Mapping Plant Functional Types at Multiple Spatial Resolutions Using Imaging Spectrometer Data

Abstract

Imaging spectrometer data have been used to map plant functional types (PFTs—plant species grouped by similarities in their resource use, ecosystem function, and responses to environmental conditions) at spatial resolutions of 30 m and finer, but not at coarser spatial resolutions that may be necessary for global PFT mapping. This study uses spatially resampled Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) data acquired over the Wasatch Mountains of northern Utah, USA to examine changes in PFT classification accuracy as spatial resolution is degraded from 20 to 60 m. Accuracy was dependent on the spatial resolution of the classified data and the spatial resolution of endmembers used in the multiple endmember spectral mixture analysis classifier.