中文摘要：

在积雪深度研究中,地面资料插值产生的平滑效应以及遥感空间分辨率不足的问题,在很大程度上影响着积雪深度的估计精度。本文采用中高分辨率成像光谱仪（moderate resolution imaging spectro-radiometer,MODIS）和微波扫描辐射计（advanced microwave scanning radiometer-EOS,AMSR-E）融合后的无云积雪面积产品构建虚拟站点,弥补了气象站点少且不均匀的不足,修正雪深克里金插值产生的平滑效应。同时,提出了基于数据同化算法融合以地面观测资料为基础的克里金空间插值雪深、MODIS积雪面积产品和AMSRE微波反演雪深产品的雪深估计方法。以新疆北疆地区为研究区域进行了算法应用及验证,并选取不同海拔的站点观测资料对融合结果进行验证分析,通过均方根、偏差和相关性系数指标检证了该方法能够有效地提高雪深估计精度。

英文摘要：

In snow depth studies,the smoothing effect of ground data interpolation and the low spatial resolution of remote sensing have a great impact on the estimation accuracy.In this paper,by using cloud-removed snow cover products from the fusion of MODIS（moderate resolution imaging spectro-radiometer）and AMSRE（advanced microwave scanning radiometer-EOS）to construct virtual station,we make up the shortage of meteorological stations less and unevenness and correct the smoothing effect of Kriging interpolation.At the same time,a new scheme is proposed to improve the estimation accuracy of snow depth interpolation,which integrates data assimilation algorithm and Kriging method to fuse ground-based snow depth measurements,MODIS snow cover products.and snow depth derived from the AMSR-E microwave brightness temperature.This method was applied in the area of northern Xinjiang.Three independent stations at different elevations were chosen to evaluate fusion results.The results indicate that the proposed algorithm can effectively improve the accuracy of snow depth spatial distribution.