Genetic inverse algorithm for retrieval of component temperature of mixed pixel by multi-angle thermal infrared remote sensing data

作     者：徐希孺 陈良富 庄家礼 

作者机构：1. LARSIS Institute of Remote Sensing Applications Chinese Academy of Sciences 100101 Beijing China 

出 版 物：《Science China Earth Sciences》 (中国科学（地球科学英文版）)

年 卷 期：2001年第44卷第4期

页      面：363-372页

核心收录：

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

基　　金：China National Key-Important Basic Research Plan (Grant No. 95-Y-38) and the Special Funds for Major State Basic Research Project (Grant No. 20000779900) 

主　　题：multi-angle thermal infrared remote sensing, component temperature of mixed pixel, genetic inverse algorithm. 

摘      要：After carefully studying the results of retrieval of land surface temperature(LST) by multi-channel thermal infrared remote sensing data, the authors of this paper point out that its accuracy and significance for applications are seriously damaged by the high correlation coefficient among multi-channel information and its disablement of direct retrieval of component temperature. Based on the model of directional radiation of non-isothermal mixed pixel, the authors point out that multi-angle thermal infrared remote sensing can offer the possibility to directly retrieve component temperature, but it is also a multi-parameter synchronous inverse problem. The results of digital simulation and field experiments show that the genetic inverse algorithm (GIA) is an effective method to fulfill multi-parameter synchronous retrieval. So it is possible to realize retrieval of component temperature with error less than 1K by multi-angle thermal infrared remote sensing data and GIA.