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Remote Sens. 2012, 4(9), 2619-2634; doi:10.3390/rs4092619
Article

Remote Sensing of Fractional Green Vegetation Cover Using Spatially-Interpolated Endmembers

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Received: 27 July 2012; in revised form: 3 September 2012 / Accepted: 4 September 2012 / Published: 12 September 2012
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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.
Keywords: fractional vegetation cover; linear spectral unmixing; spectral mixture analysis; subpixel mapping; spatial interpolation; kriging; NDVI; MSAVI fractional vegetation cover; linear spectral unmixing; spectral mixture analysis; subpixel mapping; spatial interpolation; kriging; NDVI; MSAVI
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Johnson, B.; Tateishi, R.; Kobayashi, T. Remote Sensing of Fractional Green Vegetation Cover Using Spatially-Interpolated Endmembers. Remote Sens. 2012, 4, 2619-2634.

AMA Style

Johnson B, Tateishi R, Kobayashi T. Remote Sensing of Fractional Green Vegetation Cover Using Spatially-Interpolated Endmembers. Remote Sensing. 2012; 4(9):2619-2634.

Chicago/Turabian Style

Johnson, Brian; Tateishi, Ryutaro; Kobayashi, Toshiyuki. 2012. "Remote Sensing of Fractional Green Vegetation Cover Using Spatially-Interpolated Endmembers." Remote Sens. 4, no. 9: 2619-2634.


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