摘要
针对MODIS每日积雪产品中云覆盖现象严重这一问题,以中国干旱区作为研究对象,结合AMSR-E被动微波雪深数据,采用多时相、多传感器数据融合的方法进行去云处理,获取MODIS每日,4 d,8 d和MODIS与AM-SR-E融合后的每日,4 d与8 d共6种新的积雪产品,并分别提取其积雪持续日数(SCD)。对比结果显示,MODIS与AMSR-E多传感器的阈值法4日融合产品在融合算法效率、云去除效果和融合后保持较高分类精度方面均有较好表现,其融合后的无云产品在全天气条件下具有96%的整体分类精度、80%的雪分类精度和99%的陆地分类精度,大大高于研究区原MODIS Terra-Aqua每日融合积雪产品全天候条件下64%,32%和70%的整体、雪、陆分类精度;并且由其提取的积雪持续日数不仅在最大程度上保持了原MODIS产品高的空间分辨率,而且精度较高,对研究区积雪的空间分布状况有很好反映。
Cloud coverage in daily snow cover products is a main obstacle in using Moderate Resolution Imaging Spectroradiometer（MODIS）.In this study,the multi-temporal and multi-sensor combination approaches are applied to reduce cloud obscuration with Aqua Advanced Microwave Scanning Radiometer for NASA＇S Earth Observing System（AMSR-E） snow depth products introduced as the auxiliary data to develop 6 new kinds of snow cover products.Different snow cover duration days（SCD） maps are developed from these combined products.The results are as follows：（1） MODIS and AMSR-E 4-day threshold-combined snow cover product performed well in algorithm efficiency,cloud-reducing effect and capability in maintaining relatively high spatiotemporal resolutions;（2） Under all weather conditions,the overall,snow and land accuracies of the resulted cloud-free products were 96%,80% and 99%,and they were significantly higher than 64%,32% and 70% of the original MODIS Terra and Aqua combination product,respectively;（3） The SCD map generated from this product could not only maintain a high spatial resolution of the original MODIS product,but also could precisely reflect the spatial distribution of the snow cover status in the study area.
出处
《干旱区研究》
CSCD
北大核心
2012年第2期312-319,共8页
Arid Zone Research
基金
国家自然科学基金项目(40971188)
