viewed as a function of time and space.

Retrieval of land surface temperature (LST) from landsat TM6 and TIRS data by single channel radiative transfer algorithm using satellite and ground-based inputs

Science.gov (United States)

Chatterjee, R. S.; Singh, Narendra; Thapa, Shailaja; Sharma, Dravneeta; Kumar, Dheeraj

2017-06-01

The present study proposes land surface temperature (LST) retrieval from satellite-based thermal IR data by single channel radiative transfer algorithm using atmospheric correction parameters derived from satellite-based and in-situ data and land surface emissivity (LSE) derived by a hybrid LSE model. For example, atmospheric transmittance (τ) was derived from Terra MODIS spectral radiance in atmospheric window and absorption bands, whereas the atmospheric path radiance and sky radiance were estimated using satellite- and ground-based in-situ solar radiation, geographic location and observation conditions. The hybrid LSE model which is coupled with ground-based emissivity measurements is more versatile than the previous LSE models and yields improved emissivity values by knowledge-based approach. It uses NDVI-based and NDVI Threshold method (NDVITHM) based algorithms and field-measured emissivity values. The model is applicable for dense vegetation cover, mixed vegetation cover, bare earth including coal mining related land surface classes. The study was conducted in a coalfield of India badly affected by coal fire for decades. In a coal fire affected coalfield, LST would provide precise temperature difference between thermally anomalous coal fire pixels and background pixels to facilitate coal fire detection and monitoring. The derived LST products of the present study were compared with radiant temperature images across some of the prominent coal fire locations in the study area by graphical means and by some standard mathematical dispersion coefficients such as coefficient of variation, coefficient of quartile deviation, coefficient of quartile deviation for 3rd quartile vs. maximum temperature, coefficient of mean deviation (about median) indicating significant increase in the temperature difference among the pixels. The average temperature slope between adjacent pixels, which increases the potential of coal fire pixel detection from background pixels, is

The Impact of the Rise in Vegetable Prices on Vegetable Producer Behavior–Based on the survey of vegetable producers in Jiayu, Hubei Province

Directory of Open Access Journals (Sweden)

Liu Pan

2015-01-01

Full Text Available In order to study the impact of the rise in prices of vegetables on vegetable producers, and to increase the revenue of vegetable producers, this paper does a survey by anonymous sampling questionnaire. Results shows that: most vegetable growers think that vegetable prices should rise and would continue to rise, and that vegetable prices would increase their revenue, thus in the coming year they would expand the planting scale of vegetable variety whose increase rate is the largest in this year. But because of the increase of logistics costs and production costs, some farmers benefit very little from the rising trend of vegetable prices. Most farmers expect too much in the trend estimation of the prices of vegetables and also lack of planning and forward-looking in production, thus the planting area of single variety is often decided by the market of previous year. According to analysis of the impact of the rise in vegetable prices on vegetable producer behavior, this paper gives the following suggestions to increase revenue of vegetable producers: change the mode of thinking, improve rural information platform, and increase capital investment for vegetable production base.

Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

Science.gov (United States)

Glenn, E.P.; Neale, C. M. U.; Hunsaker, D.J.; Nagler, P.L.

2011-01-01

Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil

Complementarity in dietary supplements and foods: are supplement users vegetable eaters?

Science.gov (United States)

Kang, Hyoung-Goo; Joo, Hailey Hayeon; Choi, Kyong Duk; Lee, Dongmin; Moon, Junghoon

2017-01-01

Background : The consumption of fruits, vegetables, and dietary supplements correlate. Most previous studies have aimed to identify the determinants of supplement uses or the distinct features of supplement users; this literature lacks a discussion on dietary supplement consumption as a predictor of fruit and vegetable consumption. Objective : This study examines how dietary supplement consumption correlates with fruit and vegetable consumption by combining scanner data and surveys of Korean household grocery shopping. Methods : Propensity score matching (PSM) is used to identify the relationship between dietary supplement consumption and fruit and vegetable consumption in a household. A logit regression using supplement consumption as the dependent variable is used. Then, the supplement takers (the treatment group) are matched with non-takers (the control group) based on the propensity scores estimated in the logit regression. The fruit and vegetable consumption levels of the groups are then compared. Results : We found that dietary supplement use is associated with higher fruit and vegetable consumption. This supports the health consciousness hypothesis based on attention bias, availability heuristics, the focusing effect, and the consumption episode effect. It rejects the health substitute hypothesis based on economic substitutes and mental accounting. Conclusions : Future research on the health benefits of dietary supplements should address the complementary consumption of fruits/vegetables and their health benefits to avoid misstating the health effects of supplements.

Mortality due to Vegetation Fire-Originated PM2.5 Exposure in Europe-Assessment for the Years 2005 and 2008.

Science.gov (United States)

Kollanus, Virpi; Prank, Marje; Gens, Alexandra; Soares, Joana; Vira, Julius; Kukkonen, Jaakko; Sofiev, Mikhail; Salonen, Raimo O; Lanki, Timo

2017-01-01

Vegetation fires can release substantial quantities of fine particles (PM2.5), which are harmful to health. The fire smoke may be transported over long distances and can cause adverse health effects over wide areas. We aimed to assess annual mortality attributable to short-term exposures to vegetation fire-originated PM2.5 in different regions of Europe. PM2.5 emissions from vegetation fires in Europe in 2005 and 2008 were evaluated based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data on fire radiative power. Atmospheric transport of the emissions was modeled using the System for Integrated modeLling of Atmospheric coMposition (SILAM) chemical transport model. Mortality impacts were estimated for 27 European countries based on a) modeled daily PM2.5 concentrations and b) population data, both presented in a 50 × 50 km2 spatial grid; c) an exposure-response function for short-term PM2.5 exposure and daily nonaccidental mortality; and d) country-level data for background mortality risk. In the 27 countries overall, an estimated 1,483 and 1,080 premature deaths were attributable to the vegetation fire-originated PM2.5 in 2005 and 2008, respectively. Estimated impacts were highest in southern and eastern Europe. However, all countries were affected by fire-originated PM2.5, and even the lower concentrations in western and northern Europe contributed substantially (~ 30%) to the overall estimate of attributable mortality. Our assessment suggests that air pollution caused by PM2.5 released from vegetation fires is a notable risk factor for public health in Europe. Moreover, the risk can be expected to increase in the future as climate change proceeds. This factor should be taken into consideration when evaluating the overall health and socioeconomic impacts of these fires. Citation: Kollanus V, Prank M, Gens A, Soares J, Vira J, Kukkonen J, Sofiev M, Salonen RO, Lanki T. 2017. Mortality due to vegetation fire-originated PM2.5 exposure in Europe

Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

Science.gov (United States)

Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

2017-05-01

Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.

Health Risk Assessment of Pesticide Residues via Dietary Intake of Market Vegetables from Dhaka, Bangladesh

Directory of Open Access Journals (Sweden)

Md. Shakhaoat Hossain

2013-02-01

Full Text Available The present study was designed to assess the health risk of pesticide residues via dietary intake of vegetables collected from four top agro-based markets of Dhaka, Bangladesh. High performance liquid chromatography with a photo diode array detector (HPLC-PDA was used to determine six organophosphorus (chlorpyrifos, fenitrothion, parathion, ethion, acephate, fenthion, two carbamate (carbaryl and carbofuran and one pyrethroid (cypermethrin pesticide residues in twelve samples of three common vegetables (tomato, lady’s finger and brinjal. Pesticide residues ranged from below detectable limit (<0.01 to 0.36 mg/kg. Acephate, chlorpyrifos, ethion, carbaryl and cypermethrin were detected in only one sample, while co-occurrence occurred twice for fenitrothion and parathion. Apart from chlorpyrifos in tomato and cypermethrin in brinjal, all pesticide residues exceeded the maximum residue limit (MRL. Hazard risk index (HRI for ethion (10.12 and carbaryl (1.09 was found in lady’s finger and tomato, respectively. Rest of the pesticide residues were classified as not a health risk. A continuous monitoring and strict regulation should be enforced regarding control of pesticide residues in vegetables and other food commodities.

Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area

DEFF Research Database (Denmark)

Westergaard-Nielsen, Andreas; Lund, Magnus; Hansen, Birger Ulf

2013-01-01

vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid...... and GPP (R-2 = 0.85, p remote Arctic regions....... (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved....

Effectiveness of a Parent Health Report in Increasing Fruit and Vegetable Consumption Among Preschoolers and Kindergarteners.

Science.gov (United States)

Hunsaker, Sanita L; Jensen, Chad D

2017-05-01

To determine the effectiveness of a parent health report on fruit and vegetable consumption among preschoolers and kindergarteners. Pre-post open design trial and a randomized controlled trial. A university-sponsored preschool and kindergarten. A total of 63 parents of preschool and kindergarten students participated in the pre-post open design trial and 65 parents participated in the randomized controlled trial. Parents in intervention groups were given a parent health report providing information about their child's fruit and vegetable intake as well as recommendations for how to increase their child's fruit and vegetable consumption. Change in fruit and vegetable consumption. Latent growth curve modeling with Bayesian estimation. Vegetable consumption increased by 0.3 servings/d in the open trial and 0.65 servings/d in the randomized trial. Fruit consumption did not increase significantly in either study. Results from both an open trial and a randomized controlled trial suggested that the parent health report may be a beneficial tool to increase vegetable consumption in preschoolers and kindergarteners. Increases in vegetable consumption can lead to the establishment of lifelong habits of healthy vegetable intake and decrease risk for chronic diseases. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Vegetation burn severity mapping using Landsat-8 and WorldView-2

Science.gov (United States)

Wu, Zhuoting; Middleton, Barry R.; Hetzler, Robert; Vogel, John M.; Dye, Dennis G.

2015-01-01

We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

Vegetation studies on Vandenberg Air Force Base, California

Science.gov (United States)

Schmalzer, Paul A.; Hickson, Diana E.; Hinkle, C. Ross

1988-01-01

Vandenburg Air Force Base, located in coastal central California with an area of 98,400 ac, contains resources of considerable biological significance. Available information on the vegetation and flora of Vandenburg is summarized and new data collected in this project are presented. A bibliography of 621 references dealing with vegetation and related topics related to Vanderburg was compiled from computer and manual literature searches and a review of past studies of the base. A preliminary floristic list of 642 taxa representing 311 genera and 80 families was compiled from past studies and plants identified in the vegetation sampling conducted in this project. Fifty-two special interest plant species are known to occur or were suggested to occur. Vegetation was sampled using permanent plots and transects in all major plant communities including chaparral, Bishop pine forest, tanbark oak forest, annual grassland, oak woodland, coastal sage scrub, purple sage scrub, coastal dune scrub, coastal dunes, box elder riparian woodland, will riparian woodland, freshwater marsh, salt marsh, and seasonal wetlands. Comparison of the new vegetation data to the compostie San Diego State University data does not indicate major changes in most communities since the original study. Recommendations are made for additional studies needed to maintain and extend the environmental data base and for management actions to improve resource protection.

Role of fruits, nuts, and vegetables in maintaining cognitive health.

Science.gov (United States)

Miller, Marshall G; Thangthaeng, Nopporn; Poulose, Shibu M; Shukitt-Hale, Barbara

2017-08-01

Population aging is leading to an increase in the incidence of age-related cognitive dysfunction and, with it, the health care burden of caring for older adults. Epidemiological studies have shown that consumption of fruits, nuts, and vegetables is positively associated with cognitive ability; however, these foods, which contain a variety of neuroprotective phytochemicals, are widely under-consumed. Surprisingly few studies have investigated the effects of individual plant foods on cognitive health but recent clinical trials have shown that dietary supplementation with individual foods, or switching to a diet rich in several of these foods, can improve cognitive ability. While additional research is needed, increasing fruit, nut, and vegetable intake may be an effective strategy to prevent or delay the onset of cognitive dysfunction during aging. Published by Elsevier Inc.

Network design consideration of a satellite-based mobile communications system

Science.gov (United States)

Yan, T.-Y.

1986-01-01

Technical considerations for the Mobile Satellite Experiment (MSAT-X), the ground segment testbed for the low-cost spectral efficient satellite-based mobile communications technologies being developed for the 1990's, are discussed. The Network Management Center contains a flexible resource sharing algorithm, the Demand Assigned Multiple Access scheme, which partitions the satellite transponder bandwidth among voice, data, and request channels. Satellite use of multiple UHF beams permits frequency reuse. The backhaul communications and the Telemetry, Tracking and Control traffic are provided through a single full-coverage SHF beam. Mobile Terminals communicate with the satellite using UHF. All communications including SHF-SHF between Base Stations and/or Gateways, are routed through the satellite. Because MSAT-X is an experimental network, higher level network protocols (which are service-specific) will be developed only to test the operation of the lowest three levels, the physical, data link, and network layers.

Tundra vegetation effects on pan-Arctic albedo

International Nuclear Information System (INIS)

Loranty, Michael M; Goetz, Scott J; Beck, Pieter S A

2011-01-01

Recent field experiments in tundra ecosystems describe how increased shrub cover reduces winter albedo, and how subsequent changes in surface net radiation lead to altered rates of snowmelt. These findings imply that tundra vegetation change will alter regional energy budgets, but to date the effects have not been documented at regional or greater scales. Using satellite observations and a pan-Arctic vegetation map, we examined the effects of shrub vegetation on albedo across the terrestrial Arctic. We included vegetation classes dominated by low shrubs, dwarf shrubs, tussock-dominated graminoid tundra, and non-tussock graminoid tundra. Each class was further stratified by bioclimate subzones. Low-shrub tundra had higher normalized difference vegetation index values and earlier albedo decline in spring than dwarf-shrub tundra, but for tussock tundra, spring albedo declined earlier than for low-shrub tundra. Our results illustrate how relatively small changes in vegetation properties result in differences in albedo dynamics, regardless of shrub growth, that may lead to differences in net radiation upwards of 50 W m -2 at weekly time scales. Further, our findings imply that changes to the terrestrial Arctic energy budget during this important seasonal transition are under way regardless of whether recent satellite observed productivity trends are the result of shrub expansion. We conclude that a better understanding of changes in vegetation productivity and distribution in Arctic tundra is essential for accurately quantifying and predicting carbon and energy fluxes and associated climate feedbacks.

Planning for a data base system to support satellite conceptual design

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Claydon, C. R.

1976-01-01

The conceptual design of an automated satellite design data base system is presented. The satellite catalog in the system includes data for all earth orbital satellites funded to the hardware stage for launch between 1970 and 1980, and provides a concise compilation of satellite capabilities and design parameters. The cost of satellite subsystems and components will be added to the base. Data elements are listed and discussed. Sensor and science and applications opportunities catalogs will be included in the data system. Capabilities of the BASIS storage, retrieval, and analysis system are used in the system design.

Assessing regional crop water demand using a satellite-based combination equation with a land surface temperature componen

DEFF Research Database (Denmark)

Moyano, Carmen; Garcia, Monica; Tornos, Lucia

2015-01-01

-sequence spanning for more than a decade (2002-2013). The thermal-PT-JPL model was forced with vegetation, albedo, reflectance and temperature products from the Moderate-resolution Imaging Spectroradiometer (MODIS) from both Aqua and Terra satellites. The study region, B-XII Irrigation District of the Lower...

21 CFR 101.78 - Health claims: fruits and vegetables and cancer.

Science.gov (United States)

2010-04-01

... smoking, alcohol consumption, overweight and obesity, ultraviolet or ionizing radiation, exposure to... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Health claims: fruits and vegetables and cancer. 101.78 Section 101.78 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN...

Coliform Contamination of Peri-urban Grown Vegetables and Potential Public Health Risks: Evidence from Kumasi, Ghana.

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Abass, Kabila; Ganle, John Kuumuori; Adaborna, Eric

2016-04-01

Peri-urban vegetable farming in Ghana is an important livelihood activity for an increasing number of people. However, increasing quality and public health concerns have been raised, partly because freshwater availability for irrigation purposes is a major constraint. This paper investigated on-farm vegetable contamination and potential health risks using samples of lettuce, spring onions and cabbage randomly selected from 18 vegetable farms in peri-urban Kumasi, Ghana. Vegetable samples were tested for total coliform, fecal coliform, Escherichia coli and Salmonella spp. bacteria contamination using the Most Probable Number method. Results show high contamination levels of total and fecal coliforms, and Escherichia coli bacteria in all 18 vegetable samples. The mean total coliform/100 ml concentration for spring onions, lettuce and cabbage were 9.15 × 10(9), 4.7 × 10(7) and 8.3 × 10(7) respectively. The mean fecal coliform concentration for spring onions, lettuce and cabbage were also 1.5 × 10(8), 4.15 × 10(7) and 2.15 × 10(7) respectively, while the mean Escherichia coli bacteria contamination for spring onions, lettuce and cabbage were 1.4 × 10(8), 2.2 × 10(7) and 3.2 × 10(7) respectively. The level of total coliform, fecal coliform and Escherichia coli bacteria contamination in all the vegetable samples however declined as the distance between the main water source (Wiwi River) and farms increases. Nonetheless, all contamination levels were well above acceptable standards, and could therefore pose serious public health risks to consumers. Increased education and supervision of farmers, as well as public health and food hygiene education of consumers, are critical to reducing on-farm vegetable contamination and the health risks associated with consumption of such vegetables.

Vegetation mapping of the Mond Protected Area of Bushehr Province (south-west Iran).

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Mehrabian, Ahmadreza; Naqinezhad, Alireza; Mahiny, Abdolrassoul Salman; Mostafavi, Hossein; Liaghati, Homan; Kouchekzadeh, Mohsen

2009-03-01

Arid regions of the world occupy up to 35% of the earth's surface, the basis of various definitions of climatic conditions, vegetation types or potential for food production. Due to their high ecological value, monitoring of arid regions is necessary and modern vegetation studies can help in the conservation and management of these areas. The use of remote sensing for mapping of desert vegetation is difficult due to mixing of the spectral reflectance of bright desert soils with the weak spectral response of sparse vegetation. We studied the vegetation types in the semiarid to arid region of Mond Protected Area, south-west Iran, based on unsupervised classification of the Spot XS bands and then produced updated maps. Sixteen map units covering 12 vegetation types were recognized in the area based on both field works and satellite mapping. Halocnemum strobilaceum and Suaeda fruticosa vegetation types were the dominant types and Ephedra foliata, Salicornia europaea-Suaeda heterophylla vegetation types were the smallest. Vegetation coverage decreased sharply with the increase in salinity towards the coastal areas of the Persian Gulf. The highest vegetation coverage belonged to the riparian vegetation along the Mond River, which represents the northern boundary of the protected area. The location of vegetation types was studied on the separate soil and habitat diversity maps of the study area, which helped in final refinements of the vegetation map produced.

Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data

Directory of Open Access Journals (Sweden)

Stuart E. Marsh

2010-01-01

Full Text Available Climate change and variability are expected to impact the synchronicity and interactions between the Sonoran Desert and the forested sky islands which represent steep biological and environmental gradients. The main objectives were to examine how well satellite greenness time series data and derived phenological metrics (e.g., season start, peak greenness can characterize specific vegetation communities across an elevation gradient, and to examine the interactions between climate and phenological metrics for each vegetation community. We found that representative vegetation types (11, varying between desert scrub, mesquite, grassland, mixed oak, juniper and pine, often had unique seasonal and interannual phenological trajectories and spatial patterns. Satellite derived land surface phenometrics (11 for each of the vegetation communities along the cline showed numerous distinct significant relationships in response to temperature (4 and precipitation (7 metrics. Satellite-derived sky island vegetation phenology can help assess and monitor vegetation dynamics and provide unique indicators of climate variability and patterns of change.

Quality of Vegetables Based on Total Phenolic Concentration Is Lower in More Rural Consumer Food Environments in a Rural American State.

Science.gov (United States)

Ahmed, Selena; Byker Shanks, Carmen

2017-08-17

While daily consumption of fruits and vegetables (FVs) is widely recognized to be associated with supporting nutrition and health, disparities exist in consumer food environments regarding access to high-quality produce based on location. The purpose of this study was to evaluate FV quality using total phenolic (TP) scores (a phytochemical measure for health-promoting attributes, flavor, appearance, and shelf-life) in consumer food environments along a rural to urban continuum in the rural state of Montana, United States. Significant differences were found in the means of the FV TP scores ( p vegetable TP scores ( p vegetable TP scores were highest for the least rural stores and lowest for the most rural stores. Results indicate an access gap to high-quality vegetables in more rural and more health-disparate consumer food environments of Montana compared to urban food environments. Findings highlight that food and nutrition interventions should aim to increase vegetable quality in rural consumer food environments in the state of Montana towards enhancing dietary quality and food choices. Future studies are called for that examine TP scores of a wide range of FVs in diverse food environments globally. Studies are further needed that examine linkages between FV quality, food choices, diets, and health outcomes towards enhancing food environments for public health.

Effects of Telecoupling on Global Vegetation Dynamics

Science.gov (United States)

Viña, A.; Liu, J.

2016-12-01

With the ever increasing trend in telecoupling processes, such as international trade, all countries around the world are becoming more interdependent. However, the effects of this growing interdependence on vegetation (e.g., shifts in the geographic extent and distribution) remain unknown even though vegetation dynamics are crucially important for food production, carbon sequestration, provision of other ecosystem services, and biodiversity conservation. In this study we evaluate the effects of international trade on the spatio-temporal trajectories of vegetation at national and global scales, using vegetation index imagery collected over more than three decades by the Advanced Very High Resolution Radiometer (AVHRR) satellite sensor series together with concurrent national and international data on international trade (and its associated movement of people, goods, services and information). The spatio-temporal trajectories of vegetation are obtained using the scale of fluctuation technique, which is based on the decomposition of the AVHRR image time series to obtain information on its spatial dependence structure over time. Similar to the correlation length, the scale of fluctuation corresponds to the range over which fluctuations in the vegetation index are spatially correlated. Results indicate that global vegetation has changed drastically over the last three decades. These changes are not uniform across space, with hotspots in active trading countries. This study not only has direct implications for understanding global vegetation dynamics, but also sheds important insights on the complexity of human-nature interactions across telecoupled systems.

Carbohydrates, Dietary Fiber, and Resistant Starch in White Vegetables: Links to Health Outcomes12

Science.gov (United States)

Slavin, Joanne L.

2013-01-01

Vegetables are universally promoted as healthy. Dietary Guidelines for Americans 2010 recommend that you make half of your plate fruits and vegetables. Vegetables are diverse plants that vary greatly in energy content and nutrients. Vegetables supply carbohydrates, dietary fiber, and resistant starch in the diet, all of which have been linked to positive health outcomes. Fiber lowers the incidence of cardiovascular disease and obesity. In this paper, the important role of white vegetables in the human diet is described, with a focus on the dietary fiber and resistant starch content of white vegetables. Misguided efforts to reduce consumption of white vegetables will lower intakes of dietary fiber and resistant starch, nutrients already in short supply in our diets. PMID:23674804

Occupational Health and Safety Issues among Vegetable Farmers in Trinidad and the Implications for Extension.

Science.gov (United States)

Baksh, K S; Ganpat, W; Narine, L K

2015-07-01

Trinidad has an aged farming population. For a host of reasons, young persons are not entering the agricultural sector; therefore, these aged farmers will continue to be the backbone of the industry. Hence, there is much need for improving the health and safety of the workers within this sector. This first-time study assessed the prevalence of occupational health and safety disorders and discomforts among Trinidad's vegetable farmers in an attempt to understand the extent of the problem within the general farm population. The implications for extension are highlighted, and several recommendations are provided. Small-scale commercial-oriented vegetable farmers (n = 100) from ten of the most populated agricultural areas across Trinidad were surveyed. Results indicated that there was an overall moderate prevalence of occupational injuries among vegetable farmers. Most prevalent were musculoskeletal disorders of the lower back and upper body extremities, watery/burning eyes, skin rashes/itching, headaches, fatigue, dehydration, stress, and injuries attributed to slips and falls. Based on the evidence that a problem exists with health and safety, the extension service can now prepare and deliver programs to educate farmers on the actions necessary to improve their personal health and safety and that of their workers. This type of study has not been done before among farmers in Trinidad. It brings a very important and timely issue to the fore because of the aged farming population. Additionally, since the farmer profile and farming systems are similar in the wider Caribbean, policy makers can take note of the findings and recommendations and embrace actions.

Statistical modeling of phenological phases in Poland based on coupling satellite derived products and gridded meteorological data

Science.gov (United States)

Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

2016-04-01

The aim of the study was to create and evaluate different statistical models for reconstructing and predicting selected phenological phases. This issue is of particular importance in Poland where national-wide phenological monitoring was abandoned in the middle of 1990s and the reactivated network was established in 2006. Authors decided to evaluate possibilities of using a wide-range of statistical modeling techniques to create synthetic archive dataset. Additionally, a robust tool for predicting the most distinguishable phenophases using only free of charge data as predictors was created. Study period covers the years 2007-2014 and contains only quality-controlled dataset of 10 species and 14 phenophases. Phenological data used in this study originates from the manual observations network run by the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB). Three kind of data sources were used as predictors: (i) satellite derived products, (ii) preprocessed gridded meteorological data, and (iii) spatial properties (longitude, latitude, altitude) of the monitoring site. Moderate-Resolution Imaging Spectroradiometer (MODIS) level-3 vegetation products were used for detecting onset dates of particular phenophases. Following indices were used: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (fPAR). Additionally, Interactive Multisensor Snow and Ice Mapping System (IMS) products were chosen to detect occurrence of snow cover. Due to highly noisy data, authors decided to take into account pixel reliability information. Besides satellite derived products (NDVI, EVI, FPAR, LAI, Snow cover), a wide group of observational data and agrometeorological indices derived from the European Climate Assessment & Dataset (ECA&D) were used as a potential predictors: cumulative growing degree days (GDD), cumulative growing precipitation days (GPD

Monitoring and Assessing Groundwater Impacts on Vegetation Health in Groundwater Dependent Ecosystems

Science.gov (United States)

Rohde, M. M.; Ulrich, C.; Howard, J.; Sweet, S.

2017-12-01

Sustainable groundwater management is important for preserving our economy, society, and environment. Groundwater supports important habitat throughout California, by providing a reliable source of water for these Groundwater Dependent Ecosystems (GDEs). Groundwater is particularly important in California since it supplies an additional source of water during the dry summer months and periods of drought. The drought and unsustainable pumping practices have, in some areas, lowered groundwater levels causing undesirable results to ecosystems. The Sustainable Groundwater Management Act requires local agencies to avoid undesirable results in the future, but the location and vulnerabilities of the ecosystems that depend on groundwater and interconnected surface water is often poorly understood. This presentation will feature results from a research study conducted by The Nature Conservancy and Lawrence Berkeley National Laboratory that investigated how changes in groundwater availability along an interconnected surface water body can impact the overall health of GDEs. This study was conducted in California's Central Valley along the Cosumnes River, and situated at the boundary of a high and a medium groundwater basin: South American Basin (Sacramento Hydrologic Region) and Cosumnes Basin (San Joaquin Hydrologic Region). By employing geophysical methodology (electrical resistivity tomography) in this study, spatial changes in groundwater availability were determined under groundwater-dependent vegetation. Vegetation survey data were also applied to this study to develop ecosystem health indicators for groundwater-dependent vegetation. Health indicators for groundwater-dependent vegetation were found to directly correlate with groundwater availability, such that greater availability to groundwater resulted in healthier vegetation. This study provides a case study example on how to use hydrological and biological data for setting appropriate minimum thresholds and

Environmental Drivers of NDVI-Based Vegetation Phenology in Central Asia

Directory of Open Access Journals (Sweden)

Jahan Kariyeva

2011-02-01

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

Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

Science.gov (United States)

Sheffield, J.; Lobell, D. B.; Wood, E. F.

2010-12-01

Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including

An SDR based AIS receiver for satellites

DEFF Research Database (Denmark)

Larsen, Jesper Abildgaard; Mortensen, Hans Peter; Nielsen, Jens Frederik Dalsgaard

2011-01-01

For a few years now, there has been a high interest in monitoring the global ship traffic from space. A few satellite, capable of listening for ship borne AIS transponders have already been launched, and soon the AAUSAT3, carrying two different types of AIS receivers will also be launched. One...... of the AIS receivers onboard AAUSAT3 is an SDR based AIS receiver. This paper serves to describe the background of the AIS system, and how the SDR based receiver has been integrated into the AAUSAT3 satellite. Amongst some of the benefits of using an SDR based receiver is, that due to its versatility, new...... detection algorithms are easily deployed, and it is easily adapted the new proposed AIS transmission channels....

Vegetation Water Content Mapping in a Diverse Agricultural Landscape: National Airborne Field Experiment 2006

Science.gov (United States)

Cosh, Michael H.; Jing Tao; Jackson, Thomas J.; McKee, Lynn; O'Neill, Peggy

2011-01-01

Mapping land cover and vegetation characteristics on a regional scale is critical to soil moisture retrieval using microwave remote sensing. In aircraft-based experiments such as the National Airborne Field Experiment 2006 (NAFE 06), it is challenging to provide accurate high resolution vegetation information, especially on a daily basis. A technique proposed in previous studies was adapted here to the heterogenous conditions encountered in NAFE 06, which included a hydrologically complex landscape consisting of both irrigated and dryland agriculture. Using field vegetation sampling and ground-based reflectance measurements, the knowledge base for relating the Normalized Difference Water Index (NDWI) and the vegetation water content was extended to a greater diversity of agricultural crops, which included dryland and irrigated wheat, alfalfa, and canola. Critical to the generation of vegetation water content maps, the land cover for this region was determined from satellite visible/infrared imagery and ground surveys with an accuracy of 95.5% and a kappa coefficient of 0.95. The vegetation water content was estimated with a root mean square error of 0.33 kg/sq m. The results of this investigation contribute to a more robust database of global vegetation water content observations and demonstrate that the approach can be applied with high accuracy. Keywords: Vegetation, field experimentation, thematic mapper, NDWI, agriculture.

Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations

Directory of Open Access Journals (Sweden)

Chiara Corbari

2017-11-01

Full Text Available The Food and Agricultural Organization (FAO method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data.

Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations.

Science.gov (United States)

Corbari, Chiara; Ravazzani, Giovanni; Galvagno, Marta; Cremonese, Edoardo; Mancini, Marco

2017-11-18

The Food and Agricultural Organization (FAO) method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data.

GPS-based satellite tracking system for precise positioning

Science.gov (United States)

Yunck, T. P.; Melbourne, W. G.; Thornton, C. L.

1985-01-01

NASA is developing a Global Positioning System (GPS) based measurement system to provide precise determination of earth satellite orbits, geodetic baselines, ionospheric electron content, and clock offsets between worldwide tracking sites. The system will employ variations on the differential GPS observing technique and will use a network of nine fixed ground terminals. Satellite applications will require either a GPS flight receiver or an on-board GPS beacon. Operation of the system for all but satellite tracking will begin by 1988. The first major satellite application will be a demonstration of decimeter accuracy in determining the altitude of TOPEX in the early 1990's. By then the system is expected to yield long-baseline accuracies of a few centimeters and instantaneous time synchronization to 1 ns.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

Directory of Open Access Journals (Sweden)

G. Tang

2012-08-01

Full Text Available Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i modify a DGVM for simulating land surface water balances; (ii evaluate the modified model in simulating actual evapotranspiration (ET, soil moisture, and surface runoff at regional or watershed scales; and (iii gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ DGVM. To evaluate the model we ran LH using historical (1981–2006 climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981–2006 (R² > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52. The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15% with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Linking vegetable preferences, health and local food systems through community-supported agriculture.

Science.gov (United States)

Wilkins, Jennifer L; Farrell, Tracy J; Rangarajan, Anusuya

2015-09-01

The objective of the present study was to explore the influence of participation in community-supported agriculture (CSA) on vegetable exposure, vegetable intake during and after the CSA season, and preference related to locally produced vegetables acquired directly from CSA growers. Quantitative surveys were administered at three time points in two harvest seasons to four groups of CSA participants: new full-paying, returning full-paying, new subsidized and returning subsidized members. Questionnaires included a vegetable frequency measure and measures of new and changed vegetable preference. Comparisons were made between new and returning CSA members and between those receiving subsidies and full-paying members. The research was conducted in a rural county in New York, USA. CSA members who agreed to participate in the study. Analysis was based on 151 usable questionnaires. CSA participants reported higher intake of eleven different vegetables during the CSA season, with a sustained increase in some winter vegetables. Over half of the respondents reported trying at least one, and up to eleven, new vegetables. Sustained preferences for CSA items were reported. While those who choose to join a CSA may be more likely to acquire new and expanded vegetable preferences than those who do not, the CSA experience has the potential to enhance vegetable exposure, augment vegetable preference and increase overall vegetable consumption. Dietary patterns encouraged through CSA participation can promote preferences and consumer demand that support local production and seasonal availability. Emphasis on fresh and fresh stored locally produced vegetables is consistent with sustainable community-based food systems.

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

characterize vegetation recovery after fire disturbanceInternational Journal of Applied Earth Observation and Geoinformation 26 441-446 Lanorte A, M Danese, R Lasaponara, B Murgante 2014 Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis International Journal of Applied Earth Observation and Geoinformation 20, 42-51 Tuia D, F Ratle, R Lasaponara, L Telesca, M Kanevski 2008 Scan statistics analysis of forest fire clusters Communications in Nonlinear Science and Numerical Simulation 13 (8), 1689-1694 Telesca L, R Lasaponara 2006 Pre and post fire behavioral trends revealed in satellite NDVI time series Geophysical Research Letters 33 (14) Lasaponara R 2005 Intercomparison of AVHRR based fire susceptibility indicators for the Mediterranean ecosystems of southern Italy International Journal of Remote Sensing 26 (5), 853-870

Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape

NARCIS (Netherlands)

Chen, T.; McVicar, T.R.; Wang, G.J.; Chen, X.; de Jeu, R.A.M.; Liu, Y.; Shen, H.; Zhang, F.; Dolman, A.J.

2016-01-01

To improve the understanding of water-vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow

Mapping urban impervious surface using object-based image analysis with WorldView-3 satellite imagery

Science.gov (United States)

Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

2017-10-01

Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.

Egypt satellite images for land surface characterization

DEFF Research Database (Denmark)

Hasager, Charlotte Bay

images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

Target Detection Based on EBPSK Satellite Passive Radar

Directory of Open Access Journals (Sweden)

Lu Zeyuan

2015-05-01

Full Text Available Passive radar is a topic anti stealth technology with simple structure, and low cost. Radiation source model, signal transmission model, and target detection are the key points of passive radar technology research. The paper analyzes the characteristics of EBPSK signal modulation and target detection method aspect of spaceborne radiant source. By comparison with other satellite navigation and positioning system, the characteristics of EBPSK satellite passive radar system are analyzed. It is proved that the maximum detection range of EBPSK satellite signal can satisfy the needs of the proposed model. In the passive radar model, sparse representation is used to achieve high resolution DOA detection. The comparison with the real target track by simulation demonstrates that effective detection of airborne target using EBPSK satellite passive radar system based on sparse representation is efficient.

Trace metals accumulation in soil irrigated with polluted water and assessment of human health risk from vegetable consumption in Bangladesh.

Science.gov (United States)

Islam, Md Atikul; Romić, Davor; Akber, Md Ali; Romić, Marija

2018-02-01

Trace metals accumulation in soil irrigated with polluted water and human health risk from vegetable consumption was assessed based on the data available in the literature on metals pollution of water, soil, sediment and vegetables from the cites of Bangladesh. The quantitative data on metal concentrations, their contamination levels and their pollution sources have not been systematically gathered and studied so far. The data on metal concentrations, sources, contamination levels, sample collection and analytical tools used were collected, compared and discussed. The USEPA-recommended method for health risk assessment was used to estimate human risk from vegetable consumption. Concentrations of metals in water were highly variable, and the mean concentrations of Cd, Cr, Cu and As in water were found to be higher than the FAO irrigation water quality standard. In most cases, mean concentrations of metals in soil were higher than the Bangladesh background value. Based on geoaccumulation index (I geo ) values, soils of Dhaka city are considered as highly contaminated. The I geo shows Cd, As, Cu, Ni, Pb and Cr contamination of agricultural soils and sediments of the cities all over the Bangladesh. Polluted water irrigation and agrochemicals are identified as dominant sources of metals in agricultural soils. Vegetable contamination by metals poses both non-carcinogenic and carcinogenic risks to the public. Based on the results of the pollution and health risk assessments, Cd, As, Cr, Cu, Pb and Ni are identified as the priority control metals and the Dhaka city is recommended as the priority control city. This study provides quantitative evidence demonstrating the critical need for strengthened wastewater discharge regulations in order to protect residents from heavy metal discharges into the environment.

Validity of satellite measurements used for the monitoring of UV radiation risk on health

Directory of Open Access Journals (Sweden)

F. Jégou

2011-12-01

Full Text Available In order to test the validity of ultraviolet index (UVI satellite products and UVI model simulations for general public information, intercomparison involving three satellite instruments (SCIAMACHY, OMI and GOME-2, the Chemistry and Transport Model, Modélisation de la Chimie Atmosphérique Grande Echelle (MOCAGE, and ground-based instruments was performed in 2008 and 2009. The intercomparison highlighted a systematic high bias of ~1 UVI in the OMI clear-sky products compared to the SCIAMACHY and TUV model clear-sky products. The OMI and GOME-2 all-sky products are close to the ground-based observations with a low 6 % positive bias, comparable to the results found during the satellite validation campaigns. This result shows that OMI and GOME-2 all-sky products are well appropriate to evaluate the UV-risk on health. The study has pointed out the difficulty to take into account either in the retrieval algorithms or in the models, the large spatial and temporal cloud modification effect on UV radiation. This factor is crucial to provide good quality UV information. OMI and GOME-2 show a realistic UV variability as a function of the cloud cover. Nevertheless these satellite products do not sufficiently take into account the radiation reflected by clouds. MOCAGE numerical forecasts show good results during periods with low cloud covers, but are actually not adequate for overcast conditions; this is why Météo-France currently uses human-expertised cloudiness (rather than direct outputs from Numerical Prediction Models together with MOCAGE clear-sky UV indices for its operational forecasts. From now on, the UV monitoring could be done using free satellite products (OMI, GOME-2 and operational forecast for general public by using modelling, as long as cloud forecasts and the parametrisation of the impact of cloudiness on UV radiation are adequate.

Satellite Contamination and Materials Outgassing Knowledge base

Science.gov (United States)

Minor, Jody L.; Kauffman, William J. (Technical Monitor)

2001-01-01

Satellite contamination continues to be a design problem that engineers must take into account when developing new satellites. To help with this issue, NASA's Space Environments and Effects (SEE) Program funded the development of the Satellite Contamination and Materials Outgassing Knowledge base. This engineering tool brings together in one location information about the outgassing properties of aerospace materials based upon ground-testing data, the effects of outgassing that has been observed during flight and measurements of the contamination environment by on-orbit instruments. The knowledge base contains information using the ASTM Standard E- 1559 and also consolidates data from missions using quartz-crystal microbalances (QCM's). The data contained in the knowledge base was shared with NASA by government agencies and industry in the US and international space agencies as well. The term 'knowledgebase' was used because so much information and capability was brought together in one comprehensive engineering design tool. It is the SEE Program's intent to continually add additional material contamination data as it becomes available - creating a dynamic tool whose value to the user is ever increasing. The SEE Program firmly believes that NASA, and ultimately the entire contamination user community, will greatly benefit from this new engineering tool and highly encourages the community to not only use the tool but add data to it as well.

Assessing Sahelian vegetation and stress from seasonal time series of polar orbiting and geostationary satellite imagery

DEFF Research Database (Denmark)

Olsen, Jørgen Lundegaard

that short term variations in anomalies from seasonally detrended time series of indices could carry information on vegetation stress was examined and confirmed. However, it was not found sufficiently robust on pixel level to be implemented for monitoring vegetation water stress on a per-pixel basis...... provide good sensitivity to canopy water content, which can make vegetation stress detection possible. Furthermore, the high frequency observations in the optical spectrum now available from geostationary instruments have the potential for detection of changes in vegetation related surface properties...... on short timescales, which are challenging from polar orbiting instruments. Geostationary NDVI and the NIR and SWIR based Shortwave Infrared Water Stress Index (SIWSI) indices are compared with extensive field data from the Dahra site, supplemented by data from the Agoufou and Demokeya sites. The indices...

AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

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P. Kupidura

2016-06-01

Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

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Yunjun Yao

2014-01-01

Full Text Available Satellite-based vegetation indices (VIs and Apparent Thermal Inertia (ATI derived from temperature change provide valuable information for estimating evapotranspiration (LE and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. The validation results illustrate that the daily LE can be estimated with the Root Mean Square Error (RMSE varying from 10.7 W/m2 to 87.6 W/m2, and with the square of correlation coefficient (R2 from 0.41 to 0.89 (p < 0.01. Compared with the Priestley-Taylor-based LE (PT-JPL algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02. The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.

Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

Science.gov (United States)

Kandylakis, Z.; Karantzalos, K.

2016-06-01

In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

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)

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

Science.gov (United States)

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

2006-08-01

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

Use of UAVs for Remote Measurement of Vegetation Canopy Variables

Science.gov (United States)

Rango, A.; Laliberte, A.; Herrick, J.; Steele, C.; Bestelmeyer, B.; Chopping, M. J.

2006-12-01

Remote sensing with different sensors has proven useful for measuring vegetation canopy variables at scales ranging from landscapes down to individual plants. For use at landscape scales, such as desert grasslands invaded by shrubs, it is possible to use multi-angle imagery from satellite sensors, such as MISR and CHRIS/Proba, with geometric optical models to retrieve fractional woody plant cover. Vegetation community states can be mapped using visible and near infrared ASTER imagery at 15 m resolution. At finer scales, QuickBird satellite imagery with approximately 60 cm resolution and piloted aircraft photography with 25-80 cm resolution can be used to measure shrubs above a critical size. Tests conducted with the QuickBird data in the Jornada basin of southern New Mexico have shown that 87% of all shrubs greater than 2 m2 were detected whereas only about 29% of all shrubs less than 2 m2 were detected, even at these high resolutions. Because there is an observational gap between satellite/aircraft measurements and ground observations, we have experimented with Unmanned Aerial Vehicles (UAVs) producing digital photography with approximately 5 cm resolution. We were able to detect all shrubs greater than 2 m2, and we were able to map small subshrubs indicative of rangeland deterioration, as well as remnant grass patches, for the first time. None of these could be identified on the 60 cm resolution data. Additionally, we were able to measure canopy gaps, shrub patterns, percent bare soil, and vegetation cover over mixed rangeland vegetation. This approach is directly applicable to rangeland health monitoring, and it provides a quantitative way to assess shrub invasion over time and to detect the depletion or recovery of grass patches. Further, if the UAV images have sufficient overlap, it may be possible to exploit the stereo viewing capabilities to develop a digital elevation model from the orthophotos, with a potential for extracting canopy height. We envision two

Health Risks of Heavy Metals for Population via Consumption of Greenhouse Vegetables in Hamadan, Iran

Directory of Open Access Journals (Sweden)

Mojgan Sohrabi

2015-10-01

Full Text Available Background & Aims of the Study: The last 25 years have seen a remarkable increase in public concern about food contamination. Food and water are the main sources of our essential metals.These are also the media through which we are exposed to various toxic metalsAs such, this study aimed to assess the risks arising from the use of greenhouse vegetables, cucumbers, tomatoes and peppers in Hamadan Province. Materials & Methods: Soil and plant samples were digested using wet digestion method (HClO4/HNO3, 2:1 ratio solution, and the concentrations of total As, Cd, Cu, Pb, and Zn were determined using Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AE. Results: High concentrations of elements As, Cd, Cu, Pb, and Zn were found in vegetables sampled from overused phosphate fertilized soils, which increased the daily intake of metals in food. The Health risk assessment values of all tested vegetables (pepper, cucumber and tomato were below 1 in As and Cd. The health risk index (HRI value above 1 indicated a relative health risk through the ingestion of contaminated vegetables. Conclusions: Heavy metal concentrations should be periodically monitored in vegetables grown in contaminated soils. This study found that long-term fertilizer use led to a growing accumulation of heavy metals (HMs in soils. It would also be beneficial to implement effective remediation technologies to minimize possible impacts on human health.

Health risks of heavy metals for Population via Consumption of greenhouse vegetables in Hamadan, Iran

Directory of Open Access Journals (Sweden)

Mojgan Sohrabi

2015-10-01

Full Text Available Background & Aims of the Study: The last 25 years have seen a remarkable increase in public concern about food contamination. Food and water are the main sources of our essential metals.These are also the media through which we are exposed to various toxic metalsAs such, this study aimed to assess the risks arising from the use of greenhouse vegetables, cucumbers, tomatoes and peppers in Hamadan Province. Materials & Methods: Soil and plant samples were digested using wet digestion method (HClO 4 /HNO 3 , 2:1 ratio solution, and the concentrations of total As, Cd, Cu, Pb, and Zn were determined using Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AE. Results: High concentrations of elements As, Cd, Cu, Pb, and Zn were found in vegetables sampled from overused phosphate fertilized soils, which increased the daily intake of metals in food. The Health risk assessment values of all tested vegetables (pepper, cucumber and tomato were below 1 in As and Cd. The health risk index (HRI value above 1 indicated a relative health risk through the ingestion of contaminated vegetables. Conclusions: Heavy metal concentrations should be periodically monitored in vegetables grown in contaminated soils. This study found that long-term fertilizer use led to a growing accumulation of heavy metals (HMs in soils. It would also be beneficial to implement effective remediation technologies to minimize possible impacts on human health. 

Consumption of fruits and vegetables and health status of Mexican children from the National Health and Nutrition Survey 2012.

Science.gov (United States)

Jiménez-Aguilar, Alejandra; Gaona-Pineda, Elsa Berenice; Mejía-Rodríguez, Fabiola; Gómez-Acosta, Luz María; Méndez-Gómez Humarán, Ignacio; Flores-Aldana, Mario

2014-01-01

To characterize the current consumption of fruits and vegetables based on the international recommendations, as well as its relationship to certain variables of interest in Mexican children aged 6 to 12 years. Adherence to the international recommendations for the consumption of fruits and vegetables was estimated based on data from the 2012 National Health and Nutrition Survey (Ensanut 2012). Logistic regression models were developed. Only 34.4% of children met the recommendations. Their age (years) (OR:074; p< 0.01) and the fact that they lived in the Central (OR:2.48; p< 0.01) or Southern (OR:2.66; p< 0.01) regions of Mexico or in Mexico City (OR:2.37; p< 0.01) versus the Northern region were significantly associated with adherence. An interaction was observed between the educational level of the head of the family and his or her kinship with the child. Only 3 out of every 10 Mexican children meet the recommendations; therefore, the implementation of a public policy with the appropriate legislation, financing and regulation is required.

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Science.gov (United States)

Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.;

[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.

Estimation of absorbed photosynthetically active radiation and vegetation net production efficiency using satellite data

International Nuclear Information System (INIS)

Hanan, N.P.; Prince, S.D.; Begue, A.

1995-01-01

The amount of photosynthetically active radiation (PAR) absorbed by green vegetation is an important determinant of photosynthesis and growth. Methods for the estimation of fractional absorption of PAR (iff PAR ) for areas greater than 1 km 2 using satellite data are discussed, and are applied to sites in the Sahel that have a sparse herb layer and tree cover of less than 5%. Using harvest measurements of seasonal net production, net production efficiencies are calculated. Variation in estimates of seasonal PAR absorption (APAR) caused by the atmospheric correction method and relationship between surface reflectances and iff PAR is considered. The use of maximum value composites of satellite NDVI to reduce the effect of the atmosphere is shown to produce inaccurate APAR estimates. In this data set, however, atmospheric correction using average optical depths was found to give good approximations of the fully corrected data. A simulation of canopy radiative transfer using the SAIL model was used to derive a relationship between canopy NDVI and iff PAR . Seasonal APAR estimates assuming a 1:1 relationship between iff PAR and NDVI overestimated the SAIL modeled results by up to 260%. The use of a modified 1:1 relationship, where iff PAR was assumed to be linearly related to NDVI scaled between minimum (soil) and maximum (infinite canopy) values, underestimated the SAIL modeled results by up to 35%. Estimated net production efficiencies (ϵ n , dry matter per unit APAR) fell in the range 0.12–1.61 g MJ −1 for above ground production, and in the range 0.16–1.88 g MJ −1 for total production. Sites with lower rainfall had reduced efficiencies, probably caused by physiological constraints on photosynthesis during dry conditions. (author)

Multi-spectral band selection for satellite-based systems

International Nuclear Information System (INIS)

Clodius, W.B.; Weber, P.G.; Borel, C.C.; Smith, B.W.

1998-01-01

The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed

Satellite-Based Evaluation of the Post-Fire Recovery Process from the Worst Forest Fire Case in South Korea

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Jae-Hyun Ryu

2018-06-01

Full Text Available The worst forest fire in South Korea occurred in April 2000 on the eastern coast. Forest recovery works were conducted until 2005, and the forest has been monitored since the fire. Remote sensing techniques have been used to detect the burned areas and to evaluate the recovery-time point of the post-fire processes during the past 18 years. We used three indices, Normalized Burn Ratio (NBR, Normalized Difference Vegetation Index (NDVI, and Gross Primary Production (GPP, to temporally monitor a burned area in terms of its moisture condition, vegetation biomass, and photosynthetic activity, respectively. The change of those three indices by forest recovery processes was relatively analyzed using an unburned reference area. The selected unburned area had similar characteristics to the burned area prior to the forest fire. The temporal patterns of NBR and NDVI, not only showed the forest recovery process as a result of forest management, but also statistically distinguished the recovery periods at the regions of low, moderate, and high fire severity. The NBR2.1 for all areas, calculated using 2.1 μm wavelengths, reached the unburned state in 2008. The NDVI for areas with low and moderate fire severity levels became significantly equal to the unburned state in 2009 (p > 0.05, but areas with high severity levels did not reach the unburned state until 2017. This indicated that the surface and vegetation moisture conditions recovered to the unburned state about 8 years after the fire event, while vegetation biomass and health required a longer time to recover, particularly for high severity regions. In the case of GPP, it rapidly recovered after about 3 years. Then, the steady increase in GPP surpassed the GPP of the reference area in 2015 because of the rapid growth and high photosynthetic activity of young forests. Therefore, the concluding scientific message is that, because the recovery-time point for each component of the forest ecosystem is

The Experiences of New Zealand-Based Children in Consuming Fruits and Vegetables

Science.gov (United States)

Dresler, Emma; Whitehead, Dean; Mather, Aimee

2017-01-01

Purpose: It is known that the consumption of fruits and vegetables in children is declining despite wide-spread national and international policy attempts to increase consumption. The purpose of this paper is to investigate the experiences of children's consumption of fruits and vegetables so as to facilitate better health education targeting.…

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.

The pro children intervention: applying the intervention mapping protocol to develop a school-based fruit and vegetable promotion programme.

Science.gov (United States)

Pérez-Rodrigo, Carmen; Wind, Marianne; Hildonen, Christina; Bjelland, Mona; Aranceta, Javier; Klepp, Knut-Inge; Brug, Johannes

2005-01-01

The importance of careful theory-based intervention planning is recognized for fruit and vegetable promotion. This paper describes the application of the Intervention Mapping (IM) protocol to develop the Pro Children intervention to promote consumption of fruit and vegetable among 10- to 13-year-old schoolchildren. Based on a needs assessment, promotion of intake of fruit and vegetable was split into performance objectives and related personal, social and environmental determinants. Crossing the performance objectives with related important and changeable determinants resulted in a matrix of learning and change objectives for which appropriate educational strategies were identified. Theoretically similar but culturally relevant interventions were designed, implemented and evaluated in Norway, the Netherlands and Spain during 2 school years. Programme activities included provision of fruits and vegetables in the schools, guided classroom activities, computer-tailored feedback and advice for children, and activities to be completed at home with the family. Additionally, optional intervention components for community reinforcement included incorporation of mass media, school health services or grocery stores. School project committees were supported. The Pro Children intervention was carefully developed based on the IM protocol that resulted in a comprehensive school-based fruit and vegetable promotion programme, but culturally sensible and locally relevant. (c) 2005 S. Karger AG, Basel

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Vegetation Health and Drought Products (VHDP) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The VIIRS Vegetation Health and Drought Products (VHDP) from NDE algorithm provides weekly estimates of the Vegetation Condition Index (VCI), Temperature Condition...

A dataset mapping the potential biophysical effects of vegetation cover change

Science.gov (United States)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

Recent Vegetation Fire Incidence in Russia

OpenAIRE

Hayasaka, Hiroshi

2011-01-01

MODIS hotspot data from NASA have now become a standard means of evaluating vegetation fires worldwide. Remote sensing is the most effective tool for large countries like Russia because it is hard to obtain exact, detailed forest fire data. Accumulated MODIS hotspot data of the nine years from 2002 to 2010 may allow us to assess recent changes in the vegetation fire incidence in Russia. This kind of analysis using various satellites is useful in estimating fire intensity and sever...

Merging Satellite Precipitation Products for Improved Streamflow Simulations

Science.gov (United States)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

Satellite based wind resource assessment over the South China Sea

DEFF Research Database (Denmark)

Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay

2014-01-01

variations are clearly visible across the domain; for instance sheltering effects caused by the land masses. The satellite based wind resource maps have two shortcomings. One is the lack of information at the higher vertical levels where wind turbines operate. The other is the limited number of overlapping...... years of WRF data – specifically the parameters heat flux, air temperature, and friction velocity – are used to calculate a long-term correction for atmospheric stability effects. The stability correction is applied to the satellite based wind resource maps together with a vertical wind profile...... from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In this presentation, satellite wind maps are used in combination with mast observations and numerical...

Rural interdisciplinary mental health team building via satellite: a demonstration project.

Science.gov (United States)

Cornish, Peter A; Church, Elizabeth; Callanan, Terrence; Bethune, Cheri; Robbins, Carl; Miller, Robert

2003-01-01

This paper reports on the results of a demonstration project that examined the role of telehealth/telemedicine (hereafter referred to as telehealth) in providing interdisciplinary mental health training and support to health professionals in a rural region of Atlantic Canada. Special emphasis was placed on addressing the question of how training might affect interdisciplinary collaboration among the rural health professionals. Five urban mental health professionals from three disciplines provided training and support via video-satellite and internet, print and video resources to 34 rural health and community professionals. In order to assess the rural community's needs and the impact of the interventions, questionnaires were administered and on-site interviews were conducted before and after the project. Throughout the project, field notes were recorded and satisfaction ratings were obtained. Satisfaction with the video-satellite presentations was high and stable, with the exception of one session when signal quality was very poor. Rural participants were most satisfied with opportunities for interaction and least satisfied with the variable quality of the video transmission signal. High staff turnover among rural professionals resulted in insufficient power to permit statistical analysis. Positive reports of the project impact included expanded knowledge and heightened sensitivity to mental health issues, increased cross-disciplinary connections, and greater cohesion among professionals. The results suggest that, with some refinements, telehealth technology can be used to facilitate mental health training and promote interdisciplinary collaboration among professionals in a rural setting.

Vegetation cover and their functioning in dependence on the reclamation of the Velka podkrusnohorska dump during last 20 years using satellite data analysis

International Nuclear Information System (INIS)

Prochazka, J.; Nedbal, V.; Pecharova, E.; Brom, J.

2010-01-01

Vegetation plays a significant role in mass retention, solar energy dissipation, water cycle forming and local climate changes on reclamation plots of mining areas. This paper discussed the use of Landsat satellite data in order to evaluate different types of reclamation and their development for the last 20 years in the case of the Velka podkrusnohorska dump. Biophysical parameters which can be indicators of solar energy dissipation that were utilized to analyse changes of temporal development from 1991 to 2009 included land surface temperature, surface moisture expressed as wetness index tasseled cap, and normalized difference vegetation index. From these parameters, a functional index was then developed. The paper discussed the development of these parameters and their relationship to solar energy dissipation. It was concluded that since 1995, the observed parameters significantly changed, gradually converging to the state of the surrounding landscape. 16 refs., 2 tabs., 2 figs.

Vegetation cover and their functioning in dependence on the reclamation of the Velka podkrusnohorska dump during last 20 years using satellite data analysis

Energy Technology Data Exchange (ETDEWEB)

Prochazka, J.; Nedbal, V.; Pecharova, E. [South Bohemia Univ., Ceske Budejovice (Czech Republic); Brom, J. [Enki o.p.s., Trebon (Czech Republic)

2010-07-01

Vegetation plays a significant role in mass retention, solar energy dissipation, water cycle forming and local climate changes on reclamation plots of mining areas. This paper discussed the use of Landsat satellite data in order to evaluate different types of reclamation and their development for the last 20 years in the case of the Velka podkrusnohorska dump. Biophysical parameters which can be indicators of solar energy dissipation that were utilized to analyse changes of temporal development from 1991 to 2009 included land surface temperature, surface moisture expressed as wetness index tasseled cap, and normalized difference vegetation index. From these parameters, a functional index was then developed. The paper discussed the development of these parameters and their relationship to solar energy dissipation. It was concluded that since 1995, the observed parameters significantly changed, gradually converging to the state of the surrounding landscape. 16 refs., 2 tabs., 2 figs.

Crop classification based on multi-temporal satellite remote sensing data for agro-advisory services

Science.gov (United States)

Karale, Yogita; Mohite, Jayant; Jagyasi, Bhushan

2014-11-01

In this paper, we envision the use of satellite images coupled with GIS to obtain location specific crop type information in order to disseminate crop specific advises to the farmers. In our ongoing mKRISHI R project, the accurate information about the field level crop type and acreage will help in the agro-advisory services and supply chain planning and management. The key contribution of this paper is the field level crop classification using multi temporal images of Landsat-8 acquired during November 2013 to April 2014. The study area chosen is Vani, Maharashtra, India, from where the field level ground truth information for various crops such as grape, wheat, onion, soybean, tomato, along with fodder and fallow fields has been collected using the mobile application. The ground truth information includes crop type, crop stage and GPS location for 104 farms in the study area with approximate area of 42 hectares. The seven multi-temporal images of the Landsat-8 were used to compute the vegetation indices namely: Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR) and Difference Vegetation Index (DVI) for the study area. The vegetation indices values of the pixels within a field were then averaged to obtain the field level vegetation indices. For each crop, binary classification has been carried out using the feed forward neural network operating on the field level vegetation indices. The classification accuracy for the individual crop was in the range of 74.5% to 97.5% and the overall classification accuracy was found to be 88.49%.

Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing.

Science.gov (United States)

Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve

2018-04-09

Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

Satellites

International Nuclear Information System (INIS)

Burns, J.A.; Matthews, M.S.

1986-01-01

The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from MODIS Satellite Data and Ecosystem Modeling

Science.gov (United States)

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Pr...

Assessing the population coverage of a health demographic surveillance system using satellite imagery and crowd-sourcing.

Directory of Open Access Journals (Sweden)

Aurelio Di Pasquale

Full Text Available Remotely sensed data can serve as an independent source of information about the location of residential structures in areas under demographic and health surveillance. We report on results obtained combining satellite imagery, imported from Bing, with location data routinely collected using the built-in GPS sensors of tablet computers, to assess completeness of population coverage in a Health and Demographic Surveillance System in Malawi. The Majete Malaria Project Health and Demographic Surveillance System, in Malawi, started in 2014 to support a project with the aim of studying the reduction of malaria using an integrated control approach by rolling out insecticide treated nets and improved case management supplemented with house improvement and larval source management. In order to support the monitoring of the trial a Health and Demographic Surveillance System was established in the area that surrounds the Majete Wildlife Reserve (1600 km2, using the OpenHDS data system. We compared house locations obtained using GPS recordings on mobile devices during the demographic surveillance census round with those acquired from satellite imagery. Volunteers were recruited through the crowdcrafting.org platform to identify building structures on the images, which enabled the compilation of a database with coordinates of potential residences. For every building identified on these satellite images by the volunteers (11,046 buildings identified of which 3424 (ca. 30% were part of the censused area, we calculated the distance to the nearest house enumerated on the ground by fieldworkers during the census round of the HDSS. A random sample of buildings (85 structures identified on satellite images without a nearby location enrolled in the census were visited by a fieldworker to determine how many were missed during the baseline census survey, if any were missed. The findings from this ground-truthing effort suggest that a high population coverage was

Metal poisoning and human health hazards due to contaminated salad vegetables

International Nuclear Information System (INIS)

Husaini, S.N.; Matiullah, J.; Akram, M.; Naeem, K.

2011-01-01

The consumption of salad vegetables grown in industrial areas may create adverse affects on human health by causing serious diseases and impairment of the vital organs of human body. To determine the concentrations of toxic metals such as, As, Co, Cr, Cu, Mn, Sb and Se in salad vegetables namely tomato, cabbage, turnip, radish, carrot, onion, salad leaves, beet and cucumber, the samples were collected within the vicinity of industrial areas of Faisalabad and Gujranwala regions. After processing, the samples were analyzed using neutron activation analysis (NAA) technique. The highest concentrations were observed for arsenic (2.3 ± 0.02 μg/g) in radish, manganese (16 ± 1.3 μg/g) in salad leaves, selenium (0.2 ± 0.02 μg/g) in cabbage and antimony (0.08 ± 0.001 μg/g) in salad leaves respectively which were also higher than those recommended by the National Environmental Quality Control (NEQC) standards and World Health Organization (WHO). Moreover, the amounts of injurious arsenic (2.3 μg/g) and selenium (0.4 μg/g) in all salad vegetables according to standard values of NEQS are two to four times higher (1.0 and 0.1 μg/g), respectively. (author)

[Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

Science.gov (United States)

Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

2012-12-01

This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

Vegetation of the Hantam-Tanqua-Roggeveld subregion, South Africa Part 2: Succulent Karoo Biome related vegetation

Directory of Open Access Journals (Sweden)

Helga van der Merwe

2009-03-01

Full Text Available The Hantam-Tanqua-Roggeveld subregion lies within the Succulent Karoo Hotspot that stretches along the western side of the Republic of South Africa and Namibia. This project, carried out to document the botanical diversity in the Hantam-Tanqua-Roggeveld subregion, was part of a project identified as a priority during the SKEP (Succulent Karoo Ecosystem Programme initiative in this Hotspot. Botanical surveys were conducted in an area covering over three million hectares. Satellite images of the area and topocadastral, land type and geology maps were used to stratify the area into relatively homogeneous units. An analysis of the floristic data of 390 sample plots identified two major floristic units, i.e. the Fynbos Biome related vegetation and the Succulent Karoo Biome related vegetation. A description of the vegetation related to the Succulent Karoo Biome is presented in this article. Seven associations, 16 subassociations and several mosaic vegetation units, consisting of more than one vegetation unit, were identified and mapped. Various threats to the vegetation in the region were identified during the survey and are briefly discussed.

Building a satellite climate diagnostics data base for real-time climate monitoring

International Nuclear Information System (INIS)

Ropelewski, C.F.

1991-01-01

The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

Understanding the relationship between vegetation phenology and productivity across key dryland ecosystem types through the integration of PhenoCam, satellite, and eddy covariance data

Science.gov (United States)

Yan, D.; Scott, R. L.; Moore, D. J.; Biederman, J. A.; Smith, W. K.

2017-12-01

Land surface phenology (LSP) - defined as remotely sensed seasonal variations in vegetation greenness - is intrinsically linked to seasonal carbon uptake, and is thus commonly used as a proxy for vegetation productivity (gross primary productivity; GPP). Yet, the relationship between LSP and GPP remains uncertain, particularly for understudied dryland ecosystems characterized by relatively large spatial and temporal variability. Here, we explored the relationship between LSP and the phenology of GPP for three dominant dryland ecosystem types, and we evaluated how these relationships change as a function of spatial and temporal scale. We focused on three long-term dryland eddy covariance flux tower sites: Walnut Gulch Lucky Hills Shrubland (WHS), Walnut Gulch Kendall Grassland (WKG), and Santa Rita Mesquite (SRM). We analyzed daily canopy-level, 16-day 30m, and 8-day 500m time series of greenness indices from PhenoCam, Landsat 7 ETM+/Landsat 8 OLI, and MODIS, respectively. We first quantified the impact of spatial scale by temporally resampling canopy-level PhenoCam, 30m Landsat, and 500m MODIS to 16-day intervals and then comparing against flux tower GPP estimates. We next quantified the impact of temporal scale by spatially resampling daily PhenoCam, 16-day Landsat, and 8-day MODIS to 500m time series and then comparing against flux tower GPP estimates. We find evidence of critical periods of decoupling between LSP and the phenology of GPP that vary according to the spatial and temporal scale, and as a function of ecosystem type. Our results provide key insight into dryland LSP and GPP dynamics that can be used in future efforts to improve ecosystem process models and satellite-based vegetation productivity algorithms.

A near real-time satellite-based global drought climate data record

International Nuclear Information System (INIS)

AghaKouchak, Amir; Nakhjiri, Navid

2012-01-01

Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

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.

Satellite Image-based Estimates of Snow Water Equivalence in Restored Ponderosa Pine Forests in Northern Arizona

Science.gov (United States)

Sankey, T.; Springer, A. E.; O'Donnell, F. C.; Donald, J.; McVay, J.; Masek Lopez, S.

2014-12-01

The U.S. Forest Service plans to conduct forest restoration treatments through the Four Forest Restoration Initiative (4FRI) on hundreds of thousands of acres of ponderosa pine forest in northern Arizona over the next 20 years with the goals of reducing wildfire hazard and improving forest health. The 4FRI's key objective is to thin and burn the forests to create within-stand openings that "promote snowpack accumulation and retention which benefit groundwater recharge and watershed processes at the fine (1 to 10 acres) scale". However, little is known about how these openings created by restoration treatments affect snow water equivalence (SWE) and soil moisture, which are key parts of the water balance that greatly influence water availability for healthy trees and for downstream water users in the Sonoran Desert. We have examined forest canopy cover by calculating a Normalized Difference Vegetation Index (NDVI), a key indicator of green vegetation cover, using Landsat satellite data. We have then compared NDVI between treatments at our study sites in northern Arizona and have found statistically significant differences in tree canopy cover between treatments. The control units have significantly greater forest canopy cover than the treated units. The thinned units also have significantly greater tree canopy cover than the thin-and-burn units. Winter season Landsat images have also been analyzed to calculate Normalized Difference Snow Index (NDSI), a key indicator of snow water equivalence and snow accumulation at the treated and untreated forests. The NDSI values from these dates are examined to determine if snow accumulation and snow water equivalence vary between treatments at our study sites. NDSI is significantly greater at the treated units than the control units. In particular, the thinned forest units have significantly greater snow cover than the control units. Our results indicate that forest restoration treatments result in increased snow pack

Testing of Vegetable-Based dutting Fluid by Hole Making Operation

DEFF Research Database (Denmark)

Belluco, Walter; De Chiffre, Leonardo

2000-01-01

in connection with the development of vegetable based cutting oils. Results show that drilling and tapping qualify as operations in which cutting forces can be resolved within one test when they differ by less than 1 percent by taking 6 repetitions, and measurements could be repeated with relative standard...... development and testing of vegetable based oils of equal or better performance than a reference commercial mineral oil....

Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

Science.gov (United States)

Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

2016-08-01

Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

Understanding the Seasonal Greenness Trends and Controls in South Asia Using Satellite Based Observations

Science.gov (United States)

Sarmah, S.; Jia, G.; Zhang, A.; Singha, M.

2017-12-01

South Asia (SA) is one of the most remarkable regions in changing vegetation greenness along with its major expansion of agricultural activity, especially irrigated farming. However, SA is predicted to be a vulnerable agricultural regions to future climate changes. The influence of monsoon climate on the seasonal trends and anomalies of vegetation greenness are not well understood in the region which can provide valuable information about climate-ecosystem interaction. This study analyzed the spatio-temporal patterns of seasonal vegetation trends and variability using satellite vegetation indices (VI) including AVHRR Normalized Difference Vegetation Index (NDVI) (1982-2013) and MODIS Enhanced Vegetation Index (EVI) (2000-2013) in summer monsoon (SM) (June-Sept) and winter monsoon (WM) (Dec-Apr) seasons among irrigated cropland (IC), rainfed cropland (RC) and natural vegetation (NV). Seasonal VI variations with climatic factors (precipitation and temperature) and LULC changes have been investigated to identify the forcings behind the vegetation trends and variability. We found that major greening occurred in the last three decades due to the increase in IC productivity noticeably in WM, however, recent (2000-2013) greening trends were lower than the previous decades (1982-1999) in both the IC and RC indicating the stresses on them. The browning trends, mainly concentrated in NV areas were prominent during WM and rigorous since 2000, confirmed from the moderate resolution EVI and LULC datasets. Winter time maximal temperature had been increasing tremendously whereas precipitation trend was not significant over SA. Both the climate variability and LULC changes had integrated effects on the vegetation changes in NV areas specifically in hilly regions. However, LULC impact was intensified since 2000, mostly in north east India. This study also revealed a distinct seasonal variation in spatial distribution of correlation between VI's and climate anomalies over SA

Environmental assessment for the satellite power system concept development and evaluation program: nonmicrowave health and ecological effects

Energy Technology Data Exchange (ETDEWEB)

White, M R

1980-11-01

A Concept Development and Evaluation Program is being carried out for a proposed Satellite Power System (SPS). For purposes of this evaluation, a preliminary reference system has been developed. SPS, as described in the reference system, would collect solar energy on satellites in geosychronous orbit in space. The energy would be converted to microwaves and beamed to an earth-receiving antenna (rectenna). One task in the environmental part of the program is the assessment of the nonmicrowave effects on health and the environment. These effects would result from all phases of SPS development and operation. This report covers the current knowledge regarding these effects, and is based on the reference system. The assessment is summarized as to scope, methodology, impacts of terrestrial development, launch and recovery of spacecraft, space activities (including health effects of the space environment, ionizing radiation, electromagnetic exposure, spacecraft charging and environmental interactions, occupational hazards, etc.) and construction and operation of rectenna (ground receiving station).

Environmental assessment for the satellite power system concept development and evaluation program: nonmicrowave health and ecological effects

International Nuclear Information System (INIS)

White, M.R.

1980-11-01

A Concept Development and Evaluation Program is being carried out for a proposed Satellite Power System (SPS). For purposes of this evaluation, a preliminary reference system has been developed. SPS, as described in the reference system, would collect solar energy on satellites in geosychronous orbit in space. The energy would be converted to microwaves and beamed to an earth-receiving antenna (rectenna). One task in the environmental part of the program is the assessment of the nonmicrowave effects on health and the environment. These effects would result from all phases of SPS development and operation. This report covers the current knowledge regarding these effects, and is based on the reference system. The assessment is summarized as to scope, methodology, impacts of terrestrial development, launch and recovery of spacecraft, space activities (including health effects of the space environment, ionizing radiation, electromagnetic exposure, spacecraft charging and environmental interactions, occupational hazards, etc.) and construction and operation of rectenna

Satellite stories: capturing professional experiences of academic health sciences librarians working in delocalized health sciences programs

Directory of Open Access Journals (Sweden)

Jackie Phinney

2018-01-01

Conclusions: The results from this survey suggest that the role of the academic health sciences librarian at the satellite campus needs to be clearly communicated and defined. This, in turn, will enhance the experience for the librarian and provide better service to the client.

Research on orbit prediction for solar-based calibration proper satellite

Science.gov (United States)

Chen, Xuan; Qi, Wenwen; Xu, Peng

2018-03-01

Utilizing the mathematical model of the orbit mechanics, the orbit prediction is to forecast the space target's orbit information of a certain time based on the orbit of the initial moment. The proper satellite radiometric calibration and calibration orbit prediction process are introduced briefly. On the basis of the research of the calibration space position design method and the radiative transfer model, an orbit prediction method for proper satellite radiometric calibration is proposed to select the appropriate calibration arc for the remote sensor and to predict the orbit information of the proper satellite and the remote sensor. By analyzing the orbit constraint of the proper satellite calibration, the GF-1solar synchronous orbit is chose as the proper satellite orbit in order to simulate the calibration visible durance for different satellites to be calibrated. The results of simulation and analysis provide the basis for the improvement of the radiometric calibration accuracy of the satellite remote sensor, which lays the foundation for the high precision and high frequency radiometric calibration.

Midlife women, bone health, vegetables, herbs and fruit study. The Scarborough Fair study protocol

Directory of Open Access Journals (Sweden)

Gunn Caroline A

2013-01-01

Full Text Available Abstract Background Bone loss is accelerated in middle aged women but increased fruit/vegetable intake positively affects bone health by provision of micronutrients essential for bone formation, buffer precursors which reduce acid load and phytochemicals affecting inflammation and oxidative stress. Animal studies demonstrated bone resorption inhibiting properties of specific vegetables, fruit and herbs a decade ago. Objective: To increase fruit/vegetable intake in post menopausal women to 9 servings/day using a food specific approach to significantly reduce dietary acid load and include specific vegetables, fruit and herbs with bone resorbing inhibiting properties to assess effect on bone turnover, metabolic and inflammatory markers. Methods/Design The Scarborough Fair Study is a randomised active comparator controlled multi centre trial. It aimed to increase fruit and vegetable intake in 100 post menopausal women from ≤ 5 servings/day to ≥ 9 servings/day for 3 months. The women in the dietary intervention were randomly assigned to one of the two arms of the study. Both groups consumed ≥ 9 servings/day of fruit/vegetables and selected herbs but the diet of each group emphasised different fruit/vegetables/herbs with one group (B selecting from a range of vegetables, fruit and culinary herbs with bone resorbing inhibiting properties. 50 women formed a negative control group (Group C usual diet. Primary outcome variables were plasma bone markers assessed at baseline, 6 weeks and 12 weeks. Secondary outcome variables were plasma inflammation and metabolic markers and urinary electrolytes (calcium, magnesium, potassium and sodium assessed at baseline and 12 weeks. Dietary intake and urine pH change also were outcome variables. The dietary change was calculated with 3 day diet diaries and a 24 hour recall. Intervention participants kept a twice weekly record of fruit, vegetable and herb intake and urine pH. Discussion This study will provide

Phthalate esters contamination in soils and vegetables of plastic film greenhouses of suburb Nanjing, China and the potential human health risk.

Science.gov (United States)

Ma, Ting Ting; Wu, Long Hua; Chen, Like; Zhang, Hai Bo; Teng, Ying; Luo, Yong Ming

2015-08-01

The contamination of phthalate esters (PAEs) has become a potential threat to the environment and human health because they could be easily released as plasticizers from the daily supply products, especially in polyethylene films. Concentration levels of total six PAEs, nominated as priority pollutants by the US Environmental Protection Agency (USEPA), were investigated in soils and vegetables from four greenhouse areas in suburbs of Nanjing, East China. Total PAEs concentration ranged from 930 ± 840 to 2,450 ± 710 μg kg(-1) (dry weight (DW)) in soil and from 790 ± 630 to 3,010 ± 2,130 μg kg(-1) in vegetables. Higher concentrations of PAEs were found in soils except in Suo Shi (SS) area and in vegetables, especially in potherb mustard and purple tsai-tai samples. Risk assessment mainly based on the exposures of soil ingestion and daily vegetable intake indicated that bis(2-ethylhexyl) phthalate (DEHP) in the samples from Gu Li (GL) and Hu Shu (HS) exhibited the highest hazard to children less than 6-year old. Therefore, the human health risk of the PAEs contamination in soils and vegetables should greatly be of a concern, especially for their environmental estrogen analog effects.

Association of knowledge, preventive counseling and personal health behaviors on physical activity and consumption of fruits or vegetables in community health workers.

Science.gov (United States)

Florindo, Alex A; Brownson, Ross C; Mielke, Gregore I; Gomes, Grace Ao; Parra, Diana C; Siqueira, Fernando V; Lobelo, Felipe; Simoes, Eduardo J; Ramos, Luiz R; Bracco, Mário M; Hallal, Pedro C

2015-04-09

There is evidence that if a health professional is active and has a healthy diet, he/she is more likely to advise patients about the benefits of physical activity and healthy eating The aims of this study were to: (1) describe the personal physical activity, consumption of fruits and vegetables behaviors and nutritional status of community health workers; (2) evaluate the association between knowledge, delivery of preventive counseling and personal behaviors among community health workers. This was a cross-sectional study conducted in a nationally sample of health professionals working in primary health care settings in Brazil in 2011. This survey was part of the second phase of the Guide for Useful Interventions for Activity in Brazil and Latin America project, and data were collected through telephone interviews of 269 community health workers from the Unified Health Care system of Brazil. We applied questionnaires about personal reported behaviors, knowledge and preventive counseling in physical activity and consumption of fruits and vegetables. We calculated the prevalence and associations between the variables with logistic regression. The proportion of community health workers that practiced 150 minutes per week of physical activity in leisure time or transportation was high (64.9%). Half of community health workers were overweight and only 26.2% reported consuming five portions/day of fruits or vegetables. Most community health workers reported counseling about physical activity for more than six months (59.7%), and most were not knowledgeable of the fruits and vegetables and physical activity recommendations. Meeting the fruits and vegetables recommendations was associated with correct knowledge (OR = 4.5; CI95% 1.03;19.7), with reporting 150 minutes or more of physical activity per week (OR = 2.0; CI95% 1.03;3.7) and with reporting physical activity in leisure time (OR = 2.0; CI95% 1.05;3.6). Regular physical activity counseling was associated

Monitoring Seasonal Evapotranspiration in Vulnerable Agriculture using Time Series VHSR Satellite Data

Science.gov (United States)

Dalezios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2015-04-01

The research work stems from the hypothesis that it is possible to perform an estimation of seasonal water needs of olive tree farms under drought periods by cross correlating high spatial, spectral and temporal resolution (~monthly) of satellite data, acquired at well defined time intervals of the phenological cycle of crops, with ground-truth information simultaneously applied during the image acquisitions. The present research is for the first time, demonstrating the coordinated efforts of space engineers, satellite mission control planners, remote sensing scientists and ground teams to record at specific time intervals of the phenological cycle of trees from ground "zero" and from 770 km above the Earth's surface, the status of plants for subsequent cross correlation and analysis regarding the estimation of the seasonal evapotranspiration in vulnerable agricultural environment. The ETo and ETc derived by Penman-Montieth equation and reference Kc tables, compared with new ETd using the Kc extracted from the time series satellite data. Several vegetation indices were also used especially the RedEdge and the chlorophyll one based on WorldView-2 RedEdge and second NIR bands to relate the tree status with water and nutrition needs. Keywords: Evapotransipration, Very High Spatial Resolution - VHSR, time series, remote sensing, vulnerability, agriculture, vegetation indeces.

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

Science.gov (United States)

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

2018-02-01

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

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

Science.gov (United States)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and

Effect of vegetation on soil moisture sensing observed from orbiting microwave radiometers

International Nuclear Information System (INIS)

Wang, J.R.

1985-01-01

The microwave radiometric measurements made by the Skylab 1.4 GHz radiometer and by the 6.6 GHz and 10.7 GHz channels of the Nimbus-7 Scanning Multichannel Microwave Radiometer were analyzed to study the large-area soil moisture variations of land surfaces. Two regions in Texas, one with sparse and the other with dense vegetation covers, were selected for the study. The results gave a confirmation of the vegetation effect observed by ground-level microwave radiometers. Based on the statistics of the satellite data, it was possible to estimate surface soil moisture in about five different levels from dry to wet conditions with a 1.4 GHz radiometer, provided that the biomass of the vegetation cover could be independently measured. At frequencies greater than about 6.6 GHz, the radiometric measurements showed little sensitivity to moisture variation for vegetation-covered soils. The effects of polarization in microwave emission were studied also. (author)

Tracking target objects orbiting earth using satellite-based telescopes

Science.gov (United States)

De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

2014-10-14

A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

LAND SURFACE TEMPERATURES ESTIMATED ON GROUNDOBSERVED DATA AND SATELLITE IMAGES, DURING THE VEGETATION PERIOD IN THE OLTENIA PLAIN

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ONŢEL IRINA

2015-03-01

Full Text Available The purpose of this study is to analyze the land surface temperatures by using climatological and remote sensing data during the vegetation period in the Oltenia Plain. The data used in this study refer both to climatological data (namely monthly and seasonal air and soil temperatures, and to remote sensing data delivered by MODIS Land Surface Temperature (LST, with a spatial resolution of 1 km. The analyzed period spans from 2000 to 2013 and the vegetation period considered is April-September. As main results, there were observed four years with high temperatures, namely 2000 (20.4oC-air T, 24.6oC soil T, and 26oC LST, 2003 (20.2oC air T, 23.9oC soil T and 24.5oC LST, 2007 (20.5oC air T, 24.3oC soil T and 25oC LST and 2012 (21.3oC air T, 25.7oC soil T and 26.5oC LST. The correlations between air temperature, soil temperature and LST were statisticaly significant. The diference between air temperature and soil temperature values ranked within 3-4oC, while the difference between soil temperature and land surface temperature obtained from MODIS images was about 0.8oC. Spatially, the highest temperatures were recorded on the Leu-Rotunda Field, the Caracal Plain and the Nedeia Field, and pretty high variations of observed temperatures seemed to depend on vegetation cover. The MODIS images represent one of the most important types of satellite data available for free, which can be successfully used in determining the climatic parameters and can help to predict the changes in plant activity, due to weather phenomena.

Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

Science.gov (United States)

Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

2013-08-01

Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

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.

Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale

Science.gov (United States)

Lee A. Vierling; Kerri T. Vierling; Patrick Adam; Andrew T. Hudak

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR...

Analysis of Behavior of Vegetation in the Year of 2016 for the Municipality of Remanso- BA

OpenAIRE

Ismael Farias de Freitas; Laurizio E. R. Alves; Heliofábio B. Gomes; Jeová R. S. Júnior; Dimas B. Santiago; Rafael A. Silva

2017-01-01

Droughts are a natural problem in the Northeastern Brazilian region, in addition the rainfall distribution poorly distributed spatially and temporally results in seasonal changes in the surface vegetation. Consequently, the monitoring and evaluation of vegetation in the northeast region of Brazil has become increasingly constant. For this evaluation several techniques are used, but the use of environmental satellites is increasingly applied, such as the Landsat 8 satellite, where the products...

Assessment of heavy metal contents of green leafy vegetables

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V. Jena

2013-01-01

Full Text Available Vegetables are rich sources of vitamins, minerals, and fibers, and have beneficial antioxidative effects. Ingestion of vegetables containing heavy metals is one of the main routes through which these elements enter the human body. Slowly released into the body, however, heavy metals can cause an array of diseases. In this study we investigated the concentrations of copper, chromium, zinc, and lead in the most frequently consumed vegetables including Pimpinella anisum, Spinacia oleracea, Amaranthus viridis, Coriandrum sativum, and Trigonella foenum graecum in various sites in Raipur city, India. Atomic absorption spectrophotometry was used to estimate the levels of these metals in vegetables. The mean concentration for each heavy metal in the samples was calculated and compared with the permissible levels set by the Food and Agriculture Organization and World Health Organization. The intake of heavy metals in the human diet was also calculated to estimate the risk to human health. Our findings indicated the presence of heavy metals in vegetables in the order of Cr > Zn > Cu > Pb. Based on these findings, we conclude that the vegetables grown in this region are a health hazard for human consumption.

Use of vegetation health data for estimation of aus rice yield in bangladesh.

Science.gov (United States)

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

Directory of Open Access Journals (Sweden)

Mohammad Nizamuddin

2009-04-01

Full Text Available Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH Indices [Vegetation Condition Index (VCI, Temperature Condition Index (TCI and Vegetation Health Index (VHI] computed from Advanced Very High Resolution Radiometer (AVHRR data covering a period of 15 years (1991–2005. A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8–13 of the year, several months in advance of the rice harvest. Stepwise principal component regression (PCR was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

River flow response to changes in vegetation cover in a South ...

African Journals Online (AJOL)

It was hypothesised in this study that annual river yield (river flow as a fraction of rainfall) in the Molenaars catchment near Paarl, South Africa co-varies with an index of green vegetation cover derived from satellite data (the normalised difference vegetation index, NDVI). The catchment was partitioned into 'upland' and ...

Laser Sensing of Vegetation Based on Dual Spectrum Measurements of Reflection Coefficients

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M. L. Belov

2017-01-01

Full Text Available Currently, a promising trend in remote sensing of environment is to monitor the vegetative cover: evaluate the productivity of agricultural crops; evaluate the moisture content of soils and the state of ecosystems; provide mapping the sites of bogging, desertification, drought, etc.; control the phases of vegetation of crops, etc.Development of monitoring systems for remote detection of vegetation sites being under unfavorable conditions (low or high temperature, excess or lack of water, soil salinity, disease, etc. is of relevance. Optical methods are the most effective for this task. These methods are based on the physical features of reflection spectra in the visible and near infrared spectral range for vegetation under unfavorable conditions and vegetation under normal conditions.One of the options of optoelectronic equipment for monitoring vegetation condition is laser equipment that allows remote sensing of vegetation from the aircraft and mapping of vegetation sites with abnormal (inactive periods of vegetation reflection spectra with a high degree of spatial resolution.The paper deals with development of a promising dual-spectrum method for laser remote sensing of vegetation. Using the experimentally measured reflection spectra of different vegetation types, mathematical modeling of probability for appropriate detection and false alarms to solve a problem of detecting the vegetation under unfavorable conditions (with abnormal reflection spectra is performed based on the results of dual-spectrum measurements of the reflection coefficient.In mathematical modeling, the lidar system was supposed to provide sensing at wavelengths of 0.532 μm and 0.85 μm. The noise of the measurement was supposed to be normal with zero mean value and mean-square value of 1% -10%.It is shown that the method of laser sensing of vegetation condition based on the results of dual-spectrum measurement of the reflection coefficient at wavelengths of 0.532 μm and 0

Fuel type characterization based on coarse resolution MODIS satellite data

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Lanorte A

2007-01-01

Full Text Available Fuel types is one of the most important factors that should be taken into consideration for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. In the present study, forest fuel mapping is considered from a remote sensing perspective. The purpose is to delineate forest types by exploring the use of coarse resolution satellite remote sensing MODIS imagery. In order to ascertain how well MODIS data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers and complex topography was analysed. The study area is located in the South of Italy. Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing MODIS data, were used as ground-truth dataset to assess the obtained results. The method comprised the following three steps: (I adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II model construction for the spectral characterization and mapping of fuel types based on two different approach, maximum likelihood (ML classification algorithm and spectral Mixture Analysis (MTMF; (III accuracy assessment for the performance evaluation based on the comparison of MODIS-based results with ground-truth. Results from our analyses showed that the use of remotely sensed MODIS data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 73% for ML classifier and higher than 83% for MTMF.

Evaluating the hydrological consistency of satellite based water cycle components

KAUST Repository

Lopez Valencia, Oliver Miguel

2016-06-15

Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological

SOFT project: a new forecasting system based on satellite data

Science.gov (United States)

Pascual, Ananda; Orfila, A.; Alvarez, Alberto; Hernandez, E.; Gomis, D.; Barth, Alexander; Tintore, Joaquim

2002-01-01

The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite dat, evolutionary programming and numerical ocean models. To achieve this objective two steps are proved: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build 'intelligent' systems that, learning form the past ocean variability and considering the present ocean state, will be able to infer near future ocean conditions. Validation of the forecast skill will be carried out by comparing the forecasts fields with satellite and in situ observations. Validation with satellite observations will provide the expected errors in the forecasting system. Validation with in situ data will indicate the capabilities of the satellite based forecast information to improve the performance of the numerical ocean models. This later validation will be accomplished considering in situ measurements in a specific oceanographic area at two different periods of time. The first set of observations will be employed to feed the hybrid systems while the second set will be used to validate the hybrid and traditional numerical model results.

Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery

Directory of Open Access Journals (Sweden)

M. C. Anderson

2011-01-01

Full Text Available Thermal infrared (TIR remote sensing of land-surface temperature (LST provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil + canopy land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5 to 10-km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions on the order of 10 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe, Africa

Angular Normalization of Ground and Satellite Observations of Sun-induced Chlorophyll Fluorescence for Assessing Vegetation Productivity

Science.gov (United States)

Chen, J. M.; He, L.; Chou, S.; Ju, W.; Zhang, Y.; Joiner, J.; Liu, J.; Mo, G.

2017-12-01

Sun-induced chlorophyll fluorescence (SIF) measured from plant canopies originates mostly from sunlit leaves. Observations of SIF by satellite sensors, such as GOME-2 and GOSAT, are often made over large view zenith angle ranges, causing large changes in the viewed sunlit leaf fraction across the scanning swath. Although observations made by OCO-2 are near nadir, the observed sunlit leaf fraction could still vary greatly due to changes in the solar zenith angle with latitude and time of overpass. To demonstrate the importance of considering the satellite-target-view geometry in using SIF for assessing vegetation productivity, we conducted multi-angle measurements of SIF using a hyperspectral sensor mounted on an automated rotating system over a rice field near Nanjing, China. A method is developed to separate SIF measurements at each angle into sunlit and shaded leaf components, and an angularly normalized canopy-level SIF is obtained as the weighted sum of sunlit and shaded SIF. This normalized SIF is shown to be a much better proxy of GPP of the rice field measured by an eddy covariance system than the unnormalized SIF observations. The same normalization scheme is also applied to the far-red GOME-2 SIF observations on sunny days, and we found that the normalized SIF is better correlated with model-simulated GPP than the original SIF observations. The coefficient of determination (R2) is improved by 0.07±0.04 on global average using the normalization scheme. The most significant improvement in R2 by 0.09±0.04 is found in deciduous broadleaf forests, where the observed sunlit leaf fraction is highly sensitive to solar zenith angle.

Multitemporal satellite change detection investigations for documentation and valorization of cultural landscape

Science.gov (United States)

Lasaponara, R.; Masini, n.

2012-04-01

archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

Science.gov (United States)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

Choice architectural nudge interventions to promote vegetable consumption based on automatic processes decision-making

DEFF Research Database (Denmark)

Skov, Laurits Rohden; Friis Rasmussen, Rasmus; Møller Andersen, Pernille

2014-01-01

that had a default portion size of vegetable had he intended impact of increasing vegetable consumption. This emphasises the importance of portion sizes in out of home eating as well as underlines the effect of the one-unit bias. The remaining two nudges were not successful in increasing vegetable intake......, but promoted health by decreasing total energy intake which suggests that visual variety of fruit and greens prompts a healthy-eater subconscious behaviour....

Proposed systems configurations for a satellite based ISDN

Science.gov (United States)

Capece, M.; Pavesi, B.; Tozzi, P.; Galligan, K. P.

This paper summarizes concepts developed during a study for the ESA in which the evolution of ISDN capability and the impact in the satellite land mobile area are examined. Following the progressive steps of the expected ISDN implementation and the potential market penetration, a space based system capable of satisfying particular user services classes has been investigated. The approach used is to establish a comparison between the requirements of potential mobile users and the services already envisaged by ISDN, identifying the service subclasses that might be adopted in a mobile environment through a satellite system. Two system alternatives, with different ISDN compatibility, have been identified. The first option allows a partial compatibility, by providing the central stations of the earth segment with suitable interface units. The second option permits a full integration, operating on the satellite on-board capabilities.

A MEMS-based Adaptive AHRS for Marine Satellite Tracking Antenna

DEFF Research Database (Denmark)

Wang, Yunlong; Hussain, Dil Muhammed Akbar; Soltani, Mohsen

2015-01-01

Satellite tracking is a challenging task for marine applications. An attitude determination system should estimate the wave disturbances on the ship body accurately. To achieve this, an Attitude Heading Reference System (AHRS) based on Micro-Electro-Mechanical Systems (MEMS) sensors, composed...... of three-axis gyroscope, accelerometer and magnetometer, is developed for Marine Satellite Tracking Antenna (MSTA). In this paper, the attitude determination algorithm is improved using an adaptive mechanism that tunes the attitude estimator parameters based on an estimation of ship motion frequency...

Satellite-based technique for nowcasting of thunderstorms over ...

Indian Academy of Sciences (India)

Suman Goyal

2017-08-31

Aug 31, 2017 ... Due to inadequate radar network, satellite plays the dominant role for nowcast of these thunderstorms. In this study, a nowcast based algorithm ForTracc developed by Vila ... of actual development of cumulonimbus clouds, ... MCS over Indian region using Infrared Channel ... (2016) based on case study of.

Human health risk assessment of heavy metals in soil–vegetable system: A multi-medium analysis

Energy Technology Data Exchange (ETDEWEB)

Liu, Xingmei; Song, Qiujin; Tang, Yu; Li, Wanlu [College of Environmental and Natural Resource Sciences, Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, Zhejiang University, Hangzhou 310058 (China); Xu, Jianming, E-mail: jmxu@zju.edu.cn [College of Environmental and Natural Resource Sciences, Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, Zhejiang University, Hangzhou 310058 (China); Wu, Jianjun, E-mail: wujianjun@zju.edu.cn [College of Environmental and Natural Resource Sciences, Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, Zhejiang University, Hangzhou 310058 (China); Wang, Fan [College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou 310036 (China); Brookes, Philip Charles [College of Environmental and Natural Resource Sciences, Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, Zhejiang University, Hangzhou 310058 (China)

2013-10-01

Vegetable fields near villages in China are suffering increasing heavy metal damages from various pollution sources including agriculture, traffic, mining and Chinese typical local private family-sized industry. 268 vegetable samples which included rape, celery, cabbages, carrots, asparagus lettuces, cowpeas, tomatoes and cayenne pepper and their corresponding soils in three economically developed areas of Zhejiang Province, China were collected, and the concentrations of five heavy metals (Pb, Cd, Cr, Hg and As) in all the samples were determined. The health risk assessment methods developed by the United States Environmental Protection Agency (US EPA) were employed to explore the potential health hazards of heavy metals in soils growing vegetables. Results showed that heavy metal contaminations in investigated vegetables and corresponding soils were significant. Pollution levels varied with metals and vegetable types. The highest mean soil concentrations of heavy metals were 70.36 mg kg{sup −1} Pb, 47.49 mg kg{sup −1} Cr, 13.51 mg kg{sup −1} As, 0.73 mg kg{sup −1} for Cd and 0.67 mg kg{sup −1} Hg, respectively, while the metal concentrations in vegetables and corresponding soils were poorly correlated. The health risk assessment results indicated that diet dominated the exposure pathways, so heavy metals in soil samples might cause potential harm through food-chain transfer. The total non-cancer and cancer risk results indicated that the investigated arable fields near industrial and waste mining sites were unsuitable for growing leaf and root vegetables in view of the risk of elevated intakes of heavy metals adversely affecting food safety for local residents. Chromium and Pb were the primary heavy metals posing non-cancer risks while Cd caused the greatest cancer risk. It was concluded that more effective controls should be focused on Cd and Cr to reduce pollution in this study area. - Highlights: • Flourishing private economy caused increasing

Human health risk assessment of heavy metals in soil–vegetable system: A multi-medium analysis

International Nuclear Information System (INIS)

Liu, Xingmei; Song, Qiujin; Tang, Yu; Li, Wanlu; Xu, Jianming; Wu, Jianjun; Wang, Fan; Brookes, Philip Charles

2013-01-01

Vegetable fields near villages in China are suffering increasing heavy metal damages from various pollution sources including agriculture, traffic, mining and Chinese typical local private family-sized industry. 268 vegetable samples which included rape, celery, cabbages, carrots, asparagus lettuces, cowpeas, tomatoes and cayenne pepper and their corresponding soils in three economically developed areas of Zhejiang Province, China were collected, and the concentrations of five heavy metals (Pb, Cd, Cr, Hg and As) in all the samples were determined. The health risk assessment methods developed by the United States Environmental Protection Agency (US EPA) were employed to explore the potential health hazards of heavy metals in soils growing vegetables. Results showed that heavy metal contaminations in investigated vegetables and corresponding soils were significant. Pollution levels varied with metals and vegetable types. The highest mean soil concentrations of heavy metals were 70.36 mg kg −1 Pb, 47.49 mg kg −1 Cr, 13.51 mg kg −1 As, 0.73 mg kg −1 for Cd and 0.67 mg kg −1 Hg, respectively, while the metal concentrations in vegetables and corresponding soils were poorly correlated. The health risk assessment results indicated that diet dominated the exposure pathways, so heavy metals in soil samples might cause potential harm through food-chain transfer. The total non-cancer and cancer risk results indicated that the investigated arable fields near industrial and waste mining sites were unsuitable for growing leaf and root vegetables in view of the risk of elevated intakes of heavy metals adversely affecting food safety for local residents. Chromium and Pb were the primary heavy metals posing non-cancer risks while Cd caused the greatest cancer risk. It was concluded that more effective controls should be focused on Cd and Cr to reduce pollution in this study area. - Highlights: • Flourishing private economy caused increasing heavy metal damages. �

Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

Science.gov (United States)

Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

2017-12-01

In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields

Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration

Science.gov (United States)

Soheili, Mahmoud; (Tom) Rientjes, T. H. M.; (Christiaan) van der Tol, C.

2017-04-01

Groundwater movement is influenced by several factors and processes in the hydrological cycle, from which, recharge is of high relevance. Since the amount of aquifer extractable water directly relates to the recharge amount, estimation of recharge is a perquisite of groundwater resources management. Recharge is highly affected by water loss mechanisms the major of which is actual evapotranspiration (ETa). It is, therefore, essential to have detailed assessment of ETa impact on groundwater recharge. The objective of this study was to evaluate how recharge was affected when satellite-based evapotranspiration was used instead of in-situ based ETa in the Salland area, the Netherlands. The Methodology for Interactive Planning for Water Management (MIPWA) model setup which includes a groundwater model for the northern part of the Netherlands was used for recharge estimation. The Surface Energy Balance Algorithm for Land (SEBAL) based actual evapotranspiration maps from Waterschap Groot Salland were also used. Comparison of SEBAL based ETa estimates with in-situ abased estimates in the Netherlands showed that these SEBAL estimates were not reliable. As such results could not serve for calibrating root zone parameters in the CAPSIM model. The annual cumulative ETa map produced by the model showed that the maximum amount of evapotranspiration occurs in mixed forest areas in the northeast and a portion of central parts. Estimates ranged from 579 mm to a minimum of 0 mm in the highest elevated areas with woody vegetation in the southeast of the region. Variations in mean seasonal hydraulic head and groundwater level for each layer showed that the hydraulic gradient follows elevation in the Salland area from southeast (maximum) to northwest (minimum) of the region which depicts the groundwater flow direction. The mean seasonal water balance in CAPSIM part was evaluated to represent recharge estimation in the first layer. The highest recharge estimated flux was for autumn

Satellite-based Monotoring of mitiple natural disasters in Mongolian socio-ecological system

Science.gov (United States)

Kang, Sinkyu

2016-04-01

In this presentation, a conceptual mechanisms how multiple natural hazards (i.e. drought, dust storm, land degradation, and Dzud) in Mongolia are linked with each other and how satellite earth observation (EO) data can be utilized to analyze cause-and results relations and to predict the natural hazards. Massive loss of livestock and wildlife animal during winter seasons (dzud) is an endemic climatic disaster in the Central Asia grasslands but the mechanisms are not well understood yet. Recent national-wide sever Dzud occurred during 2009-2010 winter in Mongolia. Whereas, high stocking rate of livestock may give negative effects on sustainable use of pastureland. Dzud is a natural mechanism reducing grazing pressure when stocking rate is high enough to cause the negative effect. Both Dzud and land degradation were directly linked with drought phenomena, which is associated with dust storm occurrence because those conditions can cause sparse vegetation and increase of sensible heat generating strong vertical wind. At a lower level of administration (i.e., soum), stepwise multiple regression analysis was conducted to find significant factors of inter-annual livestock change. For a period from 2003 to 2010, various datasets were prepared from national census and satellite data (summer and winter temperature and precipitation, and summer dryness and vegetation index, NDVI). As results, linear regression models were successfully produced at 70% of soums studied. Summer and winter variables appeared equally important in controlling livestock dynamics. Single-factor models were predominant. The primary factor of each soum showed certain regional patterns incident well with climate severity and foraging resource availability (e.g. temperature in north, dryness in south, and NDVI in middle). Our results indicate that Mongolian pastoral livelihood is highly vulnerable to extreme variability of endemic regional climate factors and hence, there are still rooms for enhancing

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1

Directory of Open Access Journals (Sweden)

M. Forkel

2017-12-01

Full Text Available Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1. SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with

A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)

Science.gov (United States)

Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten

2017-12-01

Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data

Concentrations and health risk assessment of rare earth elements in vegetables from mining area in Shandong, China.

Science.gov (United States)

Zhuang, Maoqiang; Zhao, Jinshan; Li, Suyun; Liu, Danru; Wang, Kebo; Xiao, Peirui; Yu, Lianlong; Jiang, Ying; Song, Jian; Zhou, Jingyang; Wang, Liansen; Chu, Zunhua

2017-02-01

To investigate the concentrations of rare earth elements in vegetables and assess human health risk through vegetable consumption, a total of 301 vegetable samples were collected from mining area and control area in Shandong, China. The contents of 14 rare earth elements were determined by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The total rare earth elements in vegetables from mining and control areas were 94.08 μg kg -1 and 38.67 μg kg -1 , respectively, and the difference was statistically significant (p vegetable had the highest rare earth elements concentration (984.24 μg kg -1 and 81.24 μg kg -1 for mining and control areas, respectively) and gourd vegetable had the lowest rare earth elements concentration (37.34 μg kg -1 and 24.63 μg kg -1 for mining and control areas, respectively). For both areas, the rare earth elements concentration in vegetables declined in the order of leaf vegetable > taproot vegetable > alliaceous vegetable > gourd vegetable. The rare earth elements distribution patterns for both areas were characterized by enrichment of light rare earth elements. The health risk assessment demonstrated that the estimated daily intakes (0.69 μg kg -1 d -1 and 0.28 μg kg -1 d -1 for mining and control areas, respectively) of rare earth elements through vegetable consumption were significantly lower than the acceptable daily intake (70 μg kg -1 d -1 ). The damage to adults can be neglected, but more attention should be paid to the effects of continuous exposure to low levels of rare earth elements on children. Copyright © 2016 Elsevier Ltd. All rights reserved.

Communications satellites in the national and global health care information infrastructure: their role, impact, and issues

Science.gov (United States)

Zuzek, J. E.; Bhasin, K. B.

1996-01-01

Health care services delivered from a distance, known collectively as telemedicine, are being increasingly demonstrated on various transmission media. Telemedicine activities have included diagnosis by a doctor at a remote location, emergency and disaster medical assistance, medical education, and medical informatics. The ability of communications satellites to offer communication channels and bandwidth on demand, connectivity to mobile, remote and under served regions, and global access will afford them a critical role for telemedicine applications within the National and Global Information Infrastructure (NII/GII). The importance that communications satellites will have in telemedicine applications within the NII/GII the differences in requirements for NII vs. GII, the major issues such as interoperability, confidentiality, quality, availability, and costs, and preliminary conclusions for future usability based on the review of several recent trails at national and global levels are presented.

Bioaccumulation of Antimony and Arsenic in Vegetables and Health Risk Assessment in the Superlarge Antimony-Mining Area, China

Directory of Open Access Journals (Sweden)

Defang Zeng

2015-01-01

Full Text Available Heavy metal pollution in soils caused by mining and smelting has attracted worldwide attention for its potential health risks to residents. This paper studies the concentrations and accumulations of Sb and As in both soils and vegetables and the human health risks of Sb and As in vegetables from Xikuangshan (XKS Sb mine, Hunan, China. Results showed that the soils were severely polluted by Sb and As; Sb and As have significant positive correlation. Sb and As concentrations in vegetables were quite different: Coriandrum sativum L. was the highest in Sb, Allium fistulosum L. was the highest in As, and Brassica pekinensis L. was the lowest in both Sb and As; Daucus carota L. and Coriandrum sativum L. showed advantage in accumulating Sb and As; Coriandrum sativum L. had higher capacity of redistributing Sb and As within the plant. Health risk assessment results showed that the hazard quotient (HQ values of Sb and As in vegetables were in the ranges of 1.61–3.33 and 0.09–0.39, respectively; the chronic daily intake (CDI and hazard quotient (HQ values of Sb were over the safe limit recommended by FAO and WHO, indicating that long-term consumption of vegetables from the surrounding soils of XKS mine may bring health risks to residents.

Radiation exposure near Chernobyl based on analysis of satellite images

Energy Technology Data Exchange (ETDEWEB)

Goldman, Marvin; Ustin, Susan [University of California, Laboratory for Energy-related Health Research, CA (United States); Warman, Edward A [Stone and Webster Engineering Corp., Boston, MA (United States)

1987-12-01

Radiation-induced damage in conifers adjacent to the damaged Chernobyl nuclear power plant has been evaluated using LANDSAT Thematic Mapper satellite images. Eight images acquired between April 22, 1986 and May 15, 1987 were used to assess the extent and magnitude of radiation effects on pine trees within 10 km of the reactor site. The timing and spatial extent of vegetation damaged was used to estimate the radiation doses in the near field around the Chernobyl nuclear power station and to derive dose rates as a function of time during and after the accident. A normalized vegetation index was developed from the TM spectral band data to visually demonstrate the damage and mortality to nearby conifer stands. The earliest date showing detectable injury 1 km west of the reactor unit was June 16, 1986. Subsequent dates revealed continued expansion of the affected areas to the west, north, and south. The greatest aerial expansion of this area occurred by October 15, 1986, with vegetation changes evident up to 5 km west, 2 km south, and 2 km north of the damaged Reactor Unit 4. By May 11, 1987, further scene changes were due principally to removal and mitigation efforts by the Soviet authorities. Areas showing spectral evidence of vegetation damage during the previous growing season do not show evidence of recovery and reflectance in the TM Bands 4 and 3 remain higher than surrounding vegetation, which infers that the trees are dead. The patterns of spectral change indicative of vegetation stress are consistent with changes expected for radiation injury and mortality. The extent and the timing of these effects enabled developing an integrated radiation dose estimate, which was combined with the information regarding the characteristics of radionuclide mix to provide an estimate of maximum dose rates during the early period of the accident. The derived peak dose rates during the 10-day release in the accident are high and are estimated at about 0.5 to 1 rad per hour. These

Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

Science.gov (United States)

Xi, B.; Dong, X.; Wu, P.; Qiu, S.

2017-12-01

A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.

Integrated modelling of the water cycle in semi arid watersheds based on ground and satellite data: the SudMed project

Science.gov (United States)

Simonneaux, V.; Abourida, A.; Boudhar, A.; Cheggour, A.; Chaponnière, A.; Berjamy, B.; Boulet, G.; Chehbouni, A.; Drapeau, L.; Duchemin, B.; Erraki, S.; Ezzahar, J.; Escadafal, R.; Guemouria, N.; Hanich, L.; Jarlan, L.; Kharrou, H.; Khabba, S.; Le Page, M.; Mangiarotti, S.; Merlin, O.; Mougenot, B.; Mokssit, A.; Ouldbba, A.; Chehbouni, A.

2010-10-01

The SudMed project aims since 2002 at modelling the hydrological cycle in the Tensift semi arid watershed located in central Morocco. To reach these modelling objectives, emphasis is put on the use of high and low resolution remote sensing data, in the visible, near infrared, thermal, and microwave domains, to initialize, to force or to control the implementation of the process models. Fundamental studies have been conducted on Soil-Vegetation-Atmosphere Transfer modelling (SVAT), especially related to the various means of incorporating both ground and remote sensing observation into them. Satellite data have been used for monitoring the snow dynamic which is a major contribution to runoff issued from the mountains. Remote sensing image time series have also been used to map the land cover, based on NDVI time profiles analysis or temporal unmixing of low resolution pixels. Subsequently, remote sensing time series proved to be very valuable for monitoring the development of vegetation and the crop water status, in order to estimate of evapotranspiration, key information for irrigation management.

Evaluation and attribution of vegetation contribution to seasonal climate predictability

Science.gov (United States)

Catalano, Franco; Alessandri, Andrea; De Felice, Matteo

2015-04-01

The land surface model of EC-Earth has been modified to include dependence of vegetation densities on the Leaf Area Index (LAI), based on the Lambert-Beer formulation. Effective vegetation fractional coverage can now vary at seasonal and interannual time-scales and therefore affect biophysical parameters such as the surface roughness, albedo and soil field capacity. The modified model is used to perform a real predictability seasonal hindcast experiment. LAI is prescribed using a recent observational dataset based on the third generation GIMMS and MODIS satellite data. Hindcast setup is: 7 months forecast length, 2 start dates (1st May and 1st November), 10 members, 28 years (1982-2009). The effect of the realistic LAI prescribed from observation is evaluated with respect to a control experiment where LAI does not vary. Hindcast results demonstrate that a realistic representation of vegetation significantly improves the forecasts of temperature and precipitation. The sensitivity is particularly large for temperature during boreal winter over central North America and Central Asia. This may be attributed in particular to the effect of the high vegetation component on the snow cover. Summer forecasts are improved in particular for precipitation over Europe, Sahel, North America, West Russia and Nordeste. Correlation improvements depends on the links between targets (temperature and precipitation) and drivers (surface heat fluxes, albedo, soil moisture, evapotranspiration, moisture divergence) which varies from region to region.

Satellite-based Tropical Cyclone Monitoring Capabilities

Science.gov (United States)

Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.

2012-12-01

Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.

The Determinants of Organic Vegetable Purchasing in Jabodetabek Region, Indonesia

Science.gov (United States)

Slamet, Alim Setiawan; Nakayasu, Akira; Bai, Hu

2016-01-01

Over the last few years, the global market of organic vegetables has grown. This is due to increased consumer concern regarding environmental and health issues, especially for food products. This study aims to examine factors that influence consumer behavior in purchasing organic vegetables. In this study, data were obtained from household surveys conducted in the Jabodetabek region (Greater Jakarta) from February to March 2015. Descriptive analysis, factor analysis, and a binary logit model were used to analyze the data. Subsequently, the results show that consumers with fewer family members and have a higher income, and are price tolerant, are more likely to purchase organic vegetables. Meanwhile, female consumers are less likely to buy organic vegetables. Another important finding is that positive attitude towards organic products, safety and health, environmental concerns, as well as degree of trust in organic attributes, are the determinants of organic vegetable purchasing among consumers. Therefore, based on the study results, the following recommendations are needed for organic vegetable development in Indonesia: (a) implementing an appropriate pricing strategy; (b) encouraging organic labeling and certification for vegetables; and (c) intensively promoting organic food with respect to consumers’ motives and concerns on health, safety, as well as environmental sustainability. PMID:28231181

The Determinants of Organic Vegetable Purchasing in Jabodetabek Region, Indonesia.

Science.gov (United States)

Slamet, Alim Setiawan; Nakayasu, Akira; Bai, Hu

2016-12-07

Over the last few years, the global market of organic vegetables has grown. This is due to increased consumer concern regarding environmental and health issues, especially for food products. This study aims to examine factors that influence consumer behavior in purchasing organic vegetables. In this study, data were obtained from household surveys conducted in the Jabodetabek region (Greater Jakarta) from February to March 2015. Descriptive analysis, factor analysis, and a binary logit model were used to analyze the data. Subsequently, the results show that consumers with fewer family members and have a higher income, and are price tolerant, are more likely to purchase organic vegetables. Meanwhile, female consumers are less likely to buy organic vegetables. Another important finding is that positive attitude towards organic products, safety and health, environmental concerns, as well as degree of trust in organic attributes, are the determinants of organic vegetable purchasing among consumers. Therefore, based on the study results, the following recommendations are needed for organic vegetable development in Indonesia: (a) implementing an appropriate pricing strategy; (b) encouraging organic labeling and certification for vegetables; and (c) intensively promoting organic food with respect to consumers' motives and concerns on health, safety, as well as environmental sustainability.

The Determinants of Organic Vegetable Purchasing in Jabodetabek Region, Indonesia

Directory of Open Access Journals (Sweden)

Alim Setiawan Slamet

2016-12-01

Full Text Available Over the last few years, the global market of organic vegetables has grown. This is due to increased consumer concern regarding environmental and health issues, especially for food products. This study aims to examine factors that influence consumer behavior in purchasing organic vegetables. In this study, data were obtained from household surveys conducted in the Jabodetabek region (Greater Jakarta from February to March 2015. Descriptive analysis, factor analysis, and a binary logit model were used to analyze the data. Subsequently, the results show that consumers with fewer family members and have a higher income, and are price tolerant, are more likely to purchase organic vegetables. Meanwhile, female consumers are less likely to buy organic vegetables. Another important finding is that positive attitude towards organic products, safety and health, environmental concerns, as well as degree of trust in organic attributes, are the determinants of organic vegetable purchasing among consumers. Therefore, based on the study results, the following recommendations are needed for organic vegetable development in Indonesia: (a implementing an appropriate pricing strategy; (b encouraging organic labeling and certification for vegetables; and (c intensively promoting organic food with respect to consumers’ motives and concerns on health, safety, as well as environmental sustainability.

EVALUATING THE POTENTIAL OF SATELLITE HYPERSPECTRAL RESURS-P DATA FOR FOREST SPECIES CLASSIFICATION

Directory of Open Access Journals (Sweden)

O. Brovkina

2016-06-01

Full Text Available Satellite-based hyperspectral sensors provide spectroscopic information in relatively narrow contiguous spectral bands over a large area which can be useful in forestry applications. This study evaluates the potential of satellite hyperspectral Resurs-P data for forest species mapping. Firstly, a comparative study between top of canopy reflectance obtained from the Resurs-P, from the airborne hyperspectral scanner CASI and from field measurement (FieldSpec ASD 4 on selected vegetation cover types is conducted. Secondly, Resurs-P data is tested in classification and verification of different forest species compartments. The results demonstrate that satellite hyperspectral Resurs-P sensor can produce useful informational and show good performance for forest species classification comparable both with forestry map and classification from airborne CASI data, but also indicate that developments in pre-processing steps are still required to improve the mapping level.

[Community vegetable gardens as a health promotion activity: an experience in Primary Healthcare Units].

Science.gov (United States)

Costa, Christiane Gasparini Araújo; Garcia, Mariana Tarricone; Ribeiro, Silvana Maria; Salandini, Marcia Fernanda de Sousa; Bógus, Cláudia Maria

2015-10-01

Urban and peri-urban agriculture (UPA) is being practiced in different settings, contributing to the improvement of health in communities and healthier environments. In order to identify the meanings and implications of the practice of UPA in Primary Healthcare Units (PHU) as an activity of health promotion (HP), and to what extent its therapeutic dimension characterizes it as an activity aligned with complementary and integrative practices (CIP), a qualitative cross-sectional study was performed in Embu das Artes, State of São Paulo. From the analysis, the following main themes arose: health concept, health outcomes, the return to traditional practices and habits and the reorientation of health services. It was possible to identify the close link between the cultivation of vegetable gardens and HP guidelines and fields of action, such as creating healthier environments, boosting community actions, developing personal skills, stimulating autonomy and empowerment and demands for the reorientation of services. The garden activities, set up in PHU areas, proved to be an implementation strategy of CIP. The conclusion reached is that vegetable gardening activities in community gardens are seen to be health promotion practices that integrate key elements of CIP.

Using remote sensing satellite data and artificial neural network for prediction of potato yield in Bangladesh

Science.gov (United States)

Akhand, Kawsar; Nizamuddin, Mohammad; Roytman, Leonid; Kogan, Felix

2016-09-01

Potato is one of the staple foods and cash crops in Bangladesh. It is widely cultivated in all of the districts and ranks second after rice in production. Bangladesh is the fourth largest potato producer in Asia and is among the world's top 15 potato producing countries. The weather condition for potato cultivation is favorable during the sowing, growing and harvesting period. It is a winter crop and is cultivated during the period of November to March. Bangladesh is mainly an agricultural based country with respect to agriculture's contribution to GDP, employment and consumption. Potato is a prominent crop in consideration of production, its internal demand and economic value. Bangladesh has a big economic activities related to potato cultivation and marketing, especially the economic relations among farmers, traders, stockers and cold storage owners. Potato yield prediction before harvest is an important issue for the Government and the stakeholders in managing and controlling the potato market. Advanced very high resolution radiometer (AVHRR) based satellite data product vegetation health indices VCI (vegetation condition index) and TCI (temperature condition index) are used as predictors for early prediction. Artificial neural network (ANN) is used to develop a prediction model. The simulated result from this model is encouraging and the error of prediction is less than 10%.

Operational Satellite-based Surface Oil Analyses (Invited)

Science.gov (United States)

Streett, D.; Warren, C.

2010-12-01

During the Deepwater Horizon spill, NOAA imagery analysts in the Satellite Analysis Branch (SAB) issued more than 300 near-real-time satellite-based oil spill analyses. These analyses were used by the oil spill response community for planning, issuing surface oil trajectories and tasking assets (e.g., oil containment booms, skimmers, overflights). SAB analysts used both Synthetic Aperture Radar (SAR) and high resolution visible/near IR multispectral satellite imagery as well as a variety of ancillary datasets. Satellite imagery used included ENVISAT ASAR (ESA), TerraSAR-X (DLR), Cosmo-Skymed (ASI), ALOS (JAXA), Radarsat (MDA), ENVISAT MERIS (ESA), SPOT (SPOT Image Corp.), Aster (NASA), MODIS (NASA), and AVHRR (NOAA). Ancillary datasets included ocean current information, wind information, location of natural oil seeps and a variety of in situ oil observations. The analyses were available as jpegs, pdfs, shapefiles and through Google, KML files and also available on a variety of websites including Geoplatform and ERMA. From the very first analysis issued just 5 hours after the rig sank through the final analysis issued in August, the complete archive is still publicly available on the NOAA/NESDIS website http://www.ssd.noaa.gov/PS/MPS/deepwater.html SAB personnel also served as the Deepwater Horizon International Disaster Charter Project Manager (at the official request of the USGS). The Project Manager’s primary responsibility was to acquire and oversee the processing and dissemination of satellite data generously donated by numerous private companies and nations in support of the oil spill response including some of the imagery described above. SAB has begun to address a number of goals that will improve our routine oil spill response as well as help assure that we are ready for the next spill of national significance. We hope to (1) secure a steady, abundant and timely stream of suitable satellite imagery even in the absence of large-scale emergencies such as

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

Directory of Open Access Journals (Sweden)

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.

Sensitivity study of land biosphere CO2 exchange through an atmospheric tracer transport model using satellite-derived vegetation index data

International Nuclear Information System (INIS)

Knorr, W.; Heimann, M.

1994-01-01

We develop a simple, globally uniform model of CO 2 exchange between the atmosphere and the terrestrial biosphere by coupling the model with a three-dimensional atmospheric tracer transport model using observed winds, and checking results against observed concentrations of CO 2 at various monitoring sites. CO 2 fluxes are derived from observed greenness using satellite-derived Global Vegetation Index data, combined with observations of temperature, radiation, and precipitation. We explore a range of CO 2 flux formulations together with some modifications of the modelled atmospheric transport. We find that while some formulations can be excluded, it cannot be decided whether or not to make CO 2 uptake and release dependent on water stress. It appears that the seasonality of net CO 2 fluxes in the tropics, which would be expected to be driven by water availability, is small and is therefore not visible in the seasonal cycle of atmospheric CO 2 . The latter is dominated largely by northern temperate and boreal vegetation, where seasonality is mostly temperature determined. We find some evidence that there is still considerable CO 2 release from soils during northern-hemisphere winter. An exponential air temperature dependence of soil release with a Q 10 of 1.5 is found to be most appropriate, with no cutoff at low freezing temperatures. This result is independent of the year from which observed winds were taken. This is remarkable insofar as year-to-year changes in modelled CO 2 concentrations caused by changes in the wind data clearly outweigh those caused by year-to-year variability in the climate and vegetation index data. (orig.)

Programmable Ultra-Lightweight System Adaptable Radio Satellite Base Station

Science.gov (United States)

Varnavas, Kosta; Sims, Herb

2015-01-01

With the explosion of the CubeSat, small sat, and nanosat markets, the need for a robust, highly capable, yet affordable satellite base station, capable of telemetry capture and relay, is significant. The Programmable Ultra-Lightweight System Adaptable Radio (PULSAR) is NASA Marshall Space Flight Center's (MSFC's) software-defined digital radio, developed with previous Technology Investment Programs and Technology Transfer Office resources. The current PULSAR will have achieved a Technology Readiness Level-6 by the end of FY 2014. The extensibility of the PULSAR will allow it to be adapted to perform the tasks of a mobile base station capable of commanding, receiving, and processing satellite, rover, or planetary probe data streams with an appropriate antenna.

a case s ation of heavy metals' health risk index in vegetable unflower

African Journals Online (AJOL)

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ntrol of pollution produce from industries affects both air and soil table Amaranth and Sunflower ... ls, Health risk, Sunflower, and Vegetable Amaranth. ign material into a .... were homogenized by grinding using ceramic coated grinder. All the ...

Children and vegetables: strategies to increase children’s liking and intake of vegetables

NARCIS (Netherlands)

Wild, de V.W.T.

2015-01-01

Background and aim

Children’s vegetable intake is far below that recommended. Despite increased awareness of the importance of vegetable consumption for health, it remains challenging to improve children’s vegetable intake. Since food preferences are central to

Do behavioural health intentions engender health behaviour change? A study on the moderating role of self-affirmation on actual fruit intake versus vegetable intake.

Science.gov (United States)

Pietersma, Suzanne; Dijkstra, Arie

2011-11-01

The purpose of this persuasion research was to show that self-affirmation (SA) increases intentions in the advocated direction and that these intentions predict actual health behaviour change. That is, these intentions not only serve the function of short-term relief of the threat caused by the persuasive message. We proposed that the effect of SA depends on the level of value-involvement. Participants were randomly assigned to one of two conditions (no SA vs. SA) of a between-subjects design. After the SA manipulation, all participants read a threatening health text about the consequences of insufficient fruit and vegetable intake. At pre-test, value-involvement was determined. Participants included were undergraduate students. The SA manipulation consisted of a writing exercise. After reading the health message, participants reported their intention to eat sufficient fruit and vegetables (N= 537). After 1 week (N= 293) and 4 weeks (N= 261), participants completed self-reports of fruit and vegetable intake. No main effect was found for SA on any outcome measure. We did find that involvement moderated the effect of SA on cooked vegetables consumption. This effect was not present for raw vegetables/salad consumption or for fruit consumption. The moderated effect on cooked vegetable consumption was most evident after 1 week and the effect was mediated by the immediate intentions of participants. SA can lead to genuine intentions that predict actual behaviour, but the effect of SA depends on the type of behaviour and people's value-involvement. ©2011 The British Psychological Society.

A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

Science.gov (United States)

Yagci, Ali Levent; Santanello, Joseph A.; Rodell, Matthew; Deng, Meixia; Di, Liping

2018-01-01

The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

Combined amplification and hybridization techniques for genome scanning in vegetatively propagated crops

International Nuclear Information System (INIS)

Kahl, G.; Ramser, J.; Terauchi, R.; Lopez-Peralta, C.; Asemota, H.N.; Weising, K.

1998-01-01

A combination of PCR- and hybridization-based genome scanning techniques and sequence comparisons between non-coding chloroplast DNA flanking tRNA genes has been employed to screen Dioscorea species for intra- and interspecific genetic diversity. This methodology detected extensive polymorphisms within Dioscorea bulbifera L., and revealed taxonomic and phylogenetic relationships among cultivated Guinea yams varieties and their potential wild progenitors. Finally, screening of yam germplasm grown in Jamaica permitted reliable discrimination between all major cultivars. Genome scanning by micro satellite-primed PCR (MP-PCR) and random amplified polymorphic DNA (RAPD) analysis in combination with the novel random amplified micro satellite polymorphisms (RAMPO) hybridization technique has shown high potential for the genetic analysis of yams, and holds promise for other vegetatively propagated orphan crops. (author)

Heavy metals in intensive greenhouse vegetable production systems along Yellow Sea of China: Levels, transfer and health risk.

Science.gov (United States)

Hu, Wenyou; Huang, Biao; Tian, Kang; Holm, Peter E; Zhang, Yanxia

2017-01-01

Recently, greenhouse vegetable production (GVP) has grown rapidly and counts a large proportion of vegetable production in China. In this study, the accumulation, health risk and threshold values of selected heavy metals were evaluated systematically. A total of 120 paired soil and vegetable samples were collected from three typical intensive GVP systems along the Yellow Sea of China. Mean concentrations of Cd, As, Hg, Pb, Cu and Zn in greenhouse soils were 0.21, 7.12, 0.05, 19.81, 24.95 and 94.11 mg kg -1 , respectively. Compared to rootstalk and fruit vegetables, leafy vegetables had relatively high concentrations and transfer factors of heavy metals. The accumulation of heavy metals in soils was affected by soil pH and soil organic matter. The calculated hazard quotients (HQ) of the heavy metals by vegetable consumption decreased in the order of leafy > rootstalk > fruit vegetables with hazard index (HI) values of 0.61, 0.33 and 0.26, respectively. The HI values were all below 1, which indicates that there is a low risk of greenhouse vegetable consumption. Soil threshold values (STVs) of heavy metals in GVP system were established according to the health risk assessment. The relatively lower transfer factors of rootstalk and fruit vegetables and higher STVs suggest that these types of vegetables are more suitable for cultivation in greenhouse soils. This study will provide an useful reference for controlling heavy metals and developing sustainable GVP. Copyright © 2016 Elsevier Ltd. All rights reserved.

Trellis-coded CPM for satellite-based mobile communications

Science.gov (United States)

Abrishamkar, Farrokh; Biglieri, Ezio

1988-01-01

Digital transmission for satellite-based land mobile communications is discussed. To satisfy the power and bandwidth limitations imposed on such systems, a combination of trellis coding and continuous-phase modulated signals are considered. Some schemes based on this idea are presented, and their performance is analyzed by computer simulation. The results obtained show that a scheme based on directional detection and Viterbi decoding appears promising for practical applications.

On the use of wavelet for extracting feature patterns from Multitemporal google earth satellite data sets

Science.gov (United States)

Lasaponara, R.

2012-04-01

, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Heri 8 (1

A Passive Microwave L-Band Boreal Forest Freeze/Thaw and Vegetation Phenology Study

Science.gov (United States)

Roy, A.; Sonnentag, O.; Pappas, C.; Mavrovic, A.; Royer, A.; Berg, A. A.; Rowlandson, T. L.; Lemay, J.; Helgason, W.; Barr, A.; Black, T. A.; Derksen, C.; Toose, P.

2016-12-01

The boreal forest is the second largest land biome in the world and thus plays a major role in the global and regional climate systems. The extent, timing and duration of seasonal freeze/thaw (F/T) state influences vegetation developmental stages (phenology) and, consequently, constitute an important control on how boreal forest ecosystems exchange carbon, water and energy with the atmosphere. The effective retrieval of seasonal F/T state from L-Band radiometry was demonstrated using satellite mission. However, disentangling the seasonally differing contributions from forest overstory and understory vegetation, and the soil surface to the satellite signal remains challenging. Here we present initial results from a radiometer field campaign to improve our understanding of the L-Band derived boreal forest F/T signal and vegetation phenology. Two L-Band surface-based radiometers (SBR) are installed on a micrometeorological tower at the Southern Old Black Spruce site in central Saskatchewan over the 2016-2017 F/T season. One radiometer unit is installed on the flux tower so it views forest including all overstory and understory vegetation and the moss-covered ground surface. A second radiometer unit is installed within the boreal forest overstory, viewing the understory and the ground surface. The objectives of our study are (i) to disentangle the L-Band F/T signal contribution of boreal forest overstory from the understory and ground surface, (ii) to link the L-Band F/T signal to related boreal forest structural and functional characteristics, and (iii) to investigate the use of the L-Band signal to characterize boreal forest carbon, water and energy fluxes. The SBR observations above and within the forest canopy are used to retrieve the transmissivity (γ) and the scattering albedo (ω), two parameters that describe the emission of the forest canopy though the F/T season. These two forest parameters are compared with boreal forest structural and functional

Assessing the role of access and price on the consumption of fruits and vegetables across New York City using agent-based modeling.

Science.gov (United States)

Li, Yan; Zhang, Donglan; Thapa, Janani R; Madondo, Kumbirai; Yi, Stella; Fisher, Elisa; Griffin, Kerry; Liu, Bian; Wang, Youfa; Pagán, José A

2018-01-01

Most residents in New York City (NYC) do not consume sufficient fruits and vegetables every day. Difficulties with access and high prices of fruits and vegetables in some neighborhoods contribute to different consumption patterns across NYC neighborhoods. We developed an agent-based model (ABM) to predict dietary behaviors of individuals at the borough and neighborhood levels. Model parameters were estimated from the 2014 NYC Community Health Survey, United States Census data, and the literature. We simulated six hypothetical interventions designed to improve access and reduce the price of fruits and vegetables. We found that all interventions would lead to increases in fruit and vegetable consumption but the results vary substantially across boroughs and neighborhoods. For example, a 10% increase in the number of fruit/vegetable vendors combined with a 10% decrease in the prices of fruits and vegetables would lead to a median increase of 2.28% (range: 0.65%-4.92%) in the consumption of fruits and vegetables, depending on neighborhood. We also found that the impact of increasing the number of vendors on fruit/vegetable consumption is more pronounced in unhealthier local food environments while the impact of reducing prices on fruits/vegetable consumption is more pronounced in neighborhoods with low levels of education. An agent-based model of dietary behaviors that takes into account neighborhood context has the potential to inform how fruit/vegetable access and pricing strategies may specifically work in tandem to increase the consumption of fruits and vegetables at the local level. Copyright © 2017 Elsevier Inc. All rights reserved.

Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

DEFF Research Database (Denmark)

Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

2007-01-01

based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

Engineering satellite-based navigation and timing global navigation satellite systems, signals, and receivers

CERN Document Server

Betz, J

2016-01-01

This book describes the design and performance analysis of satnav systems, signals, and receivers. It also provides succinct descriptions and comparisons of all the world’s satnav systems. Its comprehensive and logical structure addresses all satnav signals and systems in operation and being developed. Engineering Satellite-Based Navigation and Timing: Global Navigation Satellite Systems, Signals, and Receivers provides the technical foundation for designing and analyzing satnav signals, systems, and receivers. Its contents and structure address all satnav systems and signals: legacy, modernized, and new. It combines qualitative information with detailed techniques and analyses, providing a comprehensive set of insights and engineering tools for this complex multidisciplinary field. Part I describes system and signal engineering including orbital mechanics and constellation design, signal design principles and underlying considerations, link budgets, qua tifying receiver performance in interference, and e...

Past and future effects of climate change on spatially heterogeneous vegetation activity in China

Science.gov (United States)

Gao, Jiangbo; Jiao, Kewei; Wu, Shaohong; Ma, Danyang; Zhao, Dongsheng; Yin, Yunhe; Dai, Erfu

2017-07-01

Climate change is a major driver of vegetation activity but its complex ecological relationships impede research efforts. In this study, the spatial distribution and dynamic characteristics of climate change effects on vegetation activity in China from the 1980s to the 2010s and from 2021 to 2050 were investigated using a geographically weighted regression (GWR) model. The GWR model was based on combined datasets of satellite vegetation index, climate observation and projection, and future vegetation productivity simulation. Our results revealed that the significantly positive precipitation-vegetation relationship was and will be mostly distributed in North China. However, the regions with temperature-dominated distribution of vegetation activity were and will be mainly located in South China. Due to the varying climate features and vegetation cover, the spatial correlation between vegetation activity and climate change may be altered. There will be different dominant climatic factors for vegetation activity distribution in some regions such as Northwest China, and even opposite correlations in Northeast China. Additionally, the response of vegetation activity to precipitation will move southward in the next three decades. In contrast, although the high warming rate will restrain the vegetation activity, precipitation variability could modify hydrothermal conditions for vegetation activity. This observation is exemplified in the projected future enhancement of vegetation activity in the Tibetan Plateau and weakened vegetation activity in East and Middle China. Furthermore, the vegetation in most parts of North China may adapt to an arid environment, whereas in many southern areas, vegetation will be repressed by water shortage in the future.

Ten Years of Post-Fire Vegetation Recovery following the 2007 Zaca Fire using Landsat Satellite Imagery

Science.gov (United States)

Hallett, J. K. E.; Miller, D.; Roberts, D. A.

2017-12-01

Forest fires play a key role in shaping eco-systems. The risk to vegetation depends on the fire regime, fuel conditions (age and amount), fire temperature, and physiological characteristics such as bark thickness and stem diameter. The 2007 Zaca Fire (24 kilometers NE of Buellton, Santa Barbara County, California) burned 826.4 km2 over the course of 2 months. In this study, we used a time series of Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager imagery, to evaluate plant burn severity and post fire recovery as defined into classes of above average recovery, normal recovery, and below average recovery. We spectrally unmixed the images into green vegetation (GV), non-photosynthetic vegetation (NPV), soil surface (SOIL), and ash with a spectral library developed using Constrained Reference Endmember Selection (CRES). We delineated the fire perimeter using the differenced Normalized Burn Ratio (dNBR) and evaluated changes in this index and the Normalized Difference Vegetation Index through time. The results showed an immediate decline in GV and NPV fractions, with a rise in soil and ash fractions directly following the fire, with a slow recovery in GV fraction and a loss of bare soil cover. The was a sharp increase in the ash fraction following the fire and gradual decrease in the year after. Most areas have recovered as of 2017, with prominent recovery in the center of the burn scar and reduced recovery in areas to the south. These results indicate how post-fire vegetation varies based on initial burn severity and pre-fire GV and NPV fractions.

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

Science.gov (United States)

Vierling, Lee A.; Vierling, Kerri T.; Adam, Patrick; Hudak, Andrew T.

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2

Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic

Science.gov (United States)