寒区复杂地表冻融状态判别式算法改进  

Improvementon Soil Freeze/Thaw Discriminant Algorithm under Complex Surface Conditions in Cold Regions

作　　者：胡文星[1] 柴琳娜[1] 赵少杰[1] 赵天杰[2] 

机构地区：[1]北京师范大学地表过程与资源生态国家重点实验室,遥感与地理信息系统研究中心,地理学与遥感科学学院,北京100875 [2]中国科学院遥感与数字地球研究所遥感科学国家重点实验室,北京100101

出　　处：《遥感技术与应用》2017年第3期395-405,共11页Remote Sensing Technology and Application

基　　金：国家973计划项目(2013CB733406);国家自然科学基金项目(41301356);遥感科学国家重点实验室自主基金(15ZY04)共同资助

摘　　要：基于冻融土的微波辐射特征,在HUT(Helsinki University of Technology)积雪辐射模型的基础上,引入新的冻土介电常数模型计算冻/融土的介电常数,利用高级积分方程模型(Advanced Integrated Emission Model,AIEM)计算地表发射率,改进了寒区复杂地表微波辐射模型和冻融状态判别式算法。采用AMSR^2(The Advanced Microwave Scanning Radiometer 2)被动微波辐射计亮温数据和地基微波辐射计观测数据进行了地表冻融状态判别式算法精度的验证与比较。结果显示:改进后的判别式算法对冻土的判识精度有明显提升,总体判识精度在82%以上,是一种较可靠的判别模式。Based on the microwave radiation characteristics of frozen and thawed soils,on the basis of the HUT （Helsinki University of Technology） microwave snow emission model,introducing a new frozen soil dielectric model to calculate the dielectric constant of frozen and thawed soils.The Advanced Integrated Emission Model （AIEM） was used to calculate surface emissivity, a multi-frequency microwave radiation model and a soil freeze/thaw discriminant algorithm were improved to consider the complex surface environmental conditions.The classification accuracies of the original and improved soil freeze/thaw discrimi- nant algorithms were tested using the brightness temperature of AMSR2 （The Advanced Microwave Scanning Radiometer 2） products （level 3） and the measured values obtained by ground based microwave radiometer：The results showed that compared to the original discriminant algorithm,the frozen soil classification accuracy of the improved discriminant algorithm was effectively improved and the overall classification accuracy reached 82%.It was a comparatively reliable mode of discrimination.

关 键 词：冻土介电常数 地表冻融 被动微波 判别式算法改进 AMSR2 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]