A Physics Based on Statistics Algorithm for Retrieving Land Surface Temperature and Soil Moisture From AMSR-E Passive Microwave Data

摘要

A regression analysis between brightness of all AMSR bands and MODIS land surface temperature product provided by NASA indicated the 89VGHZ is the best single band to retrieve land surface temperature. According to simulation analysis of AIEM, we propose an algorithm for retrieving land surface temperature from AMSR-E data. The analysis results (more 800,000 pixel data set) indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately, the land surface at least are classified into two groups: non-snow covered land surface and snow covered land surface. In order to improve the practical and accuracy of the algorithm, we build different equation for different range of temperature. The average land surface temperature error is about 2-3℃ relative to the MODIS LST product. On the other hand, the emissivity of passive microwave is very important parameter for retrieving soil moisture. We compute the emissivty through land surface temperature. After analyzing the relationship between the emssivity and soil moisture by utilizing the simulation data of AIEM, we propose a method to retrieve the soil moisture and the preliminary analysis indicate that this method is available which partly eliminate the influence of roughness.