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

Abstract

AbstractThere 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 than other vegetation indices and red‐edge parameters for the linear and second‐order polynomial regression, respectively.