Article ID Journal Published Year Pages File Type
6345882 Remote Sensing of Environment 2015 16 Pages PDF
Abstract

•We evaluate relationships between species, fractional cover and surface temperature.•HyspIRI data are simulated using AVIRIS and MASTER data from the Santa Barbara area.•Plant-species and land-cover classification exceed 74% accuracy.•Green Vegetation (GV) Fraction and surface temperature were inversely related.•Plant species clustered uniquely in the GV-LST space.

The Hyperspectral Infrared Imager (HyspIRI) is a proposed satellite mission that combines a 60 m spatial resolution Visible-Shortwave Infrared (VSWIR) imaging spectrometer and a 60 m multispectral thermal infrared (TIR) scanner. HyspIRI would combine the established capability of a VSWIR sensor to discriminate plant species and estimate accurate cover fractions with improved Land Surface Temperatures (LST) retrieved from the TIR sensor. We evaluate potential synergies between Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) maps of dominant plant species and mixed species assemblages, fractional cover, and MODIS/ASTER Airborne Simulator (MASTER) LST utilizing multiple flight lines acquired in July 2011 in the Santa Barbara, California area. Species composition and green vegetation (GV), non-photosynthetic vegetation (NPV), impervious, and soil cover fractions were mapped using Multiple Endmember Spectral Mixture Analysis with a spectral library derived from 7.5 m imagery. Temperature-Emissivity Separation (TES) was accomplished using the MASTER TES algorithm. Pixel-based accuracy exceeded 50% for 23 species and land cover classes and approached 75% based on pixel majority in reference polygons. An inverse relationship was observed between GV fractions and LST. This relationship varied by dominant plant species/vegetation class, generating unique LST-GV clusters. We hypothesize clustering is a product of environmental controls on species distributions, such as slope, aspect, and elevation as well as species-level differences in canopy structure, rooting depth, water use efficiency, and available soil moisture, suggesting that relationships between LST and plant species will vary seasonally. The potential of HyspIRI as a means of providing these seasonal relationships is discussed.

Related Topics
Physical Sciences and Engineering Earth and Planetary Sciences Computers in Earth Sciences
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