Estimation of broadband emissivity from satellite multi-channel thermal infrared data using spectral libraries

Abstract

Surface broadband thermal infrared emissivity is an important parameter for estimating the longwave surface energy balance. This study focuses on estimating the broadband emissivity from the emissivities of the five channels on the Advanced Spaceborne Thermal Emission and Reflection Radiometer/Thermal Infrared Radiometer (ASTER/TIR). ASTER is a sensor onboard the Earth Observing System (EOS) Terra satellite launched in 1999, and has five channels in the thermal infrared region (8-12 /spl mu/m). Using this sensor, it is possible to estimate surface spectral emissivity for each channel at a spatial resolution of 90 m. Broadband emissivities (3-14 /spl mu/m) were calculated using two spectral libraries, John Hopkins University Spectral Library (JHU Library) and MODIS UCSB (University of California, Santa Barbara) Emissivity Library (UCSB Library). They ranged from 0.89 to 0.99 for natural surfaces, such as, rocks, soils, vegetation, water, ice, and snow. Then, we assumed that the broadband emissivity can be expressed as a linear combination emissivities for the rive ASTER/TIR channels. The linear regression was calibrated using JHU Library and validated with the UCSB Library. The absolute error on the estimated broadband emissivity was less than 0.01 for 93% of all samples and RMSE was 0.0051 over an emissivity range from 0.91 to 0.99 in validation. Finally, this calibrated regression was applied to emissivities computed from the data acquired with ASTER/TIR over the Jornada Experimental Range in New Mexico to produce a map of broadband emissivity for this area.