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Vegetation indices have been widely used as indicators of seasonal and inter‐annual variations in vegetation caused by either human activities or climate, with the overall goal of observing and documenting changes in the Earth system. While existing satellite remote sensing systems, such as NASA's Multi‐angle Imaging SpectroRadiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS), are providing improved vegetation index data products through correcting for the distortions in surface reflectance caused by atmospheric particles as well as ground covers below vegetation canopy, the impact of land‐cover mixing on vegetation indices has not been fully addressed. In this study, based on real image spectral samples for two‐component mixtures of forest and common nonforest land‐cover types directly extracted from a 1.1 km MISR image by referencing a 30 m land‐cover classification, the effect of land‐cover mixing on the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) has been quantitatively evaluated. When the areal fraction of forest was lower than 80%, both NDVI and EVI varied greatly with mixed land‐cover types, although EVI varied less than NDVI. Such a phenomenon can cause errors in applications based on use of these vegetation indices. This study suggests that methods that reduce land‐cover mixing effects should be introduced when developing new spectral vegetation indices.
Liu et al. (Wed,) studied this question.