WorldWideScience

Sample records for satellite-derived vegetation indices

  1. Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa.

    Science.gov (United States)

    Sedda, Luigi; Tatem, Andrew J; Morley, David W; Atkinson, Peter M; Wardrop, Nicola A; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J

    2015-03-01

    Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  2. A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations

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    Markus Enenkel

    2016-04-01

    Full Text Available Governments, aid organizations and researchers are struggling with the complexity of detecting and monitoring drought events, which leads to weaknesses regarding the translation of early warnings into action. Embedded in an advanced decision-support framework for Doctors without Borders (Médecins sans Frontières, this study focuses on identifying the added-value of combining different satellite-derived datasets for drought monitoring and forecasting in Ethiopia. The core of the study is the improvement of an existing drought index via methodical adaptations and the integration of various satellite-derived datasets. The resulting Enhanced Combined Drought Index (ECDI links four input datasets (rainfall, soil moisture, land surface temperature and vegetation status. The respective weight of each input dataset is calculated for every grid point at a spatial resolution of 0.25 degrees (roughly 28 kilometers. In the case of data gaps in one input dataset, the weights are automatically redistributed to other available variables. Ranking the years 1992 to 2014 according to the ECDI-based warning levels allows for the identification of all large-scale drought events in Ethiopia. Our results also indicate a good match between the ECDI-based drought warning levels and reported drought impacts for both the start and the end of the season.

  3. Trends in a satellite-derived vegetation index and environmental variables in a restored brackish lagoon

    Directory of Open Access Journals (Sweden)

    Ji Yoon Kim

    2015-07-01

    Full Text Available We evaluated relative influence of climatic variables on the plant productivity after lagoon restoration. Chilika Lagoon, the largest brackish lake ecosystem in East Asia, experienced severe problems such as excessive dominance of freshwater exotic plants and rapid debasement of biodiversity associated with decreased hydrologic connectivity between the lagoon and the ocean. To halt the degradation of the lagoon ecosystem, the Chilika Development Authority implemented a restoration project, creating a new channel to penetrate the barrier beach of the lagoon. Using a satellite-derived normalized difference vegetation index (NDVI dataset, we compared the trend of vegetation changes after the lagoon restoration, from April 1998 to May 2014. The time series of NDVI data were decomposed into trend, seasonal, and random components using a local regression method. The results were visualized to understand the traits of spatial distribution in the lagoon. The NDVI trend, indicative of primary productivity, decreased rapidly during the restoration period, and gradually increased (slope coefficient: 2.1×10−4, p<0.05 after two years of restoration. Level of seawater exchange had more influences on plant productivity than local precipitation in the restored lagoon. Higher El Niño/Southern Oscillation increased sea level pressure, and caused intrusion of seawater into the lagoon, and the subsequently elevated salinity decreased the annual mean NDVI. Our findings suggest that lagoon restoration plans for enhancing interconnectivity with the ocean should consider oceanographic effects due to meteorological forcing, and long-term NDVI results can be used as a valuable index for adaptive management of the restoration site.

  4. 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

  5. Ecosystem evaluation (1989-2012) of Ramsar wetland Deepor Beel using satellite-derived indices.

    Science.gov (United States)

    Mozumder, Chitrini; Tripathi, N K; Tipdecho, Taravudh

    2014-11-01

    The unprecedented urban growth especially in developing countries has laid immense pressure on wetlands, finally threatening their existence altogether. A long-term monitoring of wetland ecosystems is the basis of planning conservation measures for a sustainable development. Deepor Beel, a Ramsar wetland and major storm water basin of the River Brahmaputra in the northeastern region of India, needs particular attention due to its constant degradation over the past decades. A rule-based classification algorithm was developed using Landsat (2011)-derived indices, namely Normalised Difference Water Index (NDWI), Modified Normalised Difference Water Index (MNDWI), Normalised Difference Pond Index (NDPI), Normalised Difference Vegetation Index (NDVI) and field data as ancillary information. Field data, ALOS AVNIR and Google Earth images were used for accuracy assessment. A fuzzy accuracy assessment of the classified data sets showed an overall accuracy of 82 % for MAX criteria and 90 % for RIGHT criteria. The rules were used to classify major wetland cover types during low water season (January) in 1989, 2001 and 2012. The statistical analysis of the classified wetland showed heavy manifestation in aquatic vegetation and other features indicating severe eutrophication over the past 23 years. This degradation was closely related to major contributing anthropogenic factors, such as a railway line construction, growing croplands, waste disposal and illegal human settlements in the wetland catchment. In addition, the landscape development index (LDI) indicated a rapid increase in the impact of the surrounding land use on the wetland from 1989 to 2012. The techniques and results from this study may prove useful for top-down landscape analyses of this and other freshwater wetlands.

  6. The relationship between satellite-derived indices and species diversity across African savanna ecosystems

    Science.gov (United States)

    Mapfumo, Ratidzo B.; Murwira, Amon; Masocha, Mhosisi; Andriani, R.

    2016-10-01

    The ability to use remotely sensed diversity is important for the management of ecosystems at large spatial extents. However, to achieve this, there is still need to develop robust methods and approaches that enable large-scale mapping of species diversity. In this study, we tested the relationship between species diversity measured in situ with the Normalized Difference Vegetation Index (NDVI) and the Coefficient of Variation in the NDVI (CVNDVI) derived from high and medium spatial resolution satellite data at dry, wet and coastal savanna woodlands. We further tested the effect of logging on NDVI along the transects and between transects as disturbance may be a mechanism driving the patterns observed. Overall, the results of this study suggest that high tree species diversity is associated with low and high NDVI and at intermediate levels is associated with low tree species diversity and NDVI. High tree species diversity is associated with high CVNDVI and vice versa and at intermediate levels is associated with high tree species diversity and CVNDVI.

  7. Dynamic Response of Satellite-Derived Vegetation Growth to Climate Change in the Three North Shelter Forest Region in China

    Directory of Open Access Journals (Sweden)

    Bin He

    2015-08-01

    Full Text Available Since the late 1970s, the Chinese government has initiated ecological restoration programs in the Three North Shelter Forest System Project (TNSFSP area. Whether accelerated climate change will help or hinder these efforts is still poorly understood. Using the updated and extended AVHRR NDVI3g dataset from 1982 to 2011 and corresponding climatic data, we investigated vegetation variations in response to climate change. The results showed that the overall state of vegetation in the study region has improved over the past three decades. Vegetation cover significantly decreased in 23.1% and significantly increased in 21.8% of the study area. An increase in all three main vegetation types (forest, grassland, and cropland was observed, but the trend was only statistically significant in cropland. In addition, bare and sparsely vegetated areas, mainly located in the western part of the study area, have significantly expanded since the early 2000s. A moisture condition analysis indicated that the study area experienced significant climate variations, with warm-wet conditions in the western region and warm-dry conditions in the eastern region. Correlation analysis showed that variations in the Normalized Difference Vegetation Index (NDVI were positively correlated with precipitation and negatively correlated with temperature. Ultimately, climate change influenced vegetation growth by controlling the availability of soil moisture. Further investigation suggested that the positive impacts of precipitation on NDVI have weakened in the study region, whereas the negative impacts from temperature have been enhanced in the eastern study area. However, over recent years, the negative temperature impacts have been converted to positive impacts in the western region. Considering the variations in the relationship between NDVI and climatic variables, the warm–dry climate in the eastern region is likely harmful to vegetation growth, whereas the warm

  8. Identification of Forest Vegetation Using Vegetation Indices

    Institute of Scientific and Technical Information of China (English)

    Yuan Jinguo; Wang Wei

    2004-01-01

    Spectral feature of forest vegetation with remote sensing techniques is the research topic all over the world, because forest plays an important role in human beings' living environment. Research on vegetation classification with vegetation index is still very little recently. This paper proposes a method of identifying forest types based on vegetation indices,because the contrast of absorbing red waveband with reflecting near-infrared waveband strongly for different vegetation types is recognized as the theoretic basis of vegetation analysis with remote sensing. Vegetation index is highly related to leaf area index, absorbed photosynthetically active radiation and vegetation cover. Vegetation index reflects photosynthesis intensity of plants and manifests different forest types. According to reflectance data of forest canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun of China, many vegetation indices are calculated and analyzed. The result shows that the relationships between vegetation indices and forest types are that perpendicular vegetation index (PVI) identifies broadleaf forest and coniferous forest the most easily;the next is transformed soil-adjusted vegetation index(TSVI) and modified soil-adjusted vegetation index(MSVI), but their calculation is complex. Ratio vegetation index (RVT) values of different coniferous forest vary obviously, so RVI can classify conifers.Therefore, the combination of PVI and RVI is evaluated to classify different vegetation types.

  9. Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment.

    Science.gov (United States)

    Cole, Ella F; Long, Peter R; Zelazowski, Przemyslaw; Szulkin, Marta; Sheldon, Ben C

    2015-11-01

    Population-level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite-derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green-up for a 385-ha mixed-deciduous woodland. Using data spanning 13 years, we demonstrate that annual population-level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite-derived spring vegetation phenology. We go on to show that timing of local vegetation green-up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote-sensed vegetation phenology and reproductive phenology in both species. Marked within-population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small-scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within-population variation

  10. Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis.

    Science.gov (United States)

    Cong, Nan; Wang, Tao; Nan, Huijuan; Ma, Yuecun; Wang, Xuhui; Myneni, Ranga B; Piao, Shilong

    2013-03-01

    The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite-derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green-up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green-up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green-up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green-up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green-up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature. © 2012 Blackwell Publishing Ltd.

  11. 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...

  12. Prognostic land surface albedo from a dynamic global vegetation model clumped canopy radiative transfer scheme and satellite-derived geographic forest heights

    Science.gov (United States)

    Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Aleinov, I. D.; Jonas, J.

    2014-12-01

    Vegetation cover was introduced into general circulations models (GCMs) in the 1980's to account for the effect of land surface albedo and water vapor conductance on the Earth's climate. Schemes assigning canopy albedoes by broad biome type have been superceded in 1990's by canopy radiative transfer schemes for homogeneous canopies obeying Beer's Law extinction as a function of leaf area index (LAI). Leaf albedo and often canopy height are prescribed by plant functional type (PFT). It is recognized that this approach does not effectively describe geographic variation in the radiative transfer of vegetated cover, particularly for mixed and sparse canopies. GCM-coupled dynamic global vegetation models (DGVMs) have retained these simple canopy representations, with little further evaluation of their albedos. With the emergence lidar-derived canopy vertical structure data, DGVM modelers are now revisiting albedo simulation. We present preliminary prognostic global land surface albedo produced by the Ent Terrestrial Biosphere Model (TBM), a DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. The Ent TBM is a next generation DGVM designed to incorporate variation in canopy heights, and mixed and sparse canopies. For such dynamically varying canopy structure, it uses the Analytical Clumped Two-Stream (ACTS) canopy radiative transfer model, which is derived from gap probability theory for canopies of tree cohorts with ellipsoidal crowns, and accounts for soil, snow, and bare stems. We have developed a first-order global vegetation structure data set (GVSD), which gives a year of satellite-derived geographic variation in canopy height, maximum canopy leaf area, and seasonal LAI. Combined with Ent allometric relations, this data set provides population density and foliage clumping within crowns. We compare the Ent prognostic albedoes to those of the previous GISS GCM scheme, and to satellite estimates. The impact of albedo differences on surface

  13. Exploration of Loggerhead Shrike Habitats in Grassland National Park of Canada Based on in Situ Measurements and Satellite-Derived Adjusted Transformed Soil-Adjusted Vegetation Index (ATSAVI

    Directory of Open Access Journals (Sweden)

    Li Shen

    2013-01-01

    Full Text Available The population of loggerhead shrike (Lanius ludovicianus excubutirudes in Grassland National Park of Canada (GNPC has undergone a severe decline due to habitat loss and limitation. Shrike habitat availability is highly impacted by the biophysical characteristics of grassland landscapes. This study was conducted in the west block of GNPC. The overall purpose was to extract important biophysical and topographical variables from both SPOT satellite imagery and in situ measurements. Statistical analysis including Analysis of Variance (ANOVA, measuring Coefficient Variation (CV, and regression analysis were applied to these variables obtained from both imagery and in situ measurement. Vegetation spatial variation and heterogeneity among active, inactive and control nesting sites at 20 m × 20 m, 60 m × 60 m and 100 m × 100 m scales were investigated. Results indicated that shrikes prefer to nest in open areas with scattered shrubs, particularly thick or thorny species of smaller size, to discourage mammalian predators. The most important topographical characteristic is that active sites are located far away from roads at higher elevation. Vegetation index was identified as a good indicator of vegetation characteristics for shrike habitats due to its significant relation to most relevant biophysical factors. Spatial variation analysis showed that at all spatial scales, active sites have the lowest vegetation abundance and the highest heterogeneity among the three types of nesting sites. For all shrike habitat types, vegetation abundance decreases with increasing spatial scales while habitat heterogeneity increases with increasing spatial scales. This research also indicated that suitable shrike habitat for GNPC can be mapped using a logistical model with ATSAVI and dead material in shrub canopy as the independent variables.

  14. Migratory herbivorous waterfowl track satellite-derived green wave index.

    Science.gov (United States)

    Shariatinajafabadi, Mitra; Wang, Tiejun; Skidmore, Andrew K; Toxopeus, Albertus G; Kölzsch, Andrea; Nolet, Bart A; Exo, Klaus-Michael; Griffin, Larry; Stahl, Julia; Cabot, David

    2014-01-01

    Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI) time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI), has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7). Data were collected over three years (2008-2010). Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%), while the Greenland geese followed an earlier stage (GWI 20-40%). Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration), thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

  15. Migratory herbivorous waterfowl track satellite-derived green wave index.

    Directory of Open Access Journals (Sweden)

    Mitra Shariatinajafabadi

    Full Text Available Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI, has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7. Data were collected over three years (2008-2010. Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%, while the Greenland geese followed an earlier stage (GWI 20-40%. Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration, thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

  16. Atmospheric COS measurements and satellite-derived vegetation fluorescence data to evaluate the terrestrial gross primary productivity of CMIP5 model

    Science.gov (United States)

    Peylin, Philippe; MacBean, Natasha; Launois, Thomas; Belviso, Sauveur; Cadule, Patricia; Maignan, Fabienne

    2016-04-01

    Predicting the fate of the ecosystem carbon stocks and their sensitivity to climate change strongly relies on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. The Gross Primary Productivity (GPP) simulated by the different terrestrial models used in CMIP5 show large differences however, not only in terms of mean value but also in terms of phase and amplitude, thus hampering accurate investigations into carbon-climate feedbacks. While the net C flux of an ecosystem (NEE) can be measured in situ with the eddy covariance technique, the GPP is not directly accessible at larger scales and usually estimates are based on indirect measurements combining different tracers. Recent measurements of a new atmospheric tracer, the Carbonyl sulphide (COS), as well as the global measurement of Solar Induced Fluorescence (SIF) from satellite instruments (GOSAT, GOME2) open a new window for evaluating the GPP of earth system models. The use of COS relies on the fact that it is absorbed by the leaves in a similar manner to CO2, while there seems to be nothing equivalent to respiration for COS. Following recent work by Launois et al. (ACP, 2015), there is a potential to evaluate model GPP from atmospheric COS and CO2 measurements, using a transport model and recent parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of COS. Vegetation uptake of COS is modeled as a linear function of GPP and the ratio of COS to CO2 rate of uptake by plants. For the fluorescence, recent measurements of SIF from space appear to be highly correlated with monthly variations of data-driven GPP estimates (Guanter et al., 2012), following a strong dependence of vegetation SIF on photosynthetic activity. These global measurements thus provide new indications on the timing of canopy carbon uptake. In this work, we propose a dual approach that combines the strength of both COS and SIF

  17. Satellite derived 30-year trends in terrestrial frozen and non-frozen seasons and associated impacts to vegetation and atmospheric CO2

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    Kim, Y.; Kimball, J. S.; McDonald, K. C.; Glassy, J. M.

    2010-12-01

    Approximately 66 million km2 (52.5 %) of the global vegetated land area experiences seasonally frozen temperatures as a major constraint to ecosystem processes. The freeze-thaw (F/T) status of the landscape as derived from satellite microwave remote sensing is closely linked to surface energy budget and hydrological activity, vegetation phenology, terrestrial carbon budgets and land-atmosphere trace gas exchange. We utilized a seasonal threshold algorithm based temporal change classification of 37GHz frequency, vertically polarized brightness temperatures (Tb) from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) pathfinder and Special Sensor Microwave Imager (SSM/I) to classify daily F/T status for all global land areas where seasonal frozen temperatures are a major constraint to ecosystem processes. A temporally consistent, long-term (30 year) daily F/T record was created by pixel-wise correction of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements acquired during 1987. The resulting combined F/T record was validated against in situ temperature measurements from the global weather station network and applied to quantify regional patterns and trends in timing and length of frozen and non-frozen seasons. The F/T results were compared against other surrogate measures of biosphere activity including satellite AVHRR (GIMMS) based vegetation greenness (NDVI) and atmospheric CO2 concentrations over northern (>50N) land areas. The resulting F/T record showed mean annual classification accuracies of 91 (+/-1.0) and 84 (+/- 0.9) percent for PM and AM overpass retrievals relative to in situ weather station records. The F/T record showed significant (P=0.008) long-term trends in non-frozen period (0.207 days/yr) that were largely driven by earlier onset of spring thaw (-0.121 days/yr) and a small, delayed trend the arrival of the frozen period (0.107 days/yr). These results coincide with 0.025 C/yr warming trends in

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

    Science.gov (United States)

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

    2008-11-01

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

  19. Response of spectral vegetation indices to soil moisture in grasslands and shrublands

    Science.gov (United States)

    Zhang, L.; Ji, L.; Wylie, B.K.

    2011-01-01

    The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture. ?? 2011 Taylor & Francis.

  20. Quantifying landscape resilience using vegetation indices

    Science.gov (United States)

    Eddy, I. M. S.; Gergel, S. E.

    2014-12-01

    Landscape resilience refers to the ability of systems to adapt to and recover from disturbance. In pastoral landscapes, degradation can be measured in terms of increased desertification and/or shrub encroachment. In many countries across Central Asia, the use and resilience of pastoral systems has changed markedly over the past 25 years, influenced by centralized Soviet governance, private property rights and recently, communal resource governance. In Kyrgyzstan, recent governance reforms were in response to the increasing degradation of pastures attributed to livestock overgrazing. Our goal is to examine and map the landscape-level factors that influence overgrazing throughout successive governance periods. Here, we map and examine some of the spatial factors influencing landscape resilience in agro-pastoral systems in the Kyrgyzstan Republic where pastures occupy >50% of the country's area. We ask three questions: 1) which mechanisms of pasture degradation (desertification vs. shrub encroachment), are detectable using remote sensing vegetation indices?; 2) Are these degraded pastures associated with landscape features that influence herder mobility and accessibility (e.g., terrain, distance to other pastures)?; and 3) Have these patterns changed through successive governance periods? Using a chronosequence of Landsat imagery (1999-2014), NDVI and other VIs were used to identify trends in pasture condition during the growing season. Least-cost path distances as well as graph theoretic indices were derived from topographic factors to assess landscape connectivity (from villages to pastures and among pastures). Fieldwork was used to assess the feasibility and accuracy of this approach using the most recent imagery. Previous research concluded that low herder mobility hindered pasture use, thus we expect the distance from pasture to village to be an important predictor of pasture condition. This research will quantify the magnitude of pastoral degradation and test

  1. MODIS/TERRA MOD44A Vegetation Indices

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  2. State Indicator Report on Fruits and Vegetables, 2009

    Science.gov (United States)

    Centers for Disease Control and Prevention, 2009

    2009-01-01

    The "State Indicator Report on Fruits and Vegetables, 2009" provides for the first time information on fruit and vegetable (F&V) consumption and policy and environmental support within each state. Fruits and vegetables, as part of a healthy diet, are important for optimal child growth, weight management, and chronic disease…

  3. Comparison of Some Vegetation Indices in Seasonal Information

    Institute of Scientific and Technical Information of China (English)

    HAO Chengyuan; WU Shaohong; XU Chuanyang

    2008-01-01

    With the development of vegetation indices,the reflection capability of vegetation indices to the state of vegetation has been improved in various degrees.Especially,the vegetation index of Terra/MODIS-EVI is believed to have the highest sensitivity to the seasonality of vegetation.This study compares the reflection susceptibility of three vegetation indices (NOAA/AVHRR-NDVI,Teffa/MODIS-NDVI and Terra/MODIS-EVI) to the seasonal variations of vegetation in the mid-south of Yutman Province of China.It has been found that Terra/MODIS-EVI does best in the elimination of external disturbance.Firstly,it obviously improves the linear relationship with vegetation cover degree,especially in the high vegetation coverage area.Secondly,it avoids the emergence of vegetation index saturation.Thirdly,it reduces the environmental influence including both effects of atmosphere and soil.So it is believed that the Terra/MODIS-EVI can offer excellent tool for quantitative research of remote sensing and has realized to be oriented by data with high quality.

  4. Sensitivity of vegetation indices to different burn and vegetation ratios using LANDSAT-5 satellite data

    Science.gov (United States)

    Pleniou, M.; Koutsias, N.

    2013-08-01

    The application of vegetation indices is a very common approach in remote sensing of burned areas to either map the fire scar or estimate burn severity since they minimize the effect of exogenous factors and enhance the correlation with the internal parameters of vegetation. In a recent study we found that the original spectral channels, based on which these indices are estimated, are sensitive to external parameters of the vegetation as for example the spectral reflectance of the background soil. In such cases, the influence of the soil in the reflectance values is different in the various spectral regions depending on its type. These problems are further enhanced by the non-homogeneous pixels, as created from fractions of different types of land cover. Parnitha (Greece), where a wildfire occurred on July 2007, was established as test site. The purpose of this work is to explore the sensitivity of vegetation indices when used to estimate and map different fractions of fire-scorched (burned) and non fire-scorched (vegetated) areas. IKONOS, a very high resolution satellite imagery, was used to create a three-class thematic map to extract the percentages of vegetation, burned surfaces, and bare soil. Using an overlaid fishnet we extracted samples of completely "burned", completely "vegetated" pixels and proportions with different burn/vegetation ratios (45%-55% burned - 45%-55% vegetation, 20%-30% burned - 70%- 80% vegetation, 70%-80% burned - 20%-30% vegetation). Vegetation indices were calculated (NDVI, IPVI, SAVI) and their values were extracted to characterize the mentioned classes. The main findings of our recent research were that vegetation indices are less sensitive to external parameters of the vegetation by minimizing external effects. Thus, the semi-burned classes were spectrally more consistent to their different fractions of scorched and non-scorched vegetation, than the original spectral channels based on which these indices are estimated.

  5. Vegetation indices as indicators of damage by the sunn pest ...

    African Journals Online (AJOL)

    SERVER

    2008-01-18

    Jan 18, 2008 ... structure insensitive pigment index (SIPI) were chosen out of 19 indices initially tested. The NDVI ... Because chlorophyll content plays a direct role in photosynthesis ... near infrared (NIR) reflectance from its leaves. Jensen.

  6. AfSIS MODIS Collection: Vegetation Indices, April 2014

    Data.gov (United States)

    Center for International Earth Science Information Network, Columbia University — The Africa Soil Information Service (AfSIS) Moderate Resolution Imaging Spectroradiometer (MODIS) Collection's Vegetation Indices data set contains rasters with the...

  7. Monitoring vegetation responses to drought -- linking Remotely-sensed Drought Indices with Meteorological drought indices

    Science.gov (United States)

    Wang, H.; Lin, H.; Liu, D.

    2013-12-01

    Abstract: Effectively monitoring vegetation drought is of great significance in ecological conservation and agriculture irrigation at the regional scale. Combining meteorological drought indices with remotely sensed drought indices can improve tracking vegetation dynamic under the threat of drought. This study analyzes the dynamics of spatially-defined Temperature Vegetation Dryness Index (TVDI) and temporally-defined Vegetation Health Index (VHI) from remotely sensed NDVI and LST datasets in the dry spells in Southwest China. We analyzed the correlation between remotely sensed drought indices and meteorological drought index of different time scales. The results show that TVDI was limited by the spatial variations of LST and NDVI, while VHI was limited by the temporal variations of LST and NDVI. Station-based buffering analysis indicates that the extracted remotely sensed drought indices and Standard Precipitation Index (SPI) could reach stable correlation with buffering radius larger than 35 km. Three factors affect the spatiotemporal relationship between remotely sensed drought indices and SPI: i) different vegetation types; ii) the timescale of SPI; and iii) remote sensing data noise. Vegetation responds differently to meteorological drought at various time scales. The correlation between SPI6 and VHI is more significant than that between SPI6 and TVDI. Spatial consistency between VHI and TVDI varies with drought aggravation. In early drought period from October to December, VHI and TVDI show limited consistency due to the low quality of remotely sensed images. The study helps to improve monitoring vegetation drought using both meteorological drought indices and remotely sensed drought indices.

  8. Foliar anthocyanin content - Sensitivity of vegetation indices using green reflectance

    Science.gov (United States)

    Vina, A.; Gitelson, A. A.

    2009-12-01

    The amount and composition of photosynthetic and non-photosynthetic foliar pigments varies primarily as a function of species, developmental and phenological stages, and environmental stresses. Information on the absolute and relative amounts of these pigments thus provides insights onto the physiological conditions of plants and their responses to stress, and has the potential to be used for evaluating plant species composition and diversity across broad geographic regions. Anthocyanins in particular, are non-photosynthetic pigments associated with the resistance of plants to environmental stresses (e.g., drought, low soil nutrients, high radiation, herbivores, and pathogens). As they absorb radiation primarily in the green region of the electromagnetic spectrum (around 540-560 nm), broad-band vegetation indices that use this region in their formulation will respond to their presence. We evaluated the sensitivity of three vegetation indices using reflectance in the green spectral region (the green Normalized Difference Vegetation Index, gNDVI, the green Chlorophyll Index, CIg, and the Visible Atmospherically Resistant Vegetation Index, VARI) to foliar anthocyanins in five different species. For comparison purposes the widely used Normalized Difference Vegetation Index, NDVI was also evaluated. Among the four indices tested, the VARI, which uses only spectral bands in the visible region of the electromagnetic spectrum, was found to be inversely and linearly related to the relative amount of foliar anthocyanins. While this result was obtained at leaf level, it opens new possibilities for analyzing anthocyanin content across multiple scales, by means of currently operational aircraft- and spacecraft-mounted broad-band sensor systems. Further studies that evaluate the sensitivity of the VARI to the relative content of anthocyanins across space (e.g., at canopy and regional scales) and time, and its relationship with plant biodiversity and vegetation stresses, are

  9. Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation

    Science.gov (United States)

    Huete, Alfredo R.; Didan, Kamel; van Leeuwen, Willem J. D.; Vermote, Eric F.

    1999-12-01

    Vegetation indices have emerged as important tools in the seasonal and inter-annual monitoring of the Earth's vegetation. They are radiometric measures of the amount and condition of vegetation. In this study, the Sea-viewing Wide Field-of-View sensor (SeaWiFS) is used to investigate coarse resolution monitoring of vegetation with multiple indices. A 30-day series of SeaWiFS data, corrected for molecular scattering and absorption, was composited to cloud-free, single channel reflectance images. The normalized difference vegetation index (NDVI) and an optimized index, the enhanced vegetation index (EVI), were computed over various 'continental' regions. The EVI had a normal distribution of values over the continental set of biomes while the NDVI was skewed toward higher values and saturated over forested regions. The NDVI resembled the skewed distributions found in the red band while the EVI resembled the normal distributions found in the NIR band. The EVI minimized smoke contamination over extensive portions of the tropics. As a result, major biome types with continental regions were discriminable in both the EVI imagery and histograms, whereas smoke and saturation considerably degraded the NDVI histogram structure preventing reliable discrimination of biome types.

  10. 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

  11. Soil Line Influences on Two-Band Vegetation Indices and Vegetation Isolines: A Numerical Study

    Directory of Open Access Journals (Sweden)

    Alfredo R. Huete

    2010-02-01

    Full Text Available Influences of soil line variations on two-band vegetation indices (VIs and their vegetation isolines in red and near-infrared (NIR reflectance space are investigated based on recently derived relationships between the relative variations of VIs with variations of the soil line parameters in the accompanying paper by Yoshioka et al. [1]. The soil line influences are first demonstrated numerically in terms of variations of vegetation isolines and VI values along with the isolines. A hypothetical case is then analyzed by assuming the discrepancies between the general and regional soil lines for a Southern Brazil area reported elsewhere. The results indicate the validity of our analytical approach for the evaluation of soil line influences and the applicability for adjustment of VI errors using external data sources of soil reflectance spectra.

  12. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

    Science.gov (United States)

    Ji, Lei; Peters, Albert J.

    2003-01-01

    The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

  13. [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.

  14. Derivation of Relationships between Spectral Vegetation Indices from Multiple Sensors Based on Vegetation Isolines

    Directory of Open Access Journals (Sweden)

    Kenta Obata

    2012-02-01

    Full Text Available An analytical form of relationship between spectral vegetation indices (VI is derived in the context of cross calibration and translation of vegetation index products from different sensors. The derivation has been carried out based on vegetation isoline equations that relate two reflectance values observed at different wavelength ranges often represented by spectral band passes. The derivation was first introduced and explained conceptually by assuming a general functional form for VI model equation. This process is universal by which two VIs of different sensors and/or different model equations can be related conceptually. The general process was then applied to the actual case of normalized difference vegetation index (NDVI from two sensors in a framework of inter-sensor continuity. The derivation results indicate that the NDVI from one sensor can be approximated by a rational function of NDVI from the other sensor as a parameter. Similar result was obtained for the case of soil adjusted VI, enhanced VI, and two-band variance of enhanced VI.

  15. Correlation between satellite vegetation indices and crop coefficients

    Science.gov (United States)

    Russo, A. L.; Simoniello, T.; Greco, M.; Squicciarrino, G.; Lanfredi, M.; Macchiato, M.

    2010-05-01

    Accurate estimations of plant evapotranspiration and its spatial distribution are fundamental for the evaluation of vegetation water stress. Satellite remote sensing techniques represent precious tools for the evapotranspiration estimations at large scale. Many studies are based on the use of thermal signals as inputs for energy balance equations that are solved to estimate evapotranspiration (e.g., Bastiaanssen et al., 1998; Ayenew, 2003). This approach requires many inputs and a detailed theoretical background knowledge. Other works (e.g., Calera at al., 2005; Gonzalez-Dugo and Mateos, 2008) explored a second approach based on the FAO method that estimates the plant evapotranspiration by weighting the reference evapotranspiration with a crop coefficient (Kc) derived from satellite based vegetation indices. Such studies mainly investigated the usefulness of high resolution satellite data, such as Quickbird, Ikonos, TM, that in spite of the high spatial sampling, are not suitable for a dense temporal sampling. In order to generate spatially distributed values of Kc that capture field-specific crop development, we investigated the usefulness of vegetation indices derived from a time series (2005-2008) of medium resolution MODIS data. We analyzed the spatial and temporal correlation of different indices (NDVI, EVI, and WDVI) with crop coefficients available in literature for different herbaceous and arboreal cultivations present in the study area (Basilicata region, southern Italy). To take into account the background of the cultivation covers, we weighted the Kc by considering the vegetation fraction within each the pixel. By evaluating altogether the cultivations, we found that the correlation increases during the growing season (R2 > 0.80) whereas it decreases during the winter period (R2 cultivation highlighted that NDVI provided quite high correlation for all the investigated cultivation with maximum values for wheat (R2 = 0.89) and vineyards (R2 = 0.83). For

  16. Use of spectral channels and vegetation indices from satellite VEGETATION time series for the Post-Fire vegetation recovery estimation

    Science.gov (United States)

    Coluzzi, Rosa; Lasaponara, Rosa; Montesano, Tiziana; Lanorte, Antonio; de Santis, Fortunato

    2010-05-01

    Satellite data can help monitoring the dynamics of vegetation in burned and unburned areas. Several methods can be used to perform such kind of analysis. This paper is focused on the use of different satellite-based parameters for fire recovery monitoring. In particular, time series of single spectral channels and vegetation indices from SPOT-VEGETATION have investigated. The test areas is the Mediterranean ecosystems of Southern Italy. For this study we considered: 1) the most widely used index to follow the process of recovery after fire: normalized difference vegetation index (NDVI) obtained from the visible (Red) and near infrared (NIR) by using the following formula NDVI = (NIR_Red)/(NIR + Red), 2) moisture index MSI obtained from the near infrared and Mir for characterization of leaf and canopy water content. 3) NDWI obtained from the near infrared and Mir as in the case of MSI, but with the normalization (as the NDVI) to reduce the atmospheric effects. All analysis for this work was performed on ten-daily normalized difference vegetation index (NDVI) image composites (S10) from the SPOT- VEGETATION (VGT) sensor. The final data set consisted of 279 ten-daily, 1 km resolution NDVI S1O composites for the period 1 April 1998 to 31 December 2005 with additional surface reflectance values in the blue (B; 0.43-0.47,um), red (R; 0.61-0.68,um), near-infrared (NIR; 0.78-0.89,um) and shortwave-infrared (SWIR; 1.58-1.75,um) spectral bands, and information on the viewing geometry and pixel status. Preprocessing of the data was performed by the Vlaamse Instelling voor Technologisch Onderzoek (VITO) in the framework of the Global Vegetation Monitoring (GLOVEG) preprocessing chain. It consisted of the Simplified Method for Atmospheric Correction (SMAC) and compositing at ten-day intervals based on the Maximum Value Compositing (MVC) criterion. All the satellite time series were analysed using the Detrended Fluctuation Analysis (DFA) to estimate post fire vegetation recovery

  17. Derivation of Soil Line Influence on Two-Band Vegetation Indices and Vegetation Isolines

    Directory of Open Access Journals (Sweden)

    Hiroki Yoshioka

    2009-11-01

    Full Text Available This paper introduces derivations of soil line influences on two-band vegetation indices (VIs and vegetation isolines in the red and near infra-red reflectance space. Soil line variations are described as changes in the soil line parameters (slope and offset and the red reflectance of the soil surface. A general form of a VI model equation written as a ratio of two linear functions (e.g., NDVI and SAVI was assumed. It was found that relative VI variations can be approximated by a linear combination of the three soil parameters. The derived expressions imply the possibility of estimating and correcting for soil-induced bias errors in VIs and their derived biophysical parameters, caused by the assumption of a general soil line, through the use of external data sources such as regional soil maps.

  18. Derivative vegetation indices as a new approach in remote sensing of vegetation

    Institute of Scientific and Technical Information of China (English)

    Svetlana M.KOCHUBEY; Taras A.KAZANTSEV

    2012-01-01

    This paper focuses on the advantages of derivative vegetation indices over simple reflectancebased indices that are traditionally used for remote sensing of vegetation.The idea of using reflectance derivatives instead of simple reflectance spectra was proposed several decades ago.Despite this,it has not been widely used in monitoring systems because the derivatives lack reliable parameters.In addition,most satellite monitoring systems are not equipped with hyperspectral sensors,which are considered necessary for operating with the reflectance derivatives.Here,we present original data indicating that the chlorophyll-related derivative index D725/D702 we derived can be accurately estimated from a reflectance spectrum of 10 nm resolution that would be suitable for most satellite-based sensors.Furthermore,the index is not sensitive to soil reflectance and can therefore be used for testing of open crops.Presence of blanc reflectance is also unnecessary.Preliminary results of index testing are presented.Perspectives on using this and other derivative indices are discussed.

  19. Remote sensing-based vegetation indices for monitoring vegetation change in the semi-arid region of Sudan

    Science.gov (United States)

    R. A., Majdaldin; Osunmadewa, B. A.; Csaplovics, E.; Aralova, D.

    2016-10-01

    Land degradation, a phenomenon referring to (drought) in arid, semi-arid and dry sub-humid regions as a result of climatic variations and anthropogenic activities most especially in the semi-arid lands of Sudan, where vast majority of the rural population depend solely on agriculture and pasture for their daily livelihood, the ecological pattern had been greatly influenced thereby leading to loss of vegetation cover coupled with climatic variability and replacement of the natural tree composition with invasive mesquite species. The principal aim of this study is to quantitatively examine the vigour of vegetation in Sudan through different vegetation indices. The assessment was done based on indicators such as soil adjusted vegetation index (SAVI). Cloud free multi-spectral remotely sensed data from LANDSAT imagery for the dry season periods of 1984 and 2009 were used in this study. Results of this study shows conversion of vegetation to other land use type. In general, an increase in area covered by vegetation was observed from the NDVI results of 2009 which is a contrast of that of 1984. The results of the vegetation indices for NDVI in 1984 (vegetated area) showed that about 21% was covered by vegetation while 49% of the area were covered with vegetation in 2009. Similar increase in vegetated area were observed from the result of SAVI. The decrease in vegetation observed in 1984 is as a result of extensive drought period which affects vegetation productivity thereby accelerating expansion of bare surfaces and sand accumulation. Although, increase in vegetated area were observed from the result of this study, this increase has a negative impact as the natural vegetation are degraded due to human induced activities which gradually led to the replacement of the natural vegetation with invasive tree species. The results of the study shows that NDVI perform better than by SAVI.

  20. Detecting creeping thistle in sugar beet fields using vegetation indices

    DEFF Research Database (Denmark)

    Kazmi, Syed Wajahat Ali Shah; Garcia Ruiz, Francisco Jose; Nielsen, Jon

    2015-01-01

    In this article, we address the problem of thistle detection in sugar beet fields under natural, outdoor conditions. In our experiments, we used a commercial color camera and extracted vegetation indices from the images. A total of 474 field images of sugar beet and thistles were collected....... Stepwise linear regression selected nine out of 14 features and offered the highest accuracy of 97%. The results of LDA and MD were fairly close, making them both equally preferable. Finally, the results were validated by annotating images containing both sugar beet and thistles using the trained...... classifiers. The validation experiments showed that sunlight followed by the size of the plant, which is related to its growth stage, are the two most important factors affecting the classification. In this study, the best results were achieved for images of young sugar beet (in the seventh week) under...

  1. Multisensor Comparisons for Validation of MODIS Vegetation Indices

    Institute of Scientific and Technical Information of China (English)

    CHENG Qian

    2006-01-01

    Vegetation indices (Ⅵ) are one of the standard science products available from the Moderate Resolution Imaging Spectroradiometer (MODIS). Validation of MODIS-Ⅵ products was an important prerequisite to using these variables for global modeling. In this study, validation of the MODIS-VI products including single-day MODIS, level 2 (gridded) daily MODIS surface reflectance (MOD09), 16-day composited MODIS (MOD13) was performed utilizing multisensor data from MODIS, Thematic Mapper (TM), and field radiometer, for a rice-planting region in southern China. The validation approach involved scaling up independent fine-grained datasets, including ground measurement and high spatial resolution imagery, to the coarser MODIS spatial resolutions. The 16-day composited MODIS reflectance and Ⅵ matched well with the ground measurement reflectance and Ⅵ. The Ⅵ of TM and MODIS were lower than the ground Ⅵ. The results demonstrated the accuracy, reliability, and utility of the MODIS-Ⅵ products for the study region.

  2. Narrow band vegetation indices overcome the saturation problem in biomass estimation

    NARCIS (Netherlands)

    Mutanga, O.; Skidmore, A.K.

    2004-01-01

    Remotely sensed vegetation indices such as NDVI, computed using the red and near infrared bands have been used to estimate pasture biomass. These indices are of limited value since they saturate in dense vegetation. In this study, we evaluated the potential of narrow band vegetation indices for char

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

    Science.gov (United States)

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

    2011-08-01

    How urban vegetation was influenced by three decades of intensive urbanization in China is of great interest but rarely studied. In this paper, we used satellite derived Normalized Difference Vegetation Index (NDVI) and socioeconomic data to evaluate effects of urbanization on vegetation cover in China's 117 metropolises over the last three decades. Our results suggest that current urbanization has caused deterioration of urban vegetation across most cities in China, particularly in East China. At the national scale, average urban area NDVI (NDVI(u)) significantly decreased during the last three decades (P < 0.01), and two distinct periods with different trends can be identified, 1982-1990 and 1990-2006. NDVI(u) did not show statistically significant trend before 1990 but decrease remarkably after 1990 (P < 0.01). Different regions also showed difference in the timing of NDVI(u) turning point. The year when NDVI(u) started to decline significantly for Central China and East China was 1987 and 1990, respectively, while NDVI(u) in West China remained relatively constant until 1998. NDVI(u) changes in the Yangtze River Delta and the Pearl River Delta, two regions which has been undergoing the most rapid urbanization in China, also show different characteristics. The Pearl River Delta experienced a rapid decline in NDVI(u) from the early 1980s to the mid-1990s; while in the Yangtze River Delta, NDVI(u) did not decline significantly until the early 1990s. Such different patterns of NDVI(u) changes are closely linked with policy-oriented difference in urbanization dynamics of these regions, which highlights the importance of implementing a sustainable urban development policy.

  4. MODIS/TERRA MOD13A3 Vegetation Indices Monthly L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  5. MODIS/AQUA MYD13A2 Vegetation Indices 16-Day L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  6. MODIS/AQUA MYD13A3 Vegetation Indices Monthly L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  7. MODIS/TERRA MOD13A2 Vegetation Indices 16-Day L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  8. MODIS/TERRA MOD13A1 Vegetation Indices 16-Day L3 Global 500m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  9. MODIS/AQUA MYD13Q1 Vegetation Indices 16-Day L3 Global 250m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  10. MODIS/AQUA MYD13A1 Vegetation Indices 16-Day L3 Global 500m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  11. MODIS/TERRA MOD13Q1 Vegetation Indices 16-Day L3 Global 250m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  12. Estimation of arsenic in agricultural soils using hyperspectral vegetation indices of rice.

    Science.gov (United States)

    Shi, Tiezhu; Liu, Huizeng; Chen, Yiyun; Wang, Junjie; Wu, Guofeng

    2016-05-05

    This study systematically analyzed the performance of multivariate hyperspectral vegetation indices of rice (Oryza sativa L.) in estimating the arsenic content in agricultural soils. Field canopy reflectance spectra was obtained in the jointing-booting growth stage of rice. Newly developed and published multivariate vegetation indices were initially calculated to estimate soil arsenic content. The well-performing vegetation indices were then selected using successive projections algorithm (SPA), and the SPA selected vegetation indices were adopted to calibrate a multiple linear regression model for estimating soil arsenic content. Results showed that a three-band vegetation index (R716-R568)/(R552-R568) performed best in the newly developed vegetation indices in estimating soil arsenic content. The photochemical reflectance index (PRI) and red edge position (REP) performed well in the published vegetation indices. Moreover, the linear combination of two vegetation indices ((R716-R568)/(R552-R568) and REP) selected using SPA improved the estimation of soil arsenic content. These results indicated that the newly developed three-band vegetation index (R716-R568)/(R552-R568) might be recommended as an indicator for estimating soil arsenic content in the study area. PRI and REP could be used as universal vegetation indices for monitoring soil arsenic contamination.

  13. Radar vegetation indices for estimating the vegetation water content of rice and soybean

    Science.gov (United States)

    Vegetation water content (VWC) is an important biophysical parameter and has a significant role in the retrieval of soil moisture using microwave remote sensing. In this study, the Radar Vegetation Index (RVI) was evaluated for estimating VWC. Analysis utilized a data set obtained using a ground-bas...

  14. Estimating potato leaf chlorophyll content using ratio vegetation indices

    NARCIS (Netherlands)

    Kooistra, Lammert; Clevers, Jan G.P.W.

    2016-01-01

    Chlorophyll content at leaf level is an important variable because of its crucial role in photosynthesis and in understanding plant functioning. In this study, we tested the hypothesis that the ratio of a vegetation index (VI) for estimating canopy chlorophyll content (CCC) and one for estimating le

  15. Temporal Trends and Spatial Variability of Vegetation Phenology over the Northern Hemisphere during 1982-2012

    OpenAIRE

    Siyuan Wang; Bojuan Yang; Qichun Yang; Linlin Lu; Xiaoyue Wang; Yaoyao Peng

    2016-01-01

    Satellite-derived vegetation phenology has been recognized as a key indicator for detecting changes in the terrestrial biosphere in response to global climate change. However, multi-decadal changes and spatial variation of vegetation phenology over the Northern Hemisphere and their relationship to climate change have not yet been fully investigated. In this article, we investigated the spatial variability and temporal trends of vegetation phenology over the Northern Hemisphere by calibrating ...

  16. Vegetation Index and Phenology (VIP) Vegetation Indices 15Days Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  17. Vegetation Index and Phenology (VIP) Vegetation Indices Daily Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  18. Vegetation Index and Phenology (VIP) Vegetation Indices Monthly Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  19. Vegetation Index and Phenology (VIP) Vegetation Indices 7Days Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  20. 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.

  1. Irrigation Requirement Estimation Using Vegetation Indices and Inverse Biophysical Modeling

    Science.gov (United States)

    Bounoua, Lahouari; Imhoff, Marc L.; Franks, Shannon

    2010-01-01

    We explore an inverse biophysical modeling process forced by satellite and climatological data to quantify irrigation requirements in semi-arid agricultural areas. We constrain the carbon and water cycles modeled under both equilibrium, balance between vegetation and climate, and non-equilibrium, water added through irrigation. We postulate that the degree to which irrigated dry lands vary from equilibrium climate conditions is related to the amount of irrigation. The amount of water required over and above precipitation is considered as an irrigation requirement. For July, results show that spray irrigation resulted in an additional amount of water of 1.3 mm per occurrence with a frequency of 24.6 hours. In contrast, the drip irrigation required only 0.6 mm every 45.6 hours or 46% of that simulated by the spray irrigation. The modeled estimates account for 87% of the total reported irrigation water use, when soil salinity is not important and 66% in saline lands.

  2. Evaluation of vegetation indices for rangeland biomass estimation in the Kimberley area of Western Australia

    NARCIS (Netherlands)

    Mundava, C.; Helmholtz, P.; Schut, A.G.T.; Corner, R.; McAtee, B.; Lamb, D.W.

    2014-01-01

    The objective of this paper is to test the relationships between Above Ground Biomass (AGB) and remotely sensed vegetation indices for AGB assessments in the Kimberley area in Western Australia. For 19 different sites, vegetation indices were derived from eight Landsat ETM+ scenes over a period of t

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

    Science.gov (United States)

    Xu, Han-qiu; Zhang, Tie-jun

    2011-07-01

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

  4. 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 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 crop yields and

  5. Exploring Connections between Global Climate Indices and African Vegetation Phenology

    Science.gov (United States)

    Brown, Molly E.; deBeurs, Kirsten; Vrieling, Anton

    2009-01-01

    Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the continent in Africa. Agriculturally destructive droughts and floods are monitored from space using satellite remote sensing by organizations seeking to provide quantitative and predictive information about food security crises. Better knowledge on the relation between climate indices and food production may increase the use of these indices in famine early warning systems and climate outlook forums on the continent. Here we explore the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), the Multivariate ENSO Index (MEI) and the Southern Oscillation Index (SOI). We explore spatial relationships between growing conditions as measured by the NDVI and the five climate indices in Eastern, Western and Southern Africa to determine the regions and periods when they have a significant impact. The focus is to provide a clear indication as to which climate index has the most impact on the three regions during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by variations in the climate indices. The particular climate index and the timing showing highest correlation depended heavily on the region examined. The research shows that climate indices can contribute to understanding growing season variability in Eastern, Western and Southern Africa.

  6. MODIS/AQUA MYD13A3 Vegetation Indices Monthly L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  7. MODIS/AQUA MYD13A2 Vegetation Indices 16-Day L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  8. MODIS/TERRA MOD13C2 Vegetation Indices Monthly L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  9. MODIS/AQUA MYD13C2 Vegetation Indices Monthly L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  10. MODIS/TERRA MOD13Q1 Vegetation Indices 16-Day L3 Global 250m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  11. MODIS/AQUA MYD13Q1 Vegetation Indices 16-Day L3 Global 250m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  12. MODIS/AQUA MYD13A1 Vegetation Indices 16-Day L3 Global 500m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  13. MODIS/TERRA MOD13A1 Vegetation Indices 16-Day L3 Global 500m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  14. MODIS/TERRA MOD13A2 Vegetation Indices 16-Day L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  15. MODIS/TERRA MOD13A3 Vegetation Indices Monthly L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  16. Using Landsat Vegetation Indices to Estimate Impervious Surface Fractions for European Cities

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Fensholt, Rasmus; Drews, Martin

    2015-01-01

    Impervious surfaces (IS) are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy...... and applicability of vegetation indices (VI), from Landsat imagery, to estimate IS fractions for European cities. The accuracy of three different measures of vegetation cover is examined for eight urban areas at different locations in Europe. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted...... Vegetation Index (SAVI) are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR), and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs ≈ 10%, MBE’s

  17. Indicator microorganisms in fresh vegetables from “farm to fork” in Rwanda

    NARCIS (Netherlands)

    Ssemanda, James Noah; Reij, Martine; Muvunyi, Claude Mambo; Joosten, Han; Zwietering, Marcel H.

    2017-01-01

    Microbial safety of ready-to-eat vegetables is currently a global concern. We studied indicator microorganisms in fresh vegetables from “farm to fork” in Rwanda, to identify possible trends in microbial counts along the supply chain in a developing country. A total of 453 samples were taken across

  18. Sensitivity Analysis of Remote Sensing Data: Comparing the Response of Vegetation Indices in Tropical Areas.

    Science.gov (United States)

    Bonifaz, R.

    2005-12-01

    During the past two decades, satellite remote sensing systems possessing high temporal resolution, but typically moderate or coarse spatial resolution, have increasingly been used to characterize and map vegetation dynamics. Assessing the seasonality of tropical vegetation has, however, been especially challenging. Tropical regimes of temperature and precipitation are generally less variable and pronounced than those in other biomes, and variations in plant growth are often more subtle. Using samples from selected tropical land cover types (tropical rain forest, tropical grasses, tropical deciduous forest, mixed forest and agricultural areas), sensitivity analysis will be carried out comparing different 'greenness' indices such as the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI) and the Wide Dynamic Range Vegetation Index (WDRVI) derived from the MODIS/TERRA sensor. This analysis will potentially allow the selection of the best index to describe the particular behavior of tropical vegetation for further characterization of seasonal changes of such areas.

  19. Satellite-derived methane emissions from inundation in Bangladesh

    Science.gov (United States)

    Peters, C. N.; Bennartz, R.; Hornberger, G. M.

    2017-05-01

    The uncertainty in methane (CH4) source strength of rice fields and wetlands is particularly high in South Asia CH4 budgets. We used satellite observations of CH4 column mixing ratios from Atmospheric Infrared Sounder (AIRS), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Greenhouse Gases Observing Satellite (GOSAT) to estimate the contribution of Bangladesh emissions to atmospheric CH4 concentrations. Using satellite-derived inundation area as a proxy for source area, we developed a simple inverse advection model that estimates average annual CH4 surface fluxes to be 4, 9, and 19 mg CH4 m-2 h-1 in AIRS, SCIAMACHY, and GOSAT, respectively. Despite this variability, our flux estimates varied over a significantly narrower range than reported values for CH4 surface fluxes from a survey of 32 studies reporting ground-based observations between 0 and 260 mg CH4 m-2 h-1. Upscaling our satellite-derived surface flux estimates, we estimated total annual CH4 emissions for Bangladesh to be 1.3 ± 3.2, 1.8 ± 2.0, 3.1 ± 1.6 Tg yr-1, depending on the satellite. Our estimates of total emissions are in line with the median of total emission values for Bangladesh reported in earlier studies.

  20. Evaluation of Radar Vegetation Indices for Vegetation Water Content Estimation Using Data from a Ground-Based SMAP Simulator

    Science.gov (United States)

    Srivastava, Prashant K.; O'Neill, Peggy; Cosh, Michael; Lang, Roger; Joseph, Alicia

    2015-01-01

    Vegetation water content (VWC) is an important component of microwave soil moisture retrieval algorithms. This paper aims to estimate VWC using L band active and passive radar/radiometer datasets obtained from a NASA ground-based Soil Moisture Active Passive (SMAP) simulator known as ComRAD (Combined Radar/Radiometer). Several approaches to derive vegetation information from radar and radiometer data such as HH, HV, VV, Microwave Polarization Difference Index (MPDI), HH/VV ratio, HV/(HH+VV), HV/(HH+HV+VV) and Radar Vegetation Index (RVI) are tested for VWC estimation through a generalized linear model (GLM). The overall analysis indicates that HV radar backscattering could be used for VWC content estimation with highest performance followed by HH, VV, MPDI, RVI, and other ratios.

  1. Soil TPH concentration estimation using vegetation indices in an oil polluted area of eastern China

    National Research Council Canada - National Science Library

    Zhu, Linhai; Zhao, Xuechun; Lai, Liming; Wang, Jianjian; Jiang, Lianhe; Ding, Jinzhi; Liu, Nanxi; Yu, Yunjiang; Li, Junsheng; Xiao, Nengwen; Zheng, Yuanrun; Rimmington, Glyn M

    2013-01-01

    ... (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution...

  2. Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis

    Science.gov (United States)

    Choudhury, Bhaskar J.

    1987-01-01

    A two-stream approximation to the radiative-transfer equation is used to calculate the vegetation indices (simple ratio and normalized difference), the fraction of incident photosynthetically active radiation (PAR) absorbed by the canopy, and the daily mean canopy net photosynthesis under clear-sky conditions. The model calculations are tested against field observations over wheat, cotton, corn, and soybean. The relationships between the vegetation indices and radiation absorption or net photosynthesis are generally found to be curvilinear, and changes in the soil reflectance affected these relationships. The curvilinearity of the relationship between normalized differences and PAR absorption decreases as the magnitude of soil reflectance increases. The vegetation indices might provide the fractional radiation absorption with some a priori knowledge about soil reflectance. The relationship between the vegetation indices and net photosynthesis must be distinguished for C3 and C4 crops. Effects of spatial heterogeneity are discussed.

  3. Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis

    Science.gov (United States)

    Choudhury, Bhaskar J.

    1987-01-01

    A two-stream approximation to the radiative-transfer equation is used to calculate the vegetation indices (simple ratio and normalized difference), the fraction of incident photosynthetically active radiation (PAR) absorbed by the canopy, and the daily mean canopy net photosynthesis under clear-sky conditions. The model calculations are tested against field observations over wheat, cotton, corn, and soybean. The relationships between the vegetation indices and radiation absorption or net photosynthesis are generally found to be curvilinear, and changes in the soil reflectance affected these relationships. The curvilinearity of the relationship between normalized differences and PAR absorption decreases as the magnitude of soil reflectance increases. The vegetation indices might provide the fractional radiation absorption with some a priori knowledge about soil reflectance. The relationship between the vegetation indices and net photosynthesis must be distinguished for C3 and C4 crops. Effects of spatial heterogeneity are discussed.

  4. Mapping swamp timothy (Cripsis schenoides) seed productivity using spectral values and vegetation indices in managed wetlands

    Energy Technology Data Exchange (ETDEWEB)

    Rahilly, P.J.A.; Li, D.; Guo, Q.; Zhu, J.; Ortega, R.; Quinn, N.W.T.; Harmon, T.C.

    2010-01-15

    This work examines the potential to predict the seed productivity of a key wetland plant species using spectral reflectance values and spectral vegetation indices. Specifically, the seed productivity of swamp timothy (Cripsis schenoides) was investigated in two wetland ponds, managed for waterfowl habitat, in California's San Joaquin Valley. Spectral reflectance values were obtained and associated spectral vegetation indices (SVI) calculated from two sets of high resolution aerial images (May 11, 2006 and June 9, 2006) and were compared to the collected vegetation data. Vegetation data were collected and analyzed from 156 plots for total aboveground biomass, total aboveground swamp timothy biomass, and total swamp timothy seed biomass. The SVI investigated included the Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Global Environment Monitoring Index (GEMI). We evaluated the correlation of the various SVI with in situ vegetation measurements for linear, quadratic, exponential and power functions. In all cases, the June image provided better predictive capacity relative to May, a result that underscores the importance of timing imagery to coincide with more favorable vegetation maturity. The north pond with the June image using SR and the exponential function (R{sup 2}=0.603) proved to be the best predictor of swamp timothy seed productivity. The June image for the south pond was less predictive, with TSAVI and the exponential function providing the best correlation (R{sup 2}=0.448). This result was attributed to insufficient vegetal cover in the south pond (or a higher percentage of bare soil) due to poor drainage conditions which resulted in a delay in swamp timothy germination. The results of this work suggest that spectral reflectance can be used to estimate seed productivity in managed seasonal

  5. The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands—Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements

    Directory of Open Access Journals (Sweden)

    Mitsunori Ishihara

    2015-10-01

    Full Text Available A ground-based network of spectral observations is useful for ecosystem monitoring and validation of satellite data. However, these observations contain inherent uncertainties due to the change of sunlight conditions. This study investigated the impact of changing solar zenith angles and diffuse/direct light conditions on the consistency of vegetation indices (normalized difference vegetation index (NDVI and green-red vegetation index (GRVI derived from ground-based spectral measurements in three different types of cropland (paddy field, upland field, cultivated grassland in Japan. In general, the vegetation indices decreased with decreasing solar zenith angle. This response was affected significantly by the growth stage and diffuse/direct light conditions. The decreasing response of the NDVI to the decreasing solar zenith angle was high during the middle growth stage (0.4 < NDVI < 0.8. On the other hand, a similar response of the GRVI was evident except in the early growth stage (GRVI < 0. The response of vegetation indices to the solar zenith angle was evident under clear sky conditions but almost negligible under cloudy sky conditions. At large solar zenith angles, neither the NDVI nor the GRVI were affected by diffuse/direct light conditions in any growth stage. These experimental results were supported well by the results of simulations based on a physically-based canopy reflectance model (PROSAIL. Systematic selection of the data from continuous diurnal spectral measurements in consideration of the solar light conditions would be effective for accurate and consistent assessment of the canopy structure and functioning.

  6. Estimating Ground-Level Particulate Matter (PM) Concentration using Satellite-derived Aerosol Optical Depth (AOD)

    Science.gov (United States)

    Park, Seohui; Im, Jungho

    2017-04-01

    Atmospheric aerosols are strongly associated with adverse human health effects. In particular, particulate matter less than 10 micrometers and 2.5 micrometers (i.e., PM10 and PM2.5, respectively) can cause cardiovascular and lung diseases such as asthma and chronic obstructive pulmonary disease (COPD). Air quality including PM has typically been monitored using station-based in-situ measurements over the world. However, in situ measurements do not provide spatial continuity over large areas. An alternative approach is to use satellite remote sensing as it provides data over vast areas at high temporal resolution. The literature shows that PM concentrations are related with Aerosol Optical Depth (AOD) that is derived from satellite observations, but it is still difficult to identify PM concentrations directly from AOD. Some studies used statistical approaches for estimating PM concentrations from AOD while some others combined numerical models and satellite-derived AOD. In this study, satellite-derived products were used to estimate ground PM concentrations based on machine learning over South Korea. Satellite-derived products include AOD from Geostationary Ocean Color Imager (GOCI), precipitation from Tropical Rainfall Measuring Mission (TRMM), soil moisture from AMSR-2, elevation from Shuttle Radar Topography Mission (SRTM), and land cover, land surface temperature and normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS). PM concentrations data were collected from 318 stations. A statistical ordinary least squares (OLS) approach was also tested and compared with the machine learning approach (i.e., random forest). PM concentration was estimated during spring season (from March to May) in 2015 that typically shows high concentration of PM. The randomly selected 80% of data were used for model calibration and the remaining 20% were used for validation. The developed models were further tested for prediction of PM

  7. Application of satellite derived information for disaster risk reduction: vulnerability assessment for southwest coast of Pakistan

    Science.gov (United States)

    Rafiq, Lubna; Blaschke, Thomas; Zeil, Peter

    2010-10-01

    The SW-coast of Pakistan is vulnerable to natural disasters, such as cyclones and tsunamis. Lack of spatially referenced information is a major hinder for proper disaster risk management programs in Pakistan, but satellite remote sensing being reliable, fast and spatially referenced information can be used as an important component in various natural disaster risk reduction activities. This study aimed to investigate vulnerability of coastal communities to cyclone and tsunamis based on satellite derived information. It is observed that SPOT-5 is relevant source on threatened features with respect to certain vulnerabilities like road, settlements, infrastructure and used in preparation of hazard zonation and vulnerability maps. Landsat ETM found very useful in demarcation of flood inundated areas. The GIS integrated evaluation of LANDSAT and ASTER GDEM helps identify low lying areas most susceptible to flooding and inundation by cyclone surges and tsunamis. The GIS integrated evaluation of SPOT, LANDSAT and ASTER GDEM data helps identify areas and infrastructure most vulnerable to cyclone surges and tsunami. Additionally, analysis of the vulnerability of critical infrastructures (schools, hospitals) within hazard zones provides indicators for the degree of spatial exposure to disaster. Satellite derived information in conjunction with detailed surveys of hazard prone areas can provide comprehensive vulnerability and risk analysis.

  8. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains.

    Science.gov (United States)

    Kooistra, L; Salas, E A L; Clevers, J G P W; Wehrens, R; Leuven, R S E W; Nienhuis, P H; Buydens, L M C

    2004-01-01

    This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The relations were evaluated using simple linear regression in combination with two spectral vegetation indices: the Difference Vegetation Index (DVI) and the Red-Edge Position (REP). In addition, a multivariate regression approach using partial least squares (PLS) regression was adopted. The three methods achieved comparable results. The best R(2) values for the relation between metals concentrations and vegetation reflectance were obtained for grass vegetation and ranged from 0.50 to 0.73. Herbaceous species displayed a larger deviation from the established relationships, resulting in lower R(2) values and larger cross-validation errors. The results corroborate the potential of hyperspectral remote sensing to contribute to the survey of elevated metal concentrations in floodplain soils under grassland using the spectral response of the vegetation as an indicator. Additional constraints will, however, have to be taken into account, as results are resolution- and location-dependent.

  9. Angular sensitivity of vegetation indices derived from CHRIS/PROBA data

    NARCIS (Netherlands)

    Verrelst, J.; Schaepman, M.E.; Kötz, B.; Kneubühler, M.

    2008-01-01

    View angle effects present in spectral vegetation indices can either be regarded as an added source of uncertainty for variable retrieval or as a source of additional information, enhancing the variable retrieval; however, the magnitude of these angular effects remains for most indices unknown or un

  10. Cryptogamic covers control spectral vegetation indices and their seasonal variation in dryland systems

    Science.gov (United States)

    Rodriguez-Caballero, Emilio; Knerr, Tanja; Büdel, Burkhard; Hill, Joachim; Weber, Bettina

    2016-04-01

    Remote sensing data provide spatially continuous information on vegetation dynamics by means of long-term series of vegetation indices (VI). However, most of these indices show problematic results in drylands, as a consequence of the scarce vegetation cover and the strong effect of the open space between plants. Open soil between plants as well as rock surfaces in dryland ecosystems are often covered by complex communities of cyanobacteria, algae, lichens and mosses. These cryptogamic covers show a faster phenological response to water pulses than vascular vegetation, turning green almost immediately after the first rain following a dry period and modifying their spectral response. However, only few studies quantified the effects of cryptogamic covers on VI, and none of them considered them in the analysis of temporal series of satellite images, where differences in physiology and reflectance between cryptogamic covers and vascular vegetation interact. For this reason, we quantified how cryptogamic covers modify the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), based on field and lab spectral measurements. For two different biocrust-dominated ecosystems within the South African Karoo, we analyzed the effect of biocrusts on spectrally analyzed vegetation dynamics using multi-temporal series of VI obtained from LANDSAT and MODIS images . Cryptogamic covers exerted a considerable effect on both NDVI and EVI calculated from field and lab spectra. As previously described for vegetation, also increasing cryptogam cover caused an increase of both VI values, and this effect also became apparent at LANDSAT image scale. However, the response of VI extracted from LANDSAT images upon environmental factors differed between pixels dominated by cryptogams and vascular vegetation. Whereas vegetation showed the highest changes in VI values in response to water availability and temperature, cryptogamic covers, which are the main surface

  11. The role of spatial and spectral resolution on the effectiveness of satellite-based vegetation indices

    Science.gov (United States)

    Psomiadis, Emmanouil; Dercas, Nicholas; Dalezios, Nicolas R.; Spyropoulos, Nikolaos V.

    2016-10-01

    Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop needs or health problems and provide solutions for a better crop management. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. In the present study, the experimental area is located near the village Eleftherion of Larissa Prefecture in the Thessaly Plain, and consisted of two adjacent agricultural fields of cotton and corn. Imagery from WorldView-2 (WV2) satellite platform was obtained from European Space Imaging and Landsat-8 (L8) free of charge data were downloaded from the United States Geological Survey (USGS) archive. The images were selected for a four month span to evaluate continuity with respect to vegetation growth variation. VIs for each satellite platform data such as the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Fraction Photosynthetically Radiation (FPAR) were calculated. The comparison of these VIs produced from the two satellite systems with different spatial and spectral resolution was made for each growth stage of the crops and their results were analyzed in order to examine their correlation. Utilizing the WV2 new spectral data, several innovative chlorophyll and vegetation indices were created and evaluated so as to reveal their effectiveness in the detection of problematic plant growth areas. The Green Chlorophyll index appeared to be the most efficient index for the delineation of these areas.

  12. Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards

    Directory of Open Access Journals (Sweden)

    Jonathan Van Beek

    2015-08-01

    Full Text Available Yield and quality estimations provide vital information to fruit growers, yet require accurate monitoring throughout the growing season. To this end, the temporal dependency of fruit yield and quality estimations through spectral vegetation indices was investigated in irrigated and rainfed pear orchards. Both orchards were monitored throughout three consecutive growing seasons, including spectral measurements (i.e., hyperspectral canopy reflectance measurements as well as yield determination (i.e., total yield and number of fruits per tree and quality assessment (i.e., fruit firmness, total soluble solids and fruit color. The results illustrated a clear association between spectral vegetation indices and both fruit yield and fruit quality (|r| > 0.75; p < 0.001. However, the correlations between vegetation indices and production variables varied throughout the growing season, depending on the phenological stage of fruit development. In the irrigated orchard, index values showed a strong association with production variables near time of harvest (|r| > 0.6; p < 0.001, while in the rainfed orchard, index values acquired during vegetative growth periods presented stronger correlations with fruit parameters (|r| > 0.6; p < 0.001. The improved planning of remote sensing missions during (rainfed orchards and after (irrigated orchards vegetative growth periods could enable growers to more accurately predict production outcomes and improve the production process.

  13. Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape

    Directory of Open Access Journals (Sweden)

    Stephen G. Nelson

    2008-03-01

    Full Text Available Vegetation indices (VIs are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT, Surface Energy Balance (SEB, and Global Climate Models (GCM. These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with "Big Leaf" SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes.

  14. MODIS/TERRA MOD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  15. MODIS/AQUA MYD13C2 Vegetation Indices Monthly L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  16. MODIS/AQUA MYD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  17. MODIS/TERRA MOD13C1 Vegetation Indices Monthly L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  18. Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data

    Energy Technology Data Exchange (ETDEWEB)

    Chandola, Varun [ORNL; Vatsavai, Raju [ORNL; Hui, Dafeng [ORNL; Gu, Lianhong [ORNL; Bhaduri, Budhendra L [ORNL

    2010-01-01

    Characterizing vegetation phenology is a highly significant problem, due to its importance in regulating ecosystem carbon cycling, interacting with climate changes, and decision-making of croplands managements. While ground based sensors, such as the AmeriFlux sensors, can provide measurements at high temporal resolution (every hour) and can be used to accurately calculate vegetation phenology indices, they are limited to only a few sites. Remote sensing data, such as the Normalized Difference Vegetation Index (NDVI), collected using the MODerate Resolution Imaging Spectroradiometer (MODIS), can provide global coverage, though at a much coarser temporal resolution (16 days). In this study we use data mining based time series segmentation methods to derive phenology indices from NDVI data, and compare it with the phenology indices derived from the AmeriFlux data using a widely used model fitting approach. Results show a significant correlation (as high as 0.60) between the indices derived from these two different data sources. This study demonstrates that data driven methods can be effectively employed to provide realistic estimates of vegetation phenology indices using periodic time series data and has the potential to be used at large spatial scales and for long-term remote sensing data.

  19. Effects of Simulated Acid Rain on Main Nutritional Indicators of Three Leafy Vegetables

    Institute of Scientific and Technical Information of China (English)

    MENG He; DONG De-ming; WANG Ju; YANG Kai-ning; TIAN Lei; SUN Wei; FANG Chun-sheng

    2011-01-01

    The purpose of this paper was to identify content changes in the main nutritional indicators of three common leafy vegetables, and to provide a theoretical basis for the protection of leafy vegetables from acid rain. The experiment investigated the effects of simulated acid rain on four main nutritional indicators, including soluble sugar,total free amino acid, soluble protein and vitamin C during the application of simulated acid rain(SAR) in pakchoi( Brassica rapa chihensis), rape(Brassica campestris L.) and lettuce( Lactuca sativa Linn. var. ramnosa Hort). The vegetables were respectively exposed to SAR of pH=7.0, 5.6, 5.0, 4.0, 3.0 and a control level of pH=6.5. The concentrations of the four main nutritional indicators were determined at harvest. The results show that nutritional quality of the three leafy vegetable species decreased with the declining of pH values of SAR. The higher the acidity of SAR was, the more significant the inhibitions were. Nutritional quality of lettuce was the most affected by simulated acid rain, followed by pakchoi and rape. The change range of soluble protein content was higher than those of the other three indicators' contents, which indicates that soluble protein is most sensitive to simulated acid rain.

  20. Using Landsat Vegetation Indices to Estimate Impervious Surface Fractions for European Cities

    Directory of Open Access Journals (Sweden)

    Per Skougaard Kaspersen

    2015-06-01

    Full Text Available Impervious surfaces (IS are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy and applicability of vegetation indices (VI, from Landsat imagery, to estimate IS fractions for European cities. The accuracy of three different measures of vegetation cover is examined for eight urban areas at different locations in Europe. The Normalized Difference Vegetation Index (NDVI and Soil Adjusted Vegetation Index (SAVI are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR, and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs ≈ 10%, MBE’s < 2% of sub-pixel imperviousness, and are found to be applicable for cities with dissimilar climatic and vegetative conditions. The VI/IS relationship across cities is examined by quantifying the MAEs and MBEs between all combinations of models and urban areas. Also, regional regression models are developed by compiling data from multiple cities to examine the potential for developing and applying a single regression model to estimate IS fractions for numerous urban areas without reducing the accuracy considerably. Our findings indicate that the models can be applied broadly for multiple urban areas, and that the accuracy is reduced only marginally by applying the regional models. SAVI is identified as a superior index for the development of regional quantification models. The findings of this study highlight that IS fractions, and spatiotemporal changes herein, can be mapped by use of simple regression models based on VIs from remote sensors, and that the method presented enables simple, accurate and resource efficient quantification of IS.

  1. Deforestation and benthic indicators: how much vegetation cover is needed to sustain healthy Andean streams?

    Directory of Open Access Journals (Sweden)

    Carlos Iñiguez-Armijos

    Full Text Available Deforestation in the tropical Andes is affecting ecological conditions of streams, and determination of how much forest should be retained is a pressing task for conservation, restoration and management strategies. We calculated and analyzed eight benthic metrics (structural, compositional and water quality indices and a physical-chemical composite index with gradients of vegetation cover to assess the effects of deforestation on macroinvertebrate communities and water quality of 23 streams in southern Ecuadorian Andes. Using a geographical information system (GIS, we quantified vegetation cover at three spatial scales: the entire catchment, the riparian buffer of 30 m width extending the entire stream length, and the local scale defined for a stream reach of 100 m in length and similar buffer width. Macroinvertebrate and water quality metrics had the strongest relationships with vegetation cover at catchment and riparian scales, while vegetation cover did not show any association with the macroinvertebrate metrics at local scale. At catchment scale, the water quality metrics indicate that ecological condition of Andean streams is good when vegetation cover is over 70%. Further, macroinvertebrate community assemblages were more diverse and related in catchments largely covered by native vegetation (>70%. Our results suggest that retaining an important quantity of native vegetation cover within the catchments and a linkage between headwater and riparian forests help to maintain and improve stream biodiversity and water quality in Andean streams affected by deforestation. This research proposes that a strong regulation focused to the management of riparian buffers can be successful when decision making is addressed to conservation/restoration of Andean catchments.

  2. Deforestation and benthic indicators: how much vegetation cover is needed to sustain healthy Andean streams?

    Science.gov (United States)

    Iñiguez-Armijos, Carlos; Leiva, Adrián; Frede, Hans-Georg; Hampel, Henrietta; Breuer, Lutz

    2014-01-01

    Deforestation in the tropical Andes is affecting ecological conditions of streams, and determination of how much forest should be retained is a pressing task for conservation, restoration and management strategies. We calculated and analyzed eight benthic metrics (structural, compositional and water quality indices) and a physical-chemical composite index with gradients of vegetation cover to assess the effects of deforestation on macroinvertebrate communities and water quality of 23 streams in southern Ecuadorian Andes. Using a geographical information system (GIS), we quantified vegetation cover at three spatial scales: the entire catchment, the riparian buffer of 30 m width extending the entire stream length, and the local scale defined for a stream reach of 100 m in length and similar buffer width. Macroinvertebrate and water quality metrics had the strongest relationships with vegetation cover at catchment and riparian scales, while vegetation cover did not show any association with the macroinvertebrate metrics at local scale. At catchment scale, the water quality metrics indicate that ecological condition of Andean streams is good when vegetation cover is over 70%. Further, macroinvertebrate community assemblages were more diverse and related in catchments largely covered by native vegetation (>70%). Our results suggest that retaining an important quantity of native vegetation cover within the catchments and a linkage between headwater and riparian forests help to maintain and improve stream biodiversity and water quality in Andean streams affected by deforestation. This research proposes that a strong regulation focused to the management of riparian buffers can be successful when decision making is addressed to conservation/restoration of Andean catchments.

  3. Using vegetation indices as input into ramdom forest for soybean and weed classification

    Science.gov (United States)

    Weed management is a major component of a soybean (Glycine max L.) production system; thus, managers need tools to help them distinguish soybean from weeds. Vegetation indices derived from light reflectance properties of plants have shown promise as tools to enhance differences among plants. The o...

  4. Effects of Simulated Acid Rain on Main Nutritional Indicators of Three Leafy Vegetables

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The purpose of this paper was to identify content changes in the main nutritional indicators of three common leafy vegetables, and to provide a theoretical basis for the protection of leafy vegetables from acid rain. The experiment investigated the effects of simulated acid rain on four main nutritional indicators, including soluble sugar, total free amino acid, soluble protein and vitamin C during the application of simulated acid rain(SAR) in pakchoi(Brassica rapa chinensis), rape(Brassica campestris L.) and lettuce(Lactuca sativa Linn. var. ramosa Hort). The vegetables were respectively exposed to SAR of pH=7.0, 5.6, 5.0, 4.0, 3.0 and a control level of pH=6.5. The concentrations of the four main nutritional indicators were determined at harvest. The results show that nutritional quality of the three leafy vegetable species decreased with the declining of pH values of SAR. The higher the acidity of SAR was, the more significant the inhibitions were. Nutritional quality of lettuce was the most affected by simulated acid rain, followed by pakchoi and rape. The change range of soluble protein content was higher than those of the other three indicators' contents, which indicates that soluble protein is most sensitive to simulated acid rain.

  5. Initialization with diabatic heating from satellite-derived rainfall

    Science.gov (United States)

    Ma, Leiming; Chan, Johnny; Davidson, Noel E.; Turk, Joe

    2007-07-01

    In this paper, a new technique is proposed to improve initialization of a tropical cyclone (TC) prediction model using diabatic heating profiles estimated from a combination of both infrared satellite cloud imagery and satellite-derived rainfall. The method is termed Rainfall-defined Diabatic Heating, RDH. To examine the RDH performance, initialization and forecast experiments are made with the Australia Bureau of Meteorology Research Centre (BMRC) Tropical Cyclone — Limited Area Prediction System (TC-LAPS) for the case of TC Chris, which made landfall on the west coast of Australia during 3-6 Feb 2002. RDH is performed in three steps: 1) based on previous observational and numerical studies, reference diabatic heating profiles are firstly classified into three kinds: convective, stratiform or composite types; 2) NRL (Naval Research Laboratory) 3-hourly gridded satellite rainfall estimates are categorized as one of the three types according to the rain rate; 3) within a nudging phase of 24 h, the model-generated heating at each grid point during the integration is replaced by the reference heating profiles on the basis of the satellite-observed cloud top temperature and rainfall type. The results of sensitivity experiments show that RDH has a positive impact on the model initialization of TC Chris. The heating profiles generated by the model within the observed rainfall area show agreement with that of reference heating. That is, maximum heating is located in the lower troposphere for convective rainfall, and in the upper troposphere for stratiform rainfall. In response to the replaced heating and its impact on the TC structure, the model initial condition and forecasts of the track and intensity are improved.

  6. Relationships between vegetation indices and different burn and vegetation ratios: a multi-scale approach applied in a fire affected area

    Science.gov (United States)

    Pleniou, M.; Koutsias, N.

    2013-08-01

    Vegetation indices have been widely used in remote sensing literature for burned land mapping and monitoring. In the present study we used satellite data (IKONOS, LANDSAT, ASTER, MODIS) of multiple spectral (visible, near, shortwave infrared) and spatial (1-500 meters) resolutions, acquired shortly after a very destructive fire occurred in the mountain of Parnitha in Attica, Greece the summer of 2007. The aim of our study is to examine and evaluate the performance of some vegetation indices for burned land mapping and also to characterize the relationships between vegetation indices and the percent of fire-scorched (burned) and non fire-scorched (vegetated) areas. The available satellite images were processed geometrically, radiometrically and atmospherically. The very high resolution IKONOS imagery was served as a base to estimate the percent of cover of burned areas, bare soil and vegetation by applying the maximum likelihood classification algorithm. The percent of cover for each type was then correlated to vegetation indices for all the satellite images, and regression models were fit to characterize those relationships. In total 57 versions of some classical vegetation indices were computed using LANDSAT, ASTER and MODIS data. Most of them were modified by replacing Red with SWIR channel, as the latter has been proved sensitive to burned area discrimination. IPVI and NDVI showed a better performance among the indices tested to estimate the percent of vegetation, while most of the modified versions of the indices showed highest performance to estimate the percent of burned areas.

  7. Integrating Terrain and Vegetation Indices for Identifying Potential Soil Erosion Risk Area

    Institute of Scientific and Technical Information of China (English)

    Arabinda Sharma

    2010-01-01

    The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.

  8. [Effects and indications of spinal cord stimulation on the vegetative syndrome].

    Science.gov (United States)

    Funahashi, K; Komai, N; Ogura, M; Kuwata, T; Nakai, M; Tsuji, N

    1989-10-01

    The effects of spinal cord stimulation (SCS) on the vegetative syndrome were studied in six patients. Factors affecting the results were mentioned with a view to establishing indications as to whether or not the SCS should be performed. "Persistent vegetative states" were thought to be identical with Ohta's "vegetative syndrome" which consists of eleven signs. Six of these signs--polyphasic cycle of waking and sleeping, urinary incontinence, being bedridden and being tube fed etc--were important criteria of the vegetative syndrome. SCS was thought to be effective if one or more of the 6 signs disappeared after SCS. SCS was performed at level from C2 to C4 with a frequency of 25 to 120 Hz, an intensity of 2.5 to 6 volts, a pulse duration of 0.3 to 0.5 msec. and a duration of 3 to 11 hours per day. Neurological signs, ABR, CT/MRI, EEG and the grade of the vegetative syndrome were estimated before and after SCS. In the course of SCS, 2 of the 6 patients recovered from the vegetative syndrome. Both had a localized lesion in the brain stem without a cerebral lesion on CT/MRI, with bilateral appearance of the fifth peak with prolonged latency and decreased amplitude of main peaks on ABR. The other 4 patients showed little or no improvement. They all had diffuse cerebral atrophy or low density areas on CT and almost normal ABR. One of these patients, who suffered a cerebral contusion leading to transtentorial herniation with unilateral cerebral contusion on CT and unilateral disappearance of the fifth peak on ABR, showed no recovery from the vegetative syndrome.(ABSTRACT TRUNCATED AT 250 WORDS)

  9. A New EO-Based Indicator for Assessing and Monitoring Climate-Related Vegetation Stress

    Science.gov (United States)

    McCormick, Niall; Gobron, Nadine

    2016-08-01

    This paper describes a study in which a new environmental indicator, called Annual Vegetation Stress (AVS), has been developed, based on annual anomalies of satellite-measured Fraction of Absorbed Photosynthetically Active Radiation (FAPAR ), and used to map the area affected annually by vegetation stress during the period 2003-2014, for 108 selected developing countries. Analysis of the results for six countries in the "tropical and subtropical forests" ecoregion, reveals good correspondence between high AVS values, and the occurrence of climatic extremes (droughts) and anthropogenic disturbance (deforestation). The results for Equatorial Guinea suggest that the recent trend of large-scale droughts and rainfall deficits in Central and Western Africa, contribute to increased vegetation stress in the region's tropical rainforests. In East Timor there is evidence of a "biological lag" effect, whereby the main impacts of drought on the country's seasonally dry tropical forests are delayed until the year following the climate event.

  10. Soil phosphorus forms as quality indicators of soils under different vegetation covers.

    Science.gov (United States)

    Turrión, María-Belén; López, Olga; Lafuente, Francisco; Mulas, Rafael; Ruipérez, César; Puyo, Alberto

    2007-05-25

    The type of vegetation cover determines the physicochemical and biological properties of the soil over which they are developing. The objective of this study was to determine the effect of different vegetation covers on the forms of soil phosphorus, in order to know which of these forms can be used as a soil quality indicator. The experimental area was located on the acidic plateau at the North of Palencia (North Spain), where an area was selected vegetation covers very close to each other: pine (Pinus sylvestris), oak (Quercus pyrenaica), and three different shrub species (Arctostaphylos uva-ursi, Erica australis and Halimium alyssoides). The Ah horizon was sampled and pH, total organic C (C(org)), total N (N), cationic exchange capacity (CEC), sum of bases (S) and P forms by a sequential fractionation were analysed. Results showed that oak and A. uva-ursi improve the considered soil parameters (pH, C(org)/N ratio, CEC, and S) and provide soils of better quality. Inorganic soil P forms were influenced in greater extent by the vegetation cover than were P organic forms. Labile inorganic P forms could be used as indicators of soil quality. The organic P forms were less sensitive than inorganic ones to the indicated improvements.

  11. Evaluating Multispectral Images and Vegetation Indices for Precision Farming Applications from UAV Images

    Directory of Open Access Journals (Sweden)

    Sebastian Candiago

    2015-04-01

    Full Text Available Unmanned Aerial Vehicles (UAV-based remote sensing offers great possibilities to acquire in a fast and easy way field data for precision agriculture applications. This field of study is rapidly increasing due to the benefits and advantages for farm resources management, particularly for studying crop health. This paper reports some experiences related to the analysis of cultivations (vineyards and tomatoes with Tetracam multispectral data. The Tetracam camera was mounted on a multi-rotor hexacopter. The multispectral data were processed with a photogrammetric pipeline to create triband orthoimages of the surveyed sites. Those orthoimages were employed to extract some Vegetation Indices (VI such as the Normalized Difference Vegetation Index (NDVI, the Green Normalized Difference Vegetation Index (GNDVI, and the Soil Adjusted Vegetation Index (SAVI, examining the vegetation vigor for each crop. The paper demonstrates the great potential of high-resolution UAV data and photogrammetric techniques applied in the agriculture framework to collect multispectral images and evaluate different VI, suggesting that these instruments represent a fast, reliable, and cost-effective resource in crop assessment for precision farming applications.

  12. Comparison of Vegetation Indices and Red-edge Parameters for Estimating Grassland Cover from Canopy Reflectance Data

    Institute of Scientific and Technical Information of China (English)

    Zhan-Yu Liu; Jing-Feng Huang; Xin-Hong Wu; Yong-Ping Dong

    2007-01-01

    There has been a great deal of interests in the estimation of grassland biophysical parameters such as percentage of vegetation cover (PVC), aboveground biomass, and leaf-area index with remote sensing data at the canopy scale. In this paper, the percentage of vegetation cover was estimated from vegetation indices using Moderate Resolution Imaging Spectroradiometer (MODIS) data and red-edge parameters through the first derivative spectrum from in situ hypserspectral reflectance data. Hyperspectral reflectance measurements were made on grasslands in Inner Mongolia, China, using an Analytical Spectral Devices spectroradiometer. Vegetation indices such as the difference, simple ratio, normalized difference,renormalized difference, soil-adjusted and modified soil-adjusted vegetation indices (DVI, RVI, NDVI, RDVI,SAVIL = 0.5 and MSAVI2) were calculated from the hyperspectral reflectance of various vegetation covers. The percentage of vegetation cover was estimated using an unsupervised spectral-contextual classifier automatically. Relationships between percentage of vegetation cover and various vegetation indices and red-edge parameters were compared using a linear and second-order polynomial regression. Our analysis indicated that MSAVI2 and RVI yielded more accurate estimations for a wide range of vegetation cover thanother vegetation indices and red-edge parameters for the linear and second-order polynomial regression,respectively.

  13. Soil TPH concentration estimation using vegetation indices in an oil polluted area of eastern China.

    Science.gov (United States)

    Zhu, Linhai; Zhao, Xuechun; Lai, Liming; Wang, Jianjian; Jiang, Lianhe; Ding, Jinzhi; Liu, Nanxi; Yu, Yunjiang; Li, Junsheng; Xiao, Nengwen; Zheng, Yuanrun; Rimmington, Glyn M

    2013-01-01

    Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m(-2) to 5.3 g m(-2) with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg(-1) to 652 mg kg(-1). The modified chlorophyll absorption ratio index (MCARI) best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R(2) = 0.73) and accuracy of prediction (RMSE = 104.2 mg kg(-1)). For other vegetation indices and red edge parameters, the R(2) and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg(-1) to 106.8 mg kg(-1) respectively. The traditional broadband normalized difference vegetation index (NDVI), one of the broadband multispectral vegetation indices (BMVIs), produced a prediction (R(2) = 0.70 and RMSE = 110.1 mg kg(-1)) similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable.

  14. Soil TPH concentration estimation using vegetation indices in an oil polluted area of eastern China.

    Directory of Open Access Journals (Sweden)

    Linhai Zhu

    Full Text Available Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m(-2 to 5.3 g m(-2 with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg(-1 to 652 mg kg(-1. The modified chlorophyll absorption ratio index (MCARI best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R(2 = 0.73 and accuracy of prediction (RMSE = 104.2 mg kg(-1. For other vegetation indices and red edge parameters, the R(2 and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg(-1 to 106.8 mg kg(-1 respectively. The traditional broadband normalized difference vegetation index (NDVI, one of the broadband multispectral vegetation indices (BMVIs, produced a prediction (R(2 = 0.70 and RMSE = 110.1 mg kg(-1 similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable.

  15. Soil TPH Concentration Estimation Using Vegetation Indices in an Oil Polluted Area of Eastern China

    Science.gov (United States)

    Zhu, Linhai; Zhao, Xuechun; Lai, Liming; Wang, Jianjian; Jiang, Lianhe; Ding, Jinzhi; Liu, Nanxi; Yu, Yunjiang; Li, Junsheng; Xiao, Nengwen; Zheng, Yuanrun; Rimmington, Glyn M.

    2013-01-01

    Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m−2 to 5.3 g m−2 with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg−1 to 652 mg kg−1. The modified chlorophyll absorption ratio index (MCARI) best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R2 = 0.73) and accuracy of prediction (RMSE = 104.2 mg kg−1). For other vegetation indices and red edge parameters, the R2 and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg−1 to 106.8 mg kg−1 respectively. The traditional broadband normalized difference vegetation index (NDVI), one of the broadband multispectral vegetation indices (BMVIs), produced a prediction (R2 = 0.70 and RMSE = 110.1 mg kg−1) similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable. PMID:23342066

  16. Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices

    Directory of Open Access Journals (Sweden)

    D. G. Hadjimitsis

    2010-01-01

    Full Text Available Solar radiation reflected by the Earth's surface to satellite sensors is modified by its interaction with the atmosphere. The objective of applying an atmospheric correction is to determine true surface reflectance values and to retrieve physical parameters of the Earth's surface, including surface reflectance, by removing atmospheric effects from satellite images. Atmospheric correction is arguably the most important part of the pre-processing of satellite remotely sensed data. Such a correction is especially important in cases where multi-temporal images are to be compared and analyzed. For agricultural applications, in which several vegetation indices are applied for monitoring purposes, multi-temporal images are used. The integration of vegetation indices from remotely sensed images with other hydro-meteorological data is widely used for monitoring natural hazards such as droughts. Indeed, the most important task is to retrieve the true values of the vegetation status from the satellite-remotely sensed data. Any omission of considering the effects of the atmosphere when vegetation indices from satellite images are used, may lead to major discrepancies in the final outcomes. This paper highlights the importance of considering atmospheric effects when vegetation indices, such as DVI, NDVI, SAVI, MSAVI and SARVI, are used (or considered and presents the results obtained by applying the darkest-pixel atmospheric correction method on ten Landsat TM/ETM+ images of Cyprus acquired from July to December 2008. Finally, in this analysis, an attempt is made to determine evapotranspiration and to examine its dependence on the consideration of atmospheric effects when multi-temporal image data are used. It was found that, without applying any atmospheric correction, the real daily evapotranspiration was less than the one found after applying the darkest pixel atmospheric correction method.

  17. Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA/CHRIS Data Over an Agricultural Area

    OpenAIRE

    Pablo Martinez; José Moreno; Luis Guanter; Antonio Plaza; José A Sobrino; Jiménez-Muñoz, Juan C.

    2009-01-01

    Abstract: In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC) retrieval from Compact High Resolution Imaging Spectrometer (CHRIS) data onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs), in particular the Normalized Difference Vegetation Index (NDVI) and the Variable Atmospherically Resistant Index (VARI). The second methodology is b...

  18. A Dynamic Vegetation Senescence Indicator for Near-Real-Time Desert Locust Habitat Monitoring with MODIS

    Directory of Open Access Journals (Sweden)

    Cécile Renier

    2015-06-01

    Full Text Available Desert locusts (Schistocerca gregaria represent a major threat for agro-pastoral resources and food security over almost 30 million km2 from northern Africa to the Arabian peninsula and India. Given the differential food preferences of this insect pest and the extent and remoteness of the their distribution area, near-real-time remotely-sensed information on potential habitats support control operations by narrowing down field surveys to areas favorable for their development and prone to gregarization and outbreaks. The development of dynamic greenness maps, which detect the onset of photosynthetic vegetation, allowed national control centers to identify potential habitats to survey, as locusts prefer green and fresh vegetation. Their successful integration into the daily control operations led to a new need: the near-real-time identification of the onset of dryness, a synonym for the loss of habitat attractiveness, likely to be abandoned by locusts. The timely availability of this information would enable control centers to focus their surveys on areas more prone to gregarization, leading to more efficiency in the allocation of resources and in decision making. In this context, this work developed an original method to detect in near-real-time the onset of vegetation senescence. The design of the detection relies on the temporal behavior of two indices: the Normalized Difference Vegetation Index, depending on the green vegetation, and the Normalized Difference Tillage Index, sensitive to both green and dry vegetation. The method is demonstrated in Mauritania, an ever-affected country, with 10-day MODIS mean composites for the years 2010 and 2011. The discrimination performance of three classes (“growth”, “density reduction” and “drying” were analyzed for three classification methods: maximum likelihood (61.4% of overall accuracy, decision tree (71.5% and support vector machine (72.3%. The classification accuracy is heterogeneous in

  19. Model-simulated and Satellite-derived Leaf Area Index (LAI) Comparisons Across Multiple Spatial Scales

    Science.gov (United States)

    Iiames, J. S., Jr.; Cooter, E. J.

    2016-12-01

    Leaf Area Index (LAI) is an important parameter in assessing vegetation structure for characterizing forest canopies over large areas at broad spatial scales using satellite remote sensing data. However, satellite-derived LAI products can be limited by obstructed atmospheric conditions yielding sub-optimal values, or complete non-returns. The United States Environmental Protection Agency's Exposure Methods and Measurements and Computational Exposure Divisions are investigating the viability of supplemental modelled LAI inputs into satellite-derived data streams to support various regional and local scale air quality models for retrospective and future climate assessments. In this present study, one-year (2002) of plot level stand characteristics at four study sites located in Virginia and North Carolina (USA) are used to calibrate species-specific plant parameters in a semi-empirical biogeochemical model. The Environmental Policy Integrated Climate (EPIC) model was designed primarily for managed agricultural field crop ecosystems, but also includes managed woody species that span both xeric and mesic sites (e.g., mesquite, pine, oak, etc.). LAI was simulated using EPIC at a 4 km2 and 12 km2 grid coincident with the regional Community Multiscale Air Quality Model (CMAQ) grid. LAI comparisons were made between model-simulated and MODIS-derived LAI. Field/satellite-upscaled LAI was also compared to the corresponding MODIS LAI value. Preliminary results show field/satellite-upscaled LAI (1 km2) was 1.5 to 3 times smaller than that with the corresponding 1 km2 MODIS LAI for all four sites across all dates, with the largest discrepancies occurring at leaf-out and leaf senescence periods. Simulated LAI/MODIS LAI comparison results will be presented at the conference. Disclaimer: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S. Environmental Protection Agency funded and conducted the research described in this paper. Although

  20. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Teng, W.; Kempler, S.

    2012-01-01

    Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by

  1. Spatial and Quantitative Comparison of Satellite-Derived Land Cover Products over China

    Institute of Scientific and Technical Information of China (English)

    GAO Hao; JIA Gen-Suo

    2012-01-01

    Because land cover plays an important role in global climate change studies, assessing the agreement among different land cover products is critical. Significant discrepancies have been reported among satellite-derived land cover products, especially at the regional scale. Dif- ferent classification schemes are a key obstacle to the comparison of products and are considered the main fac- tor behind the disagreement among the different products. Using a feature-based overlap metric, we investigated the degree of spatial agreement and quantified the overall and class-specific agreement among the Moderate Resolution Imaging Spectoradiometer (MODIS), Global Land Cover 2000 (GLC2000), and the National Land Cover/Use Data- sets (NLCD) products, and the author assessed the prod- ucts by ground reference data at the regional scale over China. The areas with a low degree of agreement mostly occurred in heterogeneous terrain and transition zones, while the areas with a high degree of agreement occurred in major plains and areas with homogeneous vegetation. The overall agreement of the MODIS and GLC2000 products was 50.8% and 52.9%, and the overall accuracy was 50.3% and 41.9%, respectively. Class-specific agree- ment or accuracy varied significantly. The high-agreement classes are water, grassland, cropland, snow and ice, and bare areas, whereas classes with low agreement are shru- bland and wetland in both MODIS and GLC2000. These characteristics of spatial patterns and quantitative agree- ment could be partly explained by the complex landscapes, mixed vegetation, low separability of spectro-temporal- texture signals, and coarse pixels. The differences of class definition among different the classification schemes also affects the agreement. Each product had its advantages and limitations, but neither the overall accuracy nor the class-specific accuracy could meet the requirements of climate modeling.

  2. Quantitative Determination of Bandpasses for Producing Vegetation Indices from Recombined NEON Hyperspectral Imagery

    Science.gov (United States)

    Hulslander, D.

    2015-12-01

    Hyperspectral imaging systems can be used to produce spectral reflectance curves giving rich information about composition, relative abundances of materials, mixes and combinations. However, as each spectral return from these systems is a vector with several hundred elements, they can be very difficult to process and analyze, and problemeatic to compare within, across, and between datasets over time and space. Vegetation indices (e.g. NDVI, ARVI, EVI, et al) attempt to combine spectral features in to single-value scores. When derived from calibrated and atmospherically compensated reflectance data, these indices can be quantitatively compared. Historically, these indices have been calculated from multispectral sensor data. These sensors have a handful (4 to 16 or so) of bandbasses ranging from 20 nm to 200 nm FWHM covering specific spectral regions for a variety of reasons, including both intended applications and system limitations. Hyperspectral sensors, however, cover the spectrum with many, many narrow (5 to 10 nm) bandpasses. This allows for analyses using the full, detailed spectral curve, or combination of the bands in to regions by averaging or in to composites using transforms or other techniques. This raises the question of exactly which bands should be used and combined in what manner for ideally deriving well-known vegetation indices typically made from multispectral data. In this study we use derivatives and other curve and signal analysis techniques to analyze vegetation reflectance spectra to quantitatively define optimal bandpasses for several vegetation indices and combine the 5 nm hypserspectral bandpasses of the NEON Imaging Spectrometer to synthesize them.

  3. Spatial patterns and trends in remotely sensed vegetation indices 1981-2016

    Science.gov (United States)

    Spinoni, Jonathan; Duveiller, Gregory; Cescatti, Alessandro

    2017-04-01

    The current global state of vegetation and its evolution through the last decades is related with climate change issues. A few recent studies investigated the greening or browning vegetation tendencies at global and continental scales using remotely sensed data. However, the relatively short length of such data made it difficult to detect statistically robust trends in vegetation indicators. This study investigates global high-resolution (0.05°) spatial patterns and trends of vegetation conditions at a seasonal scale and over the period 1981-2016, by means of three indicators, the measured Normalized Difference Vegetation Index (NDVI) and the modelled Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FAPAR). Using very high-resolution (300 m) land cover grids, this study tries to decompose such trends into the contributions from the single different plant functional types (PFTs). Moreover, this study investigates the correlations between the trends of selected PFTs with other proxies as aggregated land cover classes, climate classification schemes, and single types of trees (this last feature over parts of Europe only). Then NDVI, LAI, and FAPAR input data used are from the Climate Data Record Program (CDR) of the National Oceanic and Atmospheric Administration (NOOA) and were subjected to extensive quality-checks. The land cover grids (2000, 2005, and 2010) are from the Climate Change Initiative (CCI) of the European Space Agency (ESA). Tree species over Europe are from European Atlas of Forest Tree Species of the Joint research Centre (JRC). Climate classification schemes used follow the Köppen-Geiger and the Holdridge life zones formulations. Seasonal trends in NDVI, LAI, and FAPAR, together with their statistical significance, are presented in global maps to focus at seasonal greening and browning tendencies. Trends in single PFTs and their relationships with land cover, climate classes, and tree species are shown in tables and

  4. Surface soil phytoliths as vegetation and altitude indicators: a study from the southern Himalaya

    Science.gov (United States)

    An, Xiaohong; Lu, Houyuan; Chu, Guoqiang

    2015-10-01

    Phytoliths represent one of the few available altitudinal vegetation proxies for mountain ecosystems. This study analyzed 41 topsoil phytolith samples collected from five altitudinal zones in the southern Himalaya as far as, and beyond, the timberline, from tropical forest (up to 1,000 m a.s.l.) to subtropical forest (1,000-2,000 m a.s.l.), to temperate forest (2,000-3,000 m a.s.l.), to subalpine forest (3,000-4,100 m a.s.l.) and finally to alpine scrub (4,100-5,200 m a.s.l.). The statistical results show a good correlation between phytolith assemblages and these five altitudinal vegetation zones: the five phytolith assemblages identified effectively differentiated these five altitudinal vegetation zones. In particular, coniferous phytoliths accurately indicated the timberline. Additionally, we tested the phytolith index Ic (a proxy for estimating the percentage of Pooideae vis-à-vis the total grass content) as a quantifier of phytolith variety versus altitude. Ic increased along altitude, as expected. An investigation of phytoliths provided an initial basis for the analysis of the composition of gramineous vegetation. Furthermore, redundancy analysis and discriminant analysis also suggested a significant correlation between phytolith assemblages and altitude. Our research therefore provides an up-to-date analogue for the reconstruction of changes to palaeovegetation and palaeoaltitude in mountainous areas.

  5. Using Landsat Vegetation Indices to Estimate Impervious Surface Fractions for European Cities

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Fensholt, Rasmus; Drews, Martin

    2015-01-01

    Impervious surfaces (IS) are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy and applic......Impervious surfaces (IS) are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy...... Vegetation Index (SAVI) are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR), and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs ≈ 10%, MBE’s ... to be applicable for cities with dissimilar climatic and vegetative conditions. The VI/IS relationship across cities is examined by quantifying the MAEs and MBEs between all combinations of models and urban areas. Also, regional regression models are developed by compiling data from multiple cities to examine...

  6. Changes in the distribution of South Korean forest vegetation simulated using thermal gradient indices

    Institute of Scientific and Technical Information of China (English)

    CHOI; Sungho; LEE; Woo-Kyun; SON; Yowhan; YOO; Seongjin; LIM; Jong-Hwan

    2010-01-01

    To predict changes in South Korean vegetation distribution,the Warmth Index(WI) and the Minimum Temperature of the Coldest Month Index(MTCI) were used.Historical climate data of the past 30 years,from 1971 to 2000,was obtained from the Korea Meteorological Administration.The Fifth-Generation National Center for Atmospheric Research(NCAR) /Penn State Mesoscale Model(MM5) was used as a source for future climatic data under the A1B scenario from the Special Report on Emission Scenario(SRES) of the Intergovernmental Panel on Climate Change(IPCC).To simulate future vegetation distribution due to climate change,the optimal habitat ranges of Korean tree species were delimited by the thermal gradient indices,such as WI and MTCI.To categorize the Thermal Analogy Groups(TAGs) for the tree species,the WI and MTCI were orthogonally plotted on a two-dimensional grid map.The TAGs were then designated by the analogue composition of tree species belonging to the optimal WI and MTCI ranges.As a result of the clustering process,22 TAGs were generated to explain the forest vegetation distribution in Korea.The primary change in distribution for these TAGs will likely be in the shrinkage of areas for the TAGs related to Pinus densiflora and P.koraiensis,and in the expansion of the other TAG areas,mainly occupied by evergreen broad-leaved trees,such as Camellia japonica,Cyclobalanopsis glauca,and Schima superba.Using the TAGs to explain the effects of climate change on vegetation distribution on a more regional scale resulted in greater detail than previously used global or continental scale vegetation models.

  7. Seasonal Biophysical Dynamics of the Amazon from Space Using MODIS Vegetation Indices

    Science.gov (United States)

    Huete, A. R.; Didan, K.; Ratana, P.; Ferreira, L.

    2002-12-01

    We utilized the Terra- Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) products to analyze the seasonal and spatial patterns of photosynthetic vegetation activity over the Amazon Basin and surrounding regions of Brazil. The seasonal patterns of vegetation activity were studied along two, eco-climatic transects extending from (1) the cerrado region (Brasilia National Park) to the seasonal tropical forest (Tapajos National Forest) and (2) the caatinga biome to the seasonal and per-humid tropical forests. In addition to the climatic transects, we also investigated the seasonal dynamics of altered, land conversion areas associated with pastures and clearcutting land use activities. Both the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) at 250-m, 500-m, and 1-km were used to extract seasonal profile curves. The quality assurance (QA) information of the output products was used in noise removal and data filtering prior to the generation of the seasonal profiles. Histogram analyses were also performed at coarse (biome) scale and fine, site intensive (flux towers) scale. The seasonal patterns of the cerrado and caatinga were very pronounced with distinct dry and wet seasonal trends. We observed decreasing dry-wet seasonal patterns in the transitional areas near Araguaia National Park. In contrast, the seasonal behavior of the tropical forests were much harder to assess, but indicated slight seasonal trends that ran counter to rainfall activity. This may be attributed to new leaf growth in the dry season. We further found MODIS VI seasonal patterns to vary significantly in land converted and land degraded areas.

  8. Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest

    Directory of Open Access Journals (Sweden)

    Zhihui Wang

    2016-06-01

    Full Text Available Hyperspectral remote sensing serves as an effective tool for estimating foliar nitrogen using a variety of techniques. Vegetation indices (VIs are a simple means of retrieving foliar nitrogen. Despite their popularity, few studies have been conducted to examine the utility of VIs for mapping canopy foliar nitrogen in a mixed forest context. In this study, we assessed the performance of 32 vegetation indices derived from HySpex airborne hyperspectral images for estimating canopy mass-based foliar nitrogen concentration (%N in the Bavarian Forest National Park. The partial least squares regression (PLSR was performed for comparison. These vegetation indices were classified into three categories that are mostly correlated to nitrogen, chlorophyll, and structural properties such as leaf area index (LAI. %N was destructively measured in 26 broadleaf, needle leaf, and mixed stand plots to represent the different species and canopy structure. The canopy foliar %N is defined as the plot-level mean foliar %N of all species weighted by species canopy foliar mass fraction. Our results showed that the variance of canopy foliar %N is mainly explained by functional type and species composition. The normalized difference nitrogen index (NDNI produced the most accurate estimation of %N (R2CV = 0.79, RMSECV = 0.26. A comparable estimation of %N was obtained by the chlorophyll index Boochs2 (R2CV = 0.76, RMSECV = 0.27. In addition, the mean NIR reflectance (800–850 nm, representing canopy structural properties, also achieved a good accuracy in %N estimation (R2CV = 0.73, RMSECV = 0.30. The PLSR model provided a less accurate estimation of %N (R2CV = 0.69, RMSECV = 0.32. We argue that the good performance of all three categories of vegetation indices in %N estimation can be attributed to the synergy among plant traits (i.e., canopy structure, leaf chemical and optical properties while these traits may converge across plant species for evolutionary reasons. Our

  9. Modified vegetation indices for Ganoderma disease detection in oil palm from field spectroradiometer data

    Science.gov (United States)

    Shafri, Helmi Z. M.; Anuar, M. Izzuddin; Saripan, M. Iqbal

    2009-10-01

    High resolution field spectroradiometers are important for spectral analysis and mobile inspection of vegetation disease. The biggest challenges in using this technology for automated vegetation disease detection are in spectral signatures pre-processing, band selection and generating reflectance indices to improve the ability of hyperspectral data for early detection of disease. In this paper, new indices for oil palm Ganoderma disease detection were generated using band ratio and different band combination techniques. Unsupervised clustering method was used to cluster the values of each class resultant from each index. The wellness of band combinations was assessed by using Optimum Index Factor (OIF) while cluster validation was executed using Average Silhouette Width (ASW). 11 modified reflectance indices were generated in this study and the indices were ranked according to the values of their ASW. These modified indices were also compared to several existing and new indices. The results showed that the combination of spectral values at 610.5nm and 738nm was the best for clustering the three classes of infection levels in the determination of the best spectral index for early detection of Ganoderma disease.

  10. Performance of vegetation indices from Landsat time series in deforestation monitoring

    Science.gov (United States)

    Schultz, Michael; Clevers, Jan G. P. W.; Carter, Sarah; Verbesselt, Jan; Avitabile, Valerio; Quang, Hien Vu; Herold, Martin

    2016-10-01

    The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies.

  11. Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques

    Directory of Open Access Journals (Sweden)

    Suranjan Panigrahi

    2010-03-01

    Full Text Available Spatial variability in a crop field creates a need for precision agriculture. Economical and rapid means of identifying spatial variability is obtained through the use of geotechnology (remotely sensed images of the crop field, image processing, GIS modeling approach, and GPS usage and data mining techniques for model development. Higher-end image processing techniques are followed to establish more precision. The goal of this paper was to investigate the strength of key spectral vegetation indices for agricultural crop yield prediction using neural network techniques. Four widely used spectral indices were investigated in a study of irrigated corn crop yields in the Oakes Irrigation Test Area research site of North Dakota, USA. These indices were: (a red and near-infrared (NIR based normalized difference vegetation index (NDVI, (b green and NIR based green vegetation index (GVI, (c red and NIR based soil adjusted vegetation index (SAVI, and (d red and NIR based perpendicular vegetation index (PVI. These four indices were investigated for corn yield during 3 years (1998, 1999, and 2001 and for the pooled data of these 3 years. Initially, Back-propagation Neural Network (BPNN models were developed, including 16 models (4 indices * 4 years including the data from the pooled years to test for the efficiency determination of those four vegetation indices in corn crop yield prediction. The corn yield was best predicted using BPNN models that used the means and standard deviations of PVI grid images. In all three years, it provided higher prediction accuracies, coefficient of determination (r2, and lower standard error of prediction than the models involving GVI, NDVI, and SAVI image information. The GVI, NDVI, and SAVI models for all three years provided average testing prediction accuracies of 24.26% to 94.85%, 19.36% to 95.04%, and 19.24% to 95.04%, respectively while the PVI models for all three years provided average testing prediction accuracies

  12. Vegetation

    DEFF Research Database (Denmark)

    Epstein, H.E.; Walker, D.A.; Bhatt, U.S.;

    2012-01-01

    • Over the past 30 years (1982-2011), the Normalized Difference Vegetation Index (NDVI), an index of green vegetation, has increased 15.5% in the North American Arctic and 8.2% in the Eurasian Arctic. In the more southern regions of Arctic tundra, the estimated aboveground plant biomass has...

  13. Non-destructive estimation of foliar carotenoid content of tree species using merged vegetation indices.

    Science.gov (United States)

    Fassnacht, Fabian E; Stenzel, Stefanie; Gitelson, Anatoly A

    2015-03-15

    Leaf pigment content is an important indicator of plant status and can serve to assess the vigor and photosynthetic activity of plants. The application of spectral information gathered from laboratory, field and remote sensing-based spectrometers to non-destructively assess total chlorophyll (Chl) content of higher plants has been demonstrated in earlier studies. However, the precise estimation of carotenoid (Car) content with non-destructive spectral measurements has so far not reached accuracies comparable to the results obtained for Chl content. Here, we examined the potential of a recently developed angular vegetation index (AVI) to estimate total foliar Car content of three tree species. Based on an iterative search of all possible band combinations, we identified a best candidate AVIcar. The identified index showed quite close but essentially not linear relation with Car contents of the examined species with increasing sensitivity to high Car content and a lack of sensitivity to low Car content for which earlier proposed vegetation indices (VI) performed better. To make use of the advantages of both VI types, we developed a simple merging procedure, which combined the AVIcar with two earlier proposed carotenoid indices. The merged indices had close linear relationship with total Car content and outperformed all other examined indices. The merged indices were able to accurately estimate total Car content with a percental root mean square error (%RMSE) of 8.12% and a coefficient of determination of 0.88. Our findings were confirmed by simulations using the radiative transfer model PROSPECT-5. For simulated data, the merged indices again showed a quasi linear relationship with Car content. This strengthens the assumption that the proposed merged indices have a general ability to accurately estimate foliar Car content. Further examination of the proposed merged indices to estimate foliar Car content of other plant species is desirable to prove the general

  14. Performance of Vegetation Indices for Wheat Yield Forecasting for Punjab, Pakistan

    Science.gov (United States)

    Dempewolf, J.; Becker-Reshef, I.; Adusei, B.; Barker, B.

    2013-12-01

    Forecasting wheat yield in major producer countries early in the growing season allows better planning for harvest deficits and surplus with implications for food security, world market transactions, sustaining adequate grain stocks, policy making and other matters. Remote sensing imagery is well suited for yield forecasting over large areas. The Normalized Difference Vegetation Index (NDVI) has been the most-used spectral index derived from remote sensing imagery for assessing crop condition of major crops and forecasting crop yield. Many authors have found that the highest correlation between NDVI and yield of wheat crops occurs at the height of the growing season when NDVI values and photosynthetic activity of the wheat plants are at their relative maximum. At the same time NDVI saturates in very dense and vigorous (healthy, green) canopies such as wheat fields during the seasonal peak and shows significantly reduced sensitivity to further increases in photosynthetic activity. In this study we compare the performance of different vegetation indices derived from space-borne red and near-infrared spectral reflectance measurements for wheat yield forecasting in the Punjab Province, Pakistan. Areas covered by wheat crop each year were determined using a time series of MODIS 8-day composites at 250 m resolution converted to temporal metrics and classified using a bagged decision tree approach, driven by classified multi-temporal Landsat scenes. Within the wheat areas we analyze and compare wheat yield forecasts derived from three different satellite-based vegetation indices at the peak of the growing season. We regressed in turn NDVI, Wide Dynamic Range Vegetation Index (WDRVI) and the Vegetation Condition Index (VCI) from the four years preceding the wheat growing season 2011/12 against reported yield values and applied the regression equations to forecast wheat yield for the 2011/12 season per district for each of 36 Punjab districts. Yield forecasts overall

  15. Vegetation indicators of transformation in the urban forest ecosystems of "Kuzminki-Lyublino" Park

    Science.gov (United States)

    Buyvolova, Anna; Trifonova, Tatiana; Bykova, Elena

    2017-04-01

    Forest ecosystems in the city are at the same time a component of its natural environment and part of urban developmental planning. It imposes upon urban forests a large functional load, both environmental (formation of environment, air purification, noise pollution reducing, etc.) and social (recreational, educational) which defines the special attitude to their management and study. It is not a simple task to preserve maximum accessibility to the forest ecosystems of the large metropolises with a minimum of change. The urban forest vegetates in naturally formed soil, it has all the elements of a morphological structure (canopy layers), represented by natural species of the zonal vegetation. Sometimes it is impossible for a specialist to distinguish between an urban forest and a rural one. However, the urban forests are changing, being under the threat of various negative influences of the city, of which pollution is arguably the most significant. This article presents some indicators of structural changes to the plant communities, which is a response of forest ecosystems to an anthropogenic impact. It is shown that the indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The assessment of the impact of the urban environment on the state of vegetation in the "Kuzminki-Lyublino" Natural-Historical Park was conducted in two key areas least affected by anthropogenic impacts under different plant communities represented by complex pine and birch forests and in similar forest types in the Prioksko-Terrasny Biosphere Reserve. The selection of pine forests as a model is due to the fact that, according to some scientists, pine (Pinus

  16. Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic

    Science.gov (United States)

    Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav

    2015-04-01

    Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in

  17. Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development

    Directory of Open Access Journals (Sweden)

    Fábio M. Breunig

    2012-06-01

    Full Text Available Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS. In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI1640 and NDWI2120 with the soybean development in two growing seasons (2004-2005 and 2005-2006. To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.Efeitos direcionais introduzem variabilidade na reflectância e na determinação de índices de vegetação, especialmente quando sensores de amplo campo de visada são usados (p.ex., Moderate Resolution Imaging Spectroradiometer - MODIS. Neste estudo, nós avaliamos os efeitos direcionais sobre a reflectância e quatro índices de vegetação (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized

  18. 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

  19. Information extraction with object based support vector machines and vegetation indices

    Science.gov (United States)

    Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

    2016-07-01

    Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

  20. Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts

    Science.gov (United States)

    Alcaraz-Segura, Domingo; Lomba, Angela; Sousa-Silva, Rita; Nieto-Lugilde, Diego; Alves, Paulo; Georges, Damien; Vicente, Joana R.; Honrado, João P.

    2017-05-01

    In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001-2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species.

  1. Analysing vegetation phenology in response to climate change using enhanced bioclimatic indices in Iraq

    Science.gov (United States)

    Daham, Afrah; Han, Dawei; Jolly, William M.; Rico-Ramirez, Miguel

    2017-04-01

    Exchanges of momentum, heat, carbon dioxide, energy, water and mass between the land's surface and the atmosphere are significantly affected by the phenological state of vegetation. Although, most phenology models have the function in analysing and predicting future trends in response to climate change, a bioclimatic index including precipitation in has not been adequately considered in the existing phenology models. In this study a new variable is added to the common set of variables found in the literature review and it is demonstrated how these variables could be combined into an index to quantify the greenness of vegetation throughout the three different years that have been selected (2001, 2006, and 2010). These four selected variables are: Suboptimal (minimum) temperatures, evaporative demand (vapour pressure deficit), photoperiod (daylength), and precipitation. Threshold limits (a lower threshold and an upper threshold) have been set for individual variables, within which the relative phenological performance of the vegetation is assumed to vary from inactive (0) to unconstrained (1). A combined Growing Season Index (GSI) is derived as the product of the four indices. The mean GSI values over twenty one days for the study area during the study period showed a good correlation with the MODerate-resolution Imaging Spectroradiometer (MODIS) and the derived Normalized Difference Vegetation Index (NDVI). The model has been tested for different locations in Iraq (Sulaymaniyah in the north, Wasit in the centre and Basrah in the south) by comparing the model results for these areas with the addition of the precipitation variable and without. The correlation for this model has been improved significantly after adding precipitation as an index in the GSI model. The modified model appears sufficiently robust to reconstruct historical variation as well as to forecast possible future phenological responses to changing climatic conditions. This study is of important value

  2. Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria

    Directory of Open Access Journals (Sweden)

    Boluwaji M. Olomiyesan

    2016-01-01

    Full Text Available In this study, the performance of three global solar radiation models and the accuracy of global solar radiation data derived from three sources were compared. Twenty-two years (1984–2005 of surface meteorological data consisting of monthly mean daily sunshine duration, minimum and maximum temperatures, and global solar radiation collected from the Nigerian Meteorological (NIMET Agency, Oshodi, Lagos, and the National Aeronautics Space Agency (NASA for three locations in North-Western region of Nigeria were used. A new model incorporating Garcia model into Angstrom-Prescott model was proposed for estimating global radiation in Nigeria. The performances of the models used were determined by using mean bias error (MBE, mean percentage error (MPE, root mean square error (RMSE, and coefficient of determination (R2. Based on the statistical error indices, the proposed model was found to have the best accuracy with the least RMSE values (0.376 for Sokoto, 0.463 for Kaduna, and 0.449 for Kano and highest coefficient of determination, R2 values of 0.922, 0.938, and 0.961 for Sokoto, Kano, and Kaduna, respectively. Also, the comparative study result indicates that the estimated global radiation from the proposed model has a better error range and fits the ground measured data better than the satellite-derived data.

  3. Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale.

    Science.gov (United States)

    Xu, Chi; Li, Yutong; Hu, Jian; Yang, Xuejiao; Sheng, Sheng; Liu, Maosong

    2012-03-01

    Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.

  4. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

    Science.gov (United States)

    Gu, Y.; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, J.F.; Verdin, J.P.

    2008-01-01

    The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

  5. MODIS/TERRA MOD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  6. MODIS/AQUA MYD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  7. Response of vegetation indices to changes in three measures of leaf water stress

    Science.gov (United States)

    Cohen, Warren B.

    1991-01-01

    The responses of vegetation indices to changes in water stress were evaluated in two separate laboratory experiments. In one experiment the normalized difference vegetation index (NDVI), the near-IR to red ratio (near-IR/red), the Infrared Index (II), and the Moisture Stress Index (MSI) were more highly correlated to leaf water potential in lodgepole pine branches than were the Leaf Water Content Index (LWCI), the mid-IR ratio (Mid-IR), or any of the single Thematic Mapper (TM) bands. In the other experiment, these six indices and the TM Tasseled Cap brightness, greenness, and wetness indices responded to changes in leaf relative water content (RWC) differently than they responded to changes in leaf water content (WC) of three plant species, and the responses were dependent on how experimental replicates were pooled. With no pooling, the LWCI was the most highly correlated index to both RWC and WC among replications, followed by the II, MSI, and wetness. Only the LWCI was highly correlated to RWC and WC when replications were pooled within species. With among species pooling the LWCI was the only index highly correlated with RWC, while the II, MSI, Mid-IR, and wetness were most highly correlated with WC.

  8. Evaluation of Fecal Indicators and Pathogens in a Beef Cattle Feedlot Vegetative Treatment System.

    Science.gov (United States)

    Durso, Lisa M; Miller, Daniel N; Snow, Daniel D; Henry, Christopher G; Santin, Monica; Woodbury, Bryan L

    2017-01-01

    Runoff from open-lot animal feeding areas contains microorganisms that may adversely affect human and animal health if not properly managed. One alternative to full manure containment systems is a vegetative treatment system (VTS) that collects runoff in a sediment basin and then applies it to a perennial vegetation (grass) treatment area that is harvested for hay. Little is known regarding the efficacy of large-scale commercial VTSs for the removal of microbial contaminants. In this study, an active, pump-based VTS designed and built for a 1200-head beef cattle feedlot operation was examined to determine the effects of repeated feedlot runoff application on fecal indicator microorganisms and pathogens over short-term (2 wk) and long-term (3 yr) operations and whether fecal bacteria were infiltrating into deeper soils within the treatment area. In a short-term study, fecal bacteria and pathogen numbers declined over time in soil. Measurements of total coliforms and Enterococcus counts taken on control soils were not effective as fecal indicators. The repeated application of manure-impacted runoff as irrigation water did not enrich the pathogens or fecal indicators in the soil, and no evidence was seen to indicate that pathogens were moving into the deeper soil at this site. These results indicate that large-scale, active VTSs reduce the potential for environmental contamination by manure-associated bacteria. Also, this study has implications to full-containment systems that apply runoff water to land application areas (cropland) and the fate of pathogens in the soils of land application sites.

  9. Estimation of Crop Gross Primary Production (GPP). 2; Do Scaled (MODIS) Vegetation Indices Improve Performance?

    Science.gov (United States)

    Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Zhang, Xiaoyang; Suyker, Andrew; Verma, Shashi; Shuai, Yanmin; Middleton, Elizabeth M.

    2015-01-01

    Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the

  10. Temporal Trends and Spatial Variability of Vegetation Phenology over the Northern Hemisphere during 1982-2012.

    Science.gov (United States)

    Wang, Siyuan; Yang, Bojuan; Yang, Qichun; Lu, Linlin; Wang, Xiaoyue; Peng, Yaoyao

    2016-01-01

    Satellite-derived vegetation phenology has been recognized as a key indicator for detecting changes in the terrestrial biosphere in response to global climate change. However, multi-decadal changes and spatial variation of vegetation phenology over the Northern Hemisphere and their relationship to climate change have not yet been fully investigated. In this article, we investigated the spatial variability and temporal trends of vegetation phenology over the Northern Hemisphere by calibrating and analyzing time series of the satellite-derived normalized difference vegetation index (NDVI) during 1982-2012, and then further examine how vegetation phenology responds to climate change within different ecological zones. We found that during the period from 1982 to 2012 most of the high latitude areas experienced an increase in growing period largely due to an earlier beginning of vegetation growing season (BGS), but there was no significant trend in the vegetation growing peaks. The spatial pattern of phenology within different eco-zones also experienced a large variation over the past three decades. Comparing the periods of 1982-1992, 1992-2002 with 2002-2012, the spatial pattern of change rate of phenology shift (RPS) shows a more significant trend in advancing of BGS, delaying of EGS (end of growing season) and prolonging of LGS (length of growing season) during 2002-2012, overall shows a trend of accelerating change. Temperature is a major determinant of phenological shifts, and the response of vegetation phenology to temperature varied across different eco-zones.

  11. Correlation of basic oil quality indices and electrical properties of model vegetable oil systems.

    Science.gov (United States)

    Prevc, Tjaša; Cigić, Blaž; Vidrih, Rajko; Poklar Ulrih, Nataša; Šegatin, Nataša

    2013-11-27

    Model vegetable oil mixtures with significantly different basic oil quality indices (free fatty acid, iodine, and Totox values) were prepared by adding oleic acids, synthetic saturated triglycerides, or oxidized safflower oil ( Carthamus tinctorius ) to the oleic type of sunflower oil. Dielectric constants, dielectric loss factors, quality factors, and electrical conductivities of model lipids were determined at frequencies from 50 Hz to 2 MHz and at temperatures from 293.15 to 323.15 K. The dependence of these dielectric parameters on basic oil quality indices was investigated. Adding oleic acids to sunflower oil resulted in lower dielectric constants and conductivities and higher quality factors. Reduced iodine values resulted in increased dielectric constants and quality factors and decreased conductivities. Higher Totox values resulted in higher dielectric constants and conductivities at high frequencies and lower quality factors. Dielectric constants decreased linearly with temperature, whereas conductivities followed the Arrhenius law.

  12. Hydrometeorological and vegetation indices for the drought monitoring system in Tuscany Region, Italy

    Directory of Open Access Journals (Sweden)

    F. Caparrini

    2009-03-01

    Full Text Available We present here the first experiments for an integrated system that is under development for drought monitoring and water resources assessment in Tuscany Region in central Italy. The system is based on the cross-evaluation of the Standardized Precipitation Index (SPI, Vegetation Indices from remote sensing (from MODIS and SEVIRI-MSG, and outputs from the distributed hydrological model MOBIDIC, that is used in real-time for water balance evaluation and hydrological forecast in the major basins of Tuscany.

    Furthermore, a telemetric network of aquifer levels is near completion in the region, and data from nearly 50 stations are already available in real-time.

    Preliminary estimates of drought indices over Tuscany in the first eight months of 2007 are shown, and pathway for further studies on the correlation between patterns of crop water stress, precipitation deficit and groundwater conditions is discussed.

  13. Assessing the Relationship Between Spectral Vegetation Indices and Shrub Cover in the Jornada Basin, New Mexico

    Science.gov (United States)

    Duncan, Jeff; Stow, D.; Franklin, J.; Hope, A.

    1993-01-01

    We assessed the statistical relations between Spectral Vegetation Indices (SVI's) derived from SPOT multi-spectral data and semi-arid shrub cover at the Jornada LTER site in New Mexico. Despite a limited range of shrub cover in the sample the analyses resulted in r(sup 2) values as high as 0 central dot 77. Greenness SVI's (e.g., Simple Ratio, NDVI, SAVI, PVI and an orthogonal Greenness index) were shown to be more sensitive to shrub type and phenology than brightness SVis (e.g., green, red and near-infrared reflectances and a Brightness index). The results varied substantially with small-scale changes in plot size (60m by 60m to 100m by 100m) as a consequence of landscape heterogeneity. The results also indicated the potential for the spectral differentiation of shrub types, and shrubs from grass, using multi-temporal, multi-spectral analysis.

  14. Distinguishing plant population and variety with UAV-derived vegetation indices

    Science.gov (United States)

    Oakes, Joseph; Balota, Maria

    2017-05-01

    Variety selection and seeding rate are two important choice that a peanut grower must make. High yielding varieties can increase profit with no additional input costs, while seeding rate often determines input cost a grower will incur from seed costs. The overall purpose of this study was to examine the effect that seeding rate has on different peanut varieties. With the advent of new UAV technology, we now have the possibility to use indices collected with the UAV to measure emergence, seeding rate, growth rate, and perhaps make yield predictions. This information could enable growers to make management decisions early in the season based on low plant populations due to poor emergence, and could be a useful tool for growers to use to estimate plant population and growth rate in order to help achieve desired crop stands. Red-Green-Blue (RGB) and near-infrared (NIR) images were collected from a UAV platform starting two weeks after planting and continued weekly for the next six weeks. Ground NDVI was also collected each time aerial images were collected. Vegetation indices were derived from both the RGB and NIR images. Greener area (GGA- the proportion of green pixels with a hue angle from 80° to 120°) and a* (the average red/green color of the image) were derived from the RGB images while Normalized Differential Vegetative Index (NDVI) was derived from NIR images. Aerial indices were successful in distinguishing seeding rates and determining emergence during the first few weeks after planting, but not later in the season. Meanwhile, these aerial indices are not an adequate predictor of yield in peanut at this point.

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

    Directory of Open Access Journals (Sweden)

    María Amparo Gilabert

    2017-02-01

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

  16. Time series of vegetation indices and the modifiable temporal unit problem

    Directory of Open Access Journals (Sweden)

    R. de Jong

    2011-08-01

    Full Text Available Time series of vegetation indices (VI derived from satellite imagery provide a consistent monitoring system for terrestrial plant systems. They enable detection and quantification of gradual changes within the time frame covered, which are of crucial importance in global change studies, for example. However, VI time series typically contain a strong seasonal signal which complicates change detection. Commonly, trends are quantified using linear regression methods, while the effect of serial autocorrelation is remediated by temporal aggregation over bins having a fixed width. Aggregating the data in this way produces temporal units which are modifiable. Analogous to the well-known Modifiable Area Unit Problem (MAUP, the way in which these temporal units are defined may influence the fitted model parameters and therefore the amount of change detected. This paper illustrates the effect of this Modifiable Temporal Unit Problem (MTUP on a synthetic data set and a real VI data set. Large variation in detected changes was found for aggregation over bins that mismatched full lengths of vegetative cycles, which demonstrates that aperiodicity in the data may influence model results. Using 26 yr of VI data and aggregation over full-length periods, deviations in VI gains of less than 1 % were found for annual periods, while deviations (with respect to seasonally adjusted data increased up to 24 % for aggregation windows of 5 yr. This demonstrates that temporal aggregation needs to be carried out with care in order to avoid spurious model results.

  17. Potential for early warning of maalria in India using NOAA-AVHRR based vegetation health indices

    Science.gov (United States)

    Dhiman, R. C.; Kogan, Felix; Singh, Neeru; Singh, R. P.; Dash, A. P.

    Malaria is still a major public health problem in India with about 1 82 million cases annually and 1000 deaths As per World Health Organization WHO estimates about 1 3 million Disability Adjusted Life Years DALYs are lost annually due to malaria in India Central peninsular region of India is prone to malaria outbreaks Meteorological parameters changes in ecological conditions development of resistance in mosquito vectors development of resistance in Plasmodium falciparum parasite and lack of surveillance are the likely reasons of outbreaks Based on satellite data and climatic factors efforts have been made to develop Early Warning System EWS in Africa but there is no headway in this regard in India In order to find out the potential of NOAA satellite AVHRR derived Vegetation Condition Index VCI Temperature Condition Index TCI and a cumulative indicator Vegetation Health Index VHI were attempted to find out their potential for development of EWS Studies were initiated by analysing epidemiological data of malaria vis-a-vis VCI TCI and VHI from Bikaner and Jaisalmer districts of Rajasthan and Tumkur and Raichur districts of Karnataka Correlation coefficients between VCI and monthly malaria cases for epidemic years were computed Positive correlation 0 67 has been found with one-month lag between VCI and malaria incidence in respect of Tumkur while a negative correlation with TCI -0 45 is observed In Bikaner VCI is found to be negatively related -0 71 with malaria cases in epidemic year of 1994 Weekly

  18. Modeling of Percentage of Canopy in Merawu Catchment Derived From Various Vegetation Indices of Remotely Sensed Data

    Directory of Open Access Journals (Sweden)

    Bambang Sulistyo

    2013-07-01

    Full Text Available The research was aimed at studying Percentage of Canopy mapping derived from various vegetation indices of remotely-sensed data int Merawu Catchment. Methodology applied was by analyzing remote sensing data of Landsat 7 ETM+ image to obtain various vegetation indices for correlation analysis with Percentage of Canopy measured directly on the field (PTactual at 48 locations. These research used 11 (eleven vegetation indices of remotely-sensed data, namely ARVI, MSAVI, TVI, VIF, NDVI, TSAVI, SAVI, EVI, RVI, DVI and PVI. The analysis resulted models (PTmodel for Percentage of Canopy mapping. The vegetation indices selected are those having high coefficient of correlation (>=0.80 to PTactual. Percentage of Canopy maps were validated using 39 locations on the field to know their accuracies. Percentage of Canopy map (PTmodel is said to be accurate when its coefficient of correlation value to PTactual is high (>=0.80. The research result in Merawu Catchment showed that from 11 vegetation indices under studied, there were 6 vegetation indices resulted high accuracy of Percentage of Canopy maps (as shown in the value of coefficient of correlation as >=0.80, i.e. TVI, VIF, NDVI, TSAVI, RVI dan SAVI, while the rest, namely ARVI, PVI, DVI, EVI and MSAVI, have r values of < 0.80.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty...... in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS......-NPP) and TBWper biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land...

  20. Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

    Science.gov (United States)

    Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

    2010-09-01

    In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional

  1. High resolution mapping of Normalized Difference Vegetation Indices (NDVI) of biological soil crusts

    Science.gov (United States)

    Fischer, T.; Veste, M.; Eisele, A.; Bens, O.; Spyra, W.; Hüttl, R. F.

    2012-04-01

    Normalized Difference Vegetation Indices (NDVI) are typically determined using satellite or airborne remote sensing, or field portable spectrometers, which give an averaged signal on centimetre to meter scale plots. Biological soil crust (BSC) patches may have smaller sizes, and ecophysiological, hydrological as well as pedological processes may be heterogeneously distributed within this level of resolution. A ground-based NDVI imaging procedure using low-cost equipment (Olympus Camedia 5000z digital camera equipped with a Hoya R72 infrared filter) was developed in this study to fill this gap at the level of field research, where carrying costly and bulky equipment to remote locations is often the limiting factor for data collection. A commercially available colour rendition chart (GretagMacbeth ColorChecker®) with known red (600-700 nm) and NIR (800-900 nm) reflectances was placed into each scene and used for calibration purposes on a per-image basis. Generation of NDVI images involved (i) determination of red and NIR reflectances from the pixel values of the red and NIR channels, respectively, and (ii) calculation and imaging of the NDVI, where NDVI values of -1 to +1 were mapped to grey values of 0 to 255. The correlation between NDVI values retrieved from these images and NDVI values determined using conventional field spectrometry (ASD FieldSpec 3 portable spectroradiometer) was close (r2 =0.91), the 95% confidence interval amounted to 0.10 NDVI units. The pixel resolution was 0.8 mm in the field and 0.2 mm in the laboratory, but can still be improved significantly with closer distance to the crust or with higher camera resolution. Geostatistical analysis revealed that both spatial variability as well as size of individual objects characterized by the NDVI increased with crust development. The latter never exceeded 4 mm in the investigated crusts, which points to the necessity of high resolution imaging for linking remote sensing with ecophysiology

  2. Integration of vegetation indices into a water balance model to estimate evapotranspiration of wheat and corn

    Directory of Open Access Journals (Sweden)

    F. L. M. Padilla

    2010-10-01

    Full Text Available Vegetation indices (VIs have been traditionally used for quantitative monitoring of vegetation. Remotely sensed radiometric measurements of visible and infrared solar energy, which is reflected or emitted by plant canopies, can be used to obtain rapid, non-destructive estimates of certain canopy attributes and parameters. One parameter of special interest for water management applications, is the crop coefficient employed by the FAO-56 model to derive actual crop evapotranspiration (ET. The aim of this study was to evaluate a methodology that combines the basal crop coefficient derived from VIs with a daily soil water balance in the root zone to estimate daily evapotranspiration rates for corn and wheat crops at field scale. The ability of the model to trace water stress in these crops was also assessed. Vegetation indices were first retrieved from field hand-held radiometer measurements and then from Landsat 5 and 7 satellite images. The results of the model were validated using two independent measurement systems for ET and regular soil moisture monitoring, in order to evaluate the behavior of the soil and atmosphere components of the model. ET estimates were compared with latent heat flux measured by an eddy covariance system and with weighing lysimeter measurements. Average overestimates of daily ET of 8 and 11% were obtained for corn and wheat, respectively, with good agreement between the estimated and measured root-zone water deficit for both crops when field radiometry was employed. Satellite remote-sensing inputs overestimated ET by 4 to 9%, showing a non-significant lost of accuracy when the satellite sensor data replaced the field radiometry data. The model was also used to monitor the water stress during the 2009 growing season, detecting several periods of water stress in both crops. Some of these stresses occurred during stages like grain filling, when the water stress is know to have a negative effect on yield. This fact could

  3. Vegetation

    DEFF Research Database (Denmark)

    Epstein, H.E.; Walker, D.A.; Bhatt, U.S.

    2012-01-01

    increased 20-26%. • Increasing shrub growth and range extension throughout the Low Arctic are related to winter and early growing season temperature increases. Growth of other tundra plant types, including graminoids and forbs, is increasing, while growth of mosses and lichens is decreasing. • Increases...... in vegetation (including shrub tundra expansion) and thunderstorm activity, each a result of Arctic warming, have created conditions that favor a more active Arctic fire regime....

  4. EVALUATION OF VEGETABLE EXTRACTS FROM THE SEMI-ARID AS NATURAL pH INDICATOR

    Directory of Open Access Journals (Sweden)

    Sebastiana Estefana Torres Brilhante

    2015-02-01

    Full Text Available Given the various difficulties to expose the contents of the subject of chemistry is a constant search for alternative materials to facilitate learning. This may partly be due to chemical science to be a significant practical character. However, due to professional educational institutions and material limitations ends up being passed on to the student of predominantly theoretical way, requiring a high degree of abstraction and consequently in their disinterest the same. In this context , we investigated the use of ethanol extracts of various plants, such as: Jitirana (Ipomoea glabra , Íxora (Ixora coccínea, Centro (Centrosema brasilianum and Candlebush (Senna alata flowers, Beet (Beta vulgaris L. fruit and Urucum (Bixa orellana seeds as an acids and bases natural indicator, from laboratory tests capable of identifying properties demonstrate the pH. Initially we evaluated the variation in the coloration of extracts using for this buffer solutions at pH 3, 7 and 12. Among the cited vegetable flowers Jitirana, ixora and Centro presented activities relevant indicator as staining variants between pH 2:13. The extracts of plants were further added in glass tubes containing buffer solutions with a pH ranging from 2 to 13. The change in color of the extracts showed good activity has the same pH indicator.

  5. The use of climatic parameters and indices in vegetation distribution. A case study in the Spanish Sistema Central.

    Science.gov (United States)

    Gavilán, Rosario G

    2005-11-01

    In this study, over 100 phytoclimatic indices and other climatic parameters were calculated using the climatic data from 260 meteorological stations in a Mediterranean territory located in the centre of the Iberian Peninsula. The nature of these indices was very different; some of them expressed general climatic features (e.g. continentality), while others were formulated for different Mediterranean territories and included particular limits of those indices that expressed differences in vegetation distribution. We wanted to know whether all of these indices were able to explain changes in vegetation on a spatial scale, and whether their boundaries worked similarly to the original territory. As they were so numerous, we investigated whether any of them were redundant. To relate vegetation to climate parameters we preferred to use its hierarchical nature, in discrete units (characterized by one or more dominant or co-dominant species), although it is known to vary continuously. These units give clearer results in this kind of phytoclimatic study. We have therefore used the main communities that represent natural potential vegetation. Multivariate and estimative analyses were used as statistical methods. The classification showed different levels of correlation among climatic parameters, but all of them were over 0.5. One hundred and eleven parameters were grouped into five larger groups: temperature (T), annual pluviothermic indices (PTY), summer pluviothermic indices (SPT), winter potential evapotranspiration (WPET) and thermal continentality indices (K). The remaining parameters showed low correlations with these five groups; some of them revealed obvious spatial changes in vegetation, such as summer hydric parameters that were zero in most vegetation types but not in high mountain vegetation. Others showed no clear results. For example, the Kerner index, an index of thermal continentality, showed lower values than expected for certain particular types of

  6. NDVI from Landsat 8 Vegetation Indices to Study Movement Dynamics of Capra Ibex in Mountain Areas

    Science.gov (United States)

    Pirotti, F.; Parraga, M. A.; Stuaro, E.; Dubbini, M.; Masiero, A.; Ramanzin, M.

    2014-09-01

    In this study we analyse the correlation between the spatial positions of Capra ibex (mountain goat) on an hourly basis and the information obtained from vegetation indices extracted from Landsat 8 datasets. Eight individuals were tagged with a collar with a GNSS receiver and their position was recorded every hour since the beginning of 2013 till 2014 (still ongoing); a total of 16 Landsat 8 cloud-free datasets overlapped that area during that time period. All images were brought to a reference radiometric level and NDVI was calculated. To assess behaviour of animal movement, NDVI values were extracted at each position (i.e. every hour). A daily "area of influence" was calculated by spatially creating a convex hull perimeter around the 24 points relative to each day, and then applying a 120 m buffer (figure 4). In each buffer a set of 24 points was randomly chosen and NDVI values again extracted. Statistical analysis and significance testing supported the hypothesis of the pseudo-random NDVI values to be have, in average, lower values than the real NDVI values, with a p value of 0.129 for not paired t test and p value of < 0.001 for pairwise t test. This is still a first study which will go more in depth in near future by testing models to see if the animal movements in different periods of the year follow in some way the phenological stage of vegetation. Different aspects have to be accounted for, such as the behaviour of animals when not feeding (e.g. resting) and the statistical significance of daily distributions, which might be improved by analysing broader gaps of time.

  7. Technical Note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation

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    E. Peled

    2010-02-01

    Full Text Available In the past years there have been many attempts to produce and improve global soil-moisture datasets and drought indices. However, comparing and validating these various datasets is not straightforward. Here, interannual variations in drought indices are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which drought index describes most realistically the actual changes in vegetation. Strong correlation between NDVI and the drought indices were found in areas that are classified as warm temperate climate with hot or warm dry summers. In these areas we ranked the PDSI, PSDI-SC, SPI3, and NSM indices, based on the interannual correlation with NDVI, and found that NSM outperformed the rest. Using this best performing index, and the ICA (Independent Component Analysis technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

  8. Satellite derived integrated water vapor and rain intensity patterns - Indicators of rapid cyclogenesis

    Science.gov (United States)

    Mcmurdie, Lynn; Katsaros, Kristina

    1992-01-01

    We examine integrated water vapor fields and rain intensity patterns derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) for several rapidly deepening and non-rapidly deepening midlatitude cyclones in the North Atlantic. Our goal is to identify features in the satellite data unique to the rapidly deepening cases, and to explore how these data can potentially be used in the analysis and forecasting of these events.

  9. Satellite derived integrated water vapor and rain intensity patterns: Indicators of rapid cyclogenesis

    Science.gov (United States)

    Mcmurdie, Lynn; Katsaros, Kristina

    1992-01-01

    We examine integrated water vapor fields and rain intensity patterns derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) for several rapidly deepening and non-rapidly deepening midlatitude cyclones in the North Atlantic. Our goal is to identify features in the satellite data unique to the rapidly deepening cases, and to explore how these data can potentially be used in the analysis and forecasting of these events.

  10. Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

    Science.gov (United States)

    Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

    2007-01-01

    An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

  11. Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

    Science.gov (United States)

    Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

    2007-01-01

    An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

  12. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains.

    NARCIS (Netherlands)

    Kooistra, L.; Salas, E.A.; Clevers, J.G.; Wehrens, H.R.M.J.; Leuven, R.S.E.W.; Nienhuis, P.H.; Buydens, L.M.C.

    2004-01-01

    This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The rela

  13. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains

    NARCIS (Netherlands)

    Kooistra, L.; Salas, E.A.L.; Clevers, J.G.P.W.; Wehrens, H.R.M.J.; Leuven, R.S.E.W.; Nienhuis, P.H.; Buydens, L.M.C.

    2004-01-01

    This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The rela

  14. Comparison and Intercalibration of Vegetation Indices from Different Sensors for Monitoring Above-Ground Plant Nitrogen Uptake in Winter Wheat

    Directory of Open Access Journals (Sweden)

    Yan Zhu

    2013-03-01

    Full Text Available Various sensors have been used to obtain the canopy spectral reflectance for monitoring above-ground plant nitrogen (N uptake in winter wheat. Comparison and intercalibration of spectral reflectance and vegetation indices derived from different sensors are important for multi-sensor data fusion and utilization. In this study, the spectral reflectance and its derived vegetation indices from three ground-based sensors (ASD Field Spec Pro spectrometer, CropScan MSR 16 and GreenSeeker RT 100 in six winter wheat field experiments were compared. Then, the best sensor (ASD and its normalized difference vegetation index (NDVI (807, 736 for estimating above-ground plant N uptake were determined (R2 of 0.885 and RMSE of 1.440 g·N·m−2 for model calibration. In order to better utilize the spectral reflectance from the three sensors, intercalibration models for vegetation indices based on different sensors were developed. The results indicated that the vegetation indices from different sensors could be intercalibrated, which should promote application of data fusion and make monitoring of above-ground plant N uptake more precise and accurate.

  15. Mapping crop evapotranspiration by integrating vegetation indices into a soil water balance model

    Science.gov (United States)

    Consoli, Simona; Vanella, Daniela

    2015-04-01

    The approach combines the basal crop coefficient (Kcb) derived from vegetation indices (VIs) with the daily soil water balance, as proposed in the FAO-56 paper, to estimate daily crop evapotranspiration (ETc) rates of orange trees. The reliability of the approach to detect water stress was also assessed. VIs were simultaneously retrieved from WorldView-2 imagery and hyper-spectral data collected in the field for comparison. ETc estimated were analysed at the light of independent measurements of the same fluxes by an eddy covariance (EC) system located in the study area. The soil water depletion in the root zone of the crop simulated by the model was also validated by using an in situ soil water monitoring. Average overestimate of daily ETc of 6% was obtained from the proposed approach with respect to EC measurements, evidencing a quite satisfactory agreement between data. The model also detected several periods of light stress for the crop under study, corresponding to an increase of the root zone water deficit matching quite well the in situ soil water monitoring. The overall outcomes of this study showed that the FAO-56 approach with remote sensing-derived basal crop coefficient can have the potential to be applied for estimating crop water requirements and enhancing water management strategies in agricultural contexts.

  16. Linking Satellite-Derived Fire Counts to Satellite-Derived Weather Data in Fire Prediction Models to Forecast Extreme Fires in Siberia

    Science.gov (United States)

    Westberg, D. J.; Soja, A. J.; Stackhouse, P. W.

    2009-12-01

    Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under climate change scenarios. Therefore to predict fire weather and ecosystem change, we must understand the factors that influence fire regimes and at what scale these are viable. The Canadian Fire Weather Index (FWI), developed by the Canadian Forestry Service, is used for this comparison, and it is calculated using local noon surface-level air temperature, relative humidity, wind speed, and daily (noon-noon) rainfall. The FWI assesses daily forest fire burning potential. Large-scale FWI are calculated at the NASA Langley Research Center (LaRC) using NASA Goddard Earth Observing System version 4 (GEOS-4) large-scale reanalysis and NASA Global Precipitation Climatology Project (GPCP) data. The GEOS-4 reanalysis weather data are 3-hourly interpolated to 1-hourly data at a 1ox1o resolution and the GPCP precipitation data are also at 1ox1o resolution. In previous work focusing on the fire season in Siberia in 1999 and 2002, we have shown the combination of GEOS-4 weather data and Global Precipitation Climatology Project (GPCP) precipitation data compares well to ground-based weather data when used as inputs for FWI calculation. The density and accuracy of Siberian surface station data can be limited, which leads to results that are not representative of the spatial reality. GEOS-4/GPCP-dervied FWI can serve to spatially enhance current and historic FWI, because these data are spatially and temporally consistency. The surface station and model reanalysis derived fire weather indices compared well spatially, temporally and quantitatively, and increased fire activity compares well with increasing FWI ratings. To continue our previous work, we statistically compare satellite-derived fire counts to FWI categories at

  17. Application of Vegetation Indices to Estimate Acorn Production at Iberian Peninsula

    Science.gov (United States)

    Escribano, Juan A.; Díaz-Ambrona, Carlos G. H.; Recuero, Laura; Huesca, Margarita; Cicuendez, Victor; Palacios, Alicia; Tarquis, Ana M.

    2014-05-01

    The Iberian pig valued natural resources of the pasture when fattened in mountain. The variability of acorn production is not contained in any line of Spanish agricultural insurance. However, the production of arable pasture is covered by line insurance number 133 for loss of pasture compensation. This scenario is only contemplated for breeding cows and brave bulls, sheep, goats and horses, although pigs are not included. This insurance is established by monitoring ten-day composites Normalized Difference Vegetation Index (NDVI) measured by satellite over treeless pastures, using MODIS TERRA satellite. The aim of this work is to check if we can use a satellite vegetation index to estimate the production of acorns. In order to do so, two Spanish grassland locations have been analyzed: regions of Olivenza (Jerez-Oliva) and Merida (Badajoz). The acorns production was evaluated through 2002-2005 gauging conducted by the Grupo Habitat de la Orden (Badajoz). Medium resolution (500x500 m2) MODIS images were used during the same time period to estimate the ten-day composites NDVI at these locations. Finally, meteorological data was obtained from SIAR and MAGRAMA network stations, calculating the ten-day averaged temperature and ten day accumulated precipitation. Considering two accumulated factors, NDVI and temperature, three phenological stages were well defined being the second one which pointed differences among campaigns. Then, accumulated precipitation versus accumulated NDVI was plot for this second phenological stage obtaining maximum differences at 300 mm of cumulative rainfall. Analyzing acorn production with accumulated NDVI in that moment a production function was obtained with a correlation coefficient of 0.71. These results will be discussed in detail. References J.A. Escribano, C.G.H. Diaz-Ambrona, L. Recuero, M. Huesca, V. Cicuendez, A. Palacios-Orueta y A.M. Tarquis. Aplicacion de Indices de Vegetacion para evaluar la falta de produccion de pastos y

  18. Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change.

    Directory of Open Access Journals (Sweden)

    Antonius G T Schut

    Full Text Available Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010 derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity.

  19. Fetal functional brain age assessed from universal developmental indices obtained from neuro-vegetative activity patterns.

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    Dirk Hoyer

    Full Text Available Fetal brain development involves the development of the neuro-vegetative (autonomic control that is mediated by the autonomic nervous system (ANS. Disturbances of the fetal brain development have implications for diseases in later postnatal life. In that context, the fetal functional brain age can be altered. Universal principles of developmental biology applied to patterns of autonomic control may allow a functional age assessment. The work aims at the development of a fetal autonomic brain age score (fABAS based on heart rate patterns. We analysed n = 113 recordings in quiet sleep, n = 286 in active sleep, and n = 29 in active awakeness from normals. We estimated fABAS from magnetocardiographic recordings (21.4-40.3 weeks of gestation preclassified in quiet sleep (n = 113, 63 females and active sleep (n = 286, 145 females state by cross-validated multivariate linear regression models in a cross-sectional study. According to universal system developmental principles, we included indices that address increasing fluctuation range, increasing complexity, and pattern formation (skewness, power spectral ratio VLF/LF, pNN5. The resulting models constituted fABAS. fABAS explained 66/63% (coefficient of determination R(2 of training and validation set of the variance by age in quiet, while 51/50% in active sleep. By means of a logistic regression model using fluctuation range and fetal age, quiet and active sleep were automatically reclassified (94.3/93.1% correct classifications. We did not find relevant gender differences. We conclude that functional brain age can be assessed based on universal developmental indices obtained from autonomic control patterns. fABAS reflect normal complex functional brain maturation. The presented normative data are supplemented by an explorative study of 19 fetuses compromised by intrauterine growth restriction. We observed a shift in the state distribution towards active awakeness. The lower WGA

  20. Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

    Directory of Open Access Journals (Sweden)

    Nora Tilly

    2015-09-01

    Full Text Available Plant biomass is an important parameter for crop management and yield estimation. However, since biomass cannot be determined non-destructively, other plant parameters are used for estimations. In this study, plant height and hyperspectral data were used for barley biomass estimations with bivariate and multivariate models. During three consecutive growing seasons a terrestrial laser scanner was used to establish crop surface models for a pixel-wise calculation of plant height and manual measurements of plant height confirmed the results (R2 up to 0.98. Hyperspectral reflectance measurements were conducted with a field spectrometer and used for calculating six vegetation indices (VIs, which have been found to be related to biomass and LAI: GnyLi, NDVI, NRI, RDVI, REIP, and RGBVI. Furthermore, biomass samples were destructively taken on almost the same dates. Linear and exponential biomass regression models (BRMs were established for evaluating plant height and VIs as estimators of fresh and dry biomass. Each BRM was established for the whole observed period and pre-anthesis, which is important for management decisions. Bivariate BRMs supported plant height as a strong estimator (R2 up to 0.85, whereas BRMs based on individual VIs showed varying performances (R2: 0.07–0.87. Fused approaches, where plant height and one VI were used for establishing multivariate BRMs, yielded improvements in some cases (R2 up to 0.89. Overall, this study reveals the potential of remotely-sensed plant parameters for estimations of barley biomass. Moreover, it is a first step towards the fusion of 3D spatial and spectral measurements for improving non-destructive biomass estimations.

  1. Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

    Directory of Open Access Journals (Sweden)

    A. Brut

    2009-08-01

    Full Text Available A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France is used to simulate photosynthesis and Leaf Area Index (LAI in southwestern France for a 3-year period (2001–2003. A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

  2. Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

    Directory of Open Access Journals (Sweden)

    A. Brut

    2009-04-01

    Full Text Available A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France is used to simulate photosynthesis and Leaf Area Index (LAI in southwestern France for a 3-year period (2001–2003. A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the inter-annual variability of LAI at a regional scale, is assessed with two satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and the second is based on MODIS data. The comparison reveals discrepancies between the two satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops and coniferous trees than the satellite observations, which may be due to a saturation effect within the satellite signal. The simulated leaf onset presents a significant delay for mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

  3. Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

    Science.gov (United States)

    Brut, A.; Rüdiger, C.; Lafont, S.; Roujean, J.-L.; Calvet, J.-C.; Jarlan, L.; Gibelin, A.-L.; Albergel, C.; Le Moigne, P.; Soussana, J.-F.; Klumpp, K.

    2009-04-01

    A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001-2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the inter-annual variability of LAI at a regional scale, is assessed with two satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and the second is based on MODIS data. The comparison reveals discrepancies between the two satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops and coniferous trees than the satellite observations, which may be due to a saturation effect within the satellite signal. The simulated leaf onset presents a significant delay for mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

  4. Comparison of Different Vegetation Indices for Very High-Resolution Images, Specific Case Ultracam-D Imagery

    Science.gov (United States)

    Barzegar, M.; Ebadi, H.; Kiani, A.

    2015-12-01

    Today digital aerial images acquired with UltraCam sensor are known to be a valuable resource for producing high resolution information of land covers. In this research, different methods for extracting vegetation from semi-urban and agricultural regions were studied and their results were compared in terms of overall accuracy and Kappa statistic. To do this, several vegetation indices were first tested on three image datasets with different object-based classifications in terms of presence or absence of sample data, defining other features and also more classes. The effects of all these cases were evaluated on final results. After it, pixel-based classification was performed on each dataset and their accuracies were compared to optimum object-based classification. The importance of this research is to test different indices in several cases (about 75 cases) and to find the quantitative and qualitative effects of increasing or decreasing auxiliary data. This way, researchers who intent to work with such high resolution data are given an insight on the whole procedure of detecting vegetation species as one of the outstanding and common features from such images. Results showed that DVI index can better detect vegetation regions in test images. Also, the object-based classification with average 93.6% overall accuracy and 86.5% Kappa was more suitable for extracting vegetation rather than the pixel-based classification with average 81.2% overall accuracy and 59.7% Kappa.

  5. COMPARISON OF DIFFERENT VEGETATION INDICES FOR VERY HIGH-RESOLUTION IMAGES, SPECIFIC CASE ULTRACAM-D IMAGERY

    Directory of Open Access Journals (Sweden)

    M. Barzegar

    2015-12-01

    Full Text Available Today digital aerial images acquired with UltraCam sensor are known to be a valuable resource for producing high resolution information of land covers. In this research, different methods for extracting vegetation from semi-urban and agricultural regions were studied and their results were compared in terms of overall accuracy and Kappa statistic. To do this, several vegetation indices were first tested on three image datasets with different object-based classifications in terms of presence or absence of sample data, defining other features and also more classes. The effects of all these cases were evaluated on final results. After it, pixel-based classification was performed on each dataset and their accuracies were compared to optimum object-based classification. The importance of this research is to test different indices in several cases (about 75 cases and to find the quantitative and qualitative effects of increasing or decreasing auxiliary data. This way, researchers who intent to work with such high resolution data are given an insight on the whole procedure of detecting vegetation species as one of the outstanding and common features from such images. Results showed that DVI index can better detect vegetation regions in test images. Also, the object-based classification with average 93.6% overall accuracy and 86.5% Kappa was more suitable for extracting vegetation rather than the pixel-based classification with average 81.2% overall accuracy and 59.7% Kappa.

  6. Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

    Directory of Open Access Journals (Sweden)

    T. Cohen Liechti

    2011-08-01

    Full Text Available In the framework of the African Dams ProjecT (ADAPT, an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin.

    Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42, the Famine Early Warning System product 2.0 (FEWS RFE2.0 and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC morphing technique (CMORPH are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps.

    The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each subbasin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular mesh.

    In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating by nearly 1.5 times the rainfall. The statistics of TRMM and FEWS estimates show quite similar results.

    Due to the its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin.

  7. Vegetation impoverishment despite greening: a case study from central Senegal

    Science.gov (United States)

    Herrmann, Stefanie M.; Tappan, G. Gray

    2013-01-01

    Recent remote sensing studies have documented a greening trend in the semi-arid Sahel and Sudan zones of West Africa since the early 1980s, which challenges the mainstream paradigm of irreversible land degradation in this region. What the greening trend means on the ground, however, has not yet been explored. This research focuses on a region in central Senegal to examine changes in woody vegetation abundance and composition in selected sites by means of a botanical inventory of woody vegetation species, repeat photography, and perceptions of local land users. Despite the greening, an impoverishment of the woody vegetation cover was observed in the studied sites, indicated by an overall reduction in woody species richness, a loss of large trees, an increasing dominance of shrubs, and a shift towards more arid-tolerant, Sahelian species since 1983. Thus, interpretation of the satellite-derived greening trend as an improvement or recovery is not always justified. The case of central Senegal represents only one of several possible pathways of greening throughout the region, all of which result in similar satellite-derived greening signals.

  8. VEGETATIVE PROVISION INDICATORS OF CARDIOVASCULAR SYSTEM AND PHYSICAL EFFICIENCY OF WOMEN ATHLET-SPRINTERS

    Directory of Open Access Journals (Sweden)

    M. V. Didenko

    2014-02-01

    Full Text Available In recent decades there has been a significant increase in physical activity during the preparation of qualified athletes-sprinters. However, it is clear that a simple increase in volume and intensity of training loads in preparation can not be infinite. Russian sport trainers see tactics mistakes. Some authors consider that optimum technique construction of training is possible when taking into account normalizing the volume and load intensity based on the types of circulation (TC. The aim of work was to study the bioelectrical activity of the heart, heart rate variability (HRV, central hemodynamics and physical performance (PP in sportswomen-sprinters qualifications from II-III level to HMS. Materials and research methods. Carried out a comprehensive survey of 30 sportswomen-sprinters, qualifications from II-III level to HMS. For the analysis of vegetative cardiovascular regulation mathematical methods of HRV were used. Central hemodynamics were studied by automated tetrapolar rheography. Determination of PP was performed by using a submaximal cycle ergometer test PWC170. The index of the functional state (IFC was counted on a formula suggested and patented by us. Results of research. The correct sinus rhythm is found in all sportswomen with sufficient voltage and not rejected electrical axis of the heart. Comparison of the mean values of HRV showed the presence in all groups of runners prevalence of a parasympathetic link of VNS. At sportswomen-sprinters qualifications MS-HMS had prevailed hypokinetic TC and the lowering of qualifications the ratio of TC varied: as a runner of qualification I level prevailed eukinetic TC, while the runners of qualifications II-III level has have appeared sportswomen-sprinters with hyperkinetic TC. PP was bigger in sprinters qualifications MS-HMS and tended to decrease with decreasing of the qualifications. Correlation analysis revealed a positive correlation between SI and CI, negative – between the CI and

  9. Temporal variation (seasonal and interannual) of vegetation indices of maize and soybeans across multiple years in central Iowa

    Science.gov (United States)

    Prueger, J. H.; Hatfield, J. L.

    2015-09-01

    Remotely sensed reflectance parameters from corn and soybean surfaces can be correlated to crop production. Surface reflectance of a typical Upper Midwest corn /soybean region in central Iowa across multiple years reveal subtle dynamics in vegetative surface response to a continually varying climate. From 2006 through 2014 remotely sensed data have been acquired over production fields of corn and soybeans in central IA, U.S.A. with the fields alternating between corn and soybeans. The data have been acquired using ground-based radiometers with 16 wavebands covering the visible, near infrared, shortwave infrared wavebands and combined into a series of vegetative indices. These data were collected on clear days with the goal of collecting data at a minimum of once per week from prior to planting until after fall tillage operations. Within each field, five sites were established and sampled during the year to reduce spatial variation and allow for an assessment of changes in the vegetative indices throughout the growing season. Ancillary data collected for each crop included the phenological stage at each sampling date along with biomass sampled at the onset of the reproductive stage and at physiological maturity. Evaluation of the vegetative indices for the different years revealed that patterns were related to weather effects on corn and soybean growth. Remote sensing provides a method to evaluate changes within and among growing seasons to assess crop growth and development as affected by differences in weather variability.

  10. Correlation analysis between forest carbon stock and spectral vegetation indices in Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam

    Science.gov (United States)

    Dung Nguyen, The; Kappas, Martin

    2017-04-01

    In the last several years, the interest in forest biomass and carbon stock estimation has increased due to its importance for forest management, modelling carbon cycle, and other ecosystem services. However, no estimates of biomass and carbon stocks of deferent forest cover types exist throughout in the Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam. This study investigates the relationship between above ground carbon stock and different vegetation indices and to identify the most likely vegetation index that best correlate with forest carbon stock. The terrestrial inventory data come from 380 sample plots that were randomly sampled. Individual tree parameters such as DBH and tree height were collected to calculate the above ground volume, biomass and carbon for different forest types. The SPOT6 2013 satellite data was used in the study to obtain five vegetation indices NDVI, RDVI, MSR, RVI, and EVI. The relationships between the forest carbon stock and vegetation indices were investigated using a multiple linear regression analysis. R-square, RMSE values and cross-validation were used to measure the strength and validate the performance of the models. The methodology presented here demonstrates the possibility of estimating forest volume, biomass and carbon stock. It can also be further improved by addressing more spectral bands data and/or elevation.

  11. Impact analysis of pansharpening Landsat ETM+, Landsat OLI, WorldView-2, and Ikonos images on vegetation indices

    Science.gov (United States)

    Jovanović, Dušan; Govedarica, Miro; Sabo, Filip; Važić, Radmila; Popović, Dragana

    2016-08-01

    The aim of our study was to verify the impact that pansharpening (PS) methods produce on vegetation indices. We used images with both moderate (Landsat 7, Landsat 8) and high (World View2, Ikonos) spatial resolution on which we performed three methods of PS (Brovey transform, Gram-Schmidt and Principal component). The study is based on the differences of vegetation indices (VI) values before and after the pansharpening method is applied. The difference is quantified as an root mean square error. Vegetation indices used in this study were: NDVI, MSAVI2, EVI2, GNDVI, OSAVI and SAVI. Statistical analysis is carried out by calculating coefficients of correlation, root mean square errors and bias calculations for every vegetation index before and after pansharpening procedure is done. The results imply that the BT gave the most diverse results between original VI values and the PS VI values, while the GS and PC methods preserved the values of pixel bands, and that the effect of any PS method is most evident when using Ikonos bands.

  12. Narrow-band and derivative-based vegetation indices for hyperspectral data

    NARCIS (Netherlands)

    Thorp, K.R.; Tian, L.F.; Yao, H.; Tang, L.

    2004-01-01

    Hyperspectral remote sensing imagery was collected over a soybean field in central Illinois in mid-June 2001 before canopy closure. Estimates of percent vegetation cover were generated through the processing of RGB (red, green, blue) digital images collected on the ground with an automated crop mapp

  13. Visual processing during recovery from vegetative state to consciousness: Comparing behavioral indices to brain responses

    NARCIS (Netherlands)

    Wijnen, V.J.; Eilander, H.J.; Gelder, B. de; Boxtel, G.J. Van

    2014-01-01

    BACKGROUND: Auditory stimulation is often used to evoke responses in unresponsive patients who have suffered severe brain injury. In order to investigate visual responses, we examined visual evoked potentials (VEPs) and behavioral responses to visual stimuli in vegetative patients during recovery to

  14. Benchmarking LSM root-zone soil mositure predictions using satellite-based vegetation indices

    Science.gov (United States)

    The application of modern land surface models (LSMs) to agricultural drought monitoring is based on the premise that anomalies in LSM root-zone soil moisture estimates can accurately anticipate the subsequent impact of drought on vegetation productivity and health. In addition, the water and energy ...

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

    Science.gov (United States)

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

    2017-01-01

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

  16. Combining Satellite-Based Precipitation and Vegetation Indices to Achieve a Mid-Summer Agricultural Forecast in Jamaica

    Science.gov (United States)

    Curtis, S.; Allen, T. L.; Gamble, D.

    2009-12-01

    In this study global Earth observations of precipitation and Normalized Difference Vegetation Indices (NDVI) are used to assess the mid-summer dry spell’s (MSD) strength and subsequent impact on agriculture in the St. Elizabeth parish of Jamaica. St. Elizabeth is known as the ‘bread basket’ of Jamaica and has been the top or second highest producer of domestic food crops in the last twenty years. Yet, St. Elizabeth sits in the Jamaican rain shadow and is highly affected by drought. In addition, the summer rainy season is regularly interrupted by an MSD, which often occurs in July, has strong interannual variability, and greatly affects cropping strategies and yields. The steps undertaken to achieve a mid-summer agricultural forecast are: 1) use relationships between Global Precipitation Climatology Project v2.1 data over western Jamaica and predictive climate modes from 1979 to present to develop a forecast of July rainfall 2) downscale the rainfall variability in time to sub-monthly and space to the St. Elizabeth parish using the Tropical Rainfall Measuring Mission 3) link rainfall variability to vegetation vigor with the MODIS NDVI data 4) communicate with St. Elizabeth farmers via the University of West Indies, Mona. An important finding from this study is a decrease in vegetative vigor follows the MSD by two to four weeks in St. Elizabeth and the vegetation in the southern portion of the parish appears to be more sensitive to the MSD than vegetation elsewhere in the country.

  17. Satellite-based Studies on Large-Scale Vegetation Changes in China

    Institute of Scientific and Technical Information of China (English)

    Xia Zhao; Daojing Zhou; Jingyun Fang

    2012-01-01

    Remotely-sensed vegetation indices,which indicate the density and photosynthetic capacity of vegetation,have been widely used to monitor vegetation dynamics over broad areas.In this paper,we reviewed satellite-based studies on vegetation cover changes,biomass and productivity variations,phenological dynamics,desertification,and grassland degradation in China that occurred over the past 2-3 decades.Our review shows that the satellite-derived index (Normalized Difference Vegetation Index,NDVI) during growing season and the vegetation net primary productivity in major terrestrial ecosystems (for example forests,grasslands,shrubs,and croplands) have significantly increased,while the number of fresh lakes and vegetation coverage in urban regions have experienced a substantial decline.The start of the growing season continually advanced in China's temperate regions until the 1990s,with a large spatial heterogeneity.We also found that the coverage of sparsely-vegetated areas declined,and the NDVI per unit in vegetated areas increased in arid and semi-arid regions because of increased vegetation activity in grassland and oasis areas.However,these results depend strongly not only on the periods chosen for investigation,but also on factors such as data sources,changes in detection methods,and geospatial heterogeneity.Therefore,we should be cautious when applying remote sensing techniques to monitor vegetation structures,functions,and changes.

  18. a Diagnostic Approach to Obtaining Planetary Boundary Layer Winds Using Satellite-Derived Thermal Data

    Science.gov (United States)

    Belt, Carol Lynn

    The feasibility of using satellite-derived thermal data to generate realistic synoptic-scale winds within the planetary boundary layer (PBL) is examined. Diagnostic "modified Ekman" wind equations from the Air Force Global Weather Central (AFGWC) Boundary Layer Model are used to compute winds at seven levels within the PBL transition layer (50 m to 1600 m AGL). Satellite-derived winds based on 62 predawn (0921 GMT 19 April 1979) TIROS-N soundings are compared to similarly-derived wind fields based on 39 AVE-SESAME II rawinsonde (RAOB) soundings taken 2 h later. Actual wind fields are also used as a basis for comparison. Qualitative and statistical comparisons show that the Ekman winds from both sources are in very close agreement, with an average vector correlation coefficient of 0.815. Best results are obtained at 300 m AGL. Satellite winds tend to be slightly weaker than their RAOB counterparts and exhibit a greater degree of cross-isobaric flow. The modified Ekman winds show a significant improvement over geostrophic values at levels nearest the surface. Horizontal moisture divergence, moisture advection, velocity divergence and relative vorticity are computed at 300 m AGL using satellite-derived winds and moisture data. Results show excellent agreement with corresponding RAOB-derived values. Areas of horizontal moisture convergence, velocity convergence, and positive vorticity are nearly coincident and align in regions which later develop intense convection. Vertical motion at 1600 m AGL is computed using stepwise integration of the satellite winds through the PBL. Values and patterns are similar to those obtained using the RAOB-derived winds. Regions of maximum upward motion correspond with areas of greatest moisture convergence and the convection that later develops.

  19. A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

    Science.gov (United States)

    Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

    2013-02-01

    Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was

  20. Technical Note: Comparing and ranking soil-moisture indices performance over Europe, through remote-sensing of vegetation

    OpenAIRE

    Peled, E.; Dutra, E.; Viterbo, P; A. Angert

    2009-01-01

    Climate change induces long-term changes in soil-moisture. These changes can have important effects on the terrestrial biosphere, which can feedback into the climate system. In the past years there have been many attempts to produce and improve global soil-moisture datasets, however, comparing and validating these various datasets is not an easy task. Here, interannual variations in indices of soil moisture are compared to interannual changes in vegetation, as captured by NDVI. By comparing t...

  1. Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

    Science.gov (United States)

    Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

    2017-01-01

    This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

  2. Spatial-temporal variations of vegetation and drought severity across Tharparkar, Pakistan, using remote sensing-derived indices

    Science.gov (United States)

    Shah, Sami Ullah; Iqbal, Javed

    2016-07-01

    Tharparkar is an arid region in the southeastern province of Sindh, Pakistan, and experienced drought as a regular phenomenon in the past. The complex nature of drought and sparsely located network of met stations handicapped reliable spatial and temporal analysis of drought severity across Tharparkar. Freely available tropical rainfall measuring mission rainfall satellite data and moderate-resolution imaging spectroradiometer normalized difference vegetation index (NDVI) satellite data fulfilled this gap and were used to generate drought indices. Commonly used NDVI and NDVI anomalies pose problems when compared with standardized meteorological drought indices such as standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI) for drought characterization. This study compared standardized vegetation index (SVI) with traditionally used, i.e., SPI and SPEI, for modeling drought severity in the arid and fragile agro-ecosystem of Tharparkar. SVI significantly correlated with standardized meteorological drought indices (SPI and SPEI) and revealed vegetation dynamics under rainfall and temperature variations. Weighted overlay analysis in geographical information systems depicted an accurate onset of the 2014 drought. This study provides useful information for drought characterization that can be used for drought monitoring and early warning systems in data scarce, arid, and semiarid regions.

  3. A Satellite-Derived Upper-Tropospheric Water Vapor Transport Index for Climate Studies

    Science.gov (United States)

    Jedlovec, Gray J.; Lerner, Jeffrey A.; Atkinson, Robert J.

    1998-01-01

    A new approach is presented to quantify upper-level moisture transport from geostationary satellite data. Daily time sequences of Geostationary Operational Environmental Satellite GOES-7 water vapor imagery were used to produce estimates of winds and water vapor mixing ratio in the cloud-free region of the upper troposphere sensed by the 6.7- microns water vapor channel. The winds and mixing ratio values were gridded and then combined to produce a parameter called the water vapor transport index (WVTI), which represents the magnitude of the two-dimensional transport of water vapor in the upper troposphere. Daily grids of WVTI, meridional moisture transport, mixing ratio, pressure, and other associated parameters were averaged to produce monthly fields for June, July, and August (JJA) of 1987 and 1988 over the Americas and surrounding oceanic regions, The WVTI was used to compare upper-tropospheric moisture transport between the summers of 1987 and 1988, contrasting the latter part of the 1986/87 El Nino event and the La Nina period of 1988. A similar product derived from the National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) 40-Year Reanalysis Project was used to help to validate the index. Although the goal of this research was to describe the formulation and utility of the WVTI, considerable insight was obtained into the interannual variability of upper-level water vapor transport. Both datasets showed large upper-level water vapor transport associated with synoptic features over the Americas and with outflow from tropical convective systems. Minimal transport occurred over tropical and subtropical high pressure regions where winds were light. Index values from NCEP-NCAR were 2-3 times larger than that determined from GOES. This difference resulted from large zonal wind differences and an apparent overestimate of upper-tropospheric moisture in the reanalysis model. A comparison of the satellite-derived monthly

  4. Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA/CHRIS Data Over an Agricultural Area

    Directory of Open Access Journals (Sweden)

    Pablo Martinez

    2009-02-01

    Full Text Available In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC retrieval from Compact High Resolution Imaging Spectrometer (CHRIS data onboard the European Space Agency (ESA Project for On-Board Autonomy (PROBA platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs, in particular the Normalized Difference Vegetation Index (NDVI and the Variable Atmospherically Resistant Index (VARI. The second methodology is based on the Spectral Mixture Analysis (SMA technique, in which a Linear Spectral Unmixing model has been considered in order to retrieve the abundance of the different constituent materials within pixel elements, called Endmembers (EMs. These EMs were extracted from the image using three different methods: i manual extraction using a land cover map, ii Pixel Purity Index (PPI and iii Automated Morphological Endmember Extraction (AMEE. The different methodologies for FVC retrieval were applied to one PROBA/CHRIS image acquired over an agricultural area in Spain, and they were calibrated and tested against in situ measurements of FVC estimated with hemispherical photographs. The results obtained from VIs show that VARI correlates better with FVC than NDVI does, with standard errors of estimation of less than 8% in the case of VARI and less than 13% in the case of NDVI when calibrated using the in situ measurements. The results obtained from the SMA-LSU technique show Root Mean Square Errors (RMSE below 12% when EMs are extracted from the AMEE method and around 9% when extracted from the PPI method. A RMSE value below 9% was obtained for manual extraction of EMs using a land cover use map.

  5. Preliminary survey on site-adaptation techniques for satellite-derived and reanalysis solar radiation datasets

    Energy Technology Data Exchange (ETDEWEB)

    Polo, J.; Wilbert, S.; Ruiz-Arias, J. A.; Meyer, R.; Gueymard, C.; Súri, M.; Martín, L.; Mieslinger, T.; Blanc, P.; Grant, I.; Boland, J.; Ineichen, P.; Remund, J.; Escobar, R.; Troccoli, A.; Sengupta, M.; Nielsen, K. P.; Renne, D.; Geuder, N.; Cebecauer, T.

    2016-07-01

    At any site, the bankability of a projected solar power plant largely depends on the accuracy and general quality of the solar radiation data generated during the solar resource assessment phase. The term 'site adaptation' has recently started to be used in the framework of solar energy projects to refer to the improvement that can be achieved in satellite-derived solar irradiance and model data when short-term local ground measurements are used to correct systematic errors and bias in the original dataset. This contribution presents a preliminary survey of different possible techniques that can improve long-term satellite-derived and model-derived solar radiation data through the use of short-term on-site ground measurements. The possible approaches that are reported here may be applied in different ways, depending on the origin and characteristics of the uncertainties in the modeled data. This work, which is the first step of a forthcoming in-depth assessment of methodologies for site adaptation, has been done within the framework of the International Energy Agency Solar Heating and Cooling Programme Task 46 'Solar Resource Assessment and Forecasting.'

  6. Detecting land-cover change using mappable vegetation related indices: A case study from Sinharaja Man and the Biosphere Reserve

    Directory of Open Access Journals (Sweden)

    BD Madurapperuma

    2014-06-01

    Full Text Available This study evaluates multi-year changes of vegetation in the Sinharaja Man and the Biosphere (MAB reserve using mappable vegetation related indices viz., Normalized Difference Vegetation Index (NDVI and Burn Index (BI. Land-cover changes in the Sinharaja MAB reserve were detected using Landsat 7 ETM+ images for 1993, 2001, and 2005. Seven individual bands of each image were converted to new multiband files by layer stacking using ENVI® 4.5. Then the multiband files were re-projected to UTM Zone 44 North, WGS-84 Datum. Each data set was exported to ENVI® EX software package to detect the changes between time steps based on NDVI and BI using an image difference tool. Land-cover data, which were obtained from the DIVA GIS web portal, were compared with Landsat image data. Results of BI showed that the Sinharaja MAB reserve fringe was vulnerable to forest fire. For example, from 1993- 2001, 160 ha identified as burned area. In contrast, from 2001-2005, 79 ha burned, and for the entire period of 1993-2005, 10 ha burned. NDVI resulted in a 962 ha increase of vegetation prime at the western Sinharaja from 2001-2005. In addition, there was a 15 ha decrease in vegetation from 1993-2005. The results were visualized using an embedded 3D render window of Google Earth and 2D view of ArcGIS explorer online. In conclusion, in-situ ground truthing data is needed for the fire-influenced area for implementing sustainable forest resource management at the Sinharaja MAB reserve. Normal 0 false false false EN-GB X-NONE X-NONE

  7. Assessing Disagreement and Tolerance of Misclassification of Satellite-derived Land Cover Products Used in WRF Model Applications

    Institute of Scientific and Technical Information of China (English)

    GAO Hao; JIA Gensuo

    2013-01-01

    As more satellite-derived land cover products used in the study of global change,especially climate modeling,assessing their quality has become vitally important.In this study,we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme.We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products,and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model.Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes,while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes.The degree of disagreement varied significantly among seven regions of China.The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly.High accuracy and fuzzy agreement occurred in the following classes:water,grassland,cropland,and barren or sparsely vegetated.Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals.Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling.Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.

  8. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

    2016-10-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30 years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and evaluate their applicability for agricultural drought evaluation when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in-situ rainfall measurements across Chile were initially compared to the satellite-based precipitation estimates. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite-based estimates. Nine statistics were used to evaluate the performance of satellite products to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to

  9. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

    2017-04-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty...... an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration...... in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS...

  11. Identifying woody vegetation on coal surface mines using phenological indicators with multitemporal Landsat imagery

    Science.gov (United States)

    Oliphant, A. J.; Li, J.; Wynne, R. H.; Donovan, P. F.; Zipper, C. E.

    2014-11-01

    Surface mining for coal has disturbed large land areas in the Appalachian Mountains. Better information on mined lands' ecosystem recovery status is necessary for effective environmental management in mining-impacted regions. Because record quality varies between state mining agencies and much mining occurred prior to widespread use of geospatial technologies, accurate maps of mining extents, durations, and land cover effects are often not available. Landsat data are well suited to mapping and characterizing land cover and forest recovery on former coal surface mines. Past mine reclamation techniques have often failed to restore premining forest vegetation but natural processes may enable native forests to re-establish on mined areas with time. However, the invasive species autumn olive (Elaeagnus umbellate) is proliferating widely on former coal surface mines, often inhibiting reestablishment of native forests. Autumn olive outcompetes native vegetation because it fixes atmospheric nitrogen and benefits from a longer growing season than native deciduous trees. This longer growing season, along with Landsat 8's high signal to noise ratio, has enabled species-level classification of autumn olive using multitemporal Landsat 8 data at accuracy levels usually only obtainable using higher spatial or spectral resolution sensors. We have used classification and regression tree (CART®) and support vector machine (SVM) to classify five counties in the coal mining region of Virginia for presence and absence of autumn olive. The best model found was a CART® model with 36 nodes which had an overall accuracy of 84% and kappa of 0.68. Autumn olive had conditional kappa of 0.65 and a producers and users accuracy of 86% and 83% respectively. The best SVM model used a second order polynomial kernel and had an overall accuracy of 77%, an overall kappa of 0.54 and a producers and users accuracy of 60% and 90% respectively.

  12. The Potential of Forest Biomass Inversion Based on Vegetation Indices Using Multi-Angle CHRIS/PROBA Data

    Directory of Open Access Journals (Sweden)

    Qiang Wang

    2016-10-01

    Full Text Available Multi-angle remote sensing can either be regarded as an added source of uncertainty for variable retrieval, or as a source of additional information, which enhances variable retrieval compared to traditional single-angle observation. However, the magnitude of these angular and band effects for forest structure parameters is difficult to quantify. We used the Discrete Anisotropic Radiative Transfer (DART model and the Zelig model to simulate the forest canopy Bidirectional Reflectance Distribution Factor (BRDF in order to build a look-up table, and eight vegetation indices were used to assess the relationship between BRDF and forest biomass in order to find the sensitive angles and bands. Further, the European Space Agency (ESA mission, Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy (CHRIS-PROBA and field sample measurements, were selected to test the angular and band effects on forest biomass retrieval. The results showed that the off-nadir vegetation indices could predict the forest biomass more accurately than the nadir. Additionally, we found that the viewing angle effect is more important, but the band effect could not be ignored, and the sensitive angles for extracting forest biomass are greater viewing angles, especially around the hot and dark spot directions. This work highlighted the combination of angles and bands, and found a new index based on the traditional vegetation index, Atmospherically Resistant Vegetation Index (ARVI, which is calculated by combining sensitive angles and sensitive bands, such as blue band 490 nm/−55°, green band 530 nm/55°, and the red band 697 nm/55°, and the new index was tested to improve the accuracy of forest biomass retrieval. This is a step forward in multi-angle remote sensing applications for mining the hidden relationship between BRDF and forest structure information, in order to increase the utilization efficiency of remote sensing data.

  13. Estimating carbon dioxide fluxes from temperate mountain grasslands using broad-band vegetation indices

    Directory of Open Access Journals (Sweden)

    G. Wohlfahrt

    2010-02-01

    Full Text Available The broad-band normalised difference vegetation index (NDVI and the simple ratio (SR were calculated from measurements of reflectance of photosynthetically active and short-wave radiation at two temperate mountain grasslands in Austria and related to the net ecosystem CO2 exchange (NEE measured concurrently by means of the eddy covariance method. There was no significant statistical difference between the relationships of midday mean NEE with narrow- and broad-band NDVI and SR, measured during and calculated for that same time window, respectively. The skill of broad-band NDVI and SR in predicting CO2 fluxes was higher for metrics dominated by gross photosynthesis and lowest for ecosystem respiration, with NEE in between. A method based on a simple light response model whose parameters were parameterised based on broad-band NDVI allowed to improve predictions of daily NEE and is suggested to hold promise for filling gaps in the NEE time series. Relationships of CO2 flux metrics with broad-band NDVI and SR however generally differed between the two studied grassland sites indicting an influence of additional factors not yet accounted for.

  14. Comparative Transcriptomics Indicates a Role for SHORT VEGETATIVE PHASE (SVP Genes in Mimulus guttatus Vernalization Response

    Directory of Open Access Journals (Sweden)

    Jill C. Preston

    2016-05-01

    Full Text Available The timing of reproduction in response to variable environmental conditions is critical to plant fitness, and is a major driver of taxon differentiation. In the yellow monkey flower, Mimulus guttatus, geographically distinct North American populations vary in their photoperiod and chilling (vernalization requirements for flowering, suggesting strong local adaptation to their surroundings. Previous analyses revealed quantitative trait loci (QTL underlying short-day mediated vernalization responsiveness using two annual M. guttatus populations that differed in their vernalization response. To narrow down candidate genes responsible for this variation, and to reveal potential downstream genes, we conducted comparative transcriptomics and quantitative PCR (qPCR in shoot apices of parental vernalization responsive IM62, and unresponsive LMC24 inbred lines grown under different photoperiods and temperatures. Our study identified several metabolic, hormone signaling, photosynthetic, stress response, and flowering time genes that are differentially expressed between treatments, suggesting a role for their protein products in short-day-mediated vernalization responsiveness. Only a small subset of these genes intersected with candidate genes from the previous QTL study, and, of the main candidates tested with qPCR under nonpermissive conditions, only SHORT VEGETATIVE PHASE (SVP gene expression met predictions for a population-specific short-day-repressor of flowering that is repressed by cold.

  15. Utilization of satellite-derived estimates of meteorological and land surface characteristics in the Land Surface Model for vast agricultural region territory

    Science.gov (United States)

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

    2015-04-01

    data from named radiometers. All technologies have been adapted to the study area. Verification of the AVHRR- and MODIS-derived LST estimates has been performed through comparison with ground-measured temperatures and analogous estimates obtained from remaining sensors. The reliability of SEVIRI-derived LST estimates has been verified by comparison with similar synchronous SEVIRI-derived estimates produced in LSA SAF (Land Surface Analysis Satellite Applications Facility, Lisbon, Portugal). Correctness of LAI estimates has been confirmed by comparing time behavior of satellite- and ground-based LAI during vegetation season. Satellite-derived estimates of precipitation have been built using the Multi Threshold Method (MTM) developed for automatic pixel-by-pixel classification of AVHRR and SEVIRI data. The method is intended for the cloud detection and identification of its types, estimation of the maximum liquid water content and water content of the cloud layer, allocation of precipitation zones and determination of instantaneous maximum intensities of precipitation in the pixel range around the clock throughout the year independently of the land surface type. Measurement data from five AVHRR channels or from eleven SEVIRI channels as well as their differences have been used in the MTM as predictors. To validate the methodology, ground-based observation data on daily precipitation sums at agricultural meteorological stations of the study region have been used. The probability of correct precipitation zone detection from satellite data is at least 70% (80-85% in some cases) when compared with ground-based observations. In the frame of this approach the transition from the rainfall intensity estimation to the calculation of their daily values has been accomplished. In the study the AVHRR- and SEVIRI-derived daily, monthly and annual sums of precipitation for the region of interest have been calculated. The daily and monthly sums have been found to be in good agreement

  16. Use of Landsat land surface temperature and vegetation indices for monitoring drought in the Salt Lake Basin Area, Turkey.

    Science.gov (United States)

    Orhan, Osman; Ekercin, Semih; Dadaser-Celik, Filiz

    2014-01-01

    The main purpose of this paper is to investigate multitemporal land surface temperature (LST) changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI), vegetation condition index (VCI), and temperature vegetation index (TVX) were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2) values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2°C) in the Salt Lake Basin area during the 28-year period (1984-2011). Analysis of air temperature data also showed increases at a rate of 1.5-2°C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  17. Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images*

    Science.gov (United States)

    Wang, Jing; Huang, Jing-Feng; Wang, Xiu-Zhen; Jin, Meng-Ting; Zhou, Zhen; Guo, Qiao-Ying; Zhao, Zhe-Wen; Huang, Wei-Jiao; Zhang, Yao; Song, Xiao-Dong

    2015-01-01

    Accurate estimation of rice phenology is of critical importance for agricultural practices and studies. However, the accuracy of phenological parameters extracted by remote sensing data cannot be guaranteed because of the influence of climate, e.g. the monsoon season, and limited available remote sensing data. In this study, we integrate the data of HJ-1 CCD and Landsat-8 operational land imager (OLI) by using the ordinary least-squares (OLS), and construct higher temporal resolution vegetation indices (VIs) time-series data to extract the phenological parameters of single-cropped rice. Two widely used VIs, namely the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2), were adopted to minimize the influence of environmental factors and the intrinsic difference between the two sensors. Savitzky-Golay (S-G) filters were applied to construct continuous VI profiles per pixel. The results showed that, compared with NDVI, EVI2 was more stable and comparable between the two sensors. Compared with the observed phenological data of the single-cropped rice, the integrated VI time-series had a relatively low root mean square error (RMSE), and EVI2 showed higher accuracy compared with NDVI. We also demonstrate the application of phenology extraction of the single-cropped rice in a spatial scale in the study area. While the work is of general value, it can also be extrapolated to other regions where qualified remote sensing data are the bottleneck but where complementary data are occasionally available. PMID:26465131

  18. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

    Directory of Open Access Journals (Sweden)

    Osman Orhan

    2014-01-01

    Full Text Available The main purpose of this paper is to investigate multitemporal land surface temperature (LST changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI, vegetation condition index (VCI, and temperature vegetation index (TVX were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2 values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2∘C in the Salt Lake Basin area during the 28-year period (1984–2011. Analysis of air temperature data also showed increases at a rate of 1.5–2∘C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  19. Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images.

    Science.gov (United States)

    Wang, Jing; Huang, Jing-feng; Wang, Xiu-zhen; Jin, Meng-ting; Zhou, Zhen; Guo, Qiao-ying; Zhao, Zhe-wen; Huang, Wei-jiao; Zhang, Yao; Song, Xiao-dong

    2015-10-01

    Accurate estimation of rice phenology is of critical importance for agricultural practices and studies. However, the accuracy of phenological parameters extracted by remote sensing data cannot be guaranteed because of the influence of climate, e.g. the monsoon season, and limited available remote sensing data. In this study, we integrate the data of HJ-1 CCD and Landsat-8 operational land imager (OLI) by using the ordinary least-squares (OLS), and construct higher temporal resolution vegetation indices (VIs) time-series data to extract the phenological parameters of single-cropped rice. Two widely used VIs, namely the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2), were adopted to minimize the influence of environmental factors and the intrinsic difference between the two sensors. Savitzky-Golay (S-G) filters were applied to construct continuous VI profiles per pixel. The results showed that, compared with NDVI, EVI2 was more stable and comparable between the two sensors. Compared with the observed phenological data of the single-cropped rice, the integrated VI time-series had a relatively low root mean square error (RMSE), and EVI2 showed higher accuracy compared with NDVI. We also demonstrate the application of phenology extraction of the single-cropped rice in a spatial scale in the study area. While the work is of general value, it can also be extrapolated to other regions where qualified remote sensing data are the bottleneck but where complementary data are occasionally available.

  20. Is the patch size distribution of vegetation a suitable indicator of desertification processes? Comment

    NARCIS (Netherlands)

    Kefi, S.; Alados, C.L. y; Chaves, R.C.G.; Pueyo, Y.; Rietkerk, M.G.

    2010-01-01

    With ongoing climate change, the search for indicators of imminent ecosystem shifts is attracting increasing attention (e.g., Scheffer et al. 2009). Recently, the spatial organization of ecosystems has been suggested as a good candidate for such an indicator in spatially structured ecosystems (Rietk

  1. Seasonal and interannual variability of climate and vegetation indices across the Amazon.

    Science.gov (United States)

    Brando, Paulo M; Goetz, Scott J; Baccini, Alessandro; Nepstad, Daniel C; Beck, Pieter S A; Christman, Mary C

    2010-08-17

    Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996-2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002-2005. Using improved enhanced vegetation index (EVI) measurements (2000-2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development.

  2. Satellite-derived sea surface height and sea surface wind data fusion for spilled oil tracking

    Science.gov (United States)

    Kozai, Katsutoshi

    2003-12-01

    An attempt is made to estimate the trajectory of the spilled oil from the sunken tanker Nakhodka occurred on January 2, 1997 in the Japan Sea by fusing two microwave sensor data, namely ERS-2 altimeter and ADEOS/NSCAT scatterometer data. In this study 'fusion' is defined as the method of more reliable prediction for the trajectory of spilled oil than before. Geostrophic current vectors are derived from ERS-2 altimeter and wind-induced drift vectors are derived from ADEOS/NSCAT scatterometer data These two different satellite-derived vectors are 'fused' together in the surface current model to estimate and evaluate the trajectory of spilled oil from the sunken tanker Nakhodka. The distribution of component of spill vector is mostly accounted for by the distribution of geostrophic velocity component during the study period with some discrepancies during March, 1997.

  3. Technical Note: Comparing and ranking soil-moisture indices performance over Europe, through remote-sensing of vegetation

    Directory of Open Access Journals (Sweden)

    E. Peled

    2009-10-01

    Full Text Available Climate change induces long-term changes in soil-moisture. These changes can have important effects on the terrestrial biosphere, which can feedback into the climate system. In the past years there have been many attempts to produce and improve global soil-moisture datasets, however, comparing and validating these various datasets is not an easy task. Here, interannual variations in indices of soil moisture are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which soil moisture index provides the most reliable soil moisture representation. We showed that NDVI can be used as an external validation dataset to soil moisture indices, in areas that are classified as warm temperate climate with hot or warm dry summers. Using the best performing index, NSM (Normalizes Soil Moisture, and the ICA (Independent Component Analysis technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

  4. Spatial Correlation of Satellite-Derived PM2.5 with Hospital Admissions for Respiratory Diseases

    Directory of Open Access Journals (Sweden)

    Ching-Ju Liu

    2016-11-01

    Full Text Available Respiratory diseases, particularly allergic rhinitis, are spatially and temporally correlated with the ground PM2.5 level. A study of the correlation between the two factors should therefore account for spatiotemporal variations. Satellite observation has the advantage of wide spatial coverage over pin-point style ground-based in situ monitoring stations. Therefore, the current study used both ground measurement and satellite data sets to investigate the spatial and temporal correlation of satellite-derived PM2.5 with respiratory diseases. This study used 4-year satellite data and PM2.5 levels of the period at eight stations in Taiwan to obtain the spatial and temporal relationship between aerosol optical depth (AOD and PM2.5. The AOD-PM2.5 model was further examined using the cross-validation (CV technique and was found to have high reliability compared with similar models. The model was used to obtain satellite-derived PM2.5 levels and to analyze the hospital admissions for allergic rhinitis in 2008. The results suggest that adults (18–65 years and children (3–18 years are the most vulnerable groups to the effect of PM2.5 compared with infants and elderly people. This result may be because the two affected age groups spend longer time outdoors. This result may also be attributed to the long-range PM2.5 transport from upper stream locations and the atmospheric circulation patterns, which are significant in spring and fall. The results of the current study suggest that additional environmental factors that might be associated with respiratory diseases should be considered in future studies.

  5. Can satellite-derived water surface changes be used to calibrate a hydrodynamic model?

    Science.gov (United States)

    Revilla-Romero, Beatriz; Beck, Hylke; Salamon, Peter; Burek, Peter; de Roo, Ad; Thielen, Jutta

    2015-04-01

    The limited availability of recent ground observational data is one of the main challenges for validation of hydrodynamic models. This is especially relevant for real-time global applications such as flood forecasting models. In this study, we aim to use remotely-sensed data from the Global Flood Detection System (GFDS) as a proxy of river discharge time series and test its value through calibration of the hydrological model LISFLOOD. This was carried out for the time period 1998-2010 at 40 sites in Africa, Europe, North America and South America by calibrating the parameters that control the flow routing and groundwater processes. We compared the performance of the calibrated simulated discharge time series that used satellite-derived data with the ground discharge time series. Furthermore, we compared it with the independent calibrated run that used ground data and also, to the non-calibrated simulated discharge time series. The non-calibrated set up used a set of parameters which values were predefined by expert-knowledge. This is currently being used by the LISFLOOD set up model embedded in the pre-operational Global Flood Awareness System (GloFAS). The results of this study showed that the satellite surface water changes from the Global Flood Detection System can be used as a proxy of river discharge data, through the demonstration of its added value for model calibration and validation. Using satellite-derived data, the skill scores obtained by the calibrated simulated model discharge improved when comparing to non-calibrated simulated time series. Calibration, post-processing and data assimilation strategies of satellite data as a proxy for streamflow data within the global hydrological model are outlined and discussed.

  6. Temporal Trends in Satellite-Derived Erythemal UVB and Implications for Ambient Sun Exposure Assessment

    Directory of Open Access Journals (Sweden)

    Marvin Langston

    2017-02-01

    Full Text Available Ultraviolet radiation (UVR has been associated with various health outcomes, including skin cancers, vitamin D insufficiency, and multiple sclerosis. Measurement of UVR has been difficult, traditionally relying on subject recall. We investigated trends in satellite-derived UVB from 1978 to 2014 within the continental United States (US to inform UVR exposure assessment and determine the potential magnitude of misclassification bias created by ignoring these trends. Monthly UVB data remotely sensed from various NASA satellites were used to investigate changes over time in the United States using linear regression with a harmonic function. Linear regression models for local geographic areas were used to make inferences across the entire study area using a global field significance test. Temporal trends were investigated across all years and separately for each satellite type due to documented differences in UVB estimation. UVB increased from 1978 to 2014 in 48% of local tests. The largest UVB increase was found in Western Nevada (0.145 kJ/m2 per five-year increment, a total 30-year increase of 0.87 kJ/m2. This largest change only represented 17% of total ambient exposure for an average January and 2% of an average July in Western Nevada. The observed trends represent cumulative UVB changes of less than a month, which are not relevant when attempting to estimate human exposure. The observation of small trends should be interpreted with caution due to measurement of satellite parameter inputs (ozone and climatological factors that may impact derived satellite UVR nearly 20% compared to ground level sources. If the observed trends hold, satellite-derived UVB data may reasonably estimate ambient UVB exposures even for outcomes with long latency phases that predate the satellite record.

  7. IN-SEASON ASSESSMENT OF WHEAT CROP HEALTH USING VEGETATION INDICES BASED ON GROUND MEASURED HYPER SPECTRAL DATA

    Directory of Open Access Journals (Sweden)

    Khalid Ali Al-Gaadi

    2014-01-01

    Full Text Available An experiment on a 50 ha center pivot field was conducted to determine the Vegetation Indices (VI’s that were helpful in assessing the in-season performance of wheat crop treated with graded levels of irrigation water and fertilizers. The irrigation levels were at 100, 90, 80 and 70% evapotranspiration (ETc; however, the fertilizer levels of N: P: K kg-1ha included 300:150:200 (low; 400:250:300 (medium and 500:300:300 (High. The crop was sown on January 1st and harvested on May 9th, 2012. Temporal data on biophysical parameters and reflectance of the crop in hyper spectral bands (350-2500 nm were collected at booting and ripening growth stages (February 17th and April 5th, 2012. Results of the study revealed that many of the tested spectral indices showed significant response to irrigation levels. Out of those, only two spectral indices (Plant Senescence Reflectance Index ‘PSRI’ and Photochemical Reflectance Index ‘PRI’ also exhibited significant response to fertilizer levels. The Middle Infrared-Based Vegetation Index (MIVI showed a significant response to the irrigation levels for both sampling dates. Among the tested spectral indices, Normalized Difference Infrared Index (NDII and Normalized Difference Nitrogen Index (NDNI exhibited the highest correlation to crop Leaf Area Index (LAI. Five indices showed the most response to wheat grain yield. These indices included Near Infrared band (NIR, Water Band Index (WBI, Normalized Water Index-1 (NWI-1, Normalized Water Index-3 (NWI-3 and Normalized Water Index-4 (NWI-4.

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

    Directory of Open Access Journals (Sweden)

    S. Kotsuki

    2015-01-01

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

  9. A multi-sensor method for in-situ quantification of multiple biodiversity and ecosystem service indicators in wetland vegetation

    Science.gov (United States)

    Zlinszky, András; Prager, Katharina; Koma, Zsófia

    2017-04-01

    Biodiversity and ecosystem services are in the focus of biogeosciences research and conservation management worldwide. However, their quantification is notoriously difficult. Since full coverage of biodiversity and/or ecosystem services is unfeasible due to their complexity, indicators are recommended: biophysical quantities that are measureable and are expected to be closely related to biodiversity or to ecosystem processes. Nevertheless, many biodiversity and ecosystem service assessments are based on upscaling very few (if any) in-situ measurements using models driven by basic land cover data. Also, many assessments select only a single or very few indicators, which then does not enable analysis of trade-offs and interconnections. Here we propose a system of simple yet reliable field measurements, based on basic sensors, measurements, imaging and sampling technology, suitable for quantitatively representing many components of biodiversity and ecosystem services in emergent wetland vegetation. Along a transect from open water to the shore, sampling stations are laid out that include water temperature, air temperature and humidity sensors, zenith facing photographs and pole contact counts of vegetation in height intervals. Additionally, for some of these stations, small quadrats of vegetation are harvested, separated to individual species and weighed in height intervals above ground/water. Underwater surface of vegetation is estimated by counting stalks and registering average diameter. Finally, decomposition is quantified by leaving a standard amount of biomass in a plastic net bag and re-weighing it a year later. This system allows measuring alpha and beta diversity together with vertical structural diversity, leaf area (as a proxy of shading and pollution absorbtion), biomass (as a proxy of carbon sequestration), underwater surface (as a proxy of fish population sustaining), microclimate influence and soil provision. The necessary tools are temperature and

  10. Hyperspectral Imagery for Mapping Disease Infection in Oil Palm PlantationUsing Vegetation Indices and Red Edge Techniques

    Directory of Open Access Journals (Sweden)

    Helmi Z.M. Shafri

    2009-01-01

    Full Text Available Problem Statement: Large scale plantation of oil palm trees requires on-time detection of diseases as the ganoderma basal stem rot disease was present in more than 50% of the oil palm plantations in Peninsular Malaysia. Approach: To deal with this problem, airborne hyperspectral imagery offers a better solution in order to detect and map the oil palm trees that were affected by the disease on time. Airborne hyperspectral can provide data on user requirement and has the capability of acquiring data in narrow and contiguous spectral bands which makes it possible to discriminate between healthy and diseased plants better compared to multispectral imagery. By using vegetation indices and red edge techniques, the condition of oil palm trees could be determined accurately. Results: Generally, all of these techniques showed better results as they could give accuracy between 73 and 84%. The highest accuracy was achieved by using Lagrangian interpolation technique with 84% of overall accuracy. Conclusions/Recommendations: The red edge based techniques were more effective than vegetation indices in detecting Ganoderma-infected oil palm trees plantation since there were three out of four techniques that could yield high accuracy results.

  11. Discrimination of growth and water stress in wheat by various vegetation indices through a clear a turbid atmosphere

    Science.gov (United States)

    Jackson, R. D.; Slater, P. M.; Pinter, P. J. (Principal Investigator)

    1982-01-01

    Reflectance data were obtained over a drought-stressed and a well-watered wheat plot with a hand-held radiometer having bands similar to the MSS bands of the LANDSAT satellites. Data for 48 clear days were interpolated to yield reflectance values for each day of the growing season, from planting until harvest. With an atmospheric path radiance model and LANDSAT-2 calibration data, the reflectance were used to simulate LANDSAT digital counts (not quantized) for the four LANDSAT bands for each day of the growing season, through a clear (approximately 100 km meteorological range) and a turbid (approximately 10 km meteorological range) atmosphere. Several ratios and linear combinations of bands were calculated using the simulated data, then assessed for their relative ability to discriminate vegetative growth and plant stress through the two atmospheres. The results show that water stress was not detected by any of the indices until after growth was retarded, and the sensitivity of the various indices to vegetation depended on plant growth stage and atmospheric path radiance.

  12. Vegetation cyclic shift in eutrophic lagoon. Assessment of dystrophic risk indices based on standing crop evaluations

    Science.gov (United States)

    Lenzi, Mauro; Renzi, Monia; Nesti, Ugo; Gennaro, Paola; Persia, Emma; Porrello, Salvatore

    2013-11-01

    Orbetello lagoon (Tuscany, Italy) is a meso-eutrophic, shallow-water ecosystem which has undergone cyclic shifts in macrophyte dominance since 1970. Field data on the total standing crops of Chlorophyceae and Rhodophyceae (from 1983 to 2011) and Angiospermae (seagrass; from 1998 to 2007), produced each year by the ecosystem, was acquired. A general lagoon environment quality score (decay level DL, categories 0-4) was attributed (a posteriori) for each annual dataset examined. Univariate and multivariate statistical analyses were used to relate total macrophyte standing crops of 29 years of monitoring to the general quality score. Two indices were proposed (Abundance of Macroalgae Index, AMI, and Abundance of Seagrass Index, ASI, the latter in two versions, ASI-1 and ASI-2) and tested against DL. The results showed that biomass data did not accurately describe general environmental quality of the lagoon ecosystem, whereas the indices gave a better fit. AMI showed the best performance, demonstrating that macroalga data was much more informative than seagrass data. Values of AMI over 4.0 were significantly associated with critical general quality scores (DL > 2).

  13. How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

    Directory of Open Access Journals (Sweden)

    Yanghui Kang

    2016-07-01

    Full Text Available Leaf Area Index (LAI is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs. We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR, Normalized Difference Vegetation Index (NDVI, two versions of the Enhanced Vegetation Index (EVI and EVI2, and Green Chlorophyll Index (CIGreen. Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 > 0.5, and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

  14. Vegetation changes and timberline fluctuations in the Central Alps as indicators of holocene climatic oscillations

    Energy Technology Data Exchange (ETDEWEB)

    Wick, L.; Tinner, W. [Univ. of Bern (Switzerland)

    1997-11-01

    Pollen and plant-macrofossil data are presented for two lakes near the timberline in the Italian (Lago Basso, 2250 m) and Swiss Central Alps (Gouille Rion, 2343 m). The reforestation at both sites started at 9700-9500 BP with Pinus cembra, Larix decidua, and Betula. The timberline reached its highest elevation between 8700 and 5000 BP and retreated after 5000 BP, due to a mid-Holocene climatic change and increasing human impact since about 3500 BP (Bronze Age). The expansion of Picea abies at Lago Basso between ca. 7500 and 6200 BP was probably favored by cold phases accompanied by increased oceanicity, whereas in the area of Gouille Rion, where spruce expanded rather late (between 4500 and 3500 BP), human influence equality might have been important. The mass expansion of Alnus viridis between ca. 5000 and 3500 BP probably can be related to both climatic change and human activity at timberline. During the early and middle Holocene a series of timberline fluctuations is recorded as declines in pollen and macrofossil concentrations of the major tree species, and as increases in nonarboreal pollen in the pollen percentage diagram of Gouille Rion. Most of the periods of low timberline can be correlated by radiocarbon dating the climatic changes in the Alps as indicated by glacier advances in combination with palynological records, solifluction, and dendroclimatical data. Lago Basso and Gouille Rion are the only sites in the Alps showing complete palaeobotanical records of cold phases between 10,000 and 2000 BP with very good time control. The altitudinal range of the Holocene treeline fluctuations caused by climate most likely was not more than 100 to 150 m. A possible correlation of a cold period at ca. 7500-6500 BP (Misox oscillation) in the Alps is made with paleoecological data from North American and Scandinavia and a climate signal in the GRIP ice core from central Greenland 8200 yr ago (ca. 7400 yr uncal. BP).

  15. Surface radiation at sea validation of satellite-derived data with shipboard measurements

    Directory of Open Access Journals (Sweden)

    Hein Dieter Behr

    2009-03-01

    Full Text Available Quality-controlled and validated radiation products are the basis for their ability to serve the climate and solar energy community. Satellite-derived radiation fluxes are well preferred for this task as they cover the whole research area in time and space. In order to monitor the accuracy of these data, validation with well maintained and calibrated ground based measurements is necessary. Over sea, however, long-term accurate reference data sets from calibrated instruments recording radiation are scarce. Therefore data from research vessels operating at sea are used to perform a reasonable validation. A prerequisite is that the instruments on board are maintained as well as land borne stations. This paper focuses on the comparison of radiation data recorded on board of the German Research Vessel "Meteor" during her 13 months cruise across the Mediterranean and the Black Sea with CM-SAF products using NOAA- and MSG-data (August 2006-August 2007: surface incoming short-wave radiation (SIS and surface downward long-wave radiation (SDL. Measuring radiation fluxes at sea causes inevitable errors, e.g.shadowing of fields of view of the radiometers by parts of the ship. These ship-inherent difficulties are discussed at first. A comparison of pairs of ship-recorded and satellite-derived mean fluxes for the complete measuring period delivers a good agreement: the mean bias deviation (MBD for SIS daily means is −7.6 W/m2 with a median bias of −4 W/m2 and consistently the MBD for monthly means is −7.3 W/m2, for SDL daily means the MBD is 8.1 and 6 W/m2 median bias respectively. The MBD for monthly means is 8.2 W/m2. The variances of the daily means (ship and satellite have the same annual courses for both fluxes. No significant dependence of the bias on the total cloud cover recorded according to WMO (1969 has been found. The results of the comparison between ship-based observations and satellite retrieved surface radiation reveal the good accuracy

  16. Satellite Derived Volcanic Ash Product Inter-Comparison in Support to SCOPE-Nowcasting

    Science.gov (United States)

    Siddans, Richard; Thomas, Gareth; Pavolonis, Mike; Bojinski, Stephan

    2016-04-01

    In support of aeronautical meteorological services, WMO organized a satellite-based volcanic ash retrieval algorithm inter-comparison activity, to improve the consistency of quantitative volcanic ash products from satellites, under the Sustained, Coordinated Processing of Environmental Satellite Data for Nowcasting (SCOPEe Nowcasting) initiative (http:/ jwww.wmo.int/pagesjprogjsatjscopee nowcasting_en.php). The aims of the intercomparison were as follows: 1. Select cases (Sarychev Peak 2009, Eyjafyallajökull 2010, Grimsvötn 2011, Puyehue-Cordón Caulle 2011, Kirishimayama 2011, Kelut 2014), and quantify the differences between satellite-derived volcanic ash cloud properties derived from different techniques and sensors; 2. Establish a basic validation protocol for satellite-derived volcanic ash cloud properties; 3. Document the strengths and weaknesses of different remote sensing approaches as a function of satellite sensor; 4. Standardize the units and quality flags associated with volcanic cloud geophysical parameters; 5. Provide recommendations to Volcanic Ash Advisory Centers (VAACs) and other users on how to best to utilize quantitative satellite products in operations; 6. Create a "road map" for future volcanic ash related scientific developments and inter-comparison/validation activities that can also be applied to SO2 clouds and emergent volcanic clouds. Volcanic ash satellite remote sensing experts from operational and research organizations were encouraged to participate in the inter-comparison activity, to establish the plans for the inter-comparison and to submit data sets. RAL was contracted by EUMETSAT to perform a systematic inter-comparison of all submitted datasets and results were reported at the WMO International Volcanic Ash Inter-comparison Meeting to held on 29 June - 2 July 2015 in Madison, WI, USA (http:/ /cimss.ssec.wisc.edujmeetings/vol_ash14). 26 different data sets were submitted, from a range of passive imagers and spectrometers and

  17. Application of advanced very high resolution radiometer (AVHRR)-based vegetation health indices for estimation of malaria cases.

    Science.gov (United States)

    Rahman, Atiqur; Krakauer, Nir; Roytman, Leonid; Goldberg, Mitch; Kogan, Felix

    2010-06-01

    Satellite data may be used to map climatic conditions conducive to malaria outbreaks, assisting in the targeting of public health interventions to mitigate the worldwide increase in incidence of the mosquito-transmitted disease. This work analyzes correlation between malaria cases and vegetation health (VH) indices derived from satellite remote sensing for each week over a period of 14 years for Bandarban, Bangladesh. Correlation analysis showed that years with a high summer temperature condition index (TCI) tended to be those with high malaria incidence. Principal components regression was performed on patterns of weekly TCI during each of the two annual malaria seasons to construct a model as a function of the TCI. These models reduced the malaria estimation error variance by 57% if first-peak (June-July) TCI was used as the estimator and 74% if second-peak (August-September) was used, compared with an estimation of average number of malaria cases for each year.

  18. Effects of Salicylic acid and Humic acid on Vegetative Indices of Periwinkle (Catharanthus roseusL.

    Directory of Open Access Journals (Sweden)

    E. Chamani

    2016-07-01

    greatest impact on the number of pods. The results showed that treatment with 1000 mg/l salicylic acid and humic acid had the greatest effect on stem diameter. Conclusion: The results of this study indicated that low concentrations of salicylic acid increased plant height, the number of leaves, chlorophyll content and stomatal conductance, which can increase plant resistance against unfavorable environmental conditions. As a result, the plants treated with salicylic acid can be increased two driven in adverse environmental conditions. The treatment of humic acid by increasing the rate of photosynthesis and increases the amount of material available for plant growth. This increase can accelerate the growth of the main branch and side periwinkle plant medicinal plants and enhances the appearance of the plant.

  19. High resolution satellite derived erodibility factors for WRF/Chem windblown dust simulations in Argentina

    Science.gov (United States)

    Cremades, Pablo Gabriel; Fernandez, Rafael Pedro; Allend, David; Mulena, Celeste; Puliafito, Salvador Enrique

    2017-04-01

    A proper representation of dust sources is critical to accurately predict atmospheric particle concentrations in regional windblown dust simulations. The Weather Research and Forecasting model with Chemistry (WRF/Chem) includes a topographic-based erodibility map originally conceived for global scale modeling, which fails to identify the geographical location of dust sources in many regions of Argentina. Therefore, this study aims at developing a method to obtain a high-resolution erodibility map suitable for regional or local scale modeling using WRF/Chem. We present two independent approaches based on global methods to estimate soil erodibility using satellite retrievals, i.e. topography from the Shuttle Radar Topography Mission (SRTM) and surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). Simulation results of a severe Zonda wind episode in the arid central-west Argentina serve as bases for the analysis of these methods. Simulated dust concentration at surface level is compared with particulate matter measurements at one site in Mendoza city. In addition, we use satellite aerosol optical depth (AOD) retrievals to investigate model performance in reproducing spatial distribution of dust emissions. The erodibility map based on surface reflectance from MODIS improves the representation of small scale features, and increases the overall dust aerosol loading with respect to the standard map included by default. Simulated concentrations are in good agreement with measurements as well as satellite derived dust spatial distribution.

  20. Spatial disaggregation of satellite-derived irradiance using a high-resolution digital elevation model

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz-Arias, Jose A.; Tovar-Pescador, Joaquin [Department of Physics, University of Jaen (Spain); Cebecauer, Tomas [European Commission, Joint Research Centre, Ispra (Italy); GeoModel s.r.o., Bratislava (Slovakia); Institute of Geography, Slovak Academy of Sciences, Bratislava (Slovakia); Suri, Marcel [European Commission, Joint Research Centre, Ispra (Italy); GeoModel s.r.o., Bratislava (Slovakia)

    2010-09-15

    Downscaling of the Meteosat-derived solar radiation ({proportional_to}5 km grid resolution) is based on decomposing the global irradiance and correcting the systematic bias of its components using the elevation and horizon shadowing that are derived from the SRTM-3 digital elevation model (3 arc sec resolution). The procedure first applies the elevation correction based on the difference between coarse and high spatial resolution. Global irradiance is split into direct, diffuse circumsolar and diffuse isotropic components using statistical models, and then corrections due to terrain shading and sky-view fraction are applied. The effect of reflected irradiance is analysed only in the theoretical section. The method was applied in the eastern Andalusia, Spain, and the validation was carried out for 22 days on April, July and December 2006 comparing 15-min estimates of the satellite-derived solar irradiance and observations from nine ground stations. Overall, the corrections of the satellite estimates in the studied region strongly reduced the mean bias of the estimates for clear and cloudy days from roughly 2.3% to 0.4%. (author)

  1. Validation of Satellite-Derived Sea Surface Temperatures for Waters around Taiwan

    Directory of Open Access Journals (Sweden)

    Ming-An Lee

    2005-01-01

    Full Text Available In order to validate the Advanced Very High Resolution Radiometer (AVHRR-derived sea surface temperatures (SST of the waters around Taiwan, we generated a match-up data set of 961 pairs, which included in situ SSTs and concurrent AVHRR measurements for the period of 1998 to 2002. Availability of cloud-free images, i.e., images with more than 85% of cloud-free area in their coverage, was about 2.23% of all AVHRR images during the study period. The range of in situ SSTs was from _ to _ The satellite derived-SSTs through MCSST and NLSST algorithms were linearly related to the in situ SSTs with correlation coefficients of 0.985 and 0.98, respectively. The MCSSTs and NLSSTs had small biases of 0.009 _ and 0.256 _ with root mean square deviations of 0.64 _ and 0.801 _ respectively, therefore the AVHRR-based MCSSTs and NLSSTs had high accuracy in the seas around Taiwan.

  2. Evaluation of a physically-based snow model with infrared and microwave satellite-derived estimates

    Science.gov (United States)

    Wang, L.

    2013-05-01

    Snow (with high albedo, as well as low roughness and thermal conductivity) has significant influence on the land-atmosphere interactions in the cold climate and regions of high elevation. The spatial and temporal variability of the snow distribution on a basin scale greatly determines the timing and magnitude of spring snowmelt runoff. For improved water resources management, a physically-based distributed snow model has been developed and applied to the upper Yellow River Basin to provide the outputs of snow variables as well as streamflows from 2001 to 2005. Remotely-sensed infrared information from MODIS satellites has been used to evaluate the model's outputs of spatially-distributed snow cover extent (SCE) and land surface temperature (LST); while the simulated snow depth (SD) and snow water equivalent (SWE) have been compared with the microwave information from SSM/I and AMSR-E satellites. In general, the simulated streamflows (including spring snowmelt) agree fairly well with the gauge-based observations; while the modeled snow variables show acceptable accuracies through comparing to various satellite-derived estimates from infrared or microwave information.;

  3. Satellite derived precipitation and freshwater flux variability and its dependence on the North Atlantic Oscillation

    Science.gov (United States)

    Andersson, Axel; Bakan, Stephan; Graßl, Hartmut

    2010-08-01

    The variability of satellite retrieved precipitation and freshwater flux from the `Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data' (HOAPS) is assessed with special emphasis on the `North Atlantic Oscillation' (NAO). To cover also land areas, a novel combination of the satellite derived precipitation climatology with the rain gauge based `Full Data Reanalysis Product Version 4', of the `Global Precipitation Climatology Centre' (GPCC) is used. This yields unique high-resolution, quasi-global precipitation fields compiled from two independent data sources. Over the ocean, the response of the freshwater balance and the related parameters to the NAO is investigated for the first time by using a purely satellite based data set. A strong dependence of precipitation patterns to the state of the NAO is found. On synoptic scale this is in accordance with earlier findings by other satellite based and reanalysis products. Furthermore, the consistency of the combined HOAPS-3/GPCC data set allows also detailed regional analyses of precipitation patterns. The response of HOAPS-3 freshwater flux to the NAO is dominated by precipitation at mid and high latitudes, while for the subtropical regions the feedback of the evaporation is stronger.

  4. Drought impacts on vegetation dynamics in the Mediterranean based on remote sensing and multi-scale drought indices

    Science.gov (United States)

    Trigo, Ricardo; Gouveia, Celia M.; Beguería, Santiago; Vicente-Serrano, Sergio

    2015-04-01

    A number of recent studies have identified a significant increase in the frequency of drought events in the Mediterranean basin (e.g. Trigo et al., 2013, Vicente-Serrano et al., 2014). In the Mediterranean region, large drought episodes are responsible for the most negative impacts on the vegetation including significant losses of crop yield, increasing risk of forest fires (e.g. Gouveia et al., 2012) and even forest decline. The aim of the present work is to analyze in detail the impacts of drought episodes on vegetation in the Mediterranean basin behavior using NDVI data from (from GIMMS) for entire Mediterranean basin (1982-2006) and the multi-scale drought index (the Standardised Precipitation-Evapotranspiration Index (SPEI). Correlation maps between fields of monthly NDVI and SPEI for at different time scales (1-24 months) were computed in order to identify the regions and seasons most affected by droughts. Affected vegetation presents high spatial and seasonal variability, with a maximum in summer and a minimum in winter. During February 50% of the affected pixels corresponded to a time scale of 6 months, while in November the most frequent time scale corresponded to 3 months, representing more than 40% of the affected region. Around 20% of grid points corresponded to the longer time scales (18 and 24 months), persisting fairly constant along the year. In all seasons the wetter clusters present higher NDVI values which indicates that aridity holds a key role to explain the spatial differences in the NDVI values along the year. Despite the localization of these clusters in areas with higher values of monthly water balance, the strongest control of drought on vegetation activity are observed for the drier classes located over regions with smaller absolute values of water balance. Gouveia C.M., Bastos A., Trigo R.M., DaCamara C.C. (2012) "Drought impacts on vegetation in the pre and post-fire events over Iberian Peninsula". Natural Hazards and Earth System

  5. Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral Measurements

    Directory of Open Access Journals (Sweden)

    Davoud Ashourloo

    2014-06-01

    Full Text Available Spectral Vegetation Indices (SVIs have been widely used to indirectly detect plant diseases. The aim of this research is to evaluate the effect of different disease symptoms on SVIs and introduce suitable SVIs to detect rust disease. Wheat leaf rust is one of the prevalent diseases and has different symptoms including yellow, orange, dark brown, and dry areas. The reflectance spectrum data for healthy and infected leaves were collected using a spectroradiometer in the 450 to 1000 nm range. The ratio of the disease-affected area to the total leaf area and the proportion of each disease symptoms were obtained using RGB digital images. As the disease severity increases, so does the scattering of all SVI values. The indices were categorized into three groups based on their accuracies in disease detection. A few SVIs showed an accuracy of more than 60% in classification. In the first group, NBNDVI, NDVI, PRI, GI, and RVSI showed the highest amount of classification accuracy. The second and third groups showed classification accuracies of about 20% and 40% respectively. Results show that few indices have the ability to indirectly detect plant disease.

  6. Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery

    Science.gov (United States)

    Zhou, X.; Zheng, H. B.; Xu, X. Q.; He, J. Y.; Ge, X. K.; Yao, X.; Cheng, T.; Zhu, Y.; Cao, W. X.; Tian, Y. C.

    2017-08-01

    Timely and non-destructive assessment of crop yield is an essential part of agricultural remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a novel approach for RS, and makes it possible to acquire high spatio-temporal resolution imagery on a regional scale. In this study, the rice grain yield was predicted with single stage vegetation indices (VIs) and multi-temporal VIs derived from the multispectral (MS) and digital images. The results showed that the booting stage was identified as the optimal stage for grain yield prediction with VIs at a single stage for both digital image and MS image. And corresponding optimal color index was VARI with R2 value of 0.71 (Log relationship). While the optimal vegetation index NDVI[800,720] based on MS images showed a linear relationship with the grain yield and gained a higher R2 value (0.75) than color index did. The multi-temporal VIs showed a higher correlation with grain yield than the single stage VIs did. And the VIs at two random growth stage with the multiple linear regression function [MLR(VI)] performed best. The highest correlation coefficient were 0.76 with MLR(NDVI[800,720]) at the booting and heading stages (for the MS image) and 0.73 with MLR(VARI) at the jointing and booting stages (for the digital image). In addition, the VIs that showed a high correlation with LAI performed well for yield prediction, and the VIs composed of red edge band (720 nm) and near infrared band (800 nm) were found to be more effective in predicting yield and LAI at high level. In conclusion, this study has demonstrated that both MS and digital sensors mounted on the UAV are reliable platforms for rice growth and grain yield estimation, and determined the best period and optimal VIs for rice grain yield prediction.

  7. Irrigation Requirement Estimation using MODIS Vegetation Indices and Inverse Biophysical Modeling; A Case Study for Oran, Algeria

    Science.gov (United States)

    Bounoua, L.; Imhoff, M.L.; Franks, S.

    2008-01-01

    Human demand for food influences the water cycle through diversion and extraction of fresh water needed to support agriculture. Future population growth and economic development alone will substantially increase water demand and much of it for agricultural uses. For many semi-arid lands, socio-economic shifts are likely to exacerbate changes in climate as a driver of future water supply and demand. For these areas in particular, where the balance between water supply and demand is fragile, variations in regional climate can have potentially predictable effect on agricultural production. Satellite data and biophysically-based models provide a powerful method to quantify the interactions between local climate, plant growth and water resource requirements. In irrigated agricultural lands, satellite observations indicate high vegetation density while the precipitation amount indicates otherwise. This inconsistency between the observed precipitation and the observed canopy leaf density triggers the possibility that the observed high leaf density is due to an alternate source of water, irrigation. We explore an inverse process approach using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), climatological data, and the NASA's Simple Biosphere model, SiB2, to quantitatively assess water demand in a semi-arid agricultural land by constraining the carbon and water cycles modeled under both equilibrium (balance between vegetation and prevailing local climate) and nonequilibrium (water added through irrigation) conditions. We postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. We added water using two distribution methods: The first method adds water on top of the canopy and is a proxy for the traditional spray irrigation. The second method allows water to be applied directly into the soil layer and serves as proxy for drip irrigation. Our approach indicates that over

  8. Earlier vegetation green-up has reduced spring dust storms.

    Science.gov (United States)

    Fan, Bihang; Guo, Li; Li, Ning; Chen, Jin; Lin, Henry; Zhang, Xiaoyang; Shen, Miaogen; Rao, Yuhan; Wang, Cong; Ma, Lei

    2014-01-01

    The observed decline of spring dust storms in Northeast Asia since the 1950s has been attributed to surface wind stilling. However, spring vegetation growth could also restrain dust storms through accumulating aboveground biomass and increasing surface roughness. To investigate the impacts of vegetation spring growth on dust storms, we examine the relationships between recorded spring dust storm outbreaks and satellite-derived vegetation green-up date in Inner Mongolia, Northern China from 1982 to 2008. We find a significant dampening effect of advanced vegetation growth on spring dust storms (r = 0.49, p = 0.01), with a one-day earlier green-up date corresponding to a decrease in annual spring dust storm outbreaks by 3%. Moreover, the higher correlation (r = 0.55, p green-up date and dust storm outbreak ratio (the ratio of dust storm outbreaks to times of strong wind events) indicates that such effect is independent of changes in surface wind. Spatially, a negative correlation is detected between areas with advanced green-up dates and regional annual spring dust storms (r = -0.49, p = 0.01). This new insight is valuable for understanding dust storms dynamics under the changing climate. Our findings suggest that dust storms in Inner Mongolia will be further mitigated by the projected earlier vegetation green-up in the warming world.

  9. Using GIS data and satellite derived irradiance to optimize siting of PV installations in Switzerland

    Science.gov (United States)

    Kahl, Annelen; Nguyen, Viet-Anh; Bartlett, Stuart; Sossan, Fabrizio; Lehning, Michael

    2016-04-01

    For a successful distribution strategy of PV installations, it does not suffice to choose the locations with highest annual total irradiance. Attention needs to be given to spatial correlation patterns of insolation to avoid large system-wide variations, which can cause extended deficits in supply or might even damage the electrical network. One alternative goal instead is to seek configurations that provide the smoothest energy production, with the most reliable and predictable supply. Our work investigates several scenarios, each pursuing a different strategy for a future renewable Switzerland without nuclear power. Based on an estimate for necessary installed capacity for solar power [Bartlett, 2015] we first use heuristics to pre-select realistic placements for PV installations. Then we apply optimization methods to find a subset of locations that provides the best possible combined electricity production. For the first part of the selection process, we use a DEM to exclude high elevation zones which would be difficult to access and which are prone to natural hazards. Then we use land surface cover information to find all zones with potential roof area, deemed suitable for installation of solar panels. The optimization employs Principal Component Analysis of satellite derived irradiance data (Surface Incoming Shortwave Radiation (SIS), based on Meteosat Second Generation sensors) to incorporate a spatial aspect into the selection process that does not simply maximize annual total production but rather provides the most robust supply, by combining regions with anti-correlated cloud cover patterns. Depending on the initial assumptions and constraints, the resulting distribution schemes for PV installations vary with respect to required surface area, annual total and lowest short-term production, and illustrate how important it is to clearly define priorities and policies for a future renewable Switzerland.

  10. Dryness Indices Based on Remotely Sensed Vegetation and Land Surface Temperature for Evaluating the Soil Moisture Status in Cropland-Forest-Dominant Watersheds

    Directory of Open Access Journals (Sweden)

    Heewon Moon and Minha Choi

    2015-01-01

    Full Text Available The Temperature Vegetation Dryness Index (TVDI was derived from the relationship between remotely sensed vegetation indices and land surface temperature (TS in this study for assessing the soil moisture status at regional scale in South Korea. The Leaf Area Index (LAI is newly applied in this method to overcome the increasing uncertainty of using the Normalized Difference Vegetation Index (NDVI at high vegetation conditions. Both dryness indices were found to be well correlated with in situ soil moisture and 8-day average precipitation at most of the in situ measurement sites. The dryness indices accuracy was found to be influenced by rainfall events. An average correlation coefficient was improved from -0.253 to -0.329 when LAI was used instead of NDVI in calculating the TVDI. In the spatial analysis between the dryness indices and Advanced SCATterometer (ASCAT surface soil moisture (SSM using geographically weighted regression (GWR, the results showed the average negative correlation (R between the variables, while LAI-induced TVDI was more strongly correlated with SSM on average with the R value improved from -0.59 to -0.62. Both dryness indices and ASCAT SSM mappings generally showed coherent patterns under low vegetation and dry conditions. Based on these results, the LAI-induced TVDI accuracy as an index for soil moisture status was validated and found appropriate for use as an alternative and complementary method for NDVI-induced TVDI.

  11. Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

    Science.gov (United States)

    Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

    2008-01-01

    The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

  12. Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.

    Directory of Open Access Journals (Sweden)

    Wenquan Zhu

    Full Text Available Carbon Flux Phenology (CFP can affect the interannual variation in Net Ecosystem Exchange (NEE of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands, using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU by more than 70% and End of Carbon Uptake (ECU by more than 60%. The Root Mean Square Error (RMSE of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.

  13. Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.

    Science.gov (United States)

    Zhu, Wenquan; Chen, Guangsheng; Jiang, Nan; Liu, Jianhong; Mou, Minjie

    2013-01-01

    Carbon Flux Phenology (CFP) can affect the interannual variation in Net Ecosystem Exchange (NEE) of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP) metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands), using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU) by more than 70% and End of Carbon Uptake (ECU) by more than 60%. The Root Mean Square Error (RMSE) of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.

  14. Data service platform for MODIS Vegetation Indices time series processing at BOKU Vienna: current status and future perspectives

    Science.gov (United States)

    Vuolo, Francesco; Mattiuzzi, Matteo; Klisch, Anja; Atzberger, Clement

    2012-10-01

    The aim of this paper is to present a freely available data service platform (http://ivfl-info.boku.ac.at/) for executing preprocessing operations (such as data smoothing, spatial and temporal sub-setting, mosaicking and reprojection) of time series of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (NDVI and EVI) on request. The web-application is based on the integration of various software and hardware components: a web-interface and a MySQL database are used to collect and store user's requests. A server-side application schedules the user's requests and delivers the results. The core of the processing system is based on the "MODIS" package developed in R, which provides MODIS data collection and pre-processing capabilities. Smoothed and gap-filled data sets are derived using the state-ofthe- art Whittaker filter implemented in Matlab. After the processing, data are delivered directly via ftp access. An analysis of the performance of the web-application, along with processing capacity is presented. Results are discussed, in particular in view of an operative platform for real time filtering, phenology and land cover mapping.

  15. Regional scaling of soil moisture dynamics on the semiarid grasslands of Mexico through remotely sensed vegetation indices

    Science.gov (United States)

    Carrera-Hernandez, J. J.; Mata-Martinez, A.; Huber-Sannwald, E.; Arredondo, T.

    2014-12-01

    Soil moisture dynamics for both native (Bouteloa gracilis) and introduced (Eragrostis curvula) species within the semiarid grasslands in Mexico are analyzed. The semiarid grasslands of Mexico are part of the shortgrass steppe ecosystem, which extends from the North American midwest in the north to Llanos de Ojuelos in the south, where the study site is located. Soil moisture dynamics are measured on two homogeneous fields; one dominated by the native species (Bouteloa gracilis), and another with an introduced species (Eragrostis curvula) at three different depths with high temporal resolution along with standard climatological data. These data are related to measured Leaf Area Index (LAI) and spectra at 16 different wavelengths, both of which, in turn, are related to remotely sensed imagery through different vegetation indices (NDVI, SAVI, EVI and Modified Chlorophyll Absorption Ratio Index (MCARI)) for different sensors (LANDSAT, SPOT, Pleiades) at different growth stages. To date, the MCARI exhibits a larger correlation with LAI for all sensors and growing stages for both grass species (ongoing field work will provide additional data). Regionalization of soil moisture dynamics (i.e. recharge) will be done using a numerical model of the vadose zone that will be linked to the temporal variation of MCARI. Financial support by the Mexico's CONACYT (project CB 158370) and UNAM's PAPIIT program (project IA100613) is acknowledged.

  16. Pollen core assemblages as indicator of Polynesian and European impact on the vegetation cover of Auckland Isthmus catchment, New Zealand

    Science.gov (United States)

    Abrahim, Ghada M. S.; Parker, Robin J.; Horrocks, Mark

    2013-10-01

    Tamaki Estuary is an arm of the Hauraki Gulf situated on the eastern side of central Auckland. Over the last 100 years, Tamaki catchment has evolved from a nearly rural landscape to an urbanised and industrialised area. Pollen, 14C and glass shards analyses, were carried out on three cores collected along the estuary with the aim to reconstruct the estuary's history over the last ˜8000 years and trace natural and anthropogenic effects recorded in the sediments. Glass shard analysis was used to establish key tephra time markers such as the peralkaline eruption of Mayor Island, ˜6000 years BP. During the pre-Polynesian period (since at least 8000 years BP), regional vegetation was podocarp/hardwood forest dominated by Dacrydium cupressinun, Prumnopits taxifolia, and Metrosideros. Major Polynesian settler impact (commencing ˜700 yr BP) was associated with forest clearance as indicated by a sharp decline in forest pollen types. This coincided with an increase in bracken (Pteridium esculentum) spores and grass pollen. Continuing landscape disturbance during European settlement (commencing after 1840 AD) was accompanied by the distinctive appearance of exotic pollen taxa such as Pinus.

  17. Land Cover Classification in an Ecuadorian Mountain Geosystem Using a Random Forest Classifier, Spectral Vegetation Indices, and Ancillary Geographic Data

    Directory of Open Access Journals (Sweden)

    Johanna E. Ayala-Izurieta

    2017-05-01

    Full Text Available We presented a methodology to accurately classify mountainous regions in the tropics. These landscapes are complex in terms of their geology, ecosystems, climate and land use. Obtaining accurate maps to assess land cover change is essential. The objectives of this study were to (1 map vegetation using the Random Forest Classifier (RFC, spectral vegetation index (SVI, and ancillar geographic data (2 identify important variables that help differentiate vegetation cover, and (3 assess the accuracy of the vegetation cover classification in hard-to-reach Ecuadorian mountain region. We used Landsat 7 ETM+ satellite images of the entire scene, a RFC algorithm, and stratified random sampling. The altitude and the two band enhanced vegetation index (EVI2 provide more information on vegetation cover than the traditional and often use normalized difference vegetation index (NDVI in other settings. We classified the vegetation cover of mountainous areas within the 1016 km2 area of study, at 30 m spatial resolution, using RFC that yielded a land cover map with an overall accuracy of 95%. The user´s accuracy and the half-width of the confidence interval for 95% of the basic map units, forest (FOR, páramo (PAR, crop (CRO and pasture (PAS were 95.85% ± 2.86%, 97.64% ± 1.24%, 91.53% ± 3.35% and 82.82% ± 7.74%, respectively. The overall disagreement was 4.47%, which results from adding 0.43% of quantity disagreement and 4.04% of allocation disagreement. The methodological framework presented in this paper and the combined use of SVIs, ancillary geographic data, and the RFC allowed the accurate mapping of hard-to-reach mountain landscapes as well as uncovering the underlying factors that help differentiate vegetation cover in the Ecuadorian mountain geosystem.

  18. A Satellite-Derived Climatological Analysis of Urban Heat Island over Shanghai during 2000–2013

    Directory of Open Access Journals (Sweden)

    Weijiao Huang

    2017-06-01

    Full Text Available The urban heat island is generally conducted based on ground observations of air temperature and remotely sensing of land surface temperature (LST. Satellite remotely sensed LST has the advantages of global coverage and consistent periodicity, which overcomes the weakness of ground observations related to sparse distributions and costs. For human related studies and urban climatology, canopy layer urban heat island (CUHI based on air temperatures is extremely important. This study has employed remote sensing methodology to produce monthly CUHI climatology maps during the period 2000–2013, revealing the spatiotemporal characteristics of daytime and nighttime CUHI during this period of rapid urbanization in Shanghai. Using stepwise linear regression, daytime and nighttime air temperatures at the four overpass times of Terra/Aqua were estimated based on time series of Terra/Aqua-MODIS LST and other auxiliary variables including enhanced vegetation index, normalized difference water index, solar zenith angle and distance to coast. The validation results indicate that the models produced an accuracy of 1.6–2.6 °C RMSE for the four overpass times of Terra/Aqua. The models based on Terra LST showed higher accuracy than those based on Aqua LST, and nighttime air temperature estimation had higher accuracy than daytime. The seasonal analysis shows daytime CUHI is strongest in summer and weakest in winter, while nighttime CUHI is weakest in summer and strongest in autumn. The annual mean daytime CUHI during 2000–2013 is 1.0 and 2.2 °C for Terra and Aqua overpass, respectively. The annual mean nighttime CUHI is about 1.0 °C for both Terra and Aqua overpass. The resultant CUHI climatology maps provide a spatiotemporal quantification of CUHI with emphasis on temperature gradients. This study has provided information of relevance to urban planners and environmental managers for assessing and monitoring urban thermal environments which are constantly

  19. Calibration of the Distributed Hydrological Model mHM using Satellite derived Land Surface Temperature

    Science.gov (United States)

    Zink, M.; Samaniego, L. E.; Cuntz, M.

    2012-12-01

    A combined investigation of the water and energy balance in hydrologic models can lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on information of few points within a catchment. This procedure does not take into account any spatio-temporal variability of fluxes or state variables. Satellite data are a useful source of information to account for this spatial distributions. The objective of this study is to calibrate the distributed hydrological model mHM with satellite derived Land Surface Temperature (LST) fields provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). LST is preferred to other satellite products such as soil moisture or evapotranspiration due to its higher precision. LST is obtained by solving the energy balance by assuming that the soil heat flux and the storage term are negligible on a daily time step. The evapotranspiration is determined by closing the water balance in mHM. The net radiation is calculated by using the incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is used to determine the aerodynamic resistance among other parameters. The optimization is performed within the time period 2008-2010 using three objective functions that consider 1) only discharge, 2) only LST, and 3) a combination of both. The proposed method is applied to seven major German river basins: Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The annual coefficient of correlation between LSA-SAF incoming shortwave radiation and 28 meteorological stations operated by the German Weather Service (DWD) is 0.94 (RMSE = 29 W m-2) in 2009. LSA-SAF incoming longwave radiation could be further evaluated at two eddy covariance stations with a very similar

  20. Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling

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    W. Tang

    2014-09-01

    Full Text Available Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O3 regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NOx emissions to identify and reduce uncertainties in bottom-up NOx emissions. However, the joint application of multiple satellite-derived model inputs to improve O3 State Implementation Plan (SIP modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O3 concentrations by up to 80 ppb and improves O3 simulations by reducing modeled normalized mean bias (NMB and normalized mean error (NME by up to 0.1. A sector-based discrete Kalman filter (DKF inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx-Decoupled Direct Method (DDM model to adjust Texas NOx emissions using a high resolution Ozone Monitoring Instrument (OMI NO2 product. The discrepancy between OMI and CAMx NO2 vertical column densities (VCD is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The sector-based DKF inversion tends to scale down area and non-road NOx emissions by 50%, leading to a 2–5 ppb decrease in ground 8 h O3 predictions. Model performance in simulating ground NO2 and O3 are improved using inverted NOx emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together reduces modeled NMB and NME by 0.05 and increases the model correlation with ground measurement in O3 simulations and makes O3 more sensitive to NOx emissions in the O3 non-attainment areas.

  1. Satellite Derived Water Quality Observations Are Related to River Discharge and Nitrogen Loads in Pensacola Bay, Florida

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    John C. Lehrter

    2017-09-01

    Full Text Available Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011 in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging Spectrometer (MERIS and used to calculate monthly and annual estuarine time-series of chlorophyll a (Chla, colored dissolved organic matter (CDOM, and total suspended sediments (TSS. Monthly MERIS Chla varied from 2.0 mg m−3 in the lower region of the bay to 17.2 mg m−3 in the upper bay. MERIS CDOM and TSS exhibited similar patterns with ranges of 0.51–2.67 (m−1 and 0.11–8.9 (g m−3. Variations in the MERIS-derived monthly and annual Chla, CDOM, and TSS time-series were significantly related to monthly and annual river discharge and loads of nitrogen, organic carbon, and suspended sediments from the Escambia and Yellow rivers. Multiple regression models based on river loads (independent variables and MERIS Chla, CDOM, or TSS (dependent variables explained significant fractions of the variability (up to 62% at monthly and annual scales. The most significant independent variables in the regressions were river nitrogen loads, which were associated with increased MERIS Chla, CDOM, and TSS concentrations, and river suspended sediment loads, which were associated with decreased concentrations. In contrast, MERIS water quality variations were not significantly related to river total phosphorus loads. The spatially synoptic, nine-year satellite record expanded upon the spatial extent of past field studies to reveal previously unseen system-wide responses to river discharge and loading variation. The results indicated that variations in Pensacola Bay Chla

  2. Potential for a biogenic influence on cloud microphysics over the ocean: a correlation study with satellite-derived data

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    A. Lana

    2012-09-01

    Full Text Available Aerosols have a large potential to influence climate through their effects on the microphysics and optical properties of clouds and, hence, on the Earth's radiation budget. Aerosol–cloud interactions have been intensively studied in polluted air, but the possibility that the marine biosphere plays an important role in regulating cloud brightness in the pristine oceanic atmosphere remains largely unexplored. We used 9 yr of global satellite data and ocean climatologies to derive parameterizations of the temporal variability of (a production fluxes of sulfur aerosols formed by the oxidation of the biogenic gas dimethylsulfide emitted from the sea surface; (b production fluxes of secondary organic aerosols from biogenic organic volatiles; (c emission fluxes of biogenic primary organic aerosols ejected by wind action on sea surface; and (d emission fluxes of sea salt also lifted by the wind upon bubble bursting. Series of global monthly estimates of these fluxes were correlated to series of potential cloud condensation nuclei (CCN numbers derived from satellite (MODIS. More detailed comparisons among weekly series of estimated fluxes and satellite-derived cloud droplet effective radius (re data were conducted at locations spread among polluted and clean regions of the oceanic atmosphere. The outcome of the statistical analysis was that positive correlation to CCN numbers and negative correlation to re were common at mid and high latitude for sulfur and organic secondary aerosols, indicating both might be important in seeding cloud droplet activation. Conversely, primary aerosols (organic and sea salt showed widespread positive correlations to CCN only at low latitudes. Correlations to re were more variable, non-significant or positive, suggesting that, despite contributing to large shares of the marine aerosol mass, primary aerosols are not widespread major drivers of the variability of cloud

  3. Estimating and mapping chlorophyll content for a heterogeneous grassland: Comparing prediction power of a suite of vegetation indices across scales between years

    Science.gov (United States)

    Tong, Alexander; He, Yuhong

    2017-04-01

    This study investigates the performance of existing vegetation indices for retrieving chlorophyll content for a semi-arid mixed grass prairie ecosystem across scales using in situ data collected in 2012 and 2013. A 144 published broadband (21) and narrowband (123) vegetation indices are evaluated to estimate chlorophyll content. Results indicate that narrowband indices utilize reflectance data from one or more wavelengths in the red-edge region (∼690-750 nm) perform better. Broadband indices are found to be as effective as narrowband indices for chlorophyll content estimation at both leaf and canopy scales. The empirical relationships are generally stronger at the canopy than the leaf scale, attributable to the fact that leaf samples are collected during the peak growing season when chlorophyll in plant species are uniform. SPOT-5 and CASI-550 derived chlorophyll maps result in map accuracies of 63.56% and 78.88% respectively. The assessment of vegetation chlorophylls at the canopy level, especially using remote sensing imagery is important for providing information pertaining to ecosystem health such as the physiological status, productivity, or phenology of vegetation.

  4. Satellite Derived Forest Phenology and Its Relation with Nephropathia Epidemica in Belgium

    Directory of Open Access Journals (Sweden)

    José Miguel Barrios

    2010-06-01

    Full Text Available The connection between nephropathia epidemica (NE and vegetation dynamics has been emphasized in recent studies. Changing climate has been suggested as a triggering factor of recently observed epidemiologic peaks in reported NE cases. We have investigated whether there is a connection between the NE occurrence pattern in Belgium and specific trends in remotely sensed phenology parameters of broad-leaved forests. The analysis of time series of the MODIS Enhanced Vegetation Index revealed that changes in forest phenology, considered in literature as an effect of climate change, may affect the mechanics of NE transmission.

  5. Determinants of patchiness of woody vegetation in an African savanna

    NARCIS (Netherlands)

    Veldhuis, Michiel P.; Rozen-Rechels, David; le Roux, Elizabeth; Cromsigt, Joris P.G.M.; Berg, Matheus P.; Olff, Han

    2016-01-01

    How is woody vegetation patchiness affected by rainfall, fire and large herbivore biomass? Can we predict woody patchiness and cover over large-scale environmental gradients? We quantified variation in local patchiness as the lacunarity of woody cover on satellite-derived images. Using Random Forest

  6. The effect of image radiometric correction on the accuracy of vegetation canopy density estimate using several Landsat-8 OLI’s vegetation indices: A case study of Wonosari area, Indonesia

    Science.gov (United States)

    Dewa, R. P.; Danoedoro, P.

    2017-01-01

    Recent studies on the use of spectral indices have involved radiometric correction as a prerequisite. However, study on the effect of radiometric correction level on the accuracy of biophysical parameters’ estimate is still rare in Indonesia. This study tried to investigate the influence of various radiometric correction levels and the number of vegetation strata on the accuracy of vegetation density estimates using NDVI, MSAVI2 and GEMI of Landsat 8 OLI. In this study, the dataset covering vegetated area in Wonosari, Gunung Kidul Regency, Indonesia was processed radiometrically using eight different methods, i.e. spectral radiance, at sensor reflectance, sun elevation correction, histogram adjustments using original DN, spectal radiance, at sensor reflectance, and sun position correction respectively, as well as dark object subtraction (DOS). Every image with specific correction level was then transformed using the aforementioned indices, in order correlate with the field-measured canopy density. The analysis were carried out by considering the number of canopy layers. This found that different radiometric correction methods resulted canopy density estimates with different accuracies. The number of canopy strata also played an important role. Every vegetation index transformation performed its best accuracy by using different radiometric correction method and different number of canopy layers.

  7. Analysis of Satellite-Derived Arctic Tropospheric BrO Columns in Conjunction with Aircraft Measurements During ARCTAS and ARCPAC

    Science.gov (United States)

    Choi, S.; Wang, Y.; Salawitch, R. J.; Canty, T.; Joiner, J.; Zeng, T.; Kurosu, T. P.; Chance, K.; Richter, A.; Huey, L. G.; hide

    2012-01-01

    We derive tropospheric column BrO during the ARCTAS and ARCPAC field campaigns in spring 2008 using retrievals of total column BrO from the satellite UV nadir sensors OMI and GOME-2 using a radiative transfer model and stratospheric column BrO from a photochemical simulation. We conduct a comprehensive comparison of satellite-derived tropospheric BrO column to aircraft in-situ observations ofBrO and related species. The aircraft profiles reveal that tropospheric BrO, when present during April 2008, was distributed over a broad range of altitudes rather than being confined to the planetary boundary layer (PBL). Perturbations to the total column resulting from tropospheric BrO are the same magnitude as perturbations due to longitudinal variations in the stratospheric component, so proper accounting of the stratospheric signal is essential for accurate determination of satellite-derived tropospheric BrO. We find reasonably good agreement between satellite-derived tropospheric BrO and columns found using aircraft in-situ BrO profiles, particularly when satellite radiances were obtained over bright surfaces (albedo> 0.7), for solar zenith angle BrO due to surface processes (the bromine explosion) is apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low surface pressure, strong wind, and high PBL height are associated with an observed BrO activation event, supporting the notion of bromine activation by high winds over snow.

  8. Analysis of satellite-derived Arctic tropospheric BrO columns in conjunction with aircraft measurements during ARCTAS and ARCPAC

    Directory of Open Access Journals (Sweden)

    S. Choi

    2012-02-01

    Full Text Available We derive tropospheric column BrO during the ARCTAS and ARCPAC field campaigns in spring 2008 using retrievals of total column BrO from the satellite UV nadir sensors OMI and GOME-2 using a radiative transfer model and stratospheric column BrO from a photochemical simulation. We conduct a comprehensive comparison of satellite-derived tropospheric BrO column to aircraft in-situ observations of BrO and related species. The aircraft profiles reveal that tropospheric BrO, when present during April 2008, was distributed over a broad range of altitudes rather than being confined to the planetary boundary layer (PBL. Perturbations to the total column resulting from tropospheric BrO are the same magnitude as perturbations due to longitudinal variations in the stratospheric component, so proper accounting of the stratospheric signal is essential for accurate determination of satellite-derived tropospheric BrO. We find reasonably good agreement between satellite-derived tropospheric BrO and columns found using aircraft in-situ BrO profiles, particularly when satellite radiances were obtained over bright surfaces (albedo >0.7, for solar zenith angle <80° and clear sky conditions. The rapid activation of BrO due to surface processes (the bromine explosion is apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low surface pressure, strong wind, and high PBL height are associated with an observed BrO activation event, supporting the notion of bromine activation by high winds over snow.

  9. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    Science.gov (United States)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  10. Regional accumulation characteristics of cadmium in vegetables: Influencing factors, transfer model and indication of soil threshold content.

    Science.gov (United States)

    Yang, Yang; Chen, Weiping; Wang, Meie; Peng, Chi

    2016-12-01

    A regional investigation in the Youxian prefecture, southern China, was conducted to analyze the impact of environmental factors including soil properties and irrigation in conjunction with the use of fertilizers on the accumulation of Cd in vegetables. The Cd transfer potential from soil to vegetable was provided by the plant uptake factor (PUF), which varied by three orders of magnitude and was described by a Gaussian distribution model. The soil pH, content of soil organic matter (SOM), concentrations of Zn in the soil, pH of irrigation water and nitrogenous fertilizers contributed significantly to the PUF variations. A path model analysis, however, revealed the principal control of the PUF values resulted from the soil pH, soil Zn concentrations and SOM. Transfer functions were developed using the total soil Cd concentrations, soil pH, and SOM. They explained 56% of the variance for all samples irrespective of the vegetable genotypes. The transfer functions predicted the probability of exceeding China food safety standard concentrations for Cd in four major consumable vegetables under different soil conditions. Poor production practices in the study area involved usage of soil with pH values ≤ 5.5, especially for the cultivation of Raphanus sativus L., even with soil Cd concentrations below the China soil quality standard. We found the soil standard Cd concentrations for cultivating vegetables was not strict enough for strongly acidic (pH ≤ 5.5) and SOM-poor (SOM ≤ 10 g kg(-1)) soils present in southern China. It is thus necessary to address the effect of environmental variables to generate a suitable Cd threshold for cultivated soils. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest

    Science.gov (United States)

    Chen, X.; Vogelmann, J.E.; Rollins, M.; Ohlen, D.; Key, C.H.; Yang, L.; Huang, C.; Shi, H.

    2011-01-01

    It is challenging to detect burn severity and vegetation recovery because of the relatively long time period required to capture the ecosystem characteristics. Multitemporal remote sensing data can providemultitemporal observations before, during and after a wildfire, and can improve the change detection accuracy. The goal of this study is to examine the correlations between multitemporal spectral indices and field-observed burn severity, and to provide a practical method to estimate burn severity and vegetation recovery. The study site is the Jasper Fire area in the Black Hills National Forest, South Dakota, that burned during August and September 2000. Six multitemporal Landsat images acquired from 2000 (pre-fire), 2001 (post-fire), 2002, 2003, 2005 and 2007 were used to assess burn severity. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized burn ratio (NBR), integrated forest index (IFI) and the differences of these indices between the pre-fire and post-fire years were computed and analysed with 66 field-based composite burn index (CBI) plots collected in 2002. Results showed that differences of NDVI and differences of EVI between the pre-fire year and the first two years post-fire were highly correlated with the CBI scores. The correlations were low beyond the second year post-fire. Differences of NBR had good correlation with CBI scores in all study years. Differences of IFI had low correlation with CBI in the first year post-fire and had good correlation in later years. A CBI map of the burnt area was produced using regression tree models and the multitemporal images. The dynamics of four spectral indices from 2000 to 2007 indicated that both NBR and IFI are valuable for monitoring long-term vegetation recovery. The high burn severity areas had a much slower recovery than the moderate and low burn areas. ?? 2011 Taylor & Francis.

  12. Extracting seasonal cropping patterns using multi-temporal vegetation indices from IRS LISS-III data in Muzaffarpur District of Bihar, India

    Directory of Open Access Journals (Sweden)

    Saptarshi Mondal

    2014-12-01

    Full Text Available The advancement in satellite technology in terms of spatial, temporal, spectral and radiometric resolutions leads, successfully, to more specific and intensified research on agriculture. Automatic assessment of spatio-temporal cropping pattern and extent at multi-scale (community level, regional level and global level has been a challenge to researchers. This study aims to develop a semi-automated approach using Indian Remote Sensing (IRS satellite data and associated vegetation indices to extract annual cropping pattern in Muzaffarpur district of Bihar, India at a fine scale (1:50,000. Three vegetation indices (VIs – NDVI, EVI2 and NDSBVI, were calculated using three seasonal (Kharif, Rabi and Zaid IRS Resourcesat 2 LISS-III images. Threshold reference values for vegetation and non-vegetation thematic classes were extracted based on 40 training samples over each of the seasonal VI. Using these estimated value range a decision tree was established to classify three seasonal VI stack images which reveals seven different cropping patterns and plantation. In addition, a digitised reference map was also generated from multi-seasonal LISS-III images to check the accuracy of the semi-automatically extracted VI based classified image. The overall accuracies of 86.08%, 83.1% and 83.3% were achieved between reference map and NDVI, EVI2 and NDSBVI, respectively. Plantation was successfully identified in all cases with 96% (NDVI, 95% (EVI2 and 91% (NDSBVI accuracy.

  13. Analysis of satellite-derived Arctic tropospheric BrO columns in conjunction with aircraft measurements during ARCTAS and ARCPAC

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    S. Choi

    2011-09-01

    Full Text Available We derive estimates of tropospheric BrO column amounts during two Arctic field campaigns in 2008 using information from the satellite UV nadir sensors Ozone Monitoring Instrument (OMI and the second Global Ozone Monitoring Experiment (GOME-2 as well as estimates of stratospheric BrO columns from a model simulation. The sensitivity of the satellite-derived tropospheric BrO columns to various parameters is investigated using a radiative transfer model. We conduct a comprehensive analysis of satellite-derived tropospheric BrO columns including a detailed comparison with aircraft in-situ observations of BrO and related species obtained during the field campaigns. In contrast to prior expectation, tropospheric BrO, when present, existed over a broad range of altitudes. Our results show reasonable agreement between tropospheric BrO columns derived from the satellite observations and columns found using aircraft in-situ BrO. After accounting for the stratospheric contribution to total BrO column, several events of rapid BrO activation due to surface processes in the Arctic are apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low pressure systems, strong surface winds, and high planetary boundary layer heights are associated with the observed tropospheric BrO activation events.

  14. Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

    Directory of Open Access Journals (Sweden)

    Alfonso F. Torres-Rua

    2016-04-01

    Full Text Available Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains challenging due to coarse spatial and temporal resolution of existing remotely-sensed products. Furthermore, while preceding research on soil moisture using remote sensing (surface energy balance, weather parameters, and vegetation indices has demonstrated a relationship between these factors and soil moisture, practical continuous spatial quantification of the latter is still unavailable for use in water and agricultural management. In this study, a methodology is presented to estimate volumetric surface soil moisture by statistical selection from potential predictors that include vegetation indices and energy balance products derived from satellite (Landsat imagery and weather data as identified in scientific literature. This methodology employs a statistical learning machine called a Relevance Vector Machine (RVM to identify and relate the potential predictors to soil moisture by means of stratified cross-validation and forward variable selection. Surface soil moisture measurements from irrigated agricultural fields in Central Utah in the 2012 irrigation season were used, along with weather data, Landsat vegetation indices, and energy balance products. The methodology, data collection, processing, and estimation accuracy are presented and discussed.

  15. Estimating ground-level PM_{2.5} concentrations over three megalopolises in China using satellite-derived aerosol optical depth measurements

    Science.gov (United States)

    Zheng, Yixuan; Zhang, Qiang; Liu, Yang; Geng, Guannan; He, Kebin

    2016-04-01

    Numerous previous studies have revealed that statistical models which combine satellite-derived aerosol optical depth (AOD) and PM2.5 measurements acquired at scattered monitoring sites provide an effective method for deriving continuous spatial distributions of ground-level PM2.5 concentrations. Using the national monitoring networks that have recently been established by central and local governments in China, we developed linear mixed-effects (LMEs) models that integrate Moderate Resolution Imaging Spectroradiometer (MODIS) AOD measurements, meteorological parameters, and satellite-derived tropospheric NO2 column density measurements as predictors to estimate PM2.5 concentrations over three major industrialized regions in China, namely, the Beijing-Tianjin-Hebei region (BTH), the Yangtze River Delta region (YRD), and the Pearl River Delta region (PRD). The models developed for these three regions exploited different predictors to account for their varying topographies and meteorological conditions. Considering the importance of unbiased PM2.5 predictions for epidemiological studies, the correction factors calculated from the surface PM2.5 measurements were applied to correct biases in the predicted annual average PM2.5 concentrations introduced by non-stochastic missing AOD measurements. Leave-one-out cross-validation (LOOCV) was used to quantify the accuracy of our models. Cross-validation of the daily predictions yielded R2 values of 0.77, 0.8 and 0.8 and normalized mean error (NME) values of 22.4%, 17.8% and 15.2% for BTH, YRD and PRD, respectively. For the annual average PM2.5 concentrations, the LOOCV R2 values were 0.85, 0.76 and 0.71 for the three regions, respectively, whereas the LOOCV NME values were 8.0%, 6.9% and 8.4%, respectively. We found that the incorporation of satellite-based NO2 column density into the LMEs model contribute to considerable improvements in annual prediction accuracy for both BTH and YRD. The satisfactory performance of our

  16. Comparisons between buoy-observed, satellite-derived, and modeled surface shortwave flux over the subtropical North Atlantic during the Subduction Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Waliser, Duane E. [Institute for Terrestrial and Planetary Atmospheres, State University of New York, Stony Brook (United States); Weller, Robert A. [Woods Hole Oceanographic Institution, Woods Hole, Massachusetts (United States); Cess, Robert D. [Institute for Terrestrial and Planetary Atmospheres, State University of New York, Stony Brook (United States)

    1999-12-27

    satellite-derived climatologies. These comparisons showed much better and more consistent agreement, with relative bias errors ranging from about -1 to 6%. Comparisons to contemporaneous, daily-average satellite derived values show relatively good agreement as well, with relative biases of the order of 2% ({approx}3-9 W m-2) and root-mean-square differences of {approx}10% (25-30 W m-2). Aspects of the role aerosols play in the above results are discussed along with the implications of the above results on the integrity of open-ocean buoy measurements of surface shortwave flux and the possibility of using the techniques developed in this study to remotely monitor the operating condition of buoy-based shortwave radiometers. (c) 1999 American Geophysical Union.

  17. 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 factor in reducing river flows. Climate change, regional groundwater pumping, changes in the intensity of monsoon rain events and lack of overbank flooding are feasible explanations for deterioration of the riparian forest in the northern reach.

  18. Time Series Vegetation Aerodynamic Roughness Fields Estimated from MODIS Observations

    Science.gov (United States)

    Borak, Jordan S.; Jasinski, Michael F.; Crago, Richard D.

    2005-01-01

    Most land surface models used today require estimates of aerodynamic roughness length in order to characterize momentum transfer between the surface and atmosphere. The most common method of prescribing roughness is through the use of empirical look-up tables based solely on land cover class. Theoretical approaches that employ satellite-based estimates of canopy density present an attractive alternative to current look-up table approaches based on vegetation cover type that do not account for within-class variability and are oftentimes simplistic with respect to temporal variability. The current research applies Raupach s formulation of momentum aerodynamic roughness to MODIS data on a regional scale in order to estimate seasonally variable roughness and zero-plane displacement height fields using bulk land cover parameters estimated by [Jasinski, M.F., Borak, J., Crago, R., 2005. Bulk surface momentum parameters for satellite-derived vegetation fields. Agric. For. Meteorol. 133, 55-68]. Results indicate promising advances over look-up approaches with respect to characterization of vegetation roughness variability in land surface and atmospheric circulation models.

  19. The use of remotely-sensed snow, soil moisture and vegetation indices to develop resilience to climate change in Kazakhstan

    Science.gov (United States)

    Saidaliyeva, Zarina; Davenport, Ian; Nobakht, Mohamad; White, Kevin; Shahgedanova, Maria

    2017-04-01

    Kazakhstan is a major producer of grain. Large scale grain production dominates in the north, making Kazakhstan one of the largest exporters of grain in the world. Agricultural production accounts for 9% of the national GDP, providing 25% of national employment. The south relies on grain production from household farms for subsistence, and has low resilience, so is vulnerable to reductions in output. Yields in the south depend on snowmelt and glacier runoff. The major limit to production is water supply, which is affected by glacier retreat and frequent droughts. Climate change is likely to impact all climate drivers negatively, leading to a decrease in crop yield, which will impact Kazakhstan and countries dependent on importing its produce. This work makes initial steps in modelling the impact of climate change on crop yield, by identifying the links between snowfall, soil moisture and agricultural productivity. Several remotely-sensed data sources are being used. The availability of snowmelt water over the period 2010-2014 is estimated by extracting the annual maximum snow water equivalent (SWE) from the Globsnow dataset, which assimilates satellite microwave observations with field observations to produce a spatial map. Soil moisture over the period 2010-2016 is provided by the ESA Soil Moisture and Ocean Salinity (SMOS) mission. Vegetation density is approximated by the Normalised Difference Vegetation Index (NDVI) produced from NASA's MODIS instruments. Statistical information on crop yields is provided by the Ministry of National Economy of the Republic of Kazakhstan Committee on Statistics. Demonstrating the link between snowmelt yield and agricultural productivity depends on showing the impact of snow mass during winter on remotely-sensed soil moisture, the link between soil moisture and vegetation density, and finally the link between vegetation density and crop yield. Soil moisture maps were extracted from SMOS observations, and resampled onto a 40km x

  20. Towards Calibration of Sentinel 3 Data: Validation of Satellite-Derived SST Against In Situ Coastal Observations of the Portuguese Marine Waters

    Science.gov (United States)

    Vicente, Ricardo; Esteves, Rita; Lamas, Luisa; Pinto, Jose Paulo; Almeida, Sara; de Azevedo, Eduardo; Correia, Cecilia; Reis, Francisco

    2016-08-01

    Validation of future Sentinel-3 SLSTR data in the Eastern Atlantic Ocean was analysed here through a comparison of satellite-derived STT against in situ mooring buoys observations.SSTskin retrieved from IR satellite radiometers on- board ERS 1-2, Envisat, and Aqua, and concurrent SSTbulk measured with 14 buoy thermistors located at 1m depth were used to assess the statistical relationships between these datasets, with 20038 match- ups spanning from 1996 to 2015.As expected, results showed consistency between SSTskin and SSTbulk, exhibiting a correlation coefficient on the order of 98 %. Biases of both (A)ATSR and MODIS for day-time suggest a warmer satellite skin retrieval of + 0.15o and + 0.06o, respectively. For the night-time dataset, biases of - 0.25o and - 0.17o for (A)A TSR and MODIS, respectively, indicate cooler skin retrievals and reveal an inversion of the upper ocean thermic gradient. The RMSE ´s found were 0.53o for (A)ATSR and 0.41o for MODIS datasets.

  1. Satellite-derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to interannual variations in rainfall: implications for groundwater decline in a drying climate.

    Science.gov (United States)

    Smettem, Keith R J; Waring, Richard H; Callow, John N; Wilson, Melissa; Mu, Qiaozhen

    2013-08-01

    There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study, we analyzed satellite-derived estimates of monthly LAI across forested coastal catchments of southwest Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, interannual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long-term decline in areal average underground water storage and diminished summer flows, with an emerging trend toward more ephemeral flow regimes.

  2. Relative Spectral Mixture Analysis: a new multitemporal index of total vegetation cover

    Science.gov (United States)

    Okin, G. S.; Liu, C. S.

    2005-12-01

    High temporal resolution remote sensing provides an opportunity to monitor phenological variability and interannual changes in vegetation cover across diverse. A principal tool in multitemporal vegetation monitoring has been the Normalized Difference Vegetation Index. NDVI provides an index of the depth of the red edge and is usually interpreted as a measure of vegetation greenness and/or green vegetation cover. NDVI as a measure of phenology has several failings, particularly when applied over large areas: 1) NDVI is sensitive to the spectra of the soil background, particularly in partially or seasonally vegetated areas, 2) NDVI does not provide information about the non-photosynthetic portion of standing biomass, and 3) NDVI is very sensitive to the presence of small amounts of snow in a pixel. A new method for measuring vegetation phenology has been developed called Relative Spectral Mixture Analysis. RSMA uses a linear spectral mixture analysis to provide an index of the relative cover of four landscape components: green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and snow. RSMA uses generalized spectral for GV, NPV and snow, but does not require knowledge of the background soil spectra. This allows RSMA to be applied over very large areas (continental-scale) in which the soil background is highly diverse. RSMA has been implemented in the IDL language and used to analyze MODIS nadir-adjusted reflectance products from 2000 to the present. Our results show that RSMA GV index values are highly correlated with NDVI, except in regions with snow where RSMA outperforms NDVI. As a result RSMA GV indices and total vegetation indices (GV+NPV) can be used to extract information from spectral timeseries such as the onset of greenness, the termination of greenness, maximum vegetation cover, integrated vegetation cover (an index of NPP), length of the growing season, and duration of fodder availability. RSMA snow indices correlate well with other satellite-derived

  3. Analysis of trends in fused AVHRR and MODIS NDVI data for 1982-2006: Indication for a CO2 fertilization effect in global vegetation

    Science.gov (United States)

    Los, S. O.

    2013-04-01

    Recent studies report an increase in vegetation greenness in mid-to-high northern latitudes. This increase is observed in leaf-out data in Europe and North America since the 1950s and in satellite data since the 1980s. Increased vegetation greenness is potentially a factor contributing to a land CO2 sink. Various causes for increased vegetation greenness are suggested, but their relative importance is uncertain. In the present study, the effect of climate and CO2 fertilization on increased vegetation greenness and the land CO2 sink are investigated. The study is organized as follows: (1) A model is used to simulate monthly global normalized difference vegetation index (NDVI) fields for 1901-2006. The model is derived from NDVI, precipitation, and temperature data for 1982-1999. The modeled fields, referred to as reconstructed vegetation index (RVI), are tested back in time on phenological data (1950s-1990s) and forward in time on Moderate Resolution Imaging Spectrometer (MODIS) data (2001-2006). The RVI represents the response of NDVI to variations in climate. (2) Residuals between RVI and NDVI are analyzed for associations with variations in downwelling solar radiation, nitrogen deposition, satellite-related artifacts, and CO2 fertilization. CO2 fertilization was the only factor that improved RVI modeling. (3) The effect of climate variations and CO2 fertilization on the land CO2 sink, as manifested in the RVI, is explored with the Carnegie Ames Stanford Assimilation (CASA) model. Climate (temperature and precipitation) and CO2 fertilization each explain approximately 40% of the observed global trend in NDVI for 1982-2006. For 1901-2006, estimated trends in NDVI related to CO2 fertilization are four to five times larger than climate-related trends. CASA simulations indicate that the CO2 fertilization effect on vegetation greenness contributes about 0.7 Pg C per year to the recent land CO2 sink. This is a conservative estimate and is likely larger. This effect of

  4. MODIS vegetation products as proxies of photosynthetic potential: a look across meteorological and biologic driven ecosystem productivity

    Directory of Open Access Journals (Sweden)

    N. Restrepo-Coupe

    2015-12-01

    Full Text Available A direct relationship between gross ecosystem productivity (GEP measured by the eddy covariance (EC method and Moderate Resolution Imaging Spectroradiometer (MODIS vegetation indices (VIs has been observed in many temperate and tropical ecosystems. However, in Australian evergreen forests, and particularly sclerophyll woodlands, MODIS VIs do not capture seasonality of GEP. In this study, we re-evaluate the connection between satellite and flux tower data at four contrasting Australian ecosystems, through comparisons of ecosystem photosynthetic activity (GEP and potential (e.g. ecosystem light use efficiency and quantum yield with MODIS vegetation satellite products, including VIs, gross primary productivity (GPPMOD, leaf area index (LAIMOD, and fraction of photosynthetic active radiation (fPARMOD. We found that satellite derived greenness products constitute a measurement of ecosystem structure (e.g. leaf area index – quantity of leaves and function (e.g. leaf level photosynthetic assimilation capacity – quality of leaves, rather than productivity. Our results show that in primarily meteorological-driven (e.g. photosynthetic active radiation, air temperature and/or precipitation and relatively aseasonal vegetation photosynthetic potential ecosystems (e.g. evergreen wet sclerophyll forests, there were no statistically significant relationships between GEP and satellite derived measures of greenness. In contrast, for phenology-driven ecosystems (e.g. tropical savannas, changes in the vegetation status drove GEP, and tower-based measurements of photosynthetic activity were best represented by VIs. We observed the highest correlations between MODIS products and GEP in locations where key meteorological variables and vegetation phenology were synchronous (e.g. semi-arid Acacia woodlands and low correlation at locations where they were asynchronous (e.g. Mediterranean ecosystems. Eddy covariance data offer much more than validation and

  5. Identifying environmental controls on vegetation greenness phenology through model-data integration

    Directory of Open Access Journals (Sweden)

    M. Forkel

    2014-07-01

    Full Text Available Existing dynamic global vegetation models (DGVMs have a~limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus to enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a~new phenology model within the LPJmL (Lund Potsdam Jena managed lands DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR, albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules

  6. Oceanic Weather Decision Support for Unmanned Global Hawk Science Missions into Hurricanes with Tailored Satellite Derived Products

    Science.gov (United States)

    Feltz, Wayne; Griffin, Sarah; Velden, Christopher; Zipser, Ed; Cecil, Daniel; Braun, Scott

    2017-04-01

    The purpose of this presentation is to identify in-flight hazards to high-altitude aircraft, namely the Global Hawk. The Global Hawk was used during Septembers 2012-2016 as part of two NASA funded Hurricane Sentinel-3 field campaigns to over-fly hurricanes in the Atlantic Ocean. This talk identifies the cause of severe turbulence experienced over Hurricane Emily (2005) and how a combination of NOAA funded GOES-R algorithm derived cloud top heights/tropical overshooting tops using GOES-13/SEVIRI imager radiances, and lightning information are used to identify areas of potential turbulence for near real-time navigation decision support. Several examples will demonstrate how the Global Hawk pilots remotely received and used real-time satellite derived cloud and lightning detection information to keep the aircraft safely above clouds and avoid regions of potential turbulence.

  7. Pollen and phytoliths from fired ancient potsherds as potential indicators for deciphering past vegetation and climate in Turpan, Xinjiang, NW China.

    Science.gov (United States)

    Yao, Yi-Feng; Li, Xiao; Jiang, Hong-En; Ferguson, David K; Hueber, Francis; Ghosh, Ruby; Bera, Subir; Li, Cheng-Sen

    2012-01-01

    It is demonstrated that palynomorphs can occur in fired ancient potsherds when the firing temperature was under 350°C. Pollen and phytoliths recovered from incompletely fired and fully fired potsherds (ca. 2700 yrs BP) from the Yanghai Tombs, Turpan, Xinjiang, NW China can be used as potential indicators for reconstructing past vegetation and corresponding climate in the area. The results show a higher rate of recovery of pollen and phytoliths from incompletely fired potsherds than from fully fired ones. Charred phytoliths recovered from both fully fired and incompletely fired potsherds prove that degree and condition of firing result in a permanent change in phytolith color. The palynological data, together with previous data of macrobotanical remains from the Yanghai Tombs, suggest that temperate vegetation and arid climatic conditions dominated in the area ca. 2700 yrs BP.

  8. Pollen and phytoliths from fired ancient potsherds as potential indicators for deciphering past vegetation and climate in Turpan, Xinjiang, NW China.

    Directory of Open Access Journals (Sweden)

    Yi-Feng Yao

    Full Text Available It is demonstrated that palynomorphs can occur in fired ancient potsherds when the firing temperature was under 350°C. Pollen and phytoliths recovered from incompletely fired and fully fired potsherds (ca. 2700 yrs BP from the Yanghai Tombs, Turpan, Xinjiang, NW China can be used as potential indicators for reconstructing past vegetation and corresponding climate in the area. The results show a higher rate of recovery of pollen and phytoliths from incompletely fired potsherds than from fully fired ones. Charred phytoliths recovered from both fully fired and incompletely fired potsherds prove that degree and condition of firing result in a permanent change in phytolith color. The palynological data, together with previous data of macrobotanical remains from the Yanghai Tombs, suggest that temperate vegetation and arid climatic conditions dominated in the area ca. 2700 yrs BP.

  9. Handling of subpixel structures in the application of satellite derived irradiance data for solar energy system analysis - a review

    Science.gov (United States)

    Beyer, Hans Georg

    2016-04-01

    With the increasing availability of satellite derived irradiance information, this type of data set is more and more in use for the design and operation of solar energy systems, most notably PV- and CSP-systems. By this, the need for data measured on-site is reduced. However, due to basic limitations of the satellite-derived data, several requirements put by the intended application cannot be coped with this data type directly. Traw satellite information has to be enhanced in both space and time resolution by additional information to be fully applicable for all aspects of the modelling od solar energy systems. To cope with this problem, several individual and collaborative projects had been performed in the recent years or are ongoing. Approaches are on one hand based on pasting synthesized high-resolution data into the low-resolution original sets. Pre-requite is an appropriate model, validated against real world data. For the case of irradiance data, these models can be extracted either directly from ground measured data sets or from data referring to the cloud situation as gained from the images of sky cameras or from monte -carlo initialized physical models. The current models refer to the spatial structure of the cloud fields. Dynamics are imposed by moving the cloud structures according to a large scale cloud motion vector, either extracted from the dynamics interfered from consecutive satellite images or taken from a meso-scale meteorological model. Dynamic irradiance information is then derived from the cloud field structure and the cloud motion vector. This contribution, which is linked to subtask A - Solar Resource Applications for High Penetration of Solar Technologies - of IEA SHC task 46, will present the different approaches and discuss examples in view of validation, need for auxiliary information and respective general applicability.

  10. Strong contribution of autumn phenology to changes in satellite-derived growing season length estimates across Europe (1982-2011).

    Science.gov (United States)

    Garonna, Irene; de Jong, Rogier; de Wit, Allard J W; Mücher, Caspar A; Schmid, Bernhard; Schaepman, Michael E

    2014-11-01

    Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegetated land surfaces as observed from satellite imagery. LSP plays a key role in characterizing land-surface fluxes, and is central to accurately parameterizing terrestrial biosphere-atmosphere interactions, as well as climate models. In this article, we present an evaluation of Pan-European LSP and its changes over the past 30 years, using the longest continuous record of Normalized Difference Vegetation Index (NDVI) available to date in combination with a landscape-based aggregation scheme. We used indicators of Start-Of-Season, End-Of-Season and Growing Season Length (SOS, EOS and GSL, respectively) for the period 1982-2011 to test for temporal trends in activity of terrestrial vegetation and their spatial distribution. We aggregated pixels into ecologically representative spatial units using the European Landscape Classification (LANMAP) and assessed the relative contribution of spring and autumn phenology. GSL increased significantly by 18-24 days decade(-1) over 18-30% of the land area of Europe, depending on methodology. This trend varied extensively within and between climatic zones and landscape classes. The areas of greatest growing-season lengthening were the Continental and Boreal zones, with hotspots concentrated in southern Fennoscandia, Western Russia and pockets of continental Europe. For the Atlantic and Steppic zones, we found an average shortening of the growing season with hotspots in Western France, the Po valley, and around the Caspian Sea. In many zones, changes in the NDVI-derived end-of-season contributed more to the GSL trend than changes in spring green-up, resulting in asymmetric trends. This underlines the importance of investigating senescence and its underlying processes more closely as a driver of LSP and global change.

  11. Associations between access to farmers’ markets and supermarkets, shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, USA

    Science.gov (United States)

    Pitts, Stephanie B Jilcott; Wu, Qiang; McGuirt, Jared T; Crawford, Thomas W; Keyserling, Thomas C; Ammerman, Alice S

    2013-01-01

    Objective We examined associations between access to food venues (farmers’ markets and supermarkets), shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, USA. Design Access to food venues was measured using a Geographic Information System incorporating distance, seasonality and business hours, to quantify access to farmers’ markets. Produce consumption was assessed by self-report of eating five or more fruits and vegetables daily. BMI and blood pressure were assessed by clinical measurements. Poisson regression with robust variance was used for dichotomous outcomes and multiple linear regression was used for continuous outcomes. As the study occurred in a university town and university students are likely to have different shopping patterns from non-students, we stratified analyses by student status. Setting Eastern North Carolina. Subjects Low-income women of reproductive age (18–44 years) with valid address information accessing family planning services at a local health department (n 400). Results Over a quarter reported ever shopping at farmers’ markets (114/400). A larger percentage of women who shopped at farmers’ markets consumed five or more fruits and vegetables daily (42·1%) than those who did not (24·0%; Pshopping was 11·4 (SD 9·0) km (7·1 (SD 5·6) miles), while the mean distance to the farmers’ market closest to the residence was 4·0 (SD 3·7) km (2·5 (SD 2·3) miles). Conclusions Among non-students, those who shopped at farmers’ markets were more likely to consume five or more servings of fruits and vegetables daily. Future research should further explore potential health benefits of farmers’ markets. PMID:23701901

  12. The Effect of Vegetation Productivity on Millet Prices in the Informal Markets of Mali, Burkina Faso and Niger

    Energy Technology Data Exchange (ETDEWEB)

    Brown, M.E. [Department of Geography, University of Maryland, NASA Goddard Space Flight Center, Code 923, Greenbelt, MD 20771 (United States); Pinzon, J.E. [Science Systems and Applications Inc., NASA Goddard Space Flight Center, Code 923, Greenbelt, MD (United States); Prince, S.D. [Department of Geography, University of Maryland, College Park, MD (United States)

    2006-09-15

    Systematic evaluation of food security throughout the Sahel has been attempted for nearly two decades. Food security analyses have used both food prices to determine the ability of the population to access food, and satellite-derived vegetation indices that measure vegetation production to establish how much food is available each year. The relationship between these two food security indicators is explored here using correspondence analysis and through the use of Markov chain models. Two sources of quantitative data were used: 8 km normalized difference vegetation index (NDVI) data from the Advanced Very High Resolution Radiometers (AVHRR) carried on the NOAA series of satellites, and monthly millet prices from 445 markets in Mali, Niger and Burkina Faso. The results show that the growing season vegetation production is related to the price of millet at the annual and the seasonal time scales. If the growing season was characterized by erratic, sparse rainfall, it resulted in higher prices, and well-distributed, abundant rainfall resulted in lower prices. The correspondence between vegetation production and millet prices is used to produce maps of millet prices for West Africa.

  13. Can grass phytoliths and indices be relied on during vegetation and climate interpretations in the eastern Himalayas? Studies from Darjeeling and Arunachal Pradesh, India

    Science.gov (United States)

    Biswas, Oindrila; Ghosh, Ruby; Paruya, Dipak Kumar; Mukherjee, Biswajit; Thapa, Kishore Kumar; Bera, Subir

    2016-02-01

    While documenting the vegetation response to climatic changes in mountains, the use of grass phytolith data relies on the ability of phytolith assemblages or indices to differentiate the elevationally stratified vegetation zones. To infer the potential and limitations of grass phytolith assemblages and indices to reconstruct vegetation vis-à-vis climate in the Himalayan mountain regions, we analyzed phytolith assemblages from 66 dominant grasses and 153 surface soils from four different forest types along the c. 130-4000 m a.s.l. elevation gradients in the Darjeeling and Arunachal Himalayas. Grass short cell phytolith assemblages from modern grasses show significant variability with rising elevation. To test the reliability of the above observation, phytoliths from the soil samples were subjected to linear discriminant analysis (DA). DA classified 85.3% and 92.3% of the sites to their correct forest zones in the Darjeeling and Arunachal Himalayas respectively. Relative abundance of bilobate, cross, short saddle, plateau saddle, rondel and trapeziform types allow discrimination of the phytolith assemblage along the elevation gradient. Canonical correspondence analysis (CCA) on the soil phytolith data further revealed their relationships with the climatic variables. Temperature and evapotranspiration were found to be the most influential for differential distribution of grass phytolith assemblages with rising elevation in the eastern Himalayas. We also tested the reliability of phytolith indices (Ic, Iph and Fs) for tracing the dominance of different grass subfamilies in the eastern Himalayas. Ic proved to be most reliable in discriminating C3/C4 grass along the elevation gradient while Iph and Fs proved to be less reliable. We observed that in the monsoon dominated eastern Himalayas, a little adjustment in Ic index may enhance the accuracy of interpretations. In future studies more precise identification of phytolith sub-types from additional sites in the eastern

  14. Environmental resilience of rangeland ecosystems: assessment drought indices and vegetation trends on arid and semi-arid zones of Central Asia

    Science.gov (United States)

    Aralova, Dildora; Toderich, Kristina; Jarihani, Ben; Gafurov, Dilshod; Gismatulina, Liliya; Osunmadewa, Babatunde A.; Rahamtallah Abualgasim, Majdaldin

    2016-10-01

    The Central Asian (CA) rangelands is a part of the arid and semi-arid ecological zones and spatial extent of drylands in CA (Tajikistan, Kazakhstan, Uzbekistan, Kyrgyzstan, and Turkmenistan) is vast. Projections averaged across a suite of climate models, as measured between 1950-2012 by Standardised Precipitation-Evapotranspiration Index (SPEI) estimated a progressively increasing drought risks across rangelands (Turkmenistan, Tajikistan and Uzbekistan) especially during late summer and autumn periods, another index: Potential Evapotranspiration (PET) indicated drought anomalies for Turkmenistan and partly in Uzbekistan (between 1950-2000). On this study, we have combined a several datasets of drought indices ( SPIE, PET, temperature_T°C and precipitation_P) for better estimation of resilience/non-resilience of the ecosystems after warming the temperature in the following five countries, meanwhile, warming of climate causing of increasing rating of degradations and extension of desertification in the lowland and foothill zones of the landscape and consequently surrounding experienced of a raising balance of evapotranspiration (ET0). The study concluded, increasing drought anomalies which is closely related with raising (ET0) in the lowland and foothill zones of CA indicated on decreasing of NDVI indices with occurred sandy and loamy soils it will resulting a loss of vegetation diversity (endangered species) and raising of wind speeds in lowlands of CA, but on regional level especially towards agricultural intensification (without rotation) it indicated no changes of greenness index. It was investigated to better interpret how vegetation feedback modifies the sensitivity of drought indices associated with raising tendency of air temperature and changes of cold and hot year seasons length in the territory of CA.

  15. MODIS vegetation products as proxies of photosynthetic potential along a gradient of meteorologically and biologically driven ecosystem productivity

    Science.gov (United States)

    Restrepo-Coupe, Natalia; Huete, Alfredo; Davies, Kevin; Cleverly, James; Beringer, Jason; Eamus, Derek; van Gorsel, Eva; Hutley, Lindsay B.; Meyer, Wayne S.

    2016-10-01

    A direct relationship between gross ecosystem productivity (GEP) estimated by the eddy covariance (EC) method and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (VIs) has been observed in many temperate and tropical ecosystems. However, in Australian evergreen forests, and particularly sclerophyll and temperate woodlands, MODIS VIs do not capture seasonality of GEP. In this study, we re-evaluate the connection between satellite and flux tower data at four contrasting Australian ecosystems, through comparisons of GEP and four measures of photosynthetic potential, derived via parameterization of the light response curve: ecosystem light use efficiency (LUE), photosynthetic capacity (Pc), GEP at saturation (GEPsat), and quantum yield (α), with MODIS vegetation satellite products, including VIs, gross primary productivity (GPPMOD), leaf area index (LAIMOD), and fraction of photosynthetic active radiation (fPARMOD). We found that satellite-derived biophysical products constitute a measurement of ecosystem structure (e.g. leaf area index - quantity of leaves) and function (e.g. leaf level photosynthetic assimilation capacity - quality of leaves), rather than GEP. Our results show that in primarily meteorological-driven (e.g. photosynthetic active radiation, air temperature, and/or precipitation) and relatively aseasonal ecosystems (e.g. evergreen wet sclerophyll forests), there were no statistically significant relationships between GEP and satellite-derived measures of greenness. In contrast, for phenology-driven ecosystems (e.g. tropical savannas), changes in the vegetation status drove GEP, and tower-based measurements of photosynthetic activity were best represented by VIs. We observed the highest correlations between MODIS products and GEP in locations where key meteorological variables and vegetation phenology were synchronous (e.g. semi-arid Acacia woodlands) and low correlation at locations where they were asynchronous (e

  16. Assessment of Vegetation Indices Derived by UAV Imagery for Durum Wheat Phenotyping under a Water Limited and Heat Stressed Mediterranean Environment.

    Science.gov (United States)

    Kyratzis, Angelos C; Skarlatos, Dimitrios P; Menexes, George C; Vamvakousis, Vasileios F; Katsiotis, Andreas

    2017-01-01

    There is growing interest for using Spectral Vegetation Indices (SVI) derived by Unmanned Aerial Vehicle (UAV) imagery as a fast and cost-efficient tool for plant phenotyping. The development of such tools is of paramount importance to continue progress through plant breeding, especially in the Mediterranean basin, where climate change is expected to further increase yield uncertainty. In the present study, Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR) and Green Normalized Difference Vegetation Index (GNDVI) derived from UAV imagery were calculated for two consecutive years in a set of twenty durum wheat varieties grown under a water limited and heat stressed environment. Statistically significant differences between genotypes were observed for SVIs. GNDVI explained more variability than NDVI and SR, when recorded at booting. GNDVI was significantly correlated with grain yield when recorded at booting and anthesis during the 1st and 2nd year, respectively, while NDVI was correlated to grain yield when recorded at booting, but only for the 1st year. These results suggest that GNDVI has a better discriminating efficiency and can be a better predictor of yield when recorded at early reproductive stages. The predictive ability of SVIs was affected by plant phenology. Correlations of grain yield with SVIs were stronger as the correlations of SVIs with heading were weaker or not significant. NDVIs recorded at the experimental site were significantly correlated with grain yield of the same set of genotypes grown in other environments. Both positive and negative correlations were observed indicating that the environmental conditions during grain filling can affect the sign of the correlations. These findings highlight the potential use of SVIs derived by UAV imagery for durum wheat phenotyping under low yielding Mediterranean conditions.

  17. Validation of satellite derived LHF using coare_3.0 scheme and time series data over north-east Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Muraleedharan, P.M.; Pankajakshan, T.; Sathe, P.V.

    -6538 versión on-line Gayana (Concepc.) v.68 n.2 supl.TIIProc Concepción 2004 Como citar este artículo Gayana 68(2): 420-426, 2004 VALIDATION OF SATELLITE DERIVED LHF USING COARE_3.0 SCHEME AND TIME SERIES DATA OVER NORTH-EAST INDIAN...

  18. Linking environmental gradients, species composition, and vegetation indicators of sugar maple health in the northeastern United States

    Science.gov (United States)

    Stephen B. Horsley; Scott W. Bailey; Todd E. Ristau; Robert P. Long; Richard A. Hallett

    2008-01-01

    Sugar maple (Acer saccharum Marsh.) decline has occurred throughout its range over the past 50 years, although decline symptoms are minimal where nutritional thresholds of Ca, Mg, and Mn are met. Here, we show that availability of these elements also controls vascular plant species composition in northern hardwood stands and we identify indicator...

  19. Changes in vegetation types and Ellenberg indicator values after 65 years of fertilizer application in the Rengen Grassland Experiment, Germany

    NARCIS (Netherlands)

    Chytry, M.; Hejcman, M.; Hennekens, S.M.; Schellberg, J.

    2009-01-01

    Question: How does semi-natural grassland diversify after 65 years of differential application of Ca, N, P, and K fertilizers? Is fertilizer application adequately reflected by the Ellenberg indicator values (EIVs)? Location: Eifel Mountains, West Germany. Methods: The Rengen Grassland Experiment (R

  20. Changes in vegetation types and Ellenberg indicator values after 65 years of fertilizer application in the Rengen Grassland Experiment, Germany

    NARCIS (Netherlands)

    Chytry, M.; Hejcman, M.; Hennekens, S.M.; Schellberg, J.

    2009-01-01

    Question: How does semi-natural grassland diversify after 65 years of differential application of Ca, N, P, and K fertilizers? Is fertilizer application adequately reflected by the Ellenberg indicator values (EIVs)? Location: Eifel Mountains, West Germany. Methods: The Rengen Grassland Experiment

  1. Satellite-derived determination of PM10 concentration and of the associated risk on public health

    Science.gov (United States)

    Sarigiannis, Dimosthenis; Sifakis, Nicolaos I.; Soulakellis, Nikos; Tombrou, Maria; Schaefer, Klaus P.

    2004-02-01

    Recent studies worldwide have revealed the relation between urban air pollution, particularly fine aerosols, and human health. The current state of the art in air quality assessment, monitoring and management comprises analytical measurements and atmospheric transport modeling. Earth observation from satellites provides an additional information layer through the calculation of synoptic air pollution indicators, such as atmospheric turbidity. Fusion of these data sources with ancillary data, including classification of population vulnerability to the adverse health effects of fine particulate and, especially, PM10 pollution, in the ambient air, integrates them into an optimally managed environmental information processing tool. Several algorithms pertaining to urban air pollution assessment using HSR satellite imagery have been developed and applied to urban sites in Europe such as Athens, Greece, the Po valley in Northern Italy, and Munich, Germany. Implementing these computational procedures on moderate spatial resolution (MSR) satellite data and coupling the result with the output of HSR data processing provides comprehensive and dynamic information on the spatial distribution of PM10 concentration. The result of EO data processing is corrected to account for the relative importance of the signal due to anthropogenic fine particles, concentrated in the lower troposphere. Fusing the corrected maps of PM10 concentration with data on vulnerable population distribution and implementation of epidemiology-derived exposure-response relationships results in the calculation of indices of the public health risk from PM10 concentration in the ambient air. Results from the pilot application of this technique for integrated environmental and health assessment in the urban environment are given.

  2. Validation of three satellite-derived databases of surface solar radiation using measurements performed at 42 stations in Brazil

    Science.gov (United States)

    Thomas, Claire; Wey, Etienne; Blanc, Philippe; Wald, Lucien

    2016-06-01

    The SoDa website (www.soda-pro.com) is populated with numerous solar-related Web services. Among them, three satellite-derived irradiation databases can be manually or automatically accessed to retrieve radiation values within the geographical coverage of the Meteosat Second Generation (MSG) satellite: the two most advanced versions of the HelioClim-3 database (versions 4 and 5, respectively HC3v4 and HC3v5), and the CAMS radiation service. So far, these databases have been validated against measurements of several stations in Europe and North Africa only. As the quality of such databases depends on the geographical regions and the climates, this paper extends this validation campaign and proposes an extensive comparison on Brazil and global irradiation received on a horizontal surface. Eleven stations from the Brazilian Institute of Space Research (INPE) network offer 1 min observations, and thirty-one stations from the Instituto Nacional de Meteorologia (INMET) network offer hourly observations. The satellite-derived estimates have been compared to the corresponding observations on hourly, daily and monthly basis. The bias relative to the mean of the measurements for HC3v5 is mostly comprised between 1 and 3 %, and that for HC3v4 between 2 and 5 %. These are very satisfactory results and they demonstrate that HC3v5, and to a lesser extent HC3v4, may be used in studies of long-term changes in SSI in Brazil. The situation is not so good with CAMS radiation service for which the relative bias is mostly comprised between 5 and 10 %. For hourly irradiation, the relative RMSE ranges from 15 to 33 %. The correlation coefficient is very large for all stations and the three databases, with an average of 0.96. The three databases reproduce well the hour from hour changes in SSI. The errors show a tendency to increase with the viewing angle of the MSG satellite. They are greater in tropical areas where the relative humidity in the atmosphere is important. It is concluded

  3. Vegetation, topography and daily weather influenced burn severity in central Idaho and western Montana forests

    Science.gov (United States)

    Donovan S. Birch; Penelope Morgan; Crystal A. Kolden; John T. Abatzoglou; Gregory K. Dillon; Andrew T. Hudak; Alistair M. S. Smith

    2015-01-01

    Burn severity as inferred from satellite-derived differenced Normalized Burn Ratio (dNBR) is useful for evaluating fire impacts on ecosystems but the environmental controls on burn severity across large forest fires are both poorly understood and likely to be different than those influencing fire extent. We related dNBR to environmental variables including vegetation,...

  4. Linking Satellite Derived Land Surface Temperature with Cholera: A Case Study for South Sudan

    Science.gov (United States)

    Aldaach, H. S. V.; Jutla, A.; Akanda, A. S.; Colwell, R. R.

    2014-12-01

    A sudden onset of cholera in South Sudan, in April 2014 in Northern Bari in Juba town resulted in more than 400 cholera cases after four weeks of initial outbreak with a case of fatality rate of CFR 5.4%. The total number of reported cholera cases for the period of April to July, 2014 were 5,141 including 114 deaths. With the limited efficacy of cholera vaccines, it is necessary to develop mechanisms to predict cholera occurrence and thereafter devise intervention strategies for mitigating impacts of the disease. Hydroclimatic processes, primarily precipitation and air temperature are related to epidemic and episodic outbreak of cholera. However, due to coarse resolution of both datasets, it is not possible to precisely locate the geographical location of disease. Here, using Land Surface Temperature (LST) from MODIS sensors, we have developed an algorithm to identify regions susceptible for cholera. Conditions for occurrence of cholera were detectable at least one month in advance in South Sudan and were statistically sensitive to hydroclimatic anomalies of land surface and air temperature, and precipitation. Our results indicate significant spatial and temporal averaging required to infer usable information from LST over South Sudan. Preliminary results that geographically location of cholera outbreak was identifiable within 1km resolution of the LST data.

  5. Cross-Comparison of Vegetation Indices Derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+ and Landsat-8 Operational Land Imager (OLI Sensors

    Directory of Open Access Journals (Sweden)

    Peng Li

    2013-12-01

    Full Text Available Landsat-7 Enhanced Thematic Mapper Plus (ETM+ and Landsat-8 Operational Land Imager (OLI and Thermal Infrared Sensor (TIRS are currently operational for routine Earth observation. There are substantial differences between instruments onboard both satellites. The enhancements achieved with Landsat-8 refer to the scanning technology (replacing of whisk-broom scanners with two separate push-broom OLI and TIRS scanners, an extended number of spectral bands (two additional bands provided and narrower bandwidths. Therefore, cross-comparative analysis is very necessary for the combined use of multi-decadal Landsat imagery. In this study, 3,311 independent sample points of four major land cover types (primary forest, unplanted cropland, swidden cultivation and water body were used to compare the spectral bands of ETM+ and OLI. Eight sample plots with different land cover types were manually selected for comparison with the Normalized Difference Vegetation Index (NDVI, the Modified Normalized Difference Water Index (MNDWI, the Land Surface Water Index (LSWI and the Normalized Burn Ratio (NBR. These indices were calculated with six pairs of ETM+ and OLI cloud-free images, which were acquired over the border area of Myanmar, Laos and Thailand just two days apart, when Landsat-8 achieved operational obit. Comparative results showed that: (1 the average surface reflectance of each band differed slightly, but with a high degree of similarities between both sensors. In comparison with ETM+, the OLI had higher values for the near-infrared band for vegetative land cover types, but lower values for non-vegetative types. The new sensor had lower values for the shortwave infrared (2.11–2.29 µm band for all land cover types. In addition, it also basically had higher values for the shortwave infrared (1.57–1.65 µm band for non-water land cover types. (2 The subtle differences of vegetation indices derived from both sensors and their high linear correlation

  6. Physiological and ecological studies of the vegetation on ore deposits. I. Zinc flora and indicator plants on the 2nd Yunwha mine. [Sedum sp. ; Dianthus sinensis

    Energy Technology Data Exchange (ETDEWEB)

    Chang, N.K.; Chang, S.M.

    1977-01-01

    During the period of 1975-76, a survey was carried out to find out zinc indicators in the natural vegetation in Korea. The symptoms of chlorosis were observed in flowering plants in the areas of zinc outcrop of Wolgok-A, Seokgok-9, and Sowolgok. Although 28 species were found to be chlorotic, the total quantity of chlorotic foliage observed was small. Reasons for chlorosis in the areas of zinc ore deposits is considered as effects of zinc, lead, copper and calcium ions. Sedum sp. and Dianthus sinensis were confined to soil containing more than exchangeable zinc of 30 ppm and to accumulation in the plants contained at least 1,300-14,000 ppm of zinc. Therefore, Sedum sp. and Dianthus sinensis might be used as zinc indicators in Korea. 12 references, 1 figure, 5 tables.

  7. Changes in satellite-derived impervious surface area at US historical climatology network stations

    Science.gov (United States)

    Gallo, Kevin; Xian, George

    2016-10-01

    The difference between 30 m gridded impervious surface area (ISA) between 2001 and 2011 was evaluated within 100 and 1000 m radii of the locations of climate stations that comprise the US Historical Climatology Network. The amount of area associated with observed increases in ISA above specific thresholds was documented for the climate stations. Over 32% of the USHCN stations exhibited an increase in ISA of ⩾20% between 2001 and 2011 for at least 1% of the grid cells within a 100 m radius of the station. However, as the required area associated with ISA change was increased from ⩾1% to ⩾10%, the number of stations that were observed with a ⩾20% increase in ISA between 2001 and 2011 decreased to 113 (9% of stations). When the 1000 m radius associated with each station was examined, over 52% (over 600) of the stations exhibited an increase in ISA of ⩾20% within at least 1% of the grid cells within that radius. However, as the required area associated with ISA change was increased to ⩾10% the number of stations that were observed with a ⩾20% increase in ISA between 2001 and 2011 decreased to 35 (less than 3% of the stations). The gridded ISA data provides an opportunity to characterize the environment around climate stations with a consistently measured indicator of a surface feature. Periodic evaluations of changes in the ISA near the USHCN and other networks of stations are recommended to assure the local environment around the stations has not significantly changed such that observations at the stations may be impacted.

  8. Vegetation as an indicator of soil properties and water quality in the Akarçay stream (Turkey).

    Science.gov (United States)

    Serteser, Ahmet; Kargioğlu, Mustafa; Içağa, Yilmaz; Konuk, Muhsin

    2008-11-01

    In this study, the relationship among water quality, soil properties, and plant coverage in the region of the Akarçay stream was examined. Correlation analyses were carried out between soil samples taken from each of four plant communities in the Akarçay basin and water in the Akarçay stream. The four plant communities in the study area are as follows: Limonium lilacinum (Boiss. et Bal.) Wag., Alhagi pseudalhagi (M. Bieb.) Desv. Peganum harmala L., and Hordeum marinum Huds. subsp. marinum. B, Cl, EC, K, Mg, Na, pH, and SO4 data from both soil and water samples were subjected to statistical analysis, and significant correlations were obtained (p indicated that the chemical features of the soil had a major effect on water quality. The important parameters were B, Cl, EC, K, Mg, Na, pH, and SO4 for Limonium lilacinum communities; Ca, K, and pV for Peganum harmala; and B, Cl, Mg, pH, and pV for Alhagi pseudalhagi. There were also statistically significant relationships (p indicators for soil chemistry and water quality.

  9. Modeling of groundwater draft based on satellite-derived crop acreage estimation over an arid region of northwest India

    Science.gov (United States)

    Bhadra, Bidyut Kumar; Kumar, Sanjay; Paliwal, Rakesh; Jeyaseelan, A. T.

    2016-11-01

    Over-exploitation of groundwater for agricultural crops puts stress on the sustainability of natural resources in the arid region of Rajasthan state, India. Hydrogeological study of groundwater levels of the study area during the pre-monsoon (May to June), post-monsoon (October to November) and post-irrigation (February to March) seasons of 2004-2005 to 2011-2012 shows a steady decline of groundwater levels at the rate of 1.28-1.68 m/year, mainly due to excessive groundwater draft for irrigation. Due to the low density of the groundwater observation-well network in the study area, assessment of groundwater draft, and thus groundwater resource management, becomes a difficult task. To overcome the situation, a linear groundwater draft model (LGDM) has been developed based on the empirical relationship between satellite-derived crop acreage and the observed groundwater draft for the year 2003-2004. The model has been validated for a decade, during three year-long intervals (2005-2006, 2008-2009 and 2011-2012) using groundwater draft, estimated through a discharge factor method. Further, the estimated draft was validated through observed pumping data from random sampled villages (2011-2012). The results suggest that the developed LGDM model provides a good alternative to the estimation of groundwater draft based on satellite-based crop area in the absence of groundwater observation wells in arid regions of northwest India.

  10. Modelling dengue fever risk in the State of Yucatan, Mexico using regional-scale satellite-derived sea surface temperature.

    Science.gov (United States)

    Laureano-Rosario, Abdiel E; Garcia-Rejon, Julian E; Gomez-Carro, Salvador; Farfan-Ale, Jose A; Muller-Karger, Frank E

    2017-08-01

    Accurately predicting vector-borne diseases, such as dengue fever, is essential for communities worldwide. Changes in environmental parameters such as precipitation, air temperature, and humidity are known to influence dengue fever dynamics. Furthermore, previous studies have shown how oceanographic variables, such as El Niño Southern Oscillation (ENSO)-related sea surface temperature from the Pacific Ocean, influences dengue fever in the Americas. However, literature is lacking on the use of regional-scale satellite-derived sea surface temperature (SST) to assess its relationship with dengue fever in coastal areas. Data on confirmed dengue cases, demographics, precipitation, and air temperature were collected. Incidence of weekly dengue cases was examined. Stepwise multiple regression analyses (AIC model selection) were used to assess which environmental variables best explained increased dengue incidence rates. SST, minimum air temperature, precipitation, and humidity substantially explained 42% of the observed variation (r(2)=0.42). Infectious diseases are characterized by the influence of past cases on current cases and results show that previous dengue cases alone explained 89% of the variation. Ordinary least-squares analyses showed a positive trend of 0.20±0.03°C in SST from 2006 to 2015. An important element of this study is to help develop strategic recommendations for public health officials in Mexico by providing a simple early warning capability for dengue incidence. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Relationships between different burn, vegetation and soil ratios with Landsat spectral reflectance values in fire affected areas

    Science.gov (United States)

    Krina, Anastasia; Koutsias, Nikos

    2016-04-01

    The proportion of unburned vegetation within a fire affected area can be regarded as a proxy measure of fire severity that can be estimated by means of remote sensing techniques. Yet, in order to obtain sound results, it is essential to improve our current knowledge regarding the spectral discrimination of areas that have been completely burnt from adjacent areas within a fire perimeter that still have patches of vegetation, or unburned proportion of vegetation on them. The aim of our research is to reveal the role of the vegetation or the small vegetation gaps in spectral characteristics of pixels with mixed land cover synthesis (burned, vegetation and soil) to achieve a better assessment of fire mapping and the impact of fire in the burned area. Three land cover types were identified, namely vegetation, bare land and burned area by applying pixel based classification using the maximum likelihood algorithm in high-resolution aerial photographs (1m). Moreover, multispectral satellite Landsat data that were acquired close to capture date of the aerial photos and were converted to TOC reflectance from USGS, were used to measure the association between land cover portions and satellite-derived VIs and spectral signatures. A grid of 30x30m was created to extract the ratio of the land cover categories corresponding to each selected pixel of the satellite image LANDSAT TM. Samples of different land cover ratios and of different types of substrate (e.g. rocks, light- or dark-colored soil) were delineated and their reflectance values at each spectral channel were extracted and used to calculate statistics in order to characterize the spectral properties. Finally, various vegetation indices were computed to investigate the role of the proportion of land cover and substrate in the variation of VIs. The results of our study reveal the spectral characteristics of burnt area at the pixel level and suggest the efficiency of certain spectral channels for the estimation of the

  12. Preparation of a Microbial Time-temperature Indicator by Using the Vegetative Form of Bacillus amyloliquefaciens for Monitoring the Quality of Chilled Food Products

    Directory of Open Access Journals (Sweden)

    Samaneh Shahrokh Esfahani

    2017-04-01

    Full Text Available Background and Objective: Time-temperature indicators are used in smart packaging, and described as intelligent tools attached to the label of food products to monitor their timetemperature history. Since the previous studies on microbial time-temperature indicators were only based on pH-dependent changes, and they were long-time response indicators, in the present work, a new microbial time-temperature indicator was designed by using the alpha amylase activity of Bacillus amyloliquefaciens vegetative cells.Material and Methods: The designed time-temperature indicator system consists of Bacillus amyloliquefaciens, specific substrate medium and iodine reagent. The relation of the timetemperatureindicator’ response to the growth and metabolic activity (starch consumption and production of reduced sugars of Bacillus amyloliquefaciens was studied. In addition, the temperature dependence of the time-temperature indicator was considered at 8 and 28˚C. Finally, in order to adjust time-temperature indicator endpoint, the effect of the inoculum level was investigated at 8ºC.Results and Conclusion: In the designed system, a color change of an iodine reagent to yellow progressively occurs due to the starch hydrolysis. The effect of the inoculum level showed the negative linear relationship between the levels of Bacillus amyloliquefaciens inoculated in the medium and the endpoints of the time-temperature indicators. The endpoints were adjusted to 156, 72 and 36 hours at the inoculum levels of 102, 104 and 106 CFU ml-1, respectively. The main advantages of the time-temperature indicator is low cost and application for monitoring the quality of chilled food products.Conflict of interest: The authors declare no conflict of interest.

  13. The Effect of Irrigation Regimes and Mulch Application on Vegetative Indices and Essential Oil Content of Peppermint (Mentha piperita L.

    Directory of Open Access Journals (Sweden)

    M. Azizi

    2016-02-01

    Full Text Available Peppermint (Mentha piperita L. from Lamiaceae family is one of the most important medicinal plants, used in food, sanitary and cosmetic industries. A field experiment was carried out in Ferdowsi University of Mashhad in 2010-2011 to evaluate the effects of three irrigation levels (100, 80 and 60 percent of water requirements calculated by evaporation pan class A and two mulch types (black plastic and wood chips in comparison to control (without mulch on physiological parameter and essential oils content in a factorial experiments on the basis of Randimised Complete Block Desing with four replications. The data obtained from each harvest analyzed as a factorial experiment on the basis of randomized complete block design with four replications and the results of two harvests analyzed as split plot on time. The results of two harvest indicated that peppermint plants grow better in the first harvest than the second harvest. Plants collected in the first harvest showed higher dry matter and essential oil yield. The highest dry herb yield (44.12 g/plant, the highest percentage of essential oil (2.835 %v/w and the highest essential oil yield (116.7 l/ha detected in plots treated with third level of irrigation and use of wood chips mulch. In conclusion the results also confirmed that the highest dry herb and the highest oil yield per area unit were observed in plots treated with third level of irrigation with use of wood chips mulch.

  14. Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

    Science.gov (United States)

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for

  15. The impact of persistent volcanic degassing on vegetation: A case study at Turrialba volcano, Costa Rica

    Science.gov (United States)

    Tortini, R.; van Manen, S. M.; Parkes, B. R. B.; Carn, S. A.

    2017-07-01

    Although the impacts of large volcanic eruptions on the global environment have been frequently studied, the impacts of lower tropospheric emissions from persistently degassing volcanoes remain poorly understood. Gas emissions from persistent degassing exceed those from sporadic eruptive activity, and can have significant long-term (years to decades) effects on local and regional scales, both on humans and the environment. Here, we exploit a variety of high temporal and high spatial resolution satellite-based time series and complementary ground-based measurements of element deposition and surveys of species richness, to enable a comprehensive spatio-temporal assessment of sulfur dioxide (SO2) emissions and their associated impacts on vegetation at Turrialba volcano (Costa Rica) from 2000 to 2013. We observe increased emissions of SO2 coincident with a decline in vegetation health downwind of the vents, in accordance with the prevalent wind direction at Turrialba. We also find that satellite-derived vegetation indices at various spatial resolutions are able to accurately define the vegetation kill zone, the extent of which is independently confirmed by ground-based sampling, and monitor its expansion over time. In addition, ecological impacts in terms of vegetation composition and diversity and physiological damage to vegetation, all spatially correspond to fumigation by Turrialba's plume. This study shows that analyzing and relating satellite observations to conditions and impacts on the ground can provide an increased understanding of volcanic degassing, its impacts in terms of the long-term vegetation response and the potential of satellite-based monitoring to inform hazard management strategies related to land use.

  16. Recent Change of Vegetation Growth Trend in China

    Science.gov (United States)

    Peng, Shushi; Chen, Anping; Xu, Liang; Cao, Chunxiang; Fang, Jingyun; Myneni, Ranga B.; Pinzon, Jorge E.; Tucker, COmpton J.; Piao, Shilong

    2011-01-01

    Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982-99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April-October) NDVI significantly increased by 0.0007/yr from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982-99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013/yr is larger than those in June, July and August (JJA) (0.0003/yr) and September and October (SO) (0.0008/yr). This relatively small increasing trend of JJA NDVI during 1982-2010 compared with that during 1982-99 (0.0012/yr) (Piao et al 2003 J. Geophys. Res.-Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039/yr) to slightly decreasing (0:0002/yr) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020/yr) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

  17. Recent Change of Vegetation Growth Trend in China

    Science.gov (United States)

    Peng, Shushi; Chen, Anping; Xu, Liang; Cao, Chunxiang; Fang, Jingyun; Myneni, Ranga B.; Pinzon, Jorge E.; Tucker, COmpton J.; Piao, Shilong

    2011-01-01

    Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982-99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April-October) NDVI significantly increased by 0.0007/yr from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982-99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013/yr is larger than those in June, July and August (JJA) (0.0003/yr) and September and October (SO) (0.0008/yr). This relatively small increasing trend of JJA NDVI during 1982-2010 compared with that during 1982-99 (0.0012/yr) (Piao et al 2003 J. Geophys. Res.-Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039/yr) to slightly decreasing (0:0002/yr) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020/yr) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

  18. Assessment of Satellite-Derived Essential Climate Variables in the Terrestrial Domain: Overview and Status of the CEOS LPV Subgroup

    Science.gov (United States)

    Roman, M. O.

    2015-12-01

    The validation of satellite-derived terrestrial observations has perennially faced the challenge of finding a consistent set of in-situ measurements that can both cover a wide range of surface conditions and provide timely and traceable product accuracy and uncertainty information. The Committee on Earth Observation Satellites (CEOS), the space arm of the Group on Earth Observations (GEO), plays a key role in coordinating the land product validation process. The Land Product Validation (LPV) sub-group of the CEOS Working Group on Calibration and Validation (WGCV) aims to address the challenges associated with the validation of global land products. This paper will provide a status of LPV subgroup focus area activities, which cover seven Global Climate Observing System (GCOS) terrestrial Essential Climate Variables (ECVs): (1) Snow Cover, (2) Surface Albedo, (3) Land Cover, (4) Leaf Area Index, (5) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), (6) Active Fires, and (7) Soil Moisture; as well as two additional variables (Land Surface Phenology and Land Surface Temperature), which are deemed of high priority of the LPV community. A primary focus of LPV is the implementation of a global validation framework for product intercomparison and validation (fig. 1). This framework is based on a citable protocol, fiducial reference data, and automated subsetting. Ideally, each of these parts will be integrated into an online platform where quantitative tests are run, and standardized intercomparison and validation results reported for all products used in the validation exercise. The establishment of consensus guidelines for in situ measurements as well as inter-comparison of trends derived from independently-obtained reference data and derived products will enhance coordination of the scientific needs of the Earth system communities with global LPV activities (http://lpvs.gsfc.nasa.gov/).

  19. An indicator to map diffuse chemical river pollution considering buffer capacity of riparian vegetation--a pan-European case study on pesticides.

    Science.gov (United States)

    Weissteiner, Christof J; Pistocchi, Alberto; Marinov, Dimitar; Bouraoui, Fayçal; Sala, Serenella

    2014-06-15

    Vegetated riparian areas alongside streams are thought to be effective at intercepting and controlling chemical loads from diffuse agricultural sources entering water bodies. Based on a recently compiled European map of riparian zones and a simplified soil chemical balance model, we propose a new indicator at a continental scale. QuBES (Qualitative indicator of Buffered Emissions to Streams) allows a qualitative assessment of European rivers exposed to pesticide input. The indicator consists of normalised pesticide loads to streams computed through a simplified steady-state fate model that distinguishes various chemical groups according to physico-chemical behaviour (solubility and persistence). The retention of pollutants in the buffer zone is modelled according to buffer width and sorption properties. While the indicator may be applied for the study of a generic emission pattern and for a chemical of generic properties, we demonstrate it to the case of agricultural emissions of pesticides. Due to missing geo-spatial data of pesticide emissions, a total pesticide emission scenario is assumed. The QuBES indicator is easy to calculate and requires far less input data and parameterisation than typical chemical-specific models. At the same time, it allows mapping of (i) riparian buffer permeability, (ii) chemical runoff from soils, and (iii) the buffered load of chemicals to the stream network. When the purpose of modelling is limited to identifying chemical pollution patterns and understanding the relative importance of emissions and natural attenuation in soils and stream buffer strips, the indicator may be suggested as a screening level, cost-effective alternative to spatially distributed models of higher complexity.

  20. COMPARING BROAD-BAND AND RED EDGE-BASED SPECTRAL VEGETATION INDICES TO ESTIMATE NITROGEN CONCENTRATION OF CROPS USING CASI DATA

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2016-06-01

    Full Text Available In recent decades, many spectral vegetation indices (SVIs have been proposed to estimate the leaf nitrogen concentration (LNC of crops. However, most of these indices were based on the field hyperspectral reflectance. To test whether they can be used in aerial remote platform effectively, in this work a comparison of the sensitivity between several broad-band and red edge-based SVIs to LNC is investigated over different crop types. By using data from experimental LNC values over 4 different crop types and image data acquired using the Compact Airborne Spectrographic Imager (CASI sensor, the extensive dataset allowed us to evaluate broad-band and red edge-based SVIs. The result indicated that NDVI performed the best among the selected SVIs while red edge-based SVIs didn’t show the potential for estimating the LNC based on the CASI data due to the spectral resolution. In order to search for the optimal SVIs, the band combination algorithm has been used in this work. The best linear correlation against the experimental LNC dataset was obtained by combining the 626.20nm and 569.00nm wavebands. These wavelengths correspond to the maximal chlorophyll absorption and reflection position region, respectively, and are known to be sensitive to the physiological status of the plant. Then this linear relationship was applied to the CASI image for generating an LNC map, which can guide farmers in the accurate application of their N fertilization strategies.

  1. Comparing Broad-Band and Red Edge-Based Spectral Vegetation Indices to Estimate Nitrogen Concentration of Crops Using Casi Data

    Science.gov (United States)

    Wang, Yanjie; Liao, Qinhong; Yang, Guijun; Feng, Haikuan; Yang, Xiaodong; Yue, Jibo

    2016-06-01

    In recent decades, many spectral vegetation indices (SVIs) have been proposed to estimate the leaf nitrogen concentration (LNC) of crops. However, most of these indices were based on the field hyperspectral reflectance. To test whether they can be used in aerial remote platform effectively, in this work a comparison of the sensitivity between several broad-band and red edge-based SVIs to LNC is investigated over different crop types. By using data from experimental LNC values over 4 different crop types and image data acquired using the Compact Airborne Spectrographic Imager (CASI) sensor, the extensive dataset allowed us to evaluate broad-band and red edge-based SVIs. The result indicated that NDVI performed the best among the selected SVIs while red edge-based SVIs didn't show the potential for estimating the LNC based on the CASI data due to the spectral resolution. In order to search for the optimal SVIs, the band combination algorithm has been used in this work. The best linear correlation against the experimental LNC dataset was obtained by combining the 626.20nm and 569.00nm wavebands. These wavelengths correspond to the maximal chlorophyll absorption and reflection position region, respectively, and are known to be sensitive to the physiological status of the plant. Then this linear relationship was applied to the CASI image for generating an LNC map, which can guide farmers in the accurate application of their N fertilization strategies.

  2. Principle and geomorphological applicability of summit level and base level technique using Aster Gdem satellite-derived data and the original software Baz

    OpenAIRE

    Akihisa Motoki; Kenji Freire Motoki; Susanna Eleonora Sichel; Samuel da Silva; José Ribeiro Aires

    2015-01-01

    This article presents principle and geomorphological applicability of summit level technique using Aster Gdem satellite-derived topographicdata. Summit level corresponds to thevirtualtopographic surface constituted bylocalhighest points, such as peaks and plateau tops, and reconstitutes palaeo-geomorphology before the drainage erosion. Summit level map is efficient for reconstitution of palaeo-surfaces and detection of active tectonic movement. Base level is thevirtualsurface composed oflocal...

  3. Predicting Vegetation Condition from ASCAT Soil Water Index over Southwest India

    Science.gov (United States)

    Pfeil, Isabella Maria; Hochstöger, Simon; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang

    2017-04-01

    In India, extreme water scarcity events are expected to occur on average every five years. Record-breaking droughts affecting millions of human beings and livestock are common. If the south-west monsoon (summer monsoon) is delayed or brings less rainfall than expected, a season's harvest can be destroyed despite optimal farm management, leading to, in the worst case, life-threatening circumstances for a large number of farmers. Therefore, the monitoring of key drought indicators, such as the healthiness of the vegetation, and subsequent early warning is crucial. The aim of this work is to predict vegetation state from earth observation data instead of relying on models which need a lot of input data, increasing the complexity of error propagation, or seasonal forecasts, that are often too uncertain to be used as a regression component for a vegetation parameter. While precipitation is the main water supply for large parts of India's agricultural areas, vegetation datasets such as the Normalized Difference Vegetation Index (NDVI) provide reliable estimates of vegetation greenness that can be related to vegetation health. Satellite-derived soil moisture represents the missing link between a deficit in rainfall and the response of vegetation. In particular the water available in the root zone plays an important role for near-future vegetation health. Exploiting the added-value of root zone soil moisture is therefore crucial, and its use in vegetation studies presents an added value for drought analyses and decision-support. The soil water index (SWI) dataset derived from the Advanced Scatterometer (ASCAT) on board the Metop satellites represents the water content that is available in the root zone. This dataset shows a strong correlation with NDVI data obtained from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is exploited in this study. A linear regression function is fit to the multi-year SWI and NDVI dataset with a temporal

  4. Drought impacts on vegetation activity in the Mediterranean region: An assessment using remote sensing data and multi-scale drought indicators

    Science.gov (United States)

    Gouveia, C. M.; Trigo, R. M.; Beguería, S.; Vicente-Serrano, S. M.

    2017-04-01

    The present work analyzes the drought impacts on vegetation over the entire Mediterranean basin, with the purpose of determining the vegetation communities, regions and seasons at which vegetation is driven by drought. Our approach is based on the use of remote sensing data and a multi-scalar drought index. Correlation maps between fields of monthly Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at different time scales (1-24 months) were computed for representative months of winter (Feb), spring (May), summer (Aug) and fall (Nov). Results for the period from 1982 to 2006 show large areas highly controlled by drought, although presenting high spatial and seasonal differences, with a maximum influence in August and a minimum in February. The highest correlation values are observed in February for 3 months' time scale and in May for 6 and 12 months. The higher control of drought on vegetation in February and May is obtained mainly over the drier vegetation communities (Mediterranean Dry and Desertic) at shorter time scales (3 to 9 months). Additionally, in February the impact of drought on vegetation is lower for Temperate Oceanic and Continental vegetation types and takes place at longer time scales (18-24). The dependence of drought time-scale response with water balance, as obtained through a simple difference between precipitation and reference evapotranspiration, varies with vegetation communities. During February and November low water balance values correspond to shorter time scales over dry vegetation communities, whereas high water balance values implies longer time scales over Temperate Oceanic and Continental areas. The strong control of drought on vegetation observed for Mediterranean Dry and Desertic vegetation types located over areas with high negative values of water balance emphasizes the need for an early warning drought system covering the entire Mediterranean basin. We are confident

  5. Plant Remains from an Archaeological Site as Indicators of Vegetation and Agricultural Practice Between (3320±400) and (2080±80) yr BP in Gangetic West Bengal, India

    Institute of Scientific and Technical Information of China (English)

    Ruby Ghosh; Subir Bera; Ashalata D'Rozario; Manju Banerjee; Supriyo Chakraborty

    2006-01-01

    Diverse plant remains recovered from an archaeological site of Chalcolithic-Early Historic age in the Bhairabdanga area of Pakhanna (latitude 23°25′N, longitude 87°23′E), situated on the west bank of the Damodar river, Bankura district, West Bengal, India, include food grains, wood charcoals, and palynomorphs. Radiocarbon dating of the recovered biological remains reveal the age of the site as (3320±400) to (2080±80) yr BP. The food grains were identified as Oryza sativa L. and Vigna mungo L, and seeds of Brassica cf.campestris L. were also found; these indicate the agricultural practice and food habits of the ancient people living at Pakhanna from the Chalcolithic to the Early Historic period. Sediments including plant remains have been broadly divided into two zones, considering archaeological findings and radiocarbon dating. Analysis of the plant remains (i.e. wood charcoals and palynomorphs) in addition to cultivated food grains has revealed that a rich vegetation cover existed in this area, with a prevailing tropical and humid climate,comprising the timber-yielding plants Shorea sp., Terminalia sp., and Tamarindus sp., with undergrowths of diverse shrubs and herbs during the Chalcolithic period (zone Ⅰ) dated (3320±400) yr BP. Comparatively poorer representation and frequency of plant remains indicate a drier climate during the Early Historic period (zone Ⅱ) dated as (2110±340) to (2080±80) yr BP. Comparisons of the archaeobotanical data recovered from the Chalcolithic and Early Historic period and also a principle components analysis indicate a change in the climate of the area from tropical and humid at (3 320 ± 400) yr BP to tropical and drier conditions at (2110±340) to (2080±80) yr BP. The present-day tropical, dry deciduous vegetation of the area suggests that climate change has occurred in the area since the contemporaneous past. The plant remains database has been utilized to reconstruct the settlement pattern of the community living

  6. The relationship of hyper-spectral vegetation indices with leaf area index (LAI) over the growth cycle of wheat and chickpea at 3 nm spectral resolution

    Science.gov (United States)

    Gupta, R. K.; Vijayan, D.; Prasad, T. S.

    2006-01-01

    Hyperspectral ratio and normalized difference vegetation indices were computed from the 3 nm bandwidth ground-based spectral data taken in 400-950 nm wave length region over the crop growth cycle (CGC) of wheat and chickpea. Synthesized broad band Landsat TM-RVI, TM-NDVI and TM-SAVI were also computed using this narrow bandwidth spectral observations. Regression analysis was carried out for these indices with leaf area index (LAI) for wheat and chickpea over CGC and the r2 values were found poor in 0.2-0.53 range for wheat and in 0.41-0.82 range for chickpea. Significant relationship with LAI were found for wheat ( r2 in 0.86-0.97 range) when growth and decline phases were analyzed independently. Here, r2 values for chickpea were less than that for wheat. The high difference in rate of change of slope for hRVI is a good discriminator for high ET (wheat) and low ET (chickpea) crops. To find out the potential hyperspectral ratios and normalized difference indices that could provide strong relationship with LAI, a correlation-based analysis was carried out for LAI with all the possible combinations of ratios and normalized difference indices in 400-950 nm region (at 3 nm spectral interval) independently for growth and decline phases of LAI and found that in addition to traditional near-IR and red pairs, the pairs within near-IR, near-IR and visible extending to near-IR were also significantly related to LAI.

  7. Investigation of Vegetation Dynamics using Long-Term Normalized Difference Vegetation Index Time-Series

    Directory of Open Access Journals (Sweden)

    Tamara Bellone

    2009-01-01

    Full Text Available Problem statement: The Normalized Difference Vegetation Index (NDVI is the most extensively used satellite-derived index of vegetation health and density. Since climate is one of the most important factors affecting vegetation condition, satellite-derived vegetation indexes have been often used to evaluate climatic and environmental changes at regional and global scale. The proposed study attempted to investigate the temporal vegetation dynamics in the whole Africa using historical NDVI time-series. Approach: For this aim, 15 day maximum value NDVI composites at 8 km spatial resolution produced from the NASA Global Inventory Mapping and Monitoring System (GIMMS had been used. They were derived from data collected daily by NOAA AVHRR satellites. The AVHRR NDVI GIMMS dataset was freely available and gives global coverage over an extensive time period. First of all, the selected NDVI base data had been geometrically pre-processed and organized into a historical database implemented in order to grant their spatial integration. Starting from this archive, monthly and yearly NDVI historical time-series, extended from 1982-2006, had been then developed and analysed on a pixel basis. Several routines hade been developed in IDL (Interactive Data Language programming tool with the purpose of applying suitable statistical analysis techniques to the historical information in the database in order to identify the long-term trend components of generated NDVI time-series and extract vegetation dynamics. Specific tests had been then considered in order to define the validity of results. Results: The existence of clear regional trends of NDVI, both decreasing and increasing had been showed, which helped to highlight areas subject, respectively to reduction or increase in vegetation greenness. Conclusion: As the relationship between the NDVI and vegetation productivity was well established, these estimated long-term trend components may be also, with much more

  8. Varying applicability of four different satellite-derived soil moisture products to global gridded crop model evaluation

    Science.gov (United States)

    Sakai, Toru; Iizumi, Toshichika; Okada, Masashi; Nishimori, Motoki; Grünwald, Thomas; Prueger, John; Cescatti, Alessandro; Korres, Wolfgang; Schmidt, Marius; Carrara, Arnaud; Loubet, Benjamin; Ceschia, Eric

    2016-06-01

    Satellite-derived daily surface soil moisture products have been increasingly available, but their applicability to global gridded crop model (GGCM) evaluation is unclear. This study compares four different soil moisture products with the flux tower site observation at 18 cropland sites across the world where either of maize, soybean, rice and wheat is grown. These products include the first and second versions of Climate Change Initiative Soil Moisture (CCISM-1 and CCISM-2) datasets distributed by the European Space Agency and two different AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System)-derived soil moisture datasets, separately provided by the Japan Aerospace Exploration Agency (AMSRE-J) and U.S. National Aeronautics and Space Administration (AMSRE-N). The comparison demonstrates varying reliability of these products in representing major characteristics of temporal pattern of cropland soil moisture by product and crop. Possible reasons for the varying reliability include the differences in sensors, algorithms, bands and criteria used when estimating soil moisture. Both the CCISM-1 and CCISM-2 products appear the most reliable for soybean- and wheat-growing area. However, the percentage of valid data of these products is always lower than other products due to relatively strict criteria when merging data derived from multiple sources, although the CCISM-2 product has much more data with valid retrievals than the CCISM-1 product. The reliability of the AMSRE-J product is the highest for maize- and rice-growing areas and comparable to or slightly lower than the CCISM products for soybean- and wheat-growing areas. The AMSRE-N is the least reliable in most location-crop combinations. The reliability of the products for rice-growing area is far lower than that of other upland crops likely due to the extensive use of irrigation and patch distribution of rice paddy in the area examined here. We conclude that the CCISM-1, CCISM-2 and AMSRE

  9. Holocene vegetation variation in the Daihai Lake region of north-central China: a direct indication of the Asian monsoon climatic history

    Science.gov (United States)

    Xiao, Jule; Xu, Qinghai; Nakamura, Toshio; Yang, Xiaolan; Liang, Wendong; Inouchi, Yoshio

    2004-07-01

    DH99a sediment core recovered at the center of Daihai Lake in north-central China was analyzed at 4-cm intervals for pollen assemblage and concentration. The pollen record spanning the last ca 10,000 yr revealed a detailed history of vegetation and climate changes over the Daihai Lake region during the Holocene. From ca 10,250 to 7900 cal yr BP, arid herbs and shrubs dominated the lake basin in company with patches of mixed pine and broadleaved forests, indicating a mild and dry climatic condition. Over this period, the woody plants displayed an increasing trend, which may suggest a gradual increase in warmth and humidity. The period between ca 7900 and 4450 cal yr BP exhibits large-scale covers of mixed coniferous and broadleaved forests, marking a warm and humid climate. Changes in the composition of the forests indicate that both temperature and precipitation displayed obvious fluctuations during this period, i.e., cool and humid ca 7900- 7250 cal yr BP, warm and slightly humid ca 7250- 6050 cal yr BP, warm and humid between ca 6050 and 5100 cal yr BP, mild and slightly humid ca 5100- 4800 cal yr BP, and mild and humid ca 4800- 4450 cal yr BP. The period can be viewed as the Holocene optimum (characterized by a warm and moist climate) of north-central China, with the maximum (dominated both by warmest temperatures and by richest precipitations) occurring from ca 6050 to 5100 cal yr BP. During the period of ca 4450- 2900 cal yr BP, the woody plants declined, and the climate generally became cooler and drier than the preceding period. This period is characterized by a cold, dry episode from ca 4450 to 3950 cal yr BP, a warm, slightly humid interval between ca 3950 and 3500 cal yr BP and a mild, slightly dry episode from ca 3500 to 2900 cal yr BP, and appears to be a transition from warm and humid to cold and dry climatic conditions. Since ca 2900 cal yr ago, the forests disappeared and the vegetation density decreased, reflecting a cool and dry climate. However, a

  10. Investigation of North American vegetation variability under recent climate - A study using the SSiB4/TRIFFID biophysical/dynamic vegetation model

    Science.gov (United States)

    Zhang, Z.; Xue, Y.; MacDonald, G. M.; Cox, P. M.; Collatz, G. J.

    2014-12-01

    This study applies a 2-D biophysical model/dynamic vegetation model (SSiB4/TRIFFID) to investigate the dominant factors affecting vegetation equilibrium conditions, to assess the model's ability to simulate seasonal to decadal variability for the past 60 years (from 1948 through 2008), to analyze vegetation spatiotemporal characteristics over North America (NA), and to identify the relationships between vegetation and climate. Satellite data are employed as constraints for this study. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation have major impact on the vegetation spatial distribution and reach to equilibrium status in SSiB4/TRIFFID. The phenomenon that vegetation competition coefficients affect equilibrium suggests the importance of including biotic effects in dynamical vegetation modeling. SSiB4/TRIFFID can reproduce the features of NA distributions of dominant vegetation types, the vegetation fraction, and LAI, including its seasonal, interannual, and decadal variability, well compared with satellite-derived products. The NA LAI shows an increasing trend after the 1970s in responding to warming. Meanwhile, both simulation and satellite observations reveal LAI increased in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S.on vegetation are also evident from the simulated and satellite-derived LAIs.Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring through their effect on photosynthesis and phenological processes. During the summer, the areas with positive correlations retreat northward. Meanwhile, in southwestern dry lands, the negative correlations appear due to the heat stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which

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

    Science.gov (United States)

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

    2010-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Ricardo JPS Guimarães

    2010-07-01

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

  13. Assessing the Impacts of the 2009/2010 Drought on Vegetation Indices, Normalized Difference Water Index, and Land Surface Temperature in Southwestern China

    Directory of Open Access Journals (Sweden)

    Xiaoqiang Zhang

    2017-01-01

    Full Text Available Droughts are projected to increase in severity and frequency on both regional and global scales. Despite the increasing occurrence and intensity of the 2009/2010 drought in southwestern China, the impacts of drought on vegetation in this region remain unclear. We examined the impacts of the 2009/2010 drought in southwestern China on vegetation by calculating the standardized anomalies of Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Normalized Difference Water Index (NDWI, and Land Surface Temperature (LST. The standardized anomalies of NDVI, EVI, and NDWI exhibited positively skewed frequency distributions, while the standardized anomalies of LST exhibited a negatively skewed frequency distribution. These results implied that the NDVI, EVI, and NDWI declined, while LST increased in the 2009/2010 drought-stricken vegetated areas during the drought period. The responses of vegetation to the 2009/2010 drought differed substantially among biomes. Savannas, croplands, and mixed forests were more vulnerable to the 2009/2010 drought than deciduous forest and grasslands, while evergreen forest was resistant to the 2009/2010 drought in southwestern China. We concluded that the 2009/2010 drought had negative impacts on vegetation in southwestern China. The resulting assessment on the impacts of drought assists in evaluating and mitigating its adverse effects in southwestern China.

  14. Rational groundwater table indicated by the eco-physiological parameters of the vegetation: A case study of ecological restoration in the lower reaches of the Tarim River

    Institute of Scientific and Technical Information of China (English)

    CHEN Yaning; WANG Qiang; LI Weihong; RUAN Xiao; CHEN Yapeng; ZHANG Lihua

    2006-01-01

    The eco-physiological response and adaptation of Populus euphratica Oliv and Tamarix ramosissima Ldb during water release period were investigated. Nine typical areas and forty-five transects were selected along the lower reaches of Tarim River. The groundwater table as well as plant performance and the contents of proline, soluble sugars,and plant endogenous hormone (ABA, CTK) in leaves were monitored and analyzed. The groundwater table was raised in different areas and transects by water release program. The physiological stress to P. euphratica and T. ramosissima had been reduced after water release. Our results suggested that the groundwater table in the studied region remained at-3.15 to -4.12 m, the proline content from 9.28 to 11.06 (mmol/L), the soluble sugar content from 224.71 to 252.16 (mmol/L), the ABA content from 3.59 to 5.01 (ng/g FW), and the CK content from 4.01 to 4.56 (ng/g FW), for the optimum growth and restoration of P. euphratica indicated by the plant performance parameters and the efficiency of water application was the highest. The groundwater table in the studied region remained at -2.16 to -3.38 m, the proline content from 12.15 to 14.17 (mmol/L), the soluble sugar content from 154.71 to 183.16 (mmol/L), the ABA content from 2.78 to 4.86 (ng/g FW), and the CK content from 3.78 to 4.22 (ng/g FW), for the optimum growth and restoration of T. ramosissima indicated by the plant performance parameters and the efficiency of water application was the highest. The rational groundwater table for the restoration of vegetation in the studied region was at -3.15 to -3.38 m.

  15. Comparison of surface energy fluxes with satellite-derived surface energy flux estimates from a shrub-steppe

    Energy Technology Data Exchange (ETDEWEB)

    Kirkham, Randy R. [Univ. of Washington, Seattle, WA (United States)

    1993-12-01

    This thesis relates the components of the surface energy balance (i.e., net radiation, sensible and latent heat flux densities, soil heat flow) to remotely sensed data for native vegetation in a semi-arid environment. Thematic mapper data from Landsat 4 and 5 were used to estimate net radiation, sensible heat flux (H), and vegetation amount. Several sources of ground truth were employed. They included soil water balance using the neutron thermalization method and weighing lysimeters, and the measurement of energy fluxes with the Bowen ratio energy balance (BREB) technique. Sensible and latent heat flux were measured at four sites on the U.S. Department of Energy`s Hanford Site using a weighing lysimeter and/or BREB stations. The objective was to calibrate an aerodynamic transport equation that related H to radiant surface temperature. The transport equation was then used with Landsat thermal data to generate estimates of H and compare these estimates against H values obtained with BREB/lysimeters at the time of overflight. Landsat and surface meteorologic data were used to estimate the radiation budget terms at the surface. Landsat estimates of short-wave radiation reflected from the surface correlate well with reflected radiation measured using inverted Eppley pyranometers. Correlation of net radiation estimates determined from satellite data, pyranometer, air temperature, and vapor pressure compared to net radiometer values obtained at time of overflight were excellent for a single image, but decrease for multiple images. Soil heat flux, GT, is a major component of the energy balance in arid systems and G{sub T} generally decreases as vegetation cover increases. Normalized difference vegetation index (NDVI) values generated from Landsat thermatic mapper data were representative of field observations of the presence of green vegetation, but it was not possible to determine a single relationship between NDVI and GT for all sites.

  16. Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets

    Science.gov (United States)

    Pedinotti, V.; Boone, A.; Decharme, B.; Crétaux, J. F.; Mognard, N.; Panthou, G.; Papa, F.; Tanimoun, B. A.

    2012-06-01

    During the 1970s and 1980s, West Africa has faced extreme climate variations with extended drought conditions. Of particular importance is the Niger basin, since it traverses a large part of the Sahel and is thus a critical source of water for an ever-increasing local population in this semi arid region. However, the understanding of the hydrological processes over this basin is currently limited by the lack of spatially distributed surface water and discharge measurements. The purpose of this study is to evaluate the ability of the ISBA-TRIP continental hydrologic system to represent key processes related to the hydrological cycle of the Niger basin. ISBA-TRIP is currently used within a coupled global climate model, so that the scheme must represent the first order processes which are critical for representing the water cycle while retaining a limited number of parameters and a simple representation of the physics. To this end, the scheme uses first-order approximations to account explicitly for the surface river routing, the floodplain dynamics, and the water storage using a deep aquifer reservoir. In the current study, simulations are done at a 0.5 by 0.5° spatial resolution over the 2002-2007 period (in order to take advantage of the recent satellite record and data from the African Monsoon Multidisciplinary Analyses project, AMMA). Four configurations of the model are compared to evaluate the separate impacts of the flooding scheme and the aquifer on the water cycle. Moreover, the model is forced by two different rainfall datasets to consider the sensitivity of the model to rainfall input uncertainties. The model is evaluated using in situ discharge measurements as well as satellite derived flood extent, total continental water storage changes and river height changes. The basic analysis of in situ discharges confirms the impact of the inner delta area, known as a significant flooded area, on the discharge, characterized by a strong reduction of the

  17. Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets

    Directory of Open Access Journals (Sweden)

    V. Pedinotti

    2012-06-01

    Full Text Available During the 1970s and 1980s, West Africa has faced extreme climate variations with extended drought conditions. Of particular importance is the Niger basin, since it traverses a large part of the Sahel and is thus a critical source of water for an ever-increasing local population in this semi arid region. However, the understanding of the hydrological processes over this basin is currently limited by the lack of spatially distributed surface water and discharge measurements. The purpose of this study is to evaluate the ability of the ISBA-TRIP continental hydrologic system to represent key processes related to the hydrological cycle of the Niger basin. ISBA-TRIP is currently used within a coupled global climate model, so that the scheme must represent the first order processes which are critical for representing the water cycle while retaining a limited number of parameters and a simple representation of the physics. To this end, the scheme uses first-order approximations to account explicitly for the surface river routing, the floodplain dynamics, and the water storage using a deep aquifer reservoir. In the current study, simulations are done at a 0.5 by 0.5° spatial resolution over the 2002–2007 period (in order to take advantage of the recent satellite record and data from the African Monsoon Multidisciplinary Analyses project, AMMA. Four configurations of the model are compared to evaluate the separate impacts of the flooding scheme and the aquifer on the water cycle. Moreover, the model is forced by two different rainfall datasets to consider the sensitivity of the model to rainfall input uncertainties. The model is evaluated using in situ discharge measurements as well as satellite derived flood extent, total continental water storage changes and river height changes. The basic analysis of in situ discharges confirms the impact of the inner delta area, known as a significant flooded area, on the discharge, characterized by a strong

  18. Socioeconomic indicators and frequency of traditional food, junk food, and fruit and vegetable consumption amongst Inuit adults in the Canadian Arctic.

    Science.gov (United States)

    Hopping, B N; Erber, E; Mead, E; Sheehy, T; Roache, C; Sharma, S

    2010-10-01

    Increasing consumption of non-nutrient-dense foods (NNDF), decreasing consumption of traditional foods (TF) and low consumption of fruit and vegetables (FV) may contribute to increasing chronic disease rates amongst Inuit. The present study aimed to assess the daily frequency and socioeconomic and demographic factors influencing consumption of TF, FV and NNDF amongst Inuit adults in Nunavut, Canada. Using a cross-sectional study design and random household sampling in three communities in Nunavut, a food frequency questionnaire developed for the population was used to assess frequency of NNDF, TF and FV consumption amongst Inuit adults. Socioeconomic status (SES) was assessed by education level, ownership of items in working condition, and whether or not people in the household were employed or on income support. Mean frequencies of daily consumption were compared across gender and age groups, and associations with socioeconomic indicators were analysed using logistic regression. Two hundred and eleven participants (36 men, 175 women; mean (standard deviation) ages 42.1 (15.0) and 42.2 (13.2) years, respectively; response rate 69-93%) completed the study. Mean frequencies of consumption for NNDF, TF and FV were 6.3, 1.9 and 1.6 times per day, respectively. On average, participants ≤50 years consumed NNDF (P=0.003) and FV (P=0.01) more frequently and TF (P=0.01) less frequently than participants >50 years. Education was positively associated with FV consumption and negatively associated with TF consumption. Households on income support were more likely to consume TF and NNDF. These results support the hypothesis that the nutrition transition taking place amongst Inuit in Nunavut results in elevated consumption of NNDF compared with TF and FV. © 2010 The Authors. Journal compilation © 2010 The British Dietetic Association Ltd.

  19. Numerical Simulation of the Impact of Vegetation Index on the Interannual Variation of Summer Precipitation in the Yellow River Basin

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Two sets of numerical experiments using the coupled National Center for Environmental Prediction General Circulation Model (NCEP/GCM T42L18) and the Simplified Simple Biosphere land surface scheme (SSiB) were carried out to investigate the climate impacts of fractional vegetation cover (FVC)and leaf area index (LAI) on East Asia summer precipitation, especially in the Yellow River Basin (YRB).One set employed prescribed FVC and LAI which have no interannual variations based on the climatology of vegetation distribution; the other with FVC and LAI derived from satellite observations of the International Satellite Land Surface Climate Project (ISLSCP) for 1987 and 1988. The simulations of the two experiments were compared to study the influence of FVC, LAI on summer precipitation interannual variation in the YRB. Compared with observations and the NCEP reanalysis data, the experiment that included both the effects of satellite-derived vegetation indexes and sea surface temperature (SST)produced better seasonal and interannual precipitation variations than the experiment with SST but no interannual variations in FVC and LAI, indicating that better representations of the vegetation index and its interannual variation may be important for climate prediction. The difference between 1987 and 1988indicated that with the increase of FVC and LAI, especially around the YRB, surface albedo decreased,net surface radiation increased, and consequently local evaporation and precipitation intensified. Further more, surface sensible heat flux, surface temperature and its diurnal variation decreased around the YRB in response to more vegetation. The decrease of surface-emitting longwave radiation due to the cooler surface outweighed the decrease of surface solar radiation income with more cloud coverage, thus maintaining the positive anomaly of net surface radiation. Further study indicated that moisture flux variations associated with changes in the general circulation also

  20. componente vegetal

    Directory of Open Access Journals (Sweden)

    Fabio Moscovich

    2005-01-01

    Full Text Available In order to determine environmental impact, indicators based on vegetation characteristics that would generate the forestry monoculture with the adjacent native forest, 32 sample unit were installed in an area of LIPSIA private enterprise, Esperanza Department, Misiones with those characteristics. The plots of 100 m2 were distributed systematically every 25 meters. The vegetation was divided in stratum: superior (DBH ≥ 10 cm, middle (1,6 cm ≤ DBH > 10 cm and inferior (DBH< cm. There were installed 10 plots in a logged native forest, 10 plots in a 18 years old Pinus elliottii Engelm. with approximately 400 trees/ha., 6 plots in a 10 – 25 years old Araucaria angustifolia (Bertd. Kuntze limiting area with approximately 900 trees/ha., and 6 plots located in this plantation. In the studied area were identified 150 vegetation species. In the inferior stratum there were found differences as function of various floristic diversity indexes. In all the cases the native forest showed larger diversity than plantations, followed by Pinus elliottii, Araucaria plantation and Araucaria limiting area. All the studied forest fitted to a logarithmical series of species distributions, that would indicate the incidence of a environmental factor in this distribution.

  1. How robust are in situ observations for validating satellite-derived albedo over the dark zone of the Greenland Ice Sheet?

    Science.gov (United States)

    Ryan, J. C.; Hubbard, A.; Irvine-Fynn, T. D.; Doyle, S. H.; Cook, J. M.; Stibal, M.; Box, J. E.

    2017-06-01

    Calibration and validation of satellite-derived ice sheet albedo data require high-quality, in situ measurements commonly acquired by up and down facing pyranometers mounted on automated weather stations (AWS). However, direct comparison between ground and satellite-derived albedo can only be justified when the measured surface is homogeneous at the length-scale of both satellite pixel and in situ footprint. Here we use digital imagery acquired by an unmanned aerial vehicle to evaluate point-to-pixel albedo comparisons across the western, ablating margin of the Greenland Ice Sheet. Our results reveal that in situ measurements overestimate albedo by up to 0.10 at the end of the melt season because the ground footprints of AWS-mounted pyranometers are insufficient to capture the spatial heterogeneity of the ice surface as it progressively ablates and darkens. Statistical analysis of 21 AWS across the entire Greenland Ice Sheet reveals that almost half suffer from this bias, including some AWS located within the wet snow zone.

  2. Effective roughness calculated from satellite-derived land cover maps and hedge-information used in a weather forecasting model

    DEFF Research Database (Denmark)

    Hasager, C.B.; Nielsen, N.,W.; Jensen, N.O.

    2003-01-01

    In numerical weather prediction, climate and hydrological modelling, the grid cell size is typically larger than the horizontal length scales of variations in aerodynamic roughness, surface temperature and surface humidity. These local land cover variations give rise to sub-grid scale surface flux...... to be well-described in any large-scale model. A method of aggregating the roughness step changes in arbitrary real terrain has been applied in flat terrain (Denmark) where sub-grid scale vegetation-driven roughness variations are a dominant characteristic of the landscape. The aggregation model...... is a physical two-dimensional atmospheric flow model in the horizontal domain based on a linearized version of the Navier Stoke equation. The equations are solved by the Fast Fourier Transformation technique, hence the code is very fast. The new effective roughness maps have been used in the HIgh Resolution...

  3. Impact of climate change on vegetation dynamics in a West African river basin

    Science.gov (United States)

    Sawada, Y.; Koike, T.

    2012-12-01

    Future changes in terrestrial biomass distribution under climate change will have a tremendous impact on water availability and land productivity in arid and semi-arid regions. Assessment of future change of biomass distribution in the regional or the river basin scale is strongly needed. An eco-hydrological model that fully couples a dynamic vegetation model (DVM) with a distributed biosphere hydrological model is applied to multi-model assessment of climate change impact on vegetation dynamics in a West African river basin. In addition, a distributed and auto optimization system of parameters in DVM is developed to make it possible to model a diversity of phonologies of plants by using different parameters in the different model grids. The simple carbon cycle modeling in a distributed hydrological model shows reliable accuracy in simulating the seasonal cycle of vegetation on the river basin scale. Model outputs indicate that generally, an extension of dry season duration and surface air temperature rising caused by climate change may cause a dieback of vegetation in West Africa. However, we get different seasonal and spatial changes of leaf area index and different mechanisms of the degradation when we used different general circulation models' outputs as meteorological forcing of the eco-hydrological model. Therefore, multi-model analysis like this study is important to deliver meaningful information to the society because we can discuss the uncertainties of our prediction by this methodology. This study makes it possible to discuss the impact of future change of terrestrial biomass on climate and water resources in the regional or the river basin scale although we need further sophistications of the system. Performance of the eco-hydrological model (WEB-DHM+DVM) in Volta River Basin, with basin-averaged leaf area index from model (blue solid line) and AVHRR satellite-derived product (red rectangles).

  4. Identical assemblage of Giardia duodenalis in humans, animals and vegetables in an urban area in southern Brazil indicates a relationship among them.

    Directory of Open Access Journals (Sweden)

    Cristiane Maria Colli

    Full Text Available Giardia duodenalis infects humans and other mammals by ingestion of cysts in contaminated water or food, or directly in environments with poor hygiene. Eight assemblages, designated A-H, are described for this species.We investigated by microscopy or by direct immunofluorescence technique the occurrence of G. duodenalis in 380 humans, 34 animals, 44 samples of water and 11 of vegetables. G. duodenalis cysts present in samples were genotyped through PCR-RFLP of β giardin and glutamate dehydrogenase (gdh genes and sequencing of gdh. The gdh gene was amplified in 76.5% (26/34 of the human faeces samples with positive microscopy and in 2.9% (1/34 of negative samples. In 70.4% (19/27 of the positive samples were found BIV assemblage. In two samples from dogs with positive microscopy and one negative sample, assemblages BIV, C, and D were found. Cysts of Giardia were not detected in water samples, but three samples used for vegetable irrigation showed total coliforms above the allowed limit, and Escherichia coli was observed in one sample. G. duodenalis BIV was detected in two samples of Lactuca sativa irrigated with this sample of water. BIV was a common genotype, with 100% similarity, between different sources or hosts (humans, animals and vegetables, and the one most often found in humans.This is the first study in Brazil that reports the connection among humans, dogs and vegetables in the transmission dynamics of G. duodenalis in the same geographic area finding identical assemblage. BIV assemblage was the most frequently observed among these different links in the epidemiological chain.

  5. Application of a regularized model inversion system (REGFLEC) to multi-temporal RapidEye imagery for retrieving vegetation characteristics

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.

    2015-10-01

    Accurate retrieval of canopy biophysical and leaf biochemical constituents from space observations is critical to diagnosing the functioning and condition of vegetation canopies across spatio-temporal scales. Retrieved vegetation characteristics may serve as important inputs to precision farming applications and as constraints in spatially and temporally distributed model simulations of water and carbon exchange processes. However significant challenges remain in the translation of composite remote sensing signals into useful biochemical, physiological or structural quantities and treatment of confounding factors in spectrum-trait relations. Bands in the red-edge spectrum have particular potential for improving the robustness of retrieved vegetation properties. The development of observationally based vegetation retrieval capacities, effectively constrained by the enhanced information content afforded by bands in the red-edge, is a needed investment towards optimizing the benefit of current and future satellite sensor systems. In this study, a REGularized canopy reFLECtance model (REGFLEC) for joint leaf chlorophyll (Chll) and leaf area index (LAI) retrieval is extended to sensor systems with a band in the red-edge region for the first time. Application to time-series of 5 m resolution multi-spectral RapidEye data is demonstrated over an irrigated agricultural region in central Saudi Arabia, showcasing the value of satellite-derived crop information at this fine scale for precision management. Validation against in-situ measurements in fields of alfalfa, Rhodes grass, carrot and maize indicate improved accuracy of retrieved vegetation properties when exploiting red-edge information in the model inversion process.

  6. Application of a regularized model inversion system (REGFLEC) to multi-temporal RapidEye imagery for retrieving vegetation characteristics

    KAUST Repository

    Houborg, Rasmus

    2015-10-14

    Accurate retrieval of canopy biophysical and leaf biochemical constituents from space observations is critical to diagnosing the functioning and condition of vegetation canopies across spatio-temporal scales. Retrieved vegetation characteristics may serve as important inputs to precision farming applications and as constraints in spatially and temporally distributed model simulations of water and carbon exchange processes. However significant challenges remain in the translation of composite remote sensing signals into useful biochemical, physiological or structural quantities and treatment of confounding factors in spectrum-trait relations. Bands in the red-edge spectrum have particular potential for improving the robustness of retrieved vegetation properties. The development of observationally based vegetation retrieval capacities, effectively constrained by the enhanced information content afforded by bands in the red-edge, is a needed investment towards optimizing the benefit of current and future satellite sensor systems. In this study, a REGularized canopy reFLECtance model (REGFLEC) for joint leaf chlorophyll (Chll) and leaf area index (LAI) retrieval is extended to sensor systems with a band in the red-edge region for the first time. Application to time-series of 5 m resolution multi-spectral RapidEye data is demonstrated over an irrigated agricultural region in central Saudi Arabia, showcasing the value of satellite-derived crop information at this fine scale for precision management. Validation against in-situ measurements in fields of alfalfa, Rhodes grass, carrot and maize indicate improved accuracy of retrieved vegetation properties when exploiting red-edge information in the model inversion process. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  7. Estimation of glacier mass balance: An approach based on satellite-derived transient snowlines and a temperature index driven by meteorological observations

    Science.gov (United States)

    Tawde, S. A.; Kulkarni, A. V.; Bala, G.

    2015-12-01

    In the Himalaya, large area is comprised of glaciers and seasonal snow, mainly due to its high elevated mountain ranges. Long term and continuous assessment of glaciers in this region is important for climatological and hydrological applications. However, rugged terrains and severe weather conditions in the Himalaya lead to paucity in field observations. Therefore, in recent decades, glacier dynamics are extensively monitored using remote sensing in inaccessible terrain like Himalaya. Estimation of glacier mass balance using empirical relationship between mass balance and area accumulation ratio (AAR) requires an accurate estimate of equilibrium-line altitude (ELA). ELA is defined as the snowline at the end of the hydrological year. However, identification of ELA, using remote sensing is difficult because of temporal gaps, cloud cover and intermediate snowfall on glaciers. This leads to large uncertainty in glacier mass-balance estimates by the conventional AAR method that uses satellite-derived highest snowline in ablation season as an ELA. The present study suggests a new approach to improve estimates of ELA location. First, positions of modelled snowlines are optimized using satellite-derived snowlines in the early melt season. Secondly, ELA at the end of the glaciological year is estimated by the melt and accumulation models driven using in situ temperature and precipitation records. From the modelled ELA, mass balance is estimated using the empirical relationship between AAR and mass balance. The modelled mass balance is validated using field measurements on Chhota Shigri and Hamtah glaciers, Himachal Pradesh, India. The new approach shows a substantial improvement in glacier mass-balance estimation, reducing bias by 46% and 108% for Chhota Shigiri and Hamtah glaciers respectively. The cumulative mass loss reconstructed from our approach is 0.85 Gt for nine glaciers in the Chandra basin from 2001 to 2009. The result of the present study is in agreement with

  8. Thermophilous fringe communities as an indicator of vegetation changes: a case study of the “Murawy Dobromierskie” steppe reserve (Poland

    Directory of Open Access Journals (Sweden)

    Szygendowski Tomasz

    2015-12-01

    Full Text Available In this paper, changes of the non-forest xerothermic vegetation of the “Murawy Dobromierskie” steppe reserve which occurred in the period 1993-2012 are examined. The material comprises 50 relevés, of which 43 date from 2012 and the other 7 - from 1993. Reléves were arranged in 5 analytic tables. A synoptic table was also compiled, and for each syntaxonomical species group distinguished, values of the cover coefficient (C, the collective group share index (G, and the systematic group value (D were estimated and compared. On the basis of the obtained results, a significant decline in abundancy and/or constancy was observed within the following groups: Ch. Artemisietea vulgaris, Ch. Cirsio-Brachypodion pinnati, Ch. Festuco-Brometea, Ch. Geranion sanguinei, Ch. Koelerio-Corynephoretea, and Ch. Origanetalia and Trifolio-Geranietea sanguinei, whereas for the taxa of the Rhamno-Prunetea, a notable increase in the share of the reserve vegetation was recorded. A sizeable expansion of the moss layer was also observed in this period. The results are discussed with special regard to differences in the methodical background of both field studies.

  9. Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories

    Science.gov (United States)

    Whitburn, S.; Van Damme, M.; Kaiser, J. W.; van der Werf, G. R.; Turquety, S.; Hurtmans, D.; Clarisse, L.; Clerbaux, C.; Coheur, P.-F.

    2015-11-01

    Vegetation fires emit large amounts of nitrogen compounds in the atmosphere, including ammonia (NH3). These emissions are still subject to large uncertainties. In this study, we analyze time series of monthly NH3 total columns (molec cm-2) from the IASI sounder on board MetOp-A satellite and their relation with MODIS fire radiative power (MW) measurements. We derive monthly NH3 emissions estimates for four regions accounting for a major part of the total area affected by fires (two in Africa, one in central South America and one in Southeast Asia), using a simplified box model, and we compare them to the emissions from both the GFEDv3.1 and GFASv1.0 biomass burning emission inventories. In order to strengthen the analysis, we perform a similar comparison for carbon monoxide (CO), also measured by IASI and for which the emission factors used in the inventories to convert biomass burned to trace gas emissions are thought to be more reliable. In general, a good correspondence between NH3 and CO columns and the FRP is found, especially for regions in central South America with correlation coefficients of 0.82 and 0.66, respectively. The comparison with the two biomass burning emission inventories GFASv1.0 and GFEDv3.1 shows good agreements, particularly in the time of the maximum of emissions for the central South America region and in the magnitude for the region of Africa south of the equator. We find evidence of significant non-pyrogenic emissions for the regions of Africa north of the equator (for NH3) and Southeast Asia (for NH3 and CO). On a yearly basis, total emissions calculated from IASI measurements for the four regions reproduce fairly well the interannual variability from the GFEDv3.1 and GFASv1.0 emissions inventories for NH3 but show values about 1.5-2 times higher than emissions given by the two biomass burning emission inventories, even when assuming a fairly long lifetime of 36 h for that species.

  10. Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on the Pan-Arctic scale

    NARCIS (Netherlands)

    Urban, M.; Eberle, J.; Hüttich, C.; Schmullius, C.; Herold, M.

    2013-01-01

    Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR) and (Advanced) Along Track Scanning Radiometer ((A)ATSR) are pr

  11. Satellite-derived changes in the permafrost landscape of central Yakutia, 2000-2011: wetting, drying, and fires

    Science.gov (United States)

    Boike, Julia; Grau, Thomas; Heim, Birgit; Günther, Frank; Langer, Moritz; Muster, Sina; Gouttevin, Isabelle; Lange, Stephan

    2016-04-01

    The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing. The study area covers the main (central) part of the Lena River catchment in the Yakutia region of Siberia (Russia), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS-derived NASA products for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat high resolution (30 m) satellite images from 2002 and 2009. Within the study area's 315,000 km² the total area covered by lakes increased by 17.5% between 2002 and 2009, but this increase varied in different parts of the study area, ranging between 11% and 42%. The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12°C/year. The average rate of warming during the April-May transition period was 0.15°C/year and 0.19°C/year in the September-October period, but ranged up to 0.45°C/year in some areas during April-May. Regional differences in the rates of land surface temperature change, and possible reasons for the temperature changes, are discussed with respect to changes in the land cover. Our analysis of a broad spectrum of variables over the study area suggests that the spring warming trend is very likely to be due to changes in the area covered by snow. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the

  12. Assessment and Intercomparison of Satellite-derived Start-of-Season (SOS) Measures in Eurasia for 1982-2006%1982-2006年欧亚大陆植被生长季开始时间遥感监测分析

    Institute of Scientific and Technical Information of China (English)

    刘玲玲; 刘良云; 胡勇

    2012-01-01

    Vegetation phenology is one of the most direct and sensitive indicators of seasonal and interanual variations of environmental conditions.Phenological changes reflect quick change of terrestrial ecosystems in response to climate change.Satellite remote-sensing techniques capture canopy reflectance and can be used for studies of vegetation phenology.In this study,satellite-derived Start of Season(SOS) dates are obtained from the GIMMS AVHRR NDVI dataset by different methods such as Dynamic Threshold method,Delayed Moving Average methods,Double Logistic analysis and Savitzky-Golay method.The derived SOS data are compared and analyzed for the ecoregions from China to Russia,and the Dynamic Threshold method is decided to be most suitable for Eurasia scale.Based on the analysis of the changes of vegetation phenology and the response of phenology to climate change from 1982 to 2006,it is concluded that the Dynamic Threshold method has high retrieval rate for the SOS dates in Eurasia,and the data show a stable trend along the latitudinal gradient.The retrieved SOS dates for boreal forests and tundra ecosystems are most stable in the long term,while in the vegetation areas of low latitudes the dates show higher variability.It is found that from 1982 to 2006,there is a trend of SOS dates becoming earlier for the majority of vegetation types,and the forest coverage areas show even stronger trend of SOS dates becoming earlier,with a change rate of 11.45-15.61 days/25 years,due to global warming.With the exception of the closed to open(15%) shrubland(5 m),for most other types of vegetation,there is a negative correlation between vegetation phenology and the average temperature of the month.In other words,for each one degree increase,there is 1.32-3.47 days decrease to SOS date in spring,which is consistent with global warming in recent years.%植被物候是环境条件季节和年际变化最直观、最敏感的生物指示器,物候变化可以反映陆地生态系统对

  13. Peculiarities of psychological, clinical and instrumental indicators in children with vegetative dysfunction and hypotension under the influence of innovative psychocorrective program

    Directory of Open Access Journals (Sweden)

    I.O. Mitjurjajeva

    2017-05-01

    Full Text Available Background. To study the features of psychological state, clinical and instrumental parameters in children with vegetative dysfunction (VD and hypotension influenced by comprehensive treatment with the inclusion of the innovative psychocorrective program with elements of music therapy, visual art therapy and gelotology. Materials and methods. The study included 57 patients with VD and hypotension aged 12 to 17 years, 37 of them received psychotherapy with innovative program “Our drugs — music, laughter, creativity” in comprehensive treatment, 20 children (control group received basic treatment without psychological assistance. General clinical, laboratory, instrumental and psychodiagnostic studies were performed both in main and control groups. Results. Using innovative psychocorrective program in children with VD and hypotension as a part of comprehensive treatment contributed to the improvement of clinical and instrumental data: number of cases with autonomic influences on the heart reduced (from 22.1 to 5.25 %, р < 0.05, orthostatic test autonomic provision was normalized in 40.5 % of children, psychological state improvement was observed in 74.1 % of cases. Conclusions. Innovative psychocorrective program with elements of music therapy, visual art therapy and gelotology can be recommended as a part of comprehensive treatment of children with VD and hypotension in hospital environment and in future psychological support of patients.

  14. Derivation of the canopy conductance from surface temperature and spectral indices for estimating evapotranspiration in semiarid vegetation; Monitorizacion de conductancia en vegetacion semiarida a partir de indices espectrales y temperatura de supeficie

    Energy Technology Data Exchange (ETDEWEB)

    Morillas, L.; Garcia, M.; Zarco-Tejada, P.; Ladron de Guevara, M.; Villagarcia, L.; Were, A.; Domingo, F.

    2009-07-01

    This work evaluates the possibilities for estimating stomata conductance (C) and leaf transpiration (Trf) at the ecosystem scale from radiometric indices and surface temperature. The relationships found between indices and the transpiration component of the water balance in a semiarid tussock ecosystem in SE Spain are discussed. Field data were collected from spring 2008 until winter 2009 in order to observe the annual variability of the relationships and the behaviour of spectral indices and surface temperature. (Author) 11 refs.

  15. Associations between access to farmers' markets and supermarkets, shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, U.S.A.

    Science.gov (United States)

    Jilcott Pitts, Stephanie B; Wu, Qiang; McGuirt, Jared T; Crawford, Thomas W; Keyserling, Thomas C; Ammerman, Alice S

    2013-11-01

    We examined associations between access to food venues (farmers’ markets and supermarkets), shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, U.S.A. Access to food venues was measured using a Geographic Information System incorporating distance, seasonality and business hours, to quantify access to farmers’ markets. Produce consumption was assessed by self-report of eating five or more fruits and vegetables daily. BMI and blood pressure were assessed by clinical measurements. Poisson regression with robust variance was used for dichotomous outcomes and multiple linear regression was used for continuous outcomes. As the study occurred in a university town and university students are likely to have different shopping patterns from non-students, we stratified analyses by student status. Eastern North Carolina. Low-income women of reproductive age (18–44 years) with valid address information accessing family planning services at a local health department (n 400). Over a quarter reported ever shopping at farmers’ markets (114/400). A larger percentage of women who shopped at farmers’ markets consumed five or more fruits and vegetables daily (42.1%) than those who did not (24.0%; P < 0.001). The mean objectively measured distance to the farmers’ markets where women reported shopping was 11.4 (SD 9.0) km (7.1 (SD 5.6) miles), while the mean distance to the farmers’ market closest to the residence was 4.0 (SD 3.7) km (2.5 (SD 2.3) miles). Among non-students, those who shopped at farmers’ markets were more likely to consume five or more servings of fruits and vegetables daily. Future research should further explore potential health benefits of farmers’ markets.

  16. Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose

    DEFF Research Database (Denmark)

    Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K.

    2017-01-01

    The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10− 5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different...... physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study...... to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data...

  17. Principle and geomorphological applicability of summit level and base level technique using Aster Gdem satellite-derived data and the original software Baz

    Directory of Open Access Journals (Sweden)

    Akihisa Motoki

    2015-05-01

    Full Text Available This article presents principle and geomorphological applicability of summit level technique using Aster Gdem satellite-derived topographicdata. Summit level corresponds to thevirtualtopographic surface constituted bylocalhighest points, such as peaks and plateau tops, and reconstitutes palaeo-geomorphology before the drainage erosion. Summit level map is efficient for reconstitution of palaeo-surfaces and detection of active tectonic movement. Base level is thevirtualsurface composed oflocallowest points, as valley bottoms. The difference between summit level and base level is called relief amount. Thesevirtualmapsareconstructed by theoriginalsoftwareBaz. Themacroconcavity index, MCI, is calculated from summit level and relief amount maps. The volume-normalised three-dimensional concavity index, TCI, is calculated from hypsometric diagram. The massifs with high erosive resistance tend to have convex general form and low MCI and TCI. Those with low resistance have concave form and high MCI and TCI. The diagram of TCI vs. MCI permits to distinguish erosive characteristics of massifs according to their constituent rocks. The base level map for ocean bottom detects the basement tectonic uplift which occurred before the formation of the volcanic seamounts.

  18. A photogrammetric DEM of Greenland based on 1978-1987 aerial photos: validation and integration with laser altimetry and satellite-derived DEMs

    Science.gov (United States)

    Korsgaard, N. J.; Kjaer, K. H.; Nuth, C.; Khan, S. A.

    2014-12-01

    Here we present a DEM of Greenland covering all ice-free terrain and the margins of the GrIS and local glaciers and ice caps. The DEM is based on the 3534 photos used in the aero-triangulation which were recorded by the Danish Geodata Agency (then the Geodetic Institute) in survey campaigns spanning the period 1978-1987. The GrIS is covered tens of kilometers into the interior due to the large footprints of the photos (30 x 30 km) and control provided by the aero-triangulation. Thus, the data are ideal for providing information for analysis of ice marginal elevation change and also control for satellite-derived DEMs.The results of the validation, error assessments and predicted uncertainties are presented. We test the DEM using Airborne Topographic Mapper (IceBridge ATM) as reference data; evaluate the a posteriori covariance matrix from the aero-triangulation; and co-register DEM blocks of 50 x 50 km to ICESat laser altimetry in order to evaluate the coherency.We complement the aero-photogrammetric DEM with modern laser altimetry and DEMs derived from stereoscopic satellite imagery (AST14DMO) to examine the mass variability of the Northeast Greenland Ice Stream (NEGIS). Our analysis suggests that dynamically-induced mass loss started around 2003 and continued throughout 2014.

  19. Evaluation of Multiple Spring Phenological Indicators of Yearly GPP and NEP at Three Canadian Forest Sites

    Directory of Open Access Journals (Sweden)

    Qian Wang

    2014-03-01

    Full Text Available Phenological shifts in events such as flowering and bud break are important indicators of ecosystem processes, and are therefore of particular significance for carbon (C cycle research. Using long-term flux data from three contrasting plant functional type (evergreen and deciduous boreal forest sites, we evaluated and compared the responses of annual C fluxes to multiple spring phenological indicators, including the C-uptake period onset (CUP onset, spring temperature (average value from March to May, and satellite-derived enhanced vegetation index (EVI (average value from March to May. We found that the CUP onset was negatively correlated with annual gross primary production (GPP for all three sites, but that its predictive strength for annual net ecosystem production (NEP differed substantially among plant functional types. Spring temperature demonstrated particularly good potential for predicting both annual GPP and NEP for the evergreen sites, but not for the deciduous site. Spring EVI was demonstrated to have potential for predicting annual NEP for all sites. However, both plant functional types confounded the correlation of annual NEP with annual GPP. Although none of these phenological indicators provided consistent insight into annual C fluxes, using various currently available datasets our results remain potentially useful for the assessment of forest C cycling with future climate change. Previous analyses using only a single phenological metric should be considered with caution.

  20. Presettlement Vegetation

    Data.gov (United States)

    Minnesota Department of Natural Resources — Presettlement vegetation of Minnesota based on Marschner's original analysis of Public Land Survey notes and landscape patterns. Marschner compiled his results in...

  1. The relationship of Hyper-spectral Vegetation Indices with LAI over the growth cycle of Wheat and Chickpea at 3nm spectral resolution

    Science.gov (United States)

    Gupta, R.; Vijayan, D.; Prasad, T.

    Using 3 nm observations over wheat and chickpea, hyperspectral indices, hNDVI= [(R 774-R677)/(R774+R677)], hRVI=R7 7 4/R 677 and TM bandwidths based NDVI, RVI and SAVI were computed. Pigment specific ratios (PSR) with reflectance at 800 nm (R800) as numerator were computed for Chlorophyll-a (PSR a= R800 /R 680 ) , Chlorophyll-b (PSR b = R800 /R 635) and Chlorophyll- Carotenoid (PSRc= R800 /R 470 ) . Structure intensive pigment indices (SIPI) given by SIPIa=(R 800 -R 445)/(R 800 -R6 8 0) and SIPIb =[(R 800 -R445)/(R 680 -R4 4 5)] were computed. Acceptable confidence level (r2 in 0.90-0.96 and 0.86-0.91 for all the above mentioned ratios and normalized difference indices, respectively) in correlation of these indices with LAI for wheat was observed when LAI for growth and decline phases were regressed separately; for ratio and normalized indices for chickpea, the r2 (for relationship with LAI) was in 0.85-0.97 range for growth phase and in 0.64-0.85 range for decline phase. In case of chickp ea, the leaves becoming yellow do not fall or undergo change in interaction cross-section to incident light; thus, LAI does not change though spectral indices will change. The r2 for the correlations of LAI for wheat, with TMRVI, PSR a, PSR b , PSRc were in 0.92-0.96 range; with TM NDVI and TM SAVI r 2 were in 0.90-0.91 range and with SIPIa and SIPIb r2 were in 0.67-0.78 range. Correlations were also computed for LAI with all possible ratio indices as well as normalized indices using 3 nm bandwidths dat a sets in 368 to 950 nm region. The correlation coefficients of LAI, for wheat, with ratios of 729-950 nm spectral region to 564-693 nm spectral region were in 0.95-0.99 range for growth phase (of LAI) and in 0.96-0.968 range during declining phase (of LAI) while for chickpea the correlations were in 0.86-0.90 range for growth phase (of LAI) and 0.91-0.96 range during declining phase (of LAI) for the ratios of 711-798 nm spectral region to 673 - 685 nm (growth phase)/693-708 nm

  2. Interet de l'indice de vegetation des satellites NOAA-AVHRR pour le suivi des cultures (resultats d'une etude dans la Basse Vallee du Rhone)

    OpenAIRE

    Lagouarde, Jean-Pierre; SEGUIN, Bernard; Clinet, S.; Gandia, S.; Kerr, Y.

    1986-01-01

    Par rapport aux satellites d’observation de la Terre (Landsat, SPOT) à forte résolution spatiale, mais faible répétitivité temporelle, les satellites météorologiques NOAA-AVHRR ont l’avantage de permettre, grâce à 4 passages par jour, un suivi des cultures au cours de la saison de végétation. L’inconvénient majeur est la résolution spatiale limitée à 1 km2. Une étude a été effectuée sur les années 1983 et 1984 pour évaluer l’intérêt des indices de végétation dérivés des données NOAA, para...

  3. Using satellite vegetation and compound topographic indices to map highly erodible cropland buffers for cellulosic biofuel crop developments in eastern Nebraska, USA

    Science.gov (United States)

    Gu, Yingxin; Wylie, Bruce K.

    2015-01-01

    Cultivating annual row crops in high topographic relief waterway buffers has negative environmental effects and can be environmentally unsustainable. Growing perennial grasses such as switchgrass (Panicum virgatum L.) for biomass (e.g., cellulosic biofuel feedstocks) instead of annual row crops in these high relief waterway buffers can improve local environmental conditions (e.g., reduce soil erosion and improve water quality through lower use of fertilizers and pesticides) and ecosystem services (e.g., minimize drought and flood impacts on production; improve wildlife habitat, plant vigor, and nitrogen retention due to post-senescence harvest for cellulosic biofuels; and serve as carbon sinks). The main objectives of this study are to: (1) identify cropland areas with high topographic relief (high runoff potentials) and high switchgrass productivity potential in eastern Nebraska that may be suitable for growing switchgrass, and (2) estimate the total switchgrass production gain from the potential biofuel areas. Results indicate that about 140,000 hectares of waterway buffers in eastern Nebraska are suitable for switchgrass development and the total annual estimated switchgrass biomass production for these suitable areas is approximately 1.2 million metric tons. The resulting map delineates high topographic relief croplands and provides useful information to land managers and biofuel plant investors to make optimal land use decisions regarding biofuel crop development and ecosystem service optimization in eastern Nebraska.

  4. Dynamic metropolitan landscapes: Residential development and vegetation change in the U.S

    Science.gov (United States)

    Jantz, Patrick Arthur

    Residential development is now a major contributor to land surface change in the U.S. From 1990 - 2000, over thirteen million housing units were added to the nation's housing stock which stood at 102.3 million in 1990. Another 15.8 million housing units were added from 2000 - 2010. Of particular concern is the ongoing increase in low-density residential development because of its large resource footprint and biodiversity impacts. In this dissertation I pose three broad questions 1) What were the trends in residential development in the U.S. from 1990 - 2000? 2) What were the trends in rural conversion to low-density residential use from 1990 - 2000 in the Mid-Atlantic and the Pacific Northwest and what social and environmental factors help explain these trends? 3) What were the effects of rural conversion to residential use on vegetation productivity in the Mid-Atlantic and the Pacific Northwest from 2000 - 2010? To answer these questions I created a database derived from U.S. Census blocks that allows for interdecadal comparison of recent housing density change in support of spatial demographic research. In a series of GIS based analyses I used the database to map changes in metropolitan housing density distributions in the Mid-Atlantic and western Washington regions and used a satellite derived index of vegetation productivity to assess the impacts of housing growth on vegetation carbon uptake. Results indicate that residential housing growth is more dynamic than previously thought and established approaches for mapping housing density tend to underestimate the local intensity of residential change. In the Mid-Atlantic and western Washington, low-density residential development is affecting large fractions of rural landscapes in metropolitan areas. The strongest correlates of low-density conversion of rural landscapes were population growth and extent of protected lands, suggesting future directions for modeling the drivers of rural conversion. Residential

  5. Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010.

    Science.gov (United States)

    Yang, Yuting; Guan, Huade; Shen, Miaogen; Liang, Wei; Jiang, Lei

    2015-02-01

    Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models. © 2014 John Wiley & Sons Ltd.

  6. Kuchler Vegetation

    Data.gov (United States)

    California Department of Resources — Digital version of potential natural plant communites as compiled and published on 'Map of the Natural Vegetation of California' by A. W. Kuchler, 1976. Source map...

  7. Wieslander Vegetation

    Data.gov (United States)

    California Department of Resources — Digital version of the 1945 California Vegetation Type Maps by A. E. Wieslander of the U.S. Forest Service. Source scale of maps are 1:100,000. These compiled maps...

  8. Vegetation survey of Sengwa

    Directory of Open Access Journals (Sweden)

    G. C. Craig

    1983-12-01

    Full Text Available The approach and initial results of a vegetation survey of the Sengwa Wildlife Area are outlined. The objectives were to produce a vegetation classification and map sufficiently detailed to serve as a base for the management of the natural vegetation. The methods adopted consist of (a stratification of the area into homogeneous units using 1:10 000 colour aerial photographs; (b plotless random sampling of each stratum by recording cover abundance on the Braun-Blaunquet scale for all woody species; and (c analysis of the data by indicator species analysis using the computer programme 'Twinspan’. The classification produced is successful in achieving recognizable vegetation types which tie in well with known environmental features.

  9. Índices de vegetação de base espectral para discriminar doses de nitrogênio em capim-tanzânia Vegetation spectral indices to discriminate nitrogen rates in tanzania grass

    Directory of Open Access Journals (Sweden)

    Selma Alves Abrahão

    2009-09-01

    Full Text Available Este trabalho foi realizado para determinar, entre seis índices de vegetação baseados em dados de refletância espectral, aquele que melhor discrimina doses de nitrogênio e que possui maior correlação com leituras de clorofila e massa seca do capim-tanzânia (Panicum maximum Jacq.. Os índices testados foram o NDVI (índice de vegetação por diferença normalizada, calculado utilizando a banda do vermelho e a banda do infravermelho próximo, VARI (índice resistente à atmosfera na região do visível, calculado utilizando a banda de transição do vermelho ao infravermelho e a banda do verde e WDRVI (índice de vegetação de amplo alcance, calculado utilizando três coeficientes de ponderação, 0,05; 0,1 e 0,2. Foram avaliadas quatro doses de nitrogênio (0, 80, 160 e 320 kg/ha em delineamento de blocos ao acaso com subamostras, com três repetições e três subamostras por bloco. Os índices VARI utilizando a banda de transição do vermelho ao infravermelho e o WDRVI utilizando os coeficientes 0,05 e 0,1 foram os melhores para discriminar as doses de nitrogênio aplicadas em todos os períodos de avaliação estudados. O índice que apresentou maior correlação com as leituras de clorofila e massa seca foi o VARI com banda de transição do vermelho ao infravermelho.The objective of this study was to determine, among five vegetation indices, calculated based on spectral reflectance data, the one that best discriminated nitrogen rates, and presented highest correlation with chlorophyll readings and tanzania grass (Panicum maximum Jacq. dry matter. The tested vegetation indices were NDVI (normalized difference vegetation index, VARI (visible atmospherically resistant index using red edge and green bands, WDRVI (wide dynamic range vegetation index using three weighted coefficients, 0.05, 0.1 and 0.2. Four nitrogen levels (0, 80, 160 and 320 kg/ha were evaluated in a randomized complete block design with three replications and three

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

    Science.gov (United States)

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

    2017-03-01

    Extreme drought, precipitation, and other extreme climatic events often have impacts on vegetation. Based on meteorological data from 52 stations in the Loess Plateau (LP) and a satellite-derived normalized difference vegetation index (NDVI) from the third-generation Global Inventory Modeling and Mapping Studies (GIMMS3g) dataset, this study investigated the relationship between vegetation change and climatic extremes from 1982 to 2013. Our results showed that the vegetation coverage increased significantly, with a linear rate of 0.025/10a (P < 0.001) from 1982 to 2013. As for the spatial distribution, NDVI revealed an increasing trend from the northwest to the southeast, with about 61.79% of the LP exhibiting a significant increasing trend (P < 0.05). Some temperature extreme indices, including TMAXmean, TMINmean, TN90p, TNx, TX90p, and TXx, increased significantly at rates of 0.77 mm/10a, 0.52 °C/10a, 0.62 °C/10a, 0.80 °C/10a, 5.16 days/10a, and 0.65 °C/10a, respectively. On the other hand, other extreme temperature indices including TX10p and TN10p decreased significantly at rates of -2.77 days/10a and 4.57 days/10a (P < 0.01), respectively. Correlation analysis showed that only TMINmean had a significant relationship with NDVI at the yearly time scale (P < 0.05). At the monthly time scale, vegetation coverage and different vegetation types responded significantly positively to precipitation and temperature extremes (TMAXmean, TMINmean, TNx, TNn, TXn, and TXx) (P < 0.01). All of the precipitation extremes and temperature extremes exhibited significant positive relationships with NDVI during the spring and autumn (P < 0.01). However, the relationship between NDVI and RX1day, TMAXmean, TXn, and TXx was insignificant in summer. Vegetation exhibited a significant negative relationship with precipitation extremes in winter (P < 0.05). In terms of human activity, our results indicate a strong correlation between the cumulative afforestation area and NDVI in Yan

  11. Subsidence hazard and risk assessments for Mexico City: An interdisciplinary analysis of satellite-derived subsidence map (PSInSAR) and census data.

    Science.gov (United States)

    Solano Rojas, D. E.; Cabral-Cano, E.; Wdowinski, S.; Hernaández Espriú, A.; Falorni, G.; Bohane, A.

    2014-12-01

    The Mexico City Metropolitan Area is the largest urban center in the American continent, with 20.4 millions of inhabitants, representing 17.8% of the total population of the country. Over the past several decades Mexico City has been experienced rapid subsidence, up to ~370 mm/yr, caused by groundwater extraction. The subsidence rate is inhomogeneous, as it controlled by the local geology. Unconsolidated sediments tend to compact and induce rapid subsidence, whereas subsurface volcanic rocks are less prone to subsidence. Intensive faulting in the city has been observed in areas of differential deformation; in these areas buildings and infrastructure are highly damaged. Quantification of subsidence-induce damage is needed for establishing the magnitude of the phenomenon. Our study uses three data sources: a satellite-derived subsidence map, census information of population distribution for 2010, and information on buildings and infrastructure. The subsidence map was calculated from 29 SAR scene acquired by the Envisat satellite during the years 2003-2010 using the Persistent Scatterers Interferometry (PSI) method with the SqueeSAR algorithm. The information of the census of population comes from the National Institute of Statistics and Geography (INEGI), which also provides the information about infrastructure. We intersected the information from the three maps using a geographic information system (GIS), which cover an area of 1, 640 km2. As subsidence-induced damage occurs mainly in areas of differential subsidence, we based the GIS analysis on the subsidence gradients, rather than subsidence rates. In order to evaluate subsidence-induced faulting risk, we generated a risk matrix that worked as the main parameter to create a risk map. We then reclassified the urban area into 5 zones according to the related risk, with R0 for the lowest risk and R4 for the highest. Our counting showed that 350 km2 of the city is located in an urban area of high to very high risk

  12. The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets

    Science.gov (United States)

    Buchwitz, Michael

    2013-04-01

    The GHG-CCI project is one of several projects of the European Space Agency's (ESA) Climate Change Initiative (CCI). The goal of the CCI is to generate and deliver data sets of various satellite-derived Essential Climate Variables (ECVs) in line with GCOS (Global Climate Observing System) requirements. The "ECV Greenhouse Gases" (ECV GHG) is the global distribution of important climate relevant gases - atmospheric CO2 and CH4 - with a quality sufficient to obtain information on regional CO2 and CH4 sources and sinks. Two satellite instruments deliver the main input data for GHG-CCI: SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT. The first order priority goal of GHG-CCI is the further development of retrieval algorithms for near-surface-sensitive column-averaged dry air mole fractions of CO2 and CH4, denoted XCO2 and XCH4, to meet the demanding user requirements. GHG-CCI focusses on four core data products: XCO2 from SCIAMACHY and TANSO and XCH4 from the same two sensors. For each of the four core data products at least two candidate retrieval algorithms have been independently further developed and the corresponding data products have been quality assessed and inter-compared. This activity is referred to as "Round Robin" (RR) activity within the CCI. The main goal of the RR was to identify for each of the four core products which algorithm to be used to generate the Climate Research Data Package (CRDP), which will essentially be the first version of the ECV GHG. This manuscript gives an overview about the GHG-CCI RR and related activities. This comprises the establishment of the user requirements, the improvement of the candidate retrieval algorithms and comparisons with ground-based observations and models. The manuscript summarizes the final RR algorithm selection decision and its justification. Comparison with ground-based Total Carbon Column Observing Network (TCCON) data indicates that the "breakthrough" single measurement precision requirement has been met for

  13. VEGETATION MAPPING IN WETLANDS

    Directory of Open Access Journals (Sweden)

    F. PEDROTTI

    2004-01-01

    Full Text Available The current work examines the main aspects of wetland vegetation mapping, which can be summarized as analysis of the ecological-vegetational (ecotone gradients; vegetation complexes; relationships between vegetation distribution and geomorphology; vegetation of the hydrographic basin lo which the wetland in question belongs; vegetation monitoring with help of four vegetation maps: phytosociological map of the real and potential vegetation, map of vegetation dynamical tendencies, map of vegetation series.

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

    OpenAIRE

    Ricardo JPS Guimarães; Corina C Freitas; Dutra,Luciano V; Ronaldo GC Scholte; Ronaldo S Amaral; Drummond,Sandra C; Shimabukuro,Yosio E; Oliveira, Guilherme C.; Omar S Carvalho

    2010-01-01

    This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship ...

  15. General Vegetation

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This file contains vector digital data for vegetation groupings in New Mexico at a 1:1,000,000 scale. The source software was ARC/INFO 5.0.1 and the conversion...

  16. Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

    Science.gov (United States)

    Thenkabail, Prasad S.; Mariotto, Isabella; Gumma, Murali Krishna; Middleton, Elizabeth M.; Landis, David R.; Huemmrich, K. Fred

    2013-01-01

    The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e

  17. Espacialização da umidade do solo por meio da temperatura da superfície e índice de vegetação Spatial distribution of soil moisture using land surface temperature and vegetation indices

    Directory of Open Access Journals (Sweden)

    Helio L. Lopes

    2011-09-01

    Full Text Available O estudo da umidade do solo é fundamental não só para a determinação da resiliência de ecossistemas e sua recuperação, mas também na modelagem da relação água-vegetação-atmosfera. Na aquisição dessas informações o sensoriamento remoto perfaz uma ferramenta importante e de potencial adequado para monitoramento e mapeamento. Visando à espacialização de índices relacionados à umidade, vários métodos têm sido propostos, embora sua aplicação ainda seja limitada. Neste trabalho se aplicou o modelo de índice de umidade do solo (IUS cujos objetivos foram: espacializar o IUS, estabelecer graus de desertificação, delimitar a área em processo de desertificação e verificar possíveis relações do IUS com parâmetros de água no solo. Na aplicação deste modelo se utilizaram, como dados de entrada, o NDVI (índice de vegetação da diferença normalizada e a LST (temperatura da superfície e se observou que o IUS representado pela média dos valores desses índices pode ser empregado na determinação do grau de degradação da superfície e para gerar classificação legendada, discriminando vários níveis de degradação ambiental. Constatou-se também que não houve relação direta do IUS com parâmetros físicos de retenção de umidade do solo. Desta forma, o sensoriamento remoto mostrou ser uma ferramenta significativa na avaliação de índices de umidade do solo em áreas degradadas tal como para delinear a dinâmica de borda em núcleo de desertificação.The study of soil moisture is important in determining the resilience of ecosystems and their recovery, as well as in the modeling of water-vegetation-atmosphere relationship. Remote sensing is an important tool for the acquisition, mapping and monitoring soil moisture through the surface temperature and vegetation indices. For the soil moisture content assessment, several methods have been proposed, however its application is still limited. In this work the

  18. Capturing Vegetation Diversity in the Ent Terrestrial Biosphere Model

    Science.gov (United States)

    Kiang, N. Y.; Haralick, R. M.; Cook, B.; Aleinov, I. D.

    2013-12-01

    We present preliminary results from data mining to develop parameter sets and global vegetation structure datasets to set boundary conditions for the Ent Terrestrial Biosphere Model (Ent TBM) for improved representation of diversity and to propagate uncertainty in simulations of land carbon dynamics in the 20th century and under future climate change. The Ent TBM is the only dynamic global vegetation model (DGVM) developed for coupling with general circulation models (GCMs) to account for the height structure of mixed canopies, including a canopy radiative transfer scheme that accounts for foliage clumping in dynamically changing canopies. It is flexibly programmed to incorporate any number of "plant functional types" (PFTs). It is now a coupled component of the ModelE2 version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM). We demonstrate a data mining method, linear manifold clustering, to be used with several very recently compiled large databases of plant traits and phenology combined with climate and satellite data, to identify new PFT groupings, and also conduct customized parameter fits of PFT traits already defined in Ent. These parameter sets are used together with satellite-derived global forest height structure and land cover derived from a combination of satellite and inventory sources and bioclimatic relations to provide a new estimate and uncertainty bounds on vegetation biomass carbon stocks. These parameter sets will also be used to reproduce atmospheric CO2 time series over the flask observational period, to evaluate the impact of improved representation of vegetation dynamics on soil carbon stocks, and finally to produce a projection of the land carbon sink under future climate change. This research is timely in taking advantage of new, globally ranging vegetation databases, satellite-derived forest heights, and the advanced framework of the Ent TBM. It will advance understanding of and reduce uncertainty in

  19. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status

    DEFF Research Database (Denmark)

    Sandholt, Inge; Rasmussen, Kjeld; Andersen, Jens Asger

    2002-01-01

    A simplified land surface dryness index (Temperature-Vegetation Dryness Index, TVDI) based on an empirical parameterisation of the relationship between surface temperature (T-s) and vegetation index (NDVI) is suggested. The index is related to soil moisture and, in comparison to existing interpre......A simplified land surface dryness index (Temperature-Vegetation Dryness Index, TVDI) based on an empirical parameterisation of the relationship between surface temperature (T-s) and vegetation index (NDVI) is suggested. The index is related to soil moisture and, in comparison to existing...... interpretations of the T-s/NDVI space, the index is conceptually and computationally straightforward. It is based on satellite derived information only, and the potential for operational application of the index is therefore large. The spatial pattern and temporal evolution in TVDI has been analysed using 37 NOAA...

  20. Land surface phenology from SPOT VEGETATION time series

    Directory of Open Access Journals (Sweden)

    A. Verger

    2016-12-01

    Full Text Available Land surface phenology from time series of satellite data are expected to contribute to improve the representation of vegetation phenology in earth system models. We characterized the baseline phenology of the vegetation at the global scale from GEOCLIM-LAI, a global climatology of leaf area index (LAI derived from 1-km SPOT VEGETATION time series for 1999-2010. The calibration with ground measurements showed that the start and end of season were best identified using respectively 30% and 40% threshold of LAI amplitude values. The satellite-derived phenology was spatially consistent with the global distributions of climatic drivers and biome land cover. The accuracy of the derived phenological metrics, evaluated using available ground observations for birch forests in Europe, cherry in Asia and lilac shrubs in North America showed an overall root mean square error lower than 19 days for the start, end and length of season, and good agreement between the latitudinal gradients of VEGETATION LAI phenology and ground data.

  1. Vegetation Map and Vegetation Monographs of China

    Institute of Scientific and Technical Information of China (English)

    GUO Ke

    2010-01-01

    @@ Vegetation Map of China As the most significant component of an ecosystem,vegetation plays the most important role in maintaining biodiversity and providing the necessary resources for human beings.A vegetation map shows the major vegetation types of a region and their geographic distribution patterns.

  2. Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data

    Science.gov (United States)

    Thenkabail, P.S.; Mariotto, I.; Gumma, M.K.; Middleton, E.M.; Landis, D.R.; Huemmrich, K.F.

    2013-01-01

    The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy ~70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using ~20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was ~ 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or “the curse of high dimensionality”) in hyperspectral data for a particular application (e.g., biophysi- al

  3. Simple method for estimating soil mass loading onto plant surface using magnetic material content as a soil indicator - Influence of soil adhesion to vegetation on radioactive cesium concentration in forage.

    Science.gov (United States)

    Sunaga, Yoshihito; Harada, Hisatomi

    2016-11-01

    A simple technique for estimating soil mass loading on vegetation was developed using magnetic material content as an indicator of soil adhesion. Magnetic material contents in plant and soil samples were determined by a magnetic analyzer. High recovery rates of 85-97% were achieved in a recovery test in which additional soil was added to powdered plant materials [stem of forage corn (Zea mays L.), aboveground part of Italian ryegrass (Lolium multiflorum Lam.)] at addition rates of 12.3-200 g dry soil kg(-1) dry plant material including soil. Samples of different Japanese cultivated soils were tested and showed a range of magnetic contents of 1.27-16.1 g kg(-1) on a dry weight basis. These levels are considered adequate for determining soil contamination in plant materials. Then, we applied this method for confirming the effect of soil adhesion on radioactive cesium concentrations in plant samples obtained at the area affected by the 2011 nuclear accident in Japan. The mean soil mass loading (±standard deviation) on forage rye (Secale cereale L.) showing mild lodging was 0.8 ± 0.6 g kg(-1), but was 7.4 ± 5.0 g kg(-1) for plants with serious lodging. No soil loading was detected on rye plants that showed no lodging. Radioactive cesium concentrations in the rye samples increased linearly with the increase in soil mass loading caused by plant lodging, and consequently mean radioactive cesium concentration for rye plants with serious lodging was about 2.7 times higher than that with no lodging. Cesium radioactivity in forage was affected by variations in soil mass loading onto forage plants caused by changes in plant growth and differences between plant species. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Effects of Leaf Hair on Leaf Reflectance and Hyperspectral Vegetation Indices%叶片茸毛对叶片反射光谱及高光谱植被指数的影响研究

    Institute of Scientific and Technical Information of China (English)

    葛昊; 卢珊; 赵云升

    2012-01-01

    Many hyperspectral vegetation indices have been used to estimate the biochemical contents such as pigment content, nondestructively. These reflectance indices are influenced by leaf hair, and the existence of the leaf hair affects the performance of the indices on the estimation of the biochemical contents. The present research studied the possible effects of the leaf hair on the reflectance of the same leaf before and after removal of leaf hair. The authors found that dehairing had decreased the reflectance between wavelength 400 and 1 000 nm, and the decrease depends on the wavelength. The changes of 39 hyperspectral indices before and after the hair removal were compared. The results revealed that some indices that only use visible wavebands or the near infrared wavebands such as CTR1: R695/R420, D740/D720, WBI: R900/R970, R860/(R550×R708) and REP (Red-edge position) were not affected much by the dehairing process and are thought relatively robust to estimate the biochemical contents.%很多高光谱植被指数被用于对植被的生化物质含量进行非破坏性的估计与反演.由于这些指数都是利用不同波段的反射率计算而得到的,因而对叶片反射具有很大影响的茸毛等叶表结构对这些植被指数的反演精度的影响不容忽视.本研究发现去茸毛处理使得在400~1 000 nm范围的的光谱反射都有所下降,但在各个波段的变化并不均匀.通过对比39个现有的高光谱植被指数在经过去茸毛处理前后的变化,发现一些只单独利用可见光或者近红外波段的高光谱植被指数,如CTR1:R695/R420,D740/D720,WBI:R900/R970,R860/(R550×R708)以及红边指数(REP)比大多数既使用可见光又使用近红外波段的高光谱植被指数受茸毛变化影响小,它们对茸毛的低敏感性可以使其在进行植被生化物质反演时更具有普适性.

  5. Satellite-derived primary productivity and its spatial and temporal variability in the China seas%中国近海初级生产力的遥感研究及其时空演化

    Institute of Scientific and Technical Information of China (English)

    檀赛春; 石广玉

    2006-01-01

    The spatial and temporal variability of primary productivity in the China seas from 2003 to 2005 was estimated using a size-fractionated primary productivity model. Primary productivity estimated from satellite-derived data showed spatial and temporal variability. Annual averaged primary productivity levels were 564.39, 363.08, 536.47, 413.88, 195.77, and 100.09 gCm-2a-1 in the Bohai Sea, northern Yellow Sea (YS), southern YS, northern East China Sea (ECS), southern ECS, and South China Sea (SCS), respectively. Peaks of primary productivity appeared in spring (April-June) and fall (October and November) in the northern YS, southern YS, and southern ECS, while a single peak (June) appeared in the Bohai Sea and northern ECS. The SCS had two peaks in primary productivity, but these peaks occurred in winter (January) and summer (August), with the winter peak far higher than the summer peak. Monthly averaged primary productivity values from 2003 to 2005 in the Bohai Sea and southern YS were higher than those in the other four seas during most months, while those in the southern ECS and SCS were the lowest. Primary productivity in spring (March-June in the southern ECS and April-July in the other five areas) contributed approximately 41% on average to the annual primary productivity in all the study seas except the SCS. The largest interannual variability also occurred in spring (average standard deviation = 6.68), according to the satellite-derived estimates. The contribution during fall (October-January in the southern ECS and August-November in the other five areas) was approximately 33% on average; the primary productivity during this period also showed interannual variability. However, in the SCS, the winter (December-March) contribution was the highest (about 42%), while the spring (April-July) contribution was the lowest (28%). The SCS did share a feature with the other five areas: the larger the contribution, the larger the interannual variability. Spatial and

  6. Generic index of aquatic vegetation (IVAM) for a rapid assessment of ecological quality of Spanish rivers: taxonomic resolution and application to Castilla-La Mancha region; Indice Generico de Vegetacion Acuatica (IVAM): Propuesta de evaluacion rapida del estado ecologico de los rios ibericos en aplicacion de la Directiva Marco del Agua

    Energy Technology Data Exchange (ETDEWEB)

    Moreno, J. L.; Navarro, C.; Hera, J. de las

    2005-07-01

    The Water Framework Directive proposes the use of aquatic flora as a valid bio indicator for assessing the ecological status of European rivers. Due to the lack of an aquatic vegetation index for Spanish rivers, we present an index to assess trophic status or eutrophication in rivers and streams. Thus, we calculated tolerance scores and indicator values for tax from nutrient levels. the index is called IVAM (Macroscopic Aquatic Vegetation Index). The index takes into account either macrophyte or microphytes (the latter making up macroscopic growth forms) including briophytes. The IVAM showed the best correlation with nutrients besides other quality indices, indicating a solid tool to assess trophic status or eutrophication. (Author) 15 refs.

  7. Edible Acid-Base Indicators.

    Science.gov (United States)

    Mebane, Robert C.; Rybolt, Thomas R.

    1985-01-01

    Reports on the colors observed during titrations of 15 natural indicators obtained from common fruits and vegetables. These edible indicators can be used for a variety of teacher demonstrations or for simple student experiments. (JN)

  8. Satellite-derived NDVI, LST, and climatic factors driving the distribution and abundance of Anopheles mosquitoes in a former malarious area in northwest Argentina.

    Science.gov (United States)

    Dantur Juri, María Julia; Estallo, Elizabet; Almirón, Walter; Santana, Mirta; Sartor, Paolo; Lamfri, Mario; Zaidenberg, Mario

    2015-06-01

    Distribution and abundance of disease vectors are directly related to climatic conditions and environmental changes. Remote sensing data have been used for monitoring environmental conditions influencing spatial patterns of vector-borne diseases. The aim of this study was to analyze the effect of the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic factors (temperature, humidity, wind velocity, and accumulated rainfall) on the distribution and abundance of Anopheles species in northwestern Argentina using Poisson regression analyses. Samples were collected from December, 2001 to December, 2005 at three localities, Aguas Blancas, El Oculto and San Ramón de la Nueva Orán. We collected 11,206 adult Anopheles species, with the major abundance observed at El Oculto (59.11%), followed by Aguas Blancas (22.10%) and San Ramón de la Nueva Orán (18.79%). Anopheles pseudopunctipennis was the most abundant species at El Oculto, Anopheles argyritarsis predominated in Aguas Blancas, and Anopheles strodei in San Ramón de la Nueva Orán. Samples were collected throughout the sampling period, with the highest peaks during the spring seasons. LST and mean temperature appear to be the most important variables determining the distribution patterns and major abundance of An. pseudopunctipennis and An. argyritarsis within malarious areas. © 2015 The Society for Vector Ecology.

  9. Satellite-Based Assessment of the spatial extent of Aquatic Vegetation in Lake Victoria

    Science.gov (United States)

    Clark, W.; Aligeti, N.; Jeyaprakash, T.; Martins, M.; Stodghill, J.; Winstanley, H.

    2011-12-01

    Lake Victoria in Africa is the second largest freshwater lake in the world and is known for its abundance of aquatic wildlife. In particular over 200 different fish species are caught and sold by local fisherman. The lake is a major contributor to the local economy as a corridor of transportation, source of drinking water, and source of hydropower. However, the invasion of aquatic vegetation such as water hyacinth in the lake has disrupted each of these markets. Aquatic vegetation now covers a substantial area of the coastline blocking waterways, disrupting hydropower, hindering the collection of drinking water and decreasing the profitability of fishing. The vegetation serves as a habitat for disease carrying mosquitoes as well as snakes and snails that spread the parasitic disease bilharzia. The current control measures of invasive aquatic vegetation rely on biological, chemical and mechanical control. The objective of this study was to utilize remote sensing to map aquatic vegetation within Lake Victoria from 2000 to 2011. MODIS, Landsat 4-5TM, and Landsat 7-ETM imagery was employed to perform change detections in vegetation and identify the extent of aquatic vegetation throughout the years. The efficiency of containment efforts were evaluated and ideal time for application of such efforts were suggested. A methodology for aquatic vegetation surveillance was created. The results of this project were presented as a workshop to the Lake Victoria Fisheries Organization, SERVIR, and other partner organizations. The workshop provided instruction into the use of NASA and other satellite derived products. Time series animations of the spatial extent of aquatic vegetation within the lake were created. By identifying seasons of decreased aquatic vegetation, ideal times to employ control efforts were identified. SERVIR will subsequently utilize the methodologies and mapping results of this study to develop operational aquatic vegetation surveillance for Lake Victoria.

  10. Regional adaptation of a dynamic global vegetation model using a remote sensing data derived land cover map of Russia

    Science.gov (United States)

    Khvostikov, S.; Venevsky, S.; Bartalev, S.

    2015-12-01

    The dynamic global vegetation model (DGVM) SEVER has been regionally adapted using a remote sensing data-derived land cover map in order to improve the reconstruction conformity of the distribution of vegetation functional types over Russia. The SEVER model was modified to address noticeable divergences between modelling results and the land cover map. The model modification included a light competition method elaboration and the introduction of a tundra class into the model. The rigorous optimisation of key model parameters was performed using a two-step procedure. First, an approximate global optimum was found using the efficient global optimisation (EGO) algorithm, and afterwards a local search in the vicinity of the approximate optimum was performed using the quasi-Newton algorithm BFGS. The regionally adapted model shows a significant improvement of the vegetation distribution reconstruction over Russia with better matching with the satellite-derived land cover map, which was confirmed by both a visual comparison and a formal conformity criterion.

  11. Investigation of North American Vegetation Variability under Recent Climate: A Study Using the SSiB4/TRIFFID Biophysical/Dynamic Vegetation Model

    Science.gov (United States)

    Zhang, Zhengqiu; Xue, Yongkang; MacDonald, Glen; Cox, Peter M.; Collatz, George J.

    2015-01-01

    s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S. on vegetation are also evident from decreases in the simulated and satellite-derived LAIs. Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental-scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with differentmodels and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.

  12. Investigation of North American vegetation variability under recent climate: A study using the SSiB4/TRIFFID biophysical/dynamic vegetation model

    Science.gov (United States)

    Zhang, Zhengqiu; Xue, Yongkang; MacDonald, Glen; Cox, Peter M.; Collatz, G. James

    2015-02-01

    s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S. on vegetation are also evident from decreases in the simulated and satellite-derived LAIs. Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental-scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with different models and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.

  13. Audubon vegetation monitoring

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This document is the summary and the analysis of vegetative data for the Audubon Refuge from NPWRC. The data included measurements of vegetation density, vegetation...

  14. Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

    Science.gov (United States)

    Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

    2009-01-01

    In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

  15. Study of Modis satellite derived aerosol angstrom exponent and in-situ measured values using Sun photometer in part of the west coast of Indian Peninsula

    Digital Repository Service at National Institute of Oceanography (India)

    SunilKumar R.K.; Suresh, T.; Govindaraju; SureshKumar, B.V.

    The aerosol angstrom exponent (AAE) is often used as a qualitative indicator of aerosol particle size. It is important to understand and quantify the microphysical impact of aerosols which are derived from natural and anthropogenic activities...

  16. Lake Bathymetric Aquatic Vegetation

    Data.gov (United States)

    Minnesota Department of Natural Resources — Aquatic vegetation represented as polygon features, coded with vegetation type (emergent, submergent, etc.) and field survey date. Polygons were digitized from...

  17. 基于冠层光谱植被指数的冬小麦作物系数估算%Estimating crop coefficients of winter wheat based on canopy spectral vegetation indices

    Institute of Scientific and Technical Information of China (English)

    李贺丽; 罗毅; 赵春江; 杨贵军

    2013-01-01

    At present, many studies have been carried out on crop coefficients and its variation over years under local climate conditions, but little attention has been given to its estimation method for a regional scale, which plays a key role in the regional application of the FAO 56 crop coefficient approach in crop evapotranspiration and transpiration estimation. In this work, experiments including five nitrogen (N) treatments were conducted in the 2008-2009 and 2009-2010 seasons to investigate the relationships between the crop coefficient (Kc), basal crop coefficient (Kcb) and eight common canopy vegetation indices (VIs) of winter wheat, as well as the effects of N and water stress on them. In addition, the feasibility and the performances of VIs on Kc and Kcb estimation of winter wheat were analyzed. Results demonstrated that high levels of N were associated with high Kcb and low Ke, and vice versa, which resulted in no obvious regular differences in Kc among different N treatments. Crop Kc was weakly correlated with VIs (the coefficient of determination R2 = 0.094 ~ 0.150, p < 0.01, n=195) due to the variations in soil evaporation and soil background, while Kcb had strong correlations with VIs (R2=0.511~0.685, p < 0.01, n=195). In addition, the water stress before resulting in an obvious sign on crop canopy spectral characteristics can introduce considerable scatter in the relations between Kcb and VIs, while N stress had no effects on them. Validation results showed that VIs performed well in crop Kcb estimation, and the enhanced vegetation index (EVI) gave the best accuracy (R2=0.765~0.864, n=150). The proposed method would be more favorable for regional application, since VIs can be easily collected by means of remote sensing. However, it should be pointed out that the method may have some limitations under the conditions with water stress but is not severe according to the above analysis, and as in this case, additional water stress information collected from

  18. Seasonal divergence in the sensitivity of evapotranspiration to climate and vegetation growth in the Yellow River Basin, China

    Science.gov (United States)

    Pei, Tingting; Wu, Xiuchen; Li, Xiaoyan; Zhang, Yu; Shi, Fangzhong; Ma, Yujun; Wang, Pei; Zhang, Cicheng

    2017-01-01

    Seasonal variations in terrestrial evapotranspiration (ET) in the Yellow River Basin (YRB) have crucial impacts on the seasonal trajectories of the regional water cycle, vegetation growth, and local climate feedback. However, the possibly divergent roles of climate and vegetation growth variations in controlling seasonal ET patterns remain poorly quantified. This study therefore quantifies the interannual sensitivity and attribution of ET to climate and vegetation growth variations in different seasons and different biomes in the YRB in China between 1982 and 2011, using the satellite-derived normalized difference vegetation index (NDVI), FLUXNET-based upscaled ET, and concurrent climate data. The results reveal a clear seasonal divergence in the interannual sensitivity of ET to climate and vegetation growth variations in the YRB. Interannual precipitation and NDVI variations play a dominant role in controlling seasonal ET variations in the YRB, with temperature having a marginal effect. Interannual ET sensitivity to precipitation weakens with an increasing mean annual precipitation gradient in almost all seasons, especially in summer and autumn. More importantly, a seasonally varying role of vegetation growth in mediating seasonal ET was discovered, and a crucial role of late-growing-season vegetation growth in controlling the seasonal trajectory of regional ET was explicitly identified. These results suggest that ongoing intensive vegetation restoration has crucial impacts on seasonal water-cycle patterns and consequent terrestrial-atmospheric biogeochemical feedback in the YRB.

  19. Research in remote sensing of vegetation

    Science.gov (United States)

    Schrumpf, Barry J.; Ripple, William J.; Isaacson, Dennis L.

    1988-01-01

    The research topics undertaken were primarily selected to further the understanding of fundamental relationships between electromagnetic energy measured from Earth orbiting satellites and terrestrial features, principally vegetation. Vegetation is an essential component in the soil formation process and the major factor in protecting and holding soil in place. Vegetation plays key roles in hydrological and nutrient cycles. Awareness of improvement or deterioration in the capacity of vegetation and the trends that those changes may indicate are, therefore, critical detections to make. A study of the relationships requires consideration of the various portions of the electromagnetic spectrum; characteristics of detector system; synergism that may be achieved by merging data from two or more detector systems or multiple dates of data; and vegetational characteristics. The vegetation of Oregon is sufficiently diverse as to provide ample opportunity to investigate the relationships suggested above several vegetation types.

  20. Real-Time Estimation of Satellite-Derived PM2.5 Based on a Semi-Physical Geographically Weighted Regression Model

    Science.gov (United States)

    Zhang, Tianhao; Liu, Gang; Zhu, Zhongmin; Gong, Wei; Ji, Yuxi; Huang, Yusi

    2016-01-01

    The real-time estimation of ambient particulate matter with diameter no greater than 2.5 μm (PM2.5) is currently quite limited in China. A semi-physical geographically weighted regression (GWR) model was adopted to estimate PM2.5 mass concentrations at national scale using the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth product fused by the Dark Target (DT) and Deep Blue (DB) algorithms, combined with meteorological parameters. The fitting results could explain over 80% of the variability in the corresponding PM2.5 mass concentrations, and the estimation tends to overestimate when measurement is low and tends to underestimate when measurement is high. Based on World Health Organization standards, results indicate that most regions in China suffered severe PM2.5 pollution during winter. Seasonal average mass concentrations of PM2.5 predicted by the model indicate that residential regions, namely Jing-Jin-Ji Region and Central China, were faced with challenge from fine particles. Moreover, estimation deviation caused primarily by the spatially uneven distribution of monitoring sites and the changes of elevation in a relatively small region has been discussed. In summary, real-time PM2.5 was estimated effectively by the satellite-based semi-physical GWR model, and the results could provide reasonable references for assessing health impacts and offer guidance on air quality management in China. PMID:27706054

  1. Appraisal of Hygiene Indicators and Farming Practices in the Production of Leafy Vegetables by Organic Small-Scale Farmers in uMbumbulu (Rural KwaZulu-Natal, South Africa

    Directory of Open Access Journals (Sweden)

    Stefan Schmidt

    2013-09-01

    Full Text Available During October, November and December 2011 (when highest sales of Agri-Hub fresh produce are observed, irrigation water, compost, lettuce and spinach sampled from four different farmer cooperatives supplying the local Agri-Hub in uMbumbulu (KwaZulu-Natal, South Africa were analyzed monthly for the presence of total and fecal coliforms and Escherichia coli using the most probable number (MPN technique. The pH values for all irrigation water samples analyzed were within the acceptable range of 6.5–8.5 for agricultural use. Fecal coliform levels were <1,000 MPN per 100 mL irrigation water and <1,000 MPN per g of compost. The vegetables produced by Agri-Hub small-scale farmers met the requirements for total coliforms of <200/g set by the South African Department of Health at the time of sampling. E. coli MPN values for irrigation water and vegetables were below the limit of detection. In addition, the farming practices of 73 farmers were assessed via a survey. The results revealed that more than 40% of farmers used microbiologically safe tap water for irrigation and that trained farmers have a significantly better understanding of the importance of production hygiene than untrained farmers. These results reiterate the importance of interventions that build capacity in the area of food safety and hygiene of small-scale farmers for market access of formal value chains.

  2. Model-data integration to improve the LPJmL dynamic global vegetation model

    Science.gov (United States)

    Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

    2017-04-01

    Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the

  3. Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

    Science.gov (United States)

    Liu, Yibo; Xiao, Jingfeng; Ju, Weimin; Xu, Ke; Zhou, Yanlian; Zhao, Yuntai

    2016-09-01

    There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of increasing vegetation greenness particularly afforestation on the hydrological cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China’s land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation ‘greening’ and ‘browning’ on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield, while vegetation browning reduced ET and increased water yield. At the large river basin and national scales, the greening trends also had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the changes in vegetation greenness on the hydrological cycle varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrological cycle are needed to account for the feedbacks to the climate.

  4. Vegetation changes in recent large-scale ecological restoration projects and subsequent impact on water resources in China's Loess Plateau.

    Science.gov (United States)

    Li, Shuai; Liang, Wei; Fu, Bojie; Lü, Yihe; Fu, Shuyi; Wang, Shuai; Su, Huimin

    2016-11-01

    Recently, relationship between vegetation activity and temperature variability has received much attention in China. However, vegetation-induced changes in water resources through changing land surface energy balance (e.g. albedo), has not been well documented. This study investigates the underlying causes of vegetation change and subsequent impacts on runoff for the Northern Shaanxi Loess Plateau. Results show that satellite-derived vegetation index has experienced a significantly increasing trend during the past three decades, especially during 2000-2012. Large-scale ecological restorations, i.e., the Natural Forest Conservation project and the Grain for Green project, are found to be the primary driving factors for vegetation increase. The increased vegetation coverage induces decrease in surface albedo and results in an increase in temperature. This positive effect can be counteracted by higher evapotranspiration and the net effect is a decrease in daytime land surface temperature. A higher evapotranspiration rate from restored vegetation is the primary reason for the reduced runoff coefficient. Other factors including less heavy precipitation, increased water consumption from town, industry and agriculture also appear to be the important causes for the reduction of runoff. These two ecological restoration projects produce both positive and negative effects on the overall ecosystem services. Thus, long-term continuous monitoring is needed. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    Science.gov (United States)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  6. Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale

    Directory of Open Access Journals (Sweden)

    Christiane Schmullius

    2013-05-01

    Full Text Available Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS, Advanced Very High Resolution Radiometer (AVHRR and (Advanced Along Track Scanning Radiometer ((AATSR are providing long-term time series information. Assessing the quality of remote sensing-based temperature measurements provides feedback to the climate modeling community and other users by identifying agreements and discrepancies when compared to temperature records from meteorological stations. This paper presents a comparison of state-of-the-art remote sensing-based land surface temperature data with air temperature measurements from meteorological stations on a pan-arctic scale (north of 60° latitude. Within this study, we compared land surface temperature products from (AATSR, MODIS and AVHRR with an in situ air temperature (Tair database provided by the National Climate Data Center (NCDC. Despite analyzing the whole acquisition time period of each land surface temperature product, we focused on the inter-annual variability comparing land surface temperature (LST and air temperature for the overlapping time period of the remote sensing data (2000–2005. In addition, land cover information was included in the evaluation approach by using GLC2000. MODIS has been identified as having the highest agreement in comparison to air temperature records. The time series of (AATSR is highly variable, whereas inconsistencies in land surface temperature data from AVHRR have been found.

  7. Circumpolar Arctic vegetation: a hierarchic review and roadmap toward an internationally consistent approach to survey, archive and classify tundra plot data

    Science.gov (United States)

    Walker, D. A.; Daniëls, F. J. A.; Alsos, I.; Bhatt, U. S.; Breen, A. L.; Buchhorn, M.; Bültmann, H.; Druckenmiller, L. A.; Edwards, M. E.; Ehrich, D.; Epstein, H. E.; Gould, W. A.; Ims, R. A.; Meltofte, H.; Raynolds, M. K.; Sibik, J.; Talbot, S. S.; Webber, P. J.

    2016-05-01

    Satellite-derived remote-sensing products are providing a modern circumpolar perspective of Arctic vegetation and its changes, but this new view is dependent on a long heritage of ground-based observations in the Arctic. Several products of the Conservation of Arctic Flora and Fauna are key to our current understanding. We review aspects of the PanArctic Flora, the Circumpolar Arctic Vegetation Map, the Arctic Biodiversity Assessment, and the Arctic Vegetation Archive (AVA) as they relate to efforts to describe and map the vegetation, plant biomass, and biodiversity of the Arctic at circumpolar, regional, landscape and plot scales. Cornerstones for all these tools are ground-based plant-species and plant-community surveys. The AVA is in progress and will store plot-based vegetation observations in a public-accessible database for vegetation classification, modeling, diversity studies, and other applications. We present the current status of the Alaska Arctic Vegetation Archive (AVA-AK), as a regional example for the panarctic archive, and with a roadmap for a coordinated international approach to survey, archive and classify Arctic vegetation. We note the need for more consistent standards of plot-based observations, and make several recommendations to improve the linkage between plot-based observations biodiversity studies and satellite-based observations of Arctic vegetation.

  8. Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

    Science.gov (United States)

    Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

    2010-01-01

    strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management

  9. Monitoring of vegetation dynamics and assessing vegetation response to drought in the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Haro, F. J.; Moreno, A.; Perez-Hoyos, A.; Gilabert, M. A.; Melia, J.; Belda, F.; Poquet, D.; Martinez, B.; Verger, A.

    2009-07-01

    Monitoring the vegetation activity over long time-scales is necessary to discern ecosystem response to climate variability. Spatial and temporally consistent estimates of the biophysical variables such as fractional vegetation cover (FVC) and leaf area index (LAI) have been obtained in the context of DULCINEA Project. We used long-term monthly climate statistics to build simple climatic indices (SPI, moisture index) at different time scales. From these indices, we estimated that the climatic disturbances affected both the growing season and the total amount of vegetation. This implies that the anomaly of vegetation cover is a good indicator of moisture condition and can be an important data source when used for detecting an monitoring drought in the Iberian Peninsula. The impact of climate variability on the vegetation dynamics has shown not to be the same for every region. We concluded that the relationships between vegetation anomaly and moisture availability are significant for the arid and semiarid areas. (Author) 6 refs.

  10. Análise da dinâmica sazonal e separabilidade espectral de algumas fitofisionomias do cerrado com índices de vegetação dos sensores MODIS/TERRA e AQUA Analysis of the seasonal dynamics and spectral separability of some savanna physiognomies with vegetation indices derived from MODIS/TERRA AND AQUA

    Directory of Open Access Journals (Sweden)

    Veraldo Liesenberg

    2007-04-01

    common set of pixels, were compared to each other. The results showed that: (a among the physiognomies under study, Dry Forest (Floresta Estacional decídua presented a marked seasonal dynamics as a result of the leaf fall from the rainy to the dry season (strong decrease in the indices and of the fast green up of vegetation with precipitation at the end of October (strong and rapid increase in NDVI and EVI values; (b NDVI showed greater variability between the vegetation classes than EVI only in the dry season; (c the discrimination between the physiognomies improved from the rainy to the dry season; (d the NDVI was more efficient than EVI to separate the vegetation classes in the dry season, but the contrary was observed in the rainy season; and (e for the majority of the dates under analysis, in spite of the variations in the quality of the pixels selected to compose the vegetation index MODIS product and in the Sun-view geometry, no statistically significant differences between the indices generated from both platforms were observed.

  11. Global change and climate-vegetation classification

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Three phrases of the quantitative study of climate-vegetation classification and their characteristics are presented based on the review of advance in climate-vegetation interaction, a key issue of "global change and terrestrial ecosystems (GCTE)" which is the core project of International Geosphere-Biosphere Programme (IGBP): (ⅰ) characterized by the correlation between natural vegetation types and climate; (ⅱ) characterized by climatic indices which have obviously been restricted to plant ecophysiology; (ⅲ) characterized by coupling both structure and function of vegetation. Thus, the prospective of climate-vegetation classification for global change study in China was proposed, especially the study coupling climate-vegetation classification models with atmospheric general circulation models (GCMs) was emphasized.

  12. Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

    Directory of Open Access Journals (Sweden)

    Xianfeng Liu

    2015-11-01

    Full Text Available In recent decades, the monitoring of vegetation dynamics has become crucial because of its important role in terrestrial ecosystems. In this study, a satellite-derived normalized difference vegetation index (NDVI was combined with climate factors to explore the spatiotemporal patterns of vegetation change during the growing season, as well as their driving forces in China from 2001 to 2012. Our results showed that the growing season NDVI increased continuously during 2001–2012, with a linear trend of 1.4%/10 years (p < 0.01. The NDVI in north China mainly exhibited an increasing spatial trend, but this trend was generally decreasing in south China. The vegetation dynamics were mainly at a moderate intensity level in both the increasing and decreasing areas. The significantly increasing trend in the NDVI for arid and semi-arid areas of northwest China was attributed mainly to an increasing trend in the NDVI during the spring, whereas that for the north and northeast of China was due to an increasing trend in the NDVI during the summer and autumn. Different vegetation types exhibited great variation in their trends, where the grass-forb community had the highest linear trend of 2%/10 years (p < 0.05, followed by meadow, and needle-leaf forest with the lowest increasing trend, i.e., a linear trend of 0.3%/10 years. Our results also suggested that the cumulative precipitation during the growing season had a dominant effect on the vegetation dynamics compared with temperature for all six vegetation types. In addition, the response of different vegetation types to climate variability exhibited considerable differences. In terms of anthropological activity, our statistical analyses showed that there was a strong correlation between the cumulative afforestation area and NDVI during the study period, especially in a pilot region for ecological restoration, thereby suggesting the important role of ecological restoration programs in ecological recovery

  13. The Weird Vegetable Price

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The Chinese Government faces the task of stabilizing vegetable prices to avoid steep increases and dips Fluctuations of vegetable prices in China have recently caused near panic in the domestic market.Purchase prices for farm produce are decreasing dramatically

  14. Procedures for Sampling Vegetation

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This report outlines vegetation sampling procedures used on various refuges in Region 3. The importance of sampling the response of marsh vegetation to management...

  15. Total Vegetation 2002

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — These are polygons that contain vegetated pixels in the May, 2002 imagery from aerial overflight of the Grand Canyon. Vegetation was mapped between stage elevations...

  16. 利用高光谱植被指数监测紧凑型玉米叶绿素荧光参数Fv/Fm%Monitoring the Chlorophyll Fluorescence Parameter Fv/Fm in Compact Corn Based on Different Hyperspectral Vegetation Indices

    Institute of Scientific and Technical Information of China (English)

    谭昌伟; 黄文江; 金秀良; 王君婵; 童璐; 王纪华; 郭文善

    2012-01-01

    为进一步评价遥感监测紧凑型玉米叶绿素荧光参数Fv/Fm的可行性,通过开展小区紧凑型玉米试验,分析紧凑型玉米整个生育期Fv/Fm与高光谱植被指数的相关关系,建立紧凑型玉米Fv/Fm高光谱监测模型.结果表明,紧凑型玉米Fv/Fm与选取的高光谱植被指数均呈极显著正相关,其中结构敏感色素指数(SIPI)与Fv/Fm的相关性最好,相关系数(r)为0.88.用SIPI建立紧凑型玉米Fv/Fm的监测模型,其决定系数(R2)为0.812 6,均方根误差(RMSE)为0.082.研究表明,利用高光谱植被指数可以有效地监测紧凑型玉米整个生育期的Fv/Fm.%In order to further assess the feasibility of monitoring the chlorophyll fluorescence parameter Fv/Fm in compact corn by hyperspectral remote sensing data, in the present study, hyperspectral vegetation indices from in-situ remote sensing measurements were utilized to monitor the chlorophyll fluorescence parameter Fv/Fm measured in the compact corn experiment. The relationships were analyzed between hyperspectral vegetation indices and Fv/Fm and the monitoring models were established for Fv/Fm in the whole growth stages of compact corn. The results indicated that Fv/Fm was significantly correlated to the hyperspectral vegetation indices. Among them, structure-sensitive pigment index (SIPI) was the most sensitive remote sensing variable for monitoring Fv/Fm with correlation coefficient (r) of 0. 88. The monitoring model of Fv/Fm was established on the base of SIPI, and the determination coefficients (r2) and the root mean square errors (RMSE) were 0. 812 6 and 0. 082 respectively. The overall results suggest that hyperspectral vegetation indices can be potential indicators to monitor Fv/Fm during growth stages of compact corn.

  17. Dutch Vegetation Database (LVD)

    NARCIS (Netherlands)

    Hennekens, S.M.

    2011-01-01

    The Dutch Vegetation Database (LVD) hosts information on all plant communities in the Netherlands. This substantial archive consists of over 600.000 recent and historic vegetation descriptions. The data provide information on more than 85 years of vegetation recording in various habitats covering te

  18. 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.

  19. Vegetation type classification and vegetation cover percentage estimation in urban green zone using pleiades imagery

    Science.gov (United States)

    Trisakti, Bambang

    2017-01-01

    Open green space in the urban area has aims to maintain the availability of land as a water catchment area, creating aspects of urban planning through a balance between the natural environment and the built environment that are useful for the public needs. Local governments have to make the green zone plan map and monitor the green space changes in their territory. Medium and high resolution satellite imageries have been widely utilized to map and monitor the changes of vegetation cover as an indicator of green space area. This paper describes the use of pleaides imagery to classify vegetation types and estimate vegetation cover percentage in the green zone. Vegetation cover was mapped using a combination of NDVI and blue band. Furthermore, vegetation types in the green space were classified using unsupervised and supervised (ISODATA and MLEN) methods. Vegetation types in the study area were divided into sparse vegetation, low-medium vegetation and medium-high vegetation. The classification accuracies were 97.9% and 98.9% for unsupervised and supervised method respectively. The vegetation cover percentage was determined by calculating the ratio between the vegetation type area and the green zone area. These information are useful to support green zone management activities.

  20. 水稻叶面积指数与MODIS植被指数、红边位置之间的相关分析%Analyses of the correlation between rice LAI and simulated MODIS vegetation indices, red edge position

    Institute of Scientific and Technical Information of China (English)

    程乾; 黄敬峰; 王人潮; 唐延林

    2003-01-01

    In the present study, analyses of the correlation between rice Leaf Area Index (LAI), hyperspectal data, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and the Red-Edge Position (REP) were studied. Hyperspectral data of hybrid rice and common rice in whole growing stage during 2002 was measured using the ASD FieldSpec UV/VNIR Spectroradiometer with resolution of 3 nm and at the same time the rice LAI was measured. The REP may be defined using the first derivative spectrum. The three bands of the Moderate Resolution Imaging Spectroradimeter (MODIS), band 1(620~670 nm, red), band 2(841~876 nm, NIR) and band 3(459~479 nm, blue) were simulated and MODIS-NDVI and EVI were calculated by averaging the continuous reflectance factor (350~1000 nm) over the spectral range of each band. A strong non-linear correlation was found between LAI of two rice varieties and the REP. The REP, MODIS-EVI and MODIS-NDVI were well related with LAI for the common rice, but the REP and MODIS-EVI were more sensitive than MODIS-NDVI to rice LAI for the hybrid rice. The reasons were that LAI of hybrid rice became greater with growth, and MODIS-NDVI was more affected by saturation, but MODIS-EVI and REP were less affected. This showed that the REP and MODIS-EVI will be more effective in monitoring the rice LAI.%对模拟中分辨率成像光谱仪(MODIS)两个植被指数归一化植被指数(NDVI)、增强植被指数(EVI)以及红边位置(REP)与水稻叶面积指数(LAI)进行了相关研究.利用光谱分辨率为3 nm 的ASD FieldSpec UV/VNIR 光谱仪获得了2002年两个不同水稻品种--杂交稻和常规稻整个生长期的高光谱数据,同时对水稻LAI进行了测定.利用一阶微分计算红边位移.模拟了MODIS 3个波段,波段1(620-670 nm,红波段),波段2(841~876 nm,近红外)和波段3(459~479 nm,蓝波段),并用这些波段计算了MODIS-NDVI和EVI.结果表明:对于常规稻,MODIS-NDVI、EVI和REP与水稻LAI呈现出

  1. Indicators of Ecological Change

    Science.gov (United States)

    2005-03-01

    measures Leaf area Branch evaluations Plant diversity Ozone bioindicators Lichen diversity Visible damage Vegetation structure Forest type...composition, and physiological status (measured as signature lipid/ DNA biomarkers) as a quick and easy indicator of changes in soil quality as a...Cryptophyte Geophyte Forb 0.17 0.45 Blazing star RL Liatris tenuafolia Asteraceae Cryptophyte Geophyte Forb 0.11 0.36 Blazing star RM Lichens Lichens 0.61

  2. Spatial relationship between climatologies and changes in global vegetation activity

    NARCIS (Netherlands)

    Jong, de R.; Schaepman, M.E.; Furrer, R.; Bruin, de S.; Verburg, P.H.

    2013-01-01

    Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time s

  3. Análise da dinâmica sazonal de fitofisionomias do bioma Mata Atlântica com base em índices de vegetação do sensor MODIS/TERRA / Analysis of the seasonal dynamics of some Atlantic Forest biome physiognomies with basis of vegetation indices derived from MOD

    Directory of Open Access Journals (Sweden)

    Elói Lennon Dalla Nora

    2010-08-01

    and with a climatic database (temperature and precipitation, for each physiognomy. The results showed that the fragments of seasonal deciduous forest and mixed rain forest present a common seasonal pattern, however, with variations of amplitude in relation to each index. The EVI was more sensible and hence, more efficient to annual variations of the vegetation compared to the NDVI. For both forest formations a positive correlation between profile EVI and NDVI with variations of temperature was established. The spectral/temporal dynamic showed a marked contrast under distinct seasonal conditions converging with the pattern presented for the vegetation indices. Data indicate potentialities of the use of MODIS sensor for the continuous monitoring of the south forest formations with moderate space resolution and high temporal resolution.

  4. Predicting children's fussiness with vegetables: The role of feeding practices.

    Science.gov (United States)

    Holley, Clare E; Haycraft, Emma; Farrow, Claire

    2017-03-01

    Vegetables are commonly rejected by children, making it is important to consider factors that are associated with children's fussiness with vegetables. The current study aimed to investigate whether fussiness with vegetables is associated with a number of factors including caregiver and child vegetable consumption; caregivers' general feeding practices; and caregivers' vegetable-specific feeding practices. Caregivers (N = 297) of preschool children completed questionnaire measures of their child's fussiness with vegetables, as well as several caregiver and child factors hypothesised to be associated with children's fussiness with vegetables. Findings indicate that children who are fussier with vegetables consume a smaller quantity of vegetables and that almost all have caregivers who eat a smaller quantity of vegetables. Children's fussiness with vegetables was not significantly related to any general feeding practices used by caregivers. However, children's fussiness with vegetables was significantly associated with the use of several vegetable specific feeding practices. Caregivers of fussier children used more encouragement/pressure to eat with vegetables (r = 0.14, p = .01), hid vegetables within other foods more often (r = 0.30, p = feeding vegetables (r = 0.14, p = .01). These findings suggest that rather than caregivers' general feeding practices being related to children's fussiness with vegetables, the specific feeding practices used when vegetables are rejected are more significant. It may therefore be helpful to develop advice for caregivers about which feeding practices to avoid when faced with a child who is fussy about eating vegetables.

  5. Environmental Efficiency Analysis of China's Vegetable Production

    Institute of Scientific and Technical Information of China (English)

    TAO ZHANG; BAO-DI XUE

    2005-01-01

    Objective To analyze and estimate the environmental efficiency of China's vegetable production. Methods The stochastic translog frontier model was used to estimate the technical efficiency of vegetable production. Based on the estimated frontier and technical inefficiency levels, we used the method developed by Reinhard, et al.[1] to estimate the environmental efficiency. Pesticide and chemical fertilizer inputs were treated as environmentally detrimental inputs. Results From estimated results, the mean environmental efficiency for pesticide input was 69.7%, indicating a great potential for reducing pesticide use in China's vegetable production. In addition, substitution and output elasticities for vegetable farms were estimated to provide farmers with helpful information on how to reallocate input resources and improve efficiency. Conclusion There exists a great potential for reducing pesticide use in China's vegetable production.

  6. Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models

    Science.gov (United States)

    Gillies, Robert R.; Carlson, Toby N.

    1995-01-01

    This study outlines a method for the estimation of regional patterns of surface moisture availability (M(sub 0)) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer (AVHRR)) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitues a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M(sub 0) into hydrologic and atmospheric prediction models. Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M(sub 0) is derived and is probabbly good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, `universal triangle,' is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M(sub 0) in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.

  7. Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models

    Science.gov (United States)

    Gillies, Robert R.; Carlson, Toby N.

    1995-01-01

    This study outlines a method for the estimation of regional patterns of surface moisture availability (M(sub 0)) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer (AVHRR)) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitues a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M(sub 0) into hydrologic and atmospheric prediction models. Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M(sub 0) is derived and is probabbly good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, `universal triangle,' is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M(sub 0) in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.

  8. Technology Drives Vegetable Industry

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    @@ Arobot for vegetable planting is able to examine growing conditions, detect disease of the vegetables and pick up the ripe ones through identifying the color; a tomato tree is able to produce up to 3,000kgs of tomatoes; sweet potatoes are growing in the air; fish and vegeta-bles are living together harmoniously...Viewing these, you may doubt that you were in a fancy world.Actually, you are here at the 12th China (Shouguang) International Vegetable Sci-tech Fair.

  9. Utilization of remote sensing data on meteorological and vegetation characteristics for modeling water and heat regimes of large agricultural region

    Science.gov (United States)

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

    2016-04-01

    Presently, physical-mathematical models such as SVAT (Soil-Vegetation-Atmosphere-Transfer) developed with varying degrees of detail are one of the most effective tools to evaluate the characteristics of the water and heat regimes of vegetation covered territories. The produced SVAT model is designed to calculate the soil water content, evapotranspiration (evaporation from bare soil and transpiration), infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat regime characteristics as well as vegetation and soil surface temperatures and the temperature and soil moisture distributions in depth. The model is adapted to satellite-derived estimates of precipitation, land surface temperatures and vegetation cover characteristics. The case study has been carried out for the located in the forest-steppe zone territory of part of the agricultural Central Black Earth Region of Russia with coordinates 49° 30'-54° N and 31° -43° E and area of 227 300 km2 for years 2011-2014 vegetation seasons. The soil and vegetation characteristics are used as the model parameters and the meteorological characteristics are considered to be input variables. These values have been obtained from ground-based observations and satellite-based measurements by radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/MSG-2,-3 (Meteosat-9, -10). To provide the retrieval of meteorological and vegetation cover characteristics the new and pre-existing methods and technologies of above radiometer thematic processing data have been developed or refined. From AVHRR data there have been derived estimates of precipitation P, efficient land surface temperature (LST) Ts.eff and emissivity E, surface-air temperature at a level of vegetation cover Ta, normalized difference vegetation index NDVI, leaf area index LAI and vegetation cover fraction B. The remote sensing products LST Tls, E, NDVI, LAI derived from MODIS data and covering the study area have been

  10. 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.

  11. Empirical Analysis of the Vegetable Industry in Hebei Province

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    We first introduce the status quo of the development of vegetable industry in Hebei Province,and then conduct empirical analysis of the development of vegetable industry in Hebei Province.Further,we analyze the development advantage of the vegetable industry in Hebei Province using SAI(Scale Advantage Indices) and SCA(Symmetric Comparative Advantage),drawing the conclusion that the vegetable industry in Hebei Province has much room for development;at the same time,we analyze the factors influencing vegetable consumption of residents in Hebei Province through the regression model,drawing the conclusion that the vegetable consumer price index is the main factor affecting the consumption.Finally we make recommendations for the development of vegetable industry in Hebei Province as follows:increasing financial input,promoting policy guarantee capacity;implementing brand strategy,promoting the competitiveness of products;improving the ecological environment,promoting industrialization of pollution-free vegetables.

  12. Incipient motion of sediment in presence of submerged flexible vegetation

    Institute of Scientific and Technical Information of China (English)

    Hao Wang; Hong-wu Tang; Han-qing Zhao; Xuan-yu Zhao; Sheng-qi Lu¨

    2015-01-01

    The presence of submerged vegetation on river beds can change the water flow structure and alter the state of sediment motion. In this study, the incipient motion of sediment in the presence of submerged flexible vegetation in open channels was investigated in a laboratory experiment. The vegetation was simulated with flexible rubber cylinders arranged in parallel arrays. The effect of the vegetation density, water depth, and sediment grain size on the incipient motion was investigated. The experimental results indicate that the incipient motion velocity of sediment increases as the vegetation density decreases and the water depth and sediment grain size increase. With flexible plants, the incipient motion velocity of sediment is lower than it is without vegetation, and is larger than it is with rigid vegetation. A general incipient motion velocity equation was derived, which can be applied to both flexible and rigid vegetation conditions.

  13. Terrestrial transect study on driving mechanism of vegetation changes

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In terms of Chinese climate-vegetation model based on the classification of plant functional types, to- gether with climatic data from 1951 to 1980 and two future climatic scenarios (SRES-A2 and SRES-B2) in China from the highest and the lowest emission scenarios of greenhouse gases, the distribution patterns of vegetation types and their changes along the Northeast China Transect (NECT) and the North-South Transect of Eastern China (NSTEC) were simulated in order to understand the driving mechanisms of vegetation changes under climatic change. The results indicated that the vegetation distribution patterns would change significantly under future climate, and the major factors driving the vegetation changes were water and heat. However, the responses of various vegetation types to the changes in water and heat factors were obviously different. The vegetation changes were more sensi- tive to heat factors than to water factors. Thus, in the future climate warming will significantly affect vegetation distribution patterns.

  14. Can a Satellite-Derived Estimate of the Fraction of PAR Absorbed by Chlorophyll (FAPAR(sub chl)) Improve Predictions of Light-Use Efficiency and Ecosystem Photosynthesis for a Boreal Aspen Forest?

    Science.gov (United States)

    Zhang, Qingyuan; Middleton, Elizabeth M.; Margolis, Hank A.; Drolet, Guillaume G.; Barr, Alan A.; Black, T. Andrew

    2009-01-01

    Gross primary production (GPP) is a key terrestrial ecophysiological process that links atmospheric composition and vegetation processes. Study of GPP is important to global carbon cycles and global warming. One of the most important of these processes, plant photosynthesis, requires solar radiation in the 0.4-0.7 micron range (also known as photosynthetically active radiation or PAR), water, carbon dioxide (CO2), and nutrients. A vegetation canopy is composed primarily of photosynthetically active vegetation (PAV) and non-photosynthetic vegetation (NPV; e.g., senescent foliage, branches and stems). A green leaf is composed of chlorophyll and various proportions of nonphotosynthetic components (e.g., other pigments in the leaf, primary/secondary/tertiary veins, and cell walls). The fraction of PAR absorbed by whole vegetation canopy (FAPAR(sub canopy)) has been widely used in satellite-based Production Efficiency Models to estimate GPP (as a product of FAPAR(sub canopy)x PAR x LUE(sub canopy), where LUE(sub canopy) is light use efficiency at canopy level). However, only the PAR absorbed by chlorophyll (a product of FAPAR(sub chl) x PAR) is used for photosynthesis. Therefore, remote sensing driven biogeochemical models that use FAPAR(sub chl) in estimating GPP (as a product of FAPAR(sub chl x PAR x LUE(sub chl) are more likely to be consistent with plant photosynthesis processes.

  15. Balkan Vegetation Database

    NARCIS (Netherlands)

    Vassilev, Kiril; Pedashenko, Hristo; Alexandrova, Alexandra; Tashev, Alexandar; Ganeva, Anna; Gavrilova, Anna; Gradevska, Asya; Assenov, Assen; Vitkova, Antonina; Grigorov, Borislav; Gussev, Chavdar; Filipova, Eva; Aneva, Ina; Knollová, Ilona; Nikolov, Ivaylo; Georgiev, Georgi; Gogushev, Georgi; Tinchev, Georgi; Pachedjieva, Kalina; Koev, Koycho; Lyubenova, Mariyana; Dimitrov, Marius; Apostolova-Stoyanova, Nadezhda; Velev, Nikolay; Zhelev, Petar; Glogov, Plamen; Natcheva, Rayna; Tzonev, Rossen; Boch, Steffen; Hennekens, Stephan M.; Georgiev, Stoyan; Stoyanov, Stoyan; Karakiev, Todor; Kalníková, Veronika; Shivarov, Veselin; Russakova, Veska; Vulchev, Vladimir

    2016-01-01

    The Balkan Vegetation Database (BVD; GIVD ID: EU-00-019; http://www.givd.info/ID/EU-00- 019) is a regional database that consists of phytosociological relevés from different vegetation types from six countries on the Balkan Peninsula (Albania, Bosnia and Herzegovina, Bulgaria, Kosovo, Montenegro

  16. Balkan Vegetation Database

    NARCIS (Netherlands)

    Vassilev, Kiril; Pedashenko, Hristo; Alexandrova, Alexandra; Tashev, Alexandar; Ganeva, Anna; Gavrilova, Anna; Gradevska, Asya; Assenov, Assen; Vitkova, Antonina; Grigorov, Borislav; Gussev, Chavdar; Filipova, Eva; Aneva, Ina; Knollová, Ilona; Nikolov, Ivaylo; Georgiev, Georgi; Gogushev, Georgi; Tinchev, Georgi; Pachedjieva, Kalina; Koev, Koycho; Lyubenova, Mariyana; Dimitrov, Marius; Apostolova-Stoyanova, Nadezhda; Velev, Nikolay; Zhelev, Petar; Glogov, Plamen; Natcheva, Rayna; Tzonev, Rossen; Boch, Steffen; Hennekens, Stephan M.; Georgiev, Stoyan; Stoyanov, Stoyan; Karakiev, Todor; Kalníková, Veronika; Shivarov, Veselin; Russakova, Veska; Vulchev, Vladimir

    2016-01-01

    The Balkan Vegetation Database (BVD; GIVD ID: EU-00-019; http://www.givd.info/ID/EU-00- 019) is a regional database that consists of phytosociological relevés from different vegetation types from six countries on the Balkan Peninsula (Albania, Bosnia and Herzegovina, Bulgaria, Kosovo, Montenegro

  17. Soil and vegetation surveillance

    Energy Technology Data Exchange (ETDEWEB)

    Antonio, E.J.

    1995-06-01

    Soil sampling and analysis evaluates long-term contamination trends and monitors environmental radionuclide inventories. This section of the 1994 Hanford Site Environmental Report summarizes the soil and vegetation surveillance programs which were conducted during 1994. Vegetation surveillance is conducted offsite to monitor atmospheric deposition of radioactive materials in areas not under cultivation and onsite at locations adjacent to potential sources of radioactivity.

  18. CRMS vegetation analytical team framework: Methods for collection, development, and use of vegetation response variables

    Science.gov (United States)

    Cretini, Kari F.; Visser, Jenneke M.; Krauss, Ken W.; Steyer, Gregory D.

    2011-01-01

    This document identifies the main objectives of the Coastwide Reference Monitoring System (CRMS) vegetation analytical team, which are to provide (1) collection and development methods for vegetation response variables and (2) the ways in which these response variables will be used to evaluate restoration project effectiveness. The vegetation parameters (that is, response variables) collected in CRMS and other coastal restoration projects funded under the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) are identified, and the field collection methods for these parameters are summarized. Existing knowledge on community and plant responses to changes in environmental drivers (for example, flooding and salinity) from published literature and from the CRMS and CWPPRA monitoring dataset are used to develop a suite of indices to assess wetland condition in coastal Louisiana. Two indices, the floristic quality index (FQI) and a productivity index, are described for herbaceous and forested vegetation. The FQI for herbaceous vegetation is tested with a long-term dataset from a CWPPRA marsh creation project. Example graphics for this index are provided and discussed. The other indices, an FQI for forest vegetation (that is, trees and shrubs) and productivity indices for herbaceous and forest vegetation, are proposed but not tested. New response variables may be added or current response variables removed as data become available and as our understanding of restoration success indicators develops. Once indices are fully developed, each will be used by the vegetation analytical team to assess and evaluate CRMS/CWPPRA project and program effectiveness. The vegetation analytical teams plan to summarize their results in the form of written reports and/or graphics and present these items to CRMS Federal and State sponsors, restoration project managers, landowners, and other data users for their input.

  19. Fruit and vegetables and cancer risk.

    Science.gov (United States)

    Key, T J

    2011-01-04

    The possibility that fruit and vegetables may help to reduce the risk of cancer has been studied for over 30 years, but no protective effects have been firmly established. For cancers of the upper gastrointestinal tract, epidemiological studies have generally observed that people with a relatively high intake of fruit and vegetables have a moderately reduced risk, but these observations must be interpreted cautiously because of potential confounding by smoking and alcohol. For lung cancer, recent large prospective analyses with detailed adjustment for smoking have not shown a convincing association between fruit and vegetable intake and reduced risk. For other common cancers, including colorectal, breast and prostate cancer, epidemiological studies suggest little or no association between total fruit and vegetable consumption and risk. It is still possible that there are benefits to be identified: there could be benefits in populations with low average intakes of fruit and vegetables, such that those eating moderate amounts have a lower cancer risk than those eating very low amounts, and there could also be effects of particular nutrients in certain fruits and vegetables, as fruit and vegetables have very varied composition. Nutritional principles indicate that healthy diets should include at least moderate amounts of fruit and vegetables, but the available data suggest that general increases in fruit and vegetable intake would not have much effect on cancer rates, at least in well-nourished populations. Current advice in relation to diet and cancer should include the recommendation to consume adequate amounts of fruit and vegetables, but should put most emphasis on the well-established adverse effects of obesity and high alcohol intakes.

  20. Fruit and vegetables and cancer risk

    Science.gov (United States)

    Key, T J

    2011-01-01

    The possibility that fruit and vegetables may help to reduce the risk of cancer has been studied for over 30 years, but no protective effects have been firmly established. For cancers of the upper gastrointestinal tract, epidemiological studies have generally observed that people with a relatively high intake of fruit and vegetables have a moderately reduced risk, but these observations must be interpreted cautiously because of potential confounding by smoking and alcohol. For lung cancer, recent large prospective analyses with detailed adjustment for smoking have not shown a convincing association between fruit and vegetable intake and reduced risk. For other common cancers, including colorectal, breast and prostate cancer, epidemiological studies suggest little or no association between total fruit and vegetable consumption and risk. It is still possible that there are benefits to be identified: there could be benefits in populations with low average intakes of fruit and vegetables, such that those eating moderate amounts have a lower cancer risk than those eating very low amounts, and there could also be effects of particular nutrients in certain fruits and vegetables, as fruit and vegetables have very varied composition. Nutritional principles indicate that healthy diets should include at least moderate amounts of fruit and vegetables, but the available data suggest that general increases in fruit and vegetable intake would not have much effect on cancer rates, at least in well-nourished populations. Current advice in relation to diet and cancer should include the recommendation to consume adequate amounts of fruit and vegetables, but should put most emphasis on the well-established adverse effects of obesity and high alcohol intakes. PMID:21119663

  1. Effects of experimental protocol on global vegetation model accuracy: a comparison of simulated and observed vegetation patterns for Asia

    Science.gov (United States)

    Tang, Guoping; Shafer, Sarah L.; Barlein, Patrick J.; Holman, Justin O.

    2009-01-01

    Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO2 concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO2 concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO2 concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

  4. [Progress in retrieving vegetation water content under different vegetation coverage condition based on remote sensing spectral information].

    Science.gov (United States)

    Zhang, Jia-Hua; Li, Li; Yao, Feng-Mei

    2010-06-01

    The present paper reviews the progress in the methods of retrieving vegetation water content using remote sensing spectral information, including vegetation spectral reflectance information (VIR, SWIR, and NIR) to directly extract vegetation water content and establish vegetation water indices (WI), i. e. NDWI = (R860 - R1 240)/(R860 + R1 240) and PWI = R970/R900; and using radiation transfer (RT) model such as PROSPAIL to detect plant water content information. The authors analyze the method of retrieving vegetation water content under low crop coverage condition. The plant water can be estimated by using canopy physiological parameters firstly, and using vegetation indices and radiation transfer model secondly, which can eliminate soil background effect. The estimated agricultural drought and vegetation water content by using multi-angle polarized reflectance and bi-directional reflectance (BRDF) was discussed in this paper. In the end, the possible development trend of retrieval methods for plant water information under plant low coverage conditions was discussed.

  5. Analysis of Vegetation Behavior in a North African Semi-Arid Region, Using SPOT-VEGETATION NDVI Data

    Directory of Open Access Journals (Sweden)

    Abdelghani Chehbouni

    2011-11-01

    Full Text Available The analysis of vegetation dynamics is essential in semi-arid regions, in particular because of the frequent occurrence of long periods of drought. In this paper, multi-temporal series of the Normalized Difference of Vegetation Index (NDVI, derived from SPOT-VEGETATION satellite data between September 1998 and June 2010, were used to analyze the vegetation dynamics over the semi-arid central region of Tunisia. A study of the persistence of three types of vegetation (pastures, annual agriculture and olive trees is proposed using fractal analysis, in order to gain insight into the stability/instability of vegetation dynamics. In order to estimate the state of vegetation cover stress, we propose evaluating the properties of an index referred to as the Vegetation Anomaly Index (VAI. A positive VAI indicates high vegetation dynamics, whereas a negative VAI indicates the presence of vegetation stress. The VAI is tested for the above three types of vegetation, during the study period from 1998 to 2010, and is compared with other drought indices. The VAI is found to be strongly correlated with precipitation.

  6. Vegetation and soil carbon storage in China

    Institute of Scientific and Technical Information of China (English)

    LI Kerang; WANG Shaoqiang; CAO Mingkui

    2004-01-01

    This study estimated the current vegetation and soil carbon storage in China using a biogeochemical model driven with climate, soil and vegetation data at 0.5°latitude-longitude grid spatial resolution. The results indicate that the total carbon storage in China's vegetation and soils was 13.33 Gt C and 82.65 Gt C respectively, about 3% and 4% of the global total. The nationally mean vegetation and soil carbon densities were 1.47 kg C/m2 and 9.17 kg C/m2, respectively, differing greatly in various regions affected by climate, vegetation, and soil types. They were generally higher in the warm and wet Southeast China and Southwest China than in the arid Northwest China; whereas vegetation carbon density was the highest in the warm Southeast China and Southwest China, soil carbon density was the highest in the cold Northeast China and southeastern fringe of the Qinghai-Tibetan Plateau. These spatial patterns are clearly correlated with variations in the climate that regulates plant growth and soil organic matter decomposition, and show that vegetation and soil carbon densities are controlled by different climatic factors.

  7. Waste indicators

    Energy Technology Data Exchange (ETDEWEB)

    Dall, O.; Lassen, C.; Hansen, E. [Cowi A/S, Lyngby (Denmark)

    2003-07-01

    The Waste Indicator Project focuses on methods to evaluate the efficiency of waste management. The project proposes the use of three indicators for resource consumption, primary energy and landfill requirements, based on the life-cycle principles applied in the EDIP Project. Trial runs are made With the indicators on paper, glass packaging and aluminium, and two models are identified for mapping the Danish waste management, of which the least extensive focuses on real and potential savings. (au)

  8. Vegetation dynamics and climate variability-associated biophysical process in West Africa

    Science.gov (United States)

    Song, G.; Xue, Y.; Cox, P. M.

    2012-12-01

    West Africa is a bioclimatic zone of predominantly annual grasses with shrubs and trees with a steep gradient in climate, soils, vegetation, fauna, land use and human utilization. West Africa ecosystem region suffered from the most severe and longest drought in the world during the Twentieth Century since the later 1960s. This study systematically investigates how climate variability and anomalies in West Africa affect the regional terrestrial ecosystem, including plant functional types' (PFT) spatial distribution and temporal variations and vegetation characteristics, through biophysical and photosynthesis processes at different scales. We use the offline Simplified Simple Biosphere Version 4/ Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), which is a fully coupled biophysical-dynamic vegetation (DVM) model to adequately incorporate the complex non-linear coupling dynamics between ecosystem and climate variability. The biophysical parameters in SSiB4 are adjusted with TRIFFID-produced vegetation parameter values, which ensure adequate biophysical process coupling. A 59-year simulation from 1948 was conducted using the meteorological forcing, which consists of substantial seasonal, interannual, and interdecal variability and long term dry trend. The results show that the simulated PFT's and leaf area index (LAI) correspond well to climate variability and are consistent with satellite derived vegetation conditions. The simulated inter-decadal variability in vegetation conditions is consistent with the Sahel drought in the 1970s and the 1980s and partial recovery in the 1990s and the 2000s (fig1). To further understand the biophysical mechanism of interactions of water, carbon, radiation, and vegetation dynamics, analyses are conducted to find relationships between vegetation variability and environmental conditions. It is found that the vegetation characteristics simulated by SSiB4/TRIFFID responds primarily to five

  9. Quality indicators

    DEFF Research Database (Denmark)

    Hjorth-Andersen, Christian

    1991-01-01

    In recent literature it has been suggested that consumers need have no knowledge of product quality as a number of quality indicators (or signals) may be used as substitutes. Very little attention has been paid to the empirical verification of these studies. The present paper is devoted...... to the issue of how well these indicators perform, using market data provided by consumer magazines from 3 countries. The results strongly indicate that price is a poor quality indicator. The paper also presents some evidence which suggests that seller reputation and easily observable characteristics are also...

  10. 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

    2017-02-01

    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.

  11. 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

  12. Preliminary results on the comparison between satellite derived ground temperature and in-situ measurement of soil CO2 flux and soil temperature at Solfatara of Pozzuoli (Naples, Italy)

    Science.gov (United States)

    Cardellini, Carlo; Silvestri, Malvina; Chiodini, Giovanni; Fabrizia Buongiorno, Maria

    2014-05-01

    temperature (at 10 cm depth) are measured periodically in about 400 point randomly distributed in the Solfatara crater area and in its surroundings. The data measured in 3 surveys performed from 2003 to 2010, in periods roughly correspondent to the available ASTER data, have been elaborated with the geostatistical method of Sequential Gaussian Simulation in order to obtain maps with a spatial resolution of 90X90 m to be compared to the ASTER data. The first results show a quite good correlations between ASTER derived temperatures and both temperatures and CO2 fluxes derived from ground measurement, especially in the most anomalous areas characterized by higher soil CO2 fluxes and temperatures. These first results encourage the possibility to use the satellite derived temperature as proxy of the CO2 fluxes and to implement methods to use long time series of satellite TIR data in a monitoring prospective.

  13. Description of vegetation types

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This document provides descriptions of five vegetation types found in Iowa- oak savannah, mature hardwoods, floodplain woods, scrub woods, and riparian woods. Oak...

  14. Total Vegetation 1992

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The coverage contains 1992 vegetation polygons representing GCES monitoring sites. These data were developed by Dr. G. Waring Northern AZ. University for use in the...

  15. Total Vegetation 1973

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The coverage contains 1973 vegetation polygons representing GCES monitoring sites. These data were developed as study by Dr. G. Waring Northern AZ. University of...

  16. Total Vegetation 1965

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The coverage contains 1965 vegetation polygons representing GCES monitoring sites. These data were developed as study by Dr. G. Waring Northern AZ. University of...

  17. Total Vegetation 1984

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The coverage contains 1984 vegetation polygons representing GCES monitoring sites. These data were developed as study by Dr. G. Waring Northern AZ. University of...

  18. Fractals in Spatial Patterns of Vegetation Formations

    Institute of Scientific and Technical Information of China (English)

    SONG Zhiyuan; HUANG Daming; Masae Shiyomi; WANG Yusheng; Shigeo Takahashi; Hori Yoshimichi; Yasuo Yamamuru; CHEN Jun

    2006-01-01

    The spatial distribution patterns of species are always scale-dependent and spatially self-similar in ecological systems. In this work, vegetation distribution data collected from the vegetation map of the Xigazê region was analyzed using a box-counting method. The power law of the box-counting dimension (DB) across a range of scales (5-160 km) confirms the fractal patterns for most vegetation formations, while the fluctuations of the scale-specific DB among the different abundance groups indicate limitations of fractal coherence. The fractal method is shown to be a useful tool for measuring the distribution patterns of vegetation formations across scales, which provides important information for both species and habitat conservation, especially in landscape management.

  19. Exploring vegetation in the fourth dimension.

    Science.gov (United States)

    Mitchell, Fraser J G

    2011-01-01

    Much ecological research focuses on changes in vegetation on spatial scales from stands to landscapes; however, capturing data on vegetation change over relevant timescales remains a challenge. Pollen analysis offers unrivalled access to data with global coverage over long timescales. Robust techniques have now been developed that enable pollen data to be converted into vegetation data in terms of individual taxa, plant communities or biomes, with the possibility of deriving from those data a range of plant attributes and ecological indicators. In this review, I discuss how coupling pollen with macrofossil, charcoal and genetic data opens up the extensive pollen databases to investigation of the drivers of vegetation change over time and also provides extensive data sets for testing hypotheses with wide ecological relevance.

  20. Authentication of vegetable oils.

    OpenAIRE

    Cunha, S.C.; Amaral, J S; Oliveira, M.B.P.P.

    2011-01-01

    Authenticity of vegetable oils continues to be a challenge and the target of many studies. Consumers expectancy on healthier products that conform to the labelled information, and the vast amount of legislation a bout the correct characterisation and classification of vegetable oils have boosted a number of scientific works on this subject. Analytical t echniques to face this challenge are, at least, as manifold as ar e the ways of adulteration, ranging fro...

  1. Multi‐angular observations of vegetation indices from UAV cameras

    DEFF Research Database (Denmark)

    Sobejano-Paz, Veronica; Wang, Sheng; Jakobsen, Jakob

    Unmanned aerial vehicles (UAVs) are found as an alternative to the classical manned aerial photogrammetry, which can be used to obtain environmental data or as a complementary solution to other methods (Nex and Remondino, 2014). Although UAVs have coverage limitations, they have better resolution...

  2. Colorado Plateau Rapid Ecoregion Assessment Indicators: Natural Vegetation Fragmentation

    Data.gov (United States)

    Bureau of Land Management, Department of the Interior — This dataset presents measures of landscape fragmentation calculated by FRAGSTATS at 4KM and HUC5 reporting unit levels. Fragmentation integrates the influence of...

  3. Relationships between Vegetation Indices and Environmental Temperature and Moisture in An Alpine Meadow along An Elevation Gradient in the Northern Tibet%藏北高原不同海拔高度高寒草甸植被指数与环境温湿度的关系

    Institute of Scientific and Technical Information of China (English)

    沈振西; 孙维; 李少伟; 何永涛; 付刚; 张宪洲; 王江伟

    2015-01-01

    in the Northern Tibet is an important component of the alpine grasslands worldwide, and it is also one of the most sensitive vegetation types to climatic changes. There are large uncertainties on the relationship between vegetation indices and environmental temperature and moisture, which limits our ability to accurately predict the responses of the vegetation growth in alpine grasslands to future climatic changes. Quantifying the relationship between vegetation indices and climatic factors improves the prediction of vegetation growth in alpine grasslands under future climatic change. Using the correlation analysis and the multiple stepwise regression analysis, we explored the relationships between vegetation indices (i.e. Normalized Difference Vegetation Index, NDVI;Enhanced Vegetation Index, EVI) and soil temperature, soil moisture, air temperature, relative humidity or vapor pressure deficit at three elevations (4 300, 4 500 and 4 700 m) in an alpine meadow from June─September in 2011─2014. The correlation analyses showed that all the correlation coefficients between