Paper Info
Title
Remote Sensing of Fractional Green Vegetation Cover Using Spatially-Interpolated Endmembers
Abstract
Fractional green vegetation cover (FVC) is a useful parameter for many environmental and climate-related applications. A common approach for estimating FVC involves the linear unmixing of two spectral endmembers in a remote sensing image; bare soil and green vegetation. The spectral properties of these two endmembers are typically determined based on field measurements, estimated using additional data sources (e. g., soil databases or land cover maps), or extracted directly from the imagery. Most FVC estimation approaches do not consider that the spectral properties of endmembers may vary across space. However, due to local differences in climate, soil type, vegetation species, etc., the spectral characteristics of soil and green vegetation may exhibit positive spatial autocorrelation. When this is the case, it may be useful to take these local variations into account for estimating FVC. In this study, spatial interpolation (Inverse Distance Weighting and Ordinary Kriging) was used to predict variations in the spectral characteristics of bare soil and green vegetation across space. When the spatially-interpolated values were used in place of scene-invariant endmember values to estimate FVC in an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image, the accuracy of FVC estimates increased, providing evidence that it may be useful to consider the effects of spatial autocorrelation for spectral mixture analysis.
Year
DOI
Venue
2012
10.3390/rs4092619
REMOTE SENSING
Keywords
Field
DocType
fractional vegetation cover,linear spectral unmixing,spectral mixture analysis,subpixel mapping,spatial interpolation,kriging,NDVI,MSAVI
Kriging,Spatial analysis,Endmember,Soil science,Vegetation,Multivariate interpolation,Inverse distance weighting,Remote sensing,Normalized Difference Vegetation Index,Geology,Land cover
Journal
Volume
Issue
ISSN
4
9
2072-4292
Citations 
PageRank 
References 
14
1.02
9
Authors
3
Name
Order
Citations
PageRank
Brian Johnson1658.83
Ryutaro Tateishi27813.21
Kobayashi, T.3151.50