Detecting biophysical properties of a semiarid grassland and distinguishing burned from unburned areas with hyperspectral reflectance

This paper examines the utility of hyperspectral remote sensing to detect fresh and dry biomass, water content, and plant area index of burned and unburned grassland in southern California. Contrary to many previously published reports, the Normalized Difference Vegetation Index (NDVI, a vegetation greenness index) was not a good indicator of any of these important biophysical properties in either the burned or unburned area, especially after regeneration. Rather, the Water Band Index (WBI, an index of water status in vegetation) showed better promise of estimating these biophysical properties in this semiarid ecosystem. Despite the post-regeneration similarities in visual and harvested values of these two areas, we found that the full range of hyperspectral reflectance in ‘visible to infra-red’ (400 to 1000 nanometers) wavelengths when used in a cluster analysis can readily differentiate the burned and unburned areas. This demonstrates the utility of hyperspectral remote sensing in mapping subtle features that may not be detectable from conventional remote sensing indices (e.g. NDVI) alone.