MODIS数据估算区域蒸散量的空间尺度误差纠正  

Spatial-scale error correction methods for regional fluxes retrieval using MODIS data

作　　者：辛晓洲[1] 刘雅妮[1] 柳钦火[1] 唐勇[1] 

机构地区：[1]遥感科学国家重点实验室中国科学院遥感应用研究所,北京100101

出　　处：《遥感学报》2012年第2期207-231,共25页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家重点基础研究发展计划(973计划)(编号:2007CB714400);国家自然科学基金(编号:40971204;40730525;40601067);中国科学院知识创新工程重要方向性项目(编号:KZCX2-YW-313)~~

摘　　要：探讨了使用中高分辨率卫星数据提供的地表分类以及植被指数信息与中低分辨率卫星数据相结合,在混合像元内部进行亚像元处理,以纠正混合像元造成的通量估算误差的方法。其意义在于利用中低分辨率卫星数据进行长期大面积蒸散监测时,只需要少量的中高分辨率数据支持,就可以在一定程度上改善监测结果,具有很好的可操作性。Large numbers of important researches have been done to estimate regional surface heat fluxes using remote sens- ing data over the past few decades. Due to the spatial heterogeneity of the land surface on a regional scale, many problems still need to be explored. Clearly, for landscapes with significant variability in vegetation cover, type, architecture, and moisture, due to the large contrasts in surface temperature, vegetation cover, surface roughness length and zero plane displacement height, the application of a land surface model to a mixed pixel causes significant errors. In this paper, we discussed the method of combin- ing the land cover information and remotely sensed vegetation index provided by Landsat data and Moderate Resolution Imaging Spectroradiometer （MODIS） data to correct spatial-scale errors. It makes full use of the advantages of the temporal resolutions of MODIS data and spatial resolutions of Landsat data to construct a regional evapotranspiration model, which meets the require- ments of spatial heterogeneity scale and makes the higher frequency of large area flux monitoring more operational.

关 键 词：蒸散 卫星遥感 混合像元 空间尺度误差 亚像元处理 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] P33[自动化与计算机技术—控制科学与工程]