Improved Remote Sensing Retrieval of Land Surface Temperature in the Thermal Infrared (TIR) Using Visible/Short Wave Infrared (VSWIR) Imaging Spectrometer Estimated Water Vapor

Abstract:

Land surface temperature (LST) is an important parameter in many ecological studies, where processes such as evapotranspiration have impacts at temperature gradients less than 1 K. Current errors in standard MODIS and ASTER LST products are greater than 1 K, and for ASTER can be greater than 2 K in humid conditions due to incomplete atmospheric correction of atmospheric water vapor. Estimates of water vapor, either derived from visible-to-shortwave-infrared (VSWIR) remote sensing data or taken from weather simulation data such as NCEP, can be combined with coincident Thermal-Infrared (TIR) remote sensing data to yield improved accuracy in LST measurements.

This study compares LST retrieval accuracies derived using the standard JPL MASTER Temperature Emissivity Separation (TES) algorithm, and the Water Vapor Scaling (WVS) atmospheric correction method proposed for the Hyperspectral Infrared Imager, or HyspIRI, mission with ground observations. The 2011 ER-2 Delano/Lost Hills flights acquired TIR data from the MODIS/ASTER Simulator (MASTER) and VSWIR data from Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) instruments flown concurrently. The TES and WVS retrieval methods are run with and without high spatial resolution AVIRIS-derived water vapor maps to assess the improvement using VSWIR water vapor estimates. We find improvement using VSWIR derived water vapor maps in both cases, with the WVS method being most accurate overall. For closed canopy agricultural vegetation we observed canopy temperature retrieval RMSEs of 0.49 K and 0.70 K using the WVS method on MASTER data with and without AVIRIS derived water vapor, respectively.