Estimating the fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil from MODIS data: Assessing the applicability of the NDVI-DFI model in the typical Xilingol grasslands

Vegetation Fractional Cover (VFC) is an important global indicator of land cover change, land use practice and landscape, and ecosystem function. In this study, we present the Global Vegetation Fractional Cover Product (GVFCP) and explore the levels and trends in VFC across World Grassland Type (WGT) Ecoregions considering variation associated with Global Livestock Production Systems (GLPS). Long-term average levels and trends in fractional cover of photosynthetic vegetation (FPV), non-photosynthetic vegetation (FNPV), and bare soil (FBS) are mapped, and variation among GLPS types within WGT Divisions and Ecoregions is explored. Analysis also focused on the savanna-woodland WGT Formations. Many WGT Divisions showed wide variation in long-term average VFC and trends in VFC across GLPS types. Results showed large areas of many ecoregions experiencing significant positive and negative trends in VFC. East Africa, Patagonia, and the Mitchell Grasslands of Australia exhibited large areas of negative trends in FNPV and positive trends FBS. These trends may reflect interactions between extended drought, heavy livestock utilization, expanded agriculture, and other land use changes. Compared to previous studies, explicit measurement of FNPV revealed interesting additional information about vegetation cover and trends in many ecoregions. The Australian and Global products are available via the GEOGLAM RAPP (Group on Earth Observations Global Agricultural Monitoring Rangeland and Pasture Productivity) website, and the scientific community is encouraged to utilize the data and contribute to improved validation.

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A method to estimate diurnal surface soil heat flux from MODIS data for a sparse vegetation and bare soil

Journal of Hydrology ◽

10.1016/j.jhydrol.2014.01.019 ◽

2014 ◽

Vol 511 ◽

pp. 139-150 ◽

Cited By ~ 16

Author(s):

Weiwei Zhu ◽

Bingfang Wu ◽

Nana Yan ◽

Xueliang Feng ◽

Qiang Xing

Keyword(s):

Heat Flux ◽

Surface Soil ◽

Bare Soil ◽

Soil Heat Flux ◽

Modis Data ◽

Sparse Vegetation

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Comparison of Hyperspectral Versus Traditional Field Measurements of Fractional Ground Cover in the Australian Arid Zone

Remote Sensing ◽

10.3390/rs11232825 ◽

2019 ◽

Vol 11 (23) ◽

pp. 2825 ◽

Cited By ~ 2

Author(s):

Claire Fisk ◽

Kenneth Clarke ◽

Megan Lewis

Keyword(s):

Spatial Scale ◽

Arid Zone ◽

Ground Cover ◽

Field Measurements ◽

Bare Soil ◽

Point Sampling ◽

Calibration And Validation ◽

Fractional Cover ◽

In Situ Methods

The collection of high-quality field measurements of ground cover is critical for calibration and validation of fractional ground cover maps derived from satellite imagery. Field-based hyperspectral ground cover sampling is a potential alternative to traditional in situ techniques. This study aimed to develop an effective sampling design for spectral ground cover surveys in order to estimate fractional ground cover in the Australian arid zone. To meet this aim, we addressed two key objectives: (1) Determining how spectral surveys and traditional step-point sampling compare when conducted at the same spatial scale and (2) comparing these two methods to current Australian satellite-derived fractional cover products. Across seven arid, sparsely vegetated survey sites, six 500-m transects were established. Ground cover reflectance was recorded taking continuous hyperspectral readings along each transect while step-point surveys were conducted along the same transects. Both measures of ground cover were converted into proportions of photosynthetic vegetation, non-photosynthetic vegetation, and bare soil for each site. Comparisons were made of the proportions of photosynthetic vegetation, non-photosynthetic vegetation, and bare soil derived from both in situ methods as well as MODIS and Landsat fractional cover products. We found strong correlations between fractional cover derived from hyperspectral and step-point sampling conducted at the same spatial scale at our survey sites. Comparison of the in situ measurements and image-derived fractional cover products showed that overall, the Landsat product was strongly related to both in situ methods for non-photosynthetic vegetation and bare soil whereas the MODIS product was strongly correlated with both in situ methods for photosynthetic vegetation. This study demonstrates the potential of the spectral transect method, both in its ability to produce results comparable to the traditional transect measures, but also in its improved objectivity and relative logistic ease. Future efforts should be made to include spectral ground cover sampling as part of Australia’s plan to produce calibration and validation datasets for remotely sensed products.

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Using broadband crop residue angle index to estimate the fractional cover of vegetation, crop residue, and bare soil in cropland systems

Remote Sensing of Environment ◽

10.1016/j.rse.2019.111538 ◽

2020 ◽

Vol 237 ◽

pp. 111538 ◽

Cited By ~ 3

Author(s):

Jibo Yue ◽

Qingjiu Tian ◽

Xinyu Dong ◽

Nianxu Xu

Keyword(s):

Crop Residue ◽

Bare Soil ◽

Fractional Cover

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Time to "Rewet the Swamp" – Application of Georgian Data Cube to Elucidate Drainage Patterns and Potential for Wet Agriculture and Forestry on Kolkheti Lowland

10.5194/egusphere-egu21-16511 ◽

2021 ◽

Author(s):

Izolda Matchutadze ◽

Aliosha Bakuridze ◽

Ira Abuladze ◽

Nana Shakarishvili ◽

Mamuka Gvilava

Keyword(s):

High Water ◽

Bare Soil ◽

Data Cube ◽

Biofuel Production ◽

The Black Sea ◽

Vegetation Removal ◽

Fractional Cover ◽

Drainage Patterns ◽

Water Detection ◽

Black Sea Coast

<p>It was established recently that gravity drainage is inefficient on Kolkheti Lowland along the Black Sea coast of Georgia and that novel approaches are urgently recommend, such as implementing rewetting schemes to restore ecosystem services and enhance economic values of these areas through wet agriculture, biofuel production with native wetland species, and/or afforestation, to achieve sustainable outcomes in both ecologic and economic terms. Water Detection, Fractional Cover and Urbanization remote sensing tools, provided by Georgian Data Cube (comprising Landsat sensor Analysis Ready Data), developed recently with UNEP/GRID support, were applied on multi-year timescale basis for Kolkheti lowland to identify priority areas with high potential for rewetting. Water Detection tool allowed establishment of low effectiveness drainage areas, as demonstrated by high cumulative values for the presence of water, indicating water-logged areas as potential intervention sites for wet agroforestry. Water Detection combined with Fractional Cover tool allowed comparative analysis of non-photosynthetic vegetation and bare soil areas versus high water detection areas to single out those lands on the Kolkheti lowland, where drainage seems effective and dry agriculture is pursued versus those lands where drainage is not effective and dry agriculture is not actually happening. Urbanization tool can also be applied to detect human activities, such as agricultural activities, visualising those areas, which are subjected to active vegetation removal on an annual basis due to crop harvesting and those areas, where vegetation was not removed, staying vegetated most of the time, interpreted as abandoned agricultural lands. Regular patters combining non-use agricultural with cumulative water covered areas could thus help locate candidate sites for piloting wet agriculture on Kolkheti Lowland in Georgia. In addition to sustainable economic practices, rewetting could certainly benefit core ecological areas of Kolkheti Lowland, protected by both national designation as Kolkheti National Park and international designation as Central Kolkheti Ramsar Site.</p>

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Assessing the effects of site heterogeneity and soil properties when unmixing photosynthetic vegetation, non-photosynthetic vegetation and bare soil fractions from Landsat and MODIS data

Remote Sensing of Environment ◽

10.1016/j.rse.2015.01.021 ◽

2015 ◽

Vol 161 ◽

pp. 12-26 ◽

Cited By ~ 70

Author(s):

Juan P. Guerschman ◽

Peter F. Scarth ◽

Tim R. McVicar ◽

Luigi J. Renzullo ◽

Tim J. Malthus ◽

...

Keyword(s):

Soil Properties ◽

Bare Soil ◽

Modis Data ◽

Soil Fractions ◽

Site Heterogeneity

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Estimating fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil in the Australian tropical savanna region upscaling the EO-1 Hyperion and MODIS sensors

Remote Sensing of Environment ◽

10.1016/j.rse.2009.01.006 ◽

2009 ◽

Vol 113 (5) ◽

pp. 928-945 ◽

Cited By ~ 211

Author(s):

Juan Pablo Guerschman ◽

Michael J. Hill ◽

Luigi J. Renzullo ◽

Damian J. Barrett ◽

Alan S. Marks ◽

...

Keyword(s):

Bare Soil ◽

Tropical Savanna ◽

Fractional Cover

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Mapping Climatological Bare Soil Albedos over the Contiguous United States Using MODIS Data

Remote Sensing ◽

10.3390/rs11060666 ◽

2019 ◽

Vol 11 (6) ◽

pp. 666 ◽

Cited By ~ 3

Author(s):

Tao He ◽

Feng Gao ◽

Shunlin Liang ◽

Yi Peng

Keyword(s):

United States ◽

Soil Moisture ◽

Land Cover ◽

Land Surface ◽

Climate Modeling ◽

Bare Soil ◽

Surface Energy Budget ◽

Vegetation Density ◽

Exponential Relationship ◽

Modis Data

Surface bare soil albedo is an important variable in climate modeling studies and satellite-based retrievals of land-surface properties. In this study, we used multiyear 500 m albedo products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to derive the bare soil albedo for seven spectral bands and three broadbands over the contiguous United States (CONUS). The soil line based on red and green spectral signatures derived from MODIS data was used as the basis to detect and extract bare soil albedo. A comparison against bare soil albedo derived from 30 m Landsat data has been made, showing that the MODIS bare soil albedo had a bias of 0.003 and a root-mean-square-error (RMSE) of 0.036. We found that the bare soil albedo was negatively correlated with soil moisture from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), with a relatively stable exponential relationship reflecting the darkening effect that moisture has on most soils. However, quantification of the relationship between bare soil albedo and soil moisture still needs to be improved through simultaneous and instantaneous measurements at a finer spatial resolution. Statistics of the multiyear climatological bare soil albedos calculated using soil types and the International Geosphere-Biosphere Programme (IGBP) land cover types suggest that: Land cover type is a better indicator for determining the magnitude of bare soil albedos for the vegetated areas, as the vegetation density is correlated with soil moisture; and soil type is a better indicator for determining the slope of soil lines over sparsely vegetated areas, as it contains information of the soil texture, roughness, and composition. The generated bare soil albedo can be applied to improve the parameterization of surface energy budget in climate and remote sensing models as well as the retrieval accuracy of some satellite products.

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