热红外联合被动微波重构裸土区地表温度时间序列数据算法  

Algorithm of reconstructing bare soil temperature time series by combining thermal infrared and passive microwave remote sensing technology

作　　者：马红章[1,2] 柳钦火[2] 杨乐[2] 杜鹤娟[2] 施建[2] 

机构地区：[1]中国石油大学(华东)物理科学与技术学院,山东东营266555 [2]中国科学院遥感应用研究所遥感科学国家重点实验室,北京100101

出　　处：《红外与激光工程》2011年第3期418-423,共6页Infrared and Laser Engineering

基　　金：国家自然科学基金重点项目(40730525);国家重点基础研究计划项目(973计划)(2007CB714401)

摘　　要：在进行一定区域地表温度时间序列的研究中,常遇到由于天气原因造成的温度数据缺失问题,针对这一突出问题,在分析土壤发射率数据库的基础上,提出了一种裸露地表晴空时段热红外、微波亮温数据与非晴空时段微波亮温数据相结合来获取时间序列中缺失的地表温度数据的算法。此算法不仅解决了被动微波进行地表温度反演过程中下垫面发射率难以确定的问题,而且算法简捷、计算量小。通过理论分析和数据验证得出算法本身造成的温度反演的均方根误差小于0.9 K,数据验证结果的均方根误差小于1.74 K,表明了所提出算法的可行性与合理性。In the research of the land surface temperature time series,the critical problem is the miss of partial temperature data due to bad weather.Therefore,a novel method based on the analysis of soil emissivity database was put forward.The core of the method was to reconstruct bare soil temperature time series by means of combining thermal infrared and passive microwave remote sensing technology.It conquered the difficulty of determining the land microwave emissivity in the process of land surface temperature inversion by passive microwave remote sensing.Through the theoretical analysis of the algorithm and data verification,the retrieval temperature is accurate,and its root mean square error is less than 0.9 K caused by algorithm itself and is less than 1.74 K from data validation result.It shows that the algorithm proposed in this paper is reasonable and feasible.

关 键 词：时间序列 地表温度 微波亮温 AIEM模型 

分 类 号：P237[天文地球—摄影测量与遥感] TP79[天文地球—测绘科学与技术]