Atmospheric compensation for surface temperature and emissivity separation

摘要

A new method for atmospheric compensation of longwave infrared (LWIR) hyerspectral images is presented. The technique exploits the large amount of data in hyperspectral images to btain the most information about atmospheric and surface parameters of interest. This is doen with Canonical Correlation Analysis (CCA) by casting the problem onto a multivariate framework. The procedure accounts for the joint effects of surface and atmospheric rediation, thus addressing the complex interaction between the Earth's surface properties, thermodynamic state, and the atmosphere. After atmospheric compensation, the calculated surface readiance is used to estimate temperature and emissivity. The technique was tested with radiative transfer model simulations and airborne multispectral data. Results obtained from MODTRAN simulations and the MODerate resolution Imaging Spectrometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (MASTER) airborne sensor show that it is feasible to retrieve land surface temperature and emissivity with 1 deg K and 0.01 accuracies, respectively.