MODIS影像雪深遥感反演特征参数选择与模型研究  

Study of Characteristic Parametric Selection and Model Construction for Snow Depth Retrieval from MODIS Image

作　　者：刘海[1] 陈晓玲[1,2] 宋珍[1] 殷守敬[1] 

机构地区：[1]武汉大学测绘遥感信息工程国家重点实验室,武汉市珞喻路129号430079 [2]江西师范大学鄱阳湖湿地与流域研究教育部重点实验室,南昌市紫阳大道99号330027

出　　处：《武汉大学学报（信息科学版）》2011年第1期113-116,121,共5页Geomatics and Information Science of Wuhan University

基　　金：国家973计划资助项目(2009CB723905);国家863计划资助项目(2009AA122100);国家自然科学基金资助项目(40721001);国家科技支撑计划资助项目(2008BAK49B01)

摘　　要：在综合分析已有研究成果的基础上,选择MODIS遥感影像,借助灰色系统理论,结合观测站实测雪深数据,选择雪深反演特征参数,构建反演模型,并定义多元回归模型的综合评价系数,进而从构建的多个回归模型中,选择出雪深反演最优模型。Snow depth is an important parameter in snow monitoring.How to select the charactersitic parameter and construct model is one of the key issues in snow depth retrieval using remotely sensed images.In this paper,MODIS images over Tianshan region were used,from which 37 potential retrieval variables were pre-selected,and ten days in-situ snow depth data of seven in-situ observations were used for analysis,Gray system theory,which has the advantage of multi-variable analysis of the small samples was selected to analyse the correlation between snow depth and retrieval parameters,and four characteristic parameters were selected based on above analysis.15 snow depth retrieval models were established.using the selected characteristic parameters,Then a comprehensive evaluation coefficient CEC of multiple regression model was defined using AIC criterion,BIC criterion and Pearson r.Then the optimal retrieval model of snow depth was selected from the above 15 models according to CEC,and the test showed the average relative error retrieval accuracy was 11.2% which was in line with operational monitoring requirements.

关 键 词：雪深 遥感反演 特征参数选择 MODIS 

分 类 号：P237.3[天文地球—摄影测量与遥感]