利用被动微波遥感数据反演我国积雪深度及其精度评

考虑到我国西部地区使用SSM/I全球算法将高估积雪深度,故以东经105°为界将我国分为东部和西部。在西部地区采用修正后的雪深算法,东部地区沿用全球算法。对散射系数较高,容易和积雪相混淆的降雨、寒漠和冻土地表类型,通过积雪分类树进行剔除,进而发展了一套适用于全国积雪深度的业务化反演方案。最后利用MODIS积雪产品对冬季90天的结果进行了精度评价,总体精度平均达到86.4%,最高精度达到95.5%,Kappa系数均值为65.5%,最大值达到86.2%。

Retrieval of Snow Depth in China by Passive Microwave Remote Sensing Data and Its Accuracy Assessment

Retrieval of Snow Depth in China by Passive MicrowaveRemote Sensing Data and Its Accuracy AssessmentCHE Tao,LI Xin(Cold and Arid Regions Environmental and Engineering Research Institute,Chinese Academy ofSceiences,Lanzhou Gansu730000,China)Abstract:Considering the overestimation of snow depth in West China using the global algorithm, thegeographic region is divided into two parts by 105°E. The modified and global algorithms are used toretrieve the snow depth in West and East part, respectively. However, the retrieval of snow cover anddepth will be overestimated due to the influence of precipitation, cold desert, and frozen ground.Therefore, for setting up the operational scheme, a land surface type classification tree based on the SSM/I data has been used to remove these factors. In final, the MODIS snow products in 2000/2001 wintershave been collected for the assessment of accuracy from passive microwave remote sensing data. In theninety days, the means of overall accuracy and Kappa coefficient are 86% and 66%, respectively.Key words:Snow depth, Passive microwave, Remote sensing, SSM/I, Assessment of accuracy