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《Journal of Glaciology and Geocryology》 2009-03
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Accuracy Evaluation of the Four Remote Sensing Based Land Cover Products over China

RAN You-hua,LI Xin,LU Ling(Laboratory of Remote Sensing and Geo-Science,Cold and Aird Regions Environmental and Engineering Research Insititute,Chinese Academy of Sciences,Lanzhou Gansu 730000,China)  
Precise global/regional land cover mapping is foundational data in the studies of land surface processes and modelling.The quantitative assessments of the map quality and classification accuracy for the available land cover maps will help to improve the accuracy of land cover mapping in future.Four land cover data sets over China are compared and evaluated.The data sets include Version 2 global land cover dataset of IGBP,the MODIS Land cover map 2001,global land cover map produced by the University of Maryland,and the land cover map from Global Vegetation Monitoring unit of the European Commission Joint Research Centre(GLC2000).The four maps have different classification systems,which makes the comparison difficult.It is necessary to aggregate these maps by reclassifying them using a unified legend system.A large scale,i.e.1∶100 000 land cover map of China was used as the reference data to validate the four maps.The results show that the GLC2000 land cover map has the highest accuracy.But it has obvious rating error locally and its rating accuracy is zero for wetland.The MODIS land cover map ranks second for type area consistency and ranks third for sub fraction overall accuracy as compared with reference data,which may be affect by local rating error.The IGBP land cover map hast good rating accuracy though it has a local rating error and third consistency for type area.The rating accuracy and type area consistency with reference data of UMD land cover map is low wholly.It is believed that the accuracies of all the datasets can not meet the requirement of land surface modelling.Addition,an information fusion strategy is proposed to produce a higher accuracy land cover map of China,whose classification system should be compatible with the well-accepted classification system used in land surface modelling.
【Fund】: 国家自然科学基金项目(40871190);; 中国科学院资源与环境信息系统国家重点实验室2008年开放研究基金项目;; 中国科学院创新团队国际合作伙伴计划“干旱区内陆河流域水问题基础研究”(CXTD-Z2005-2)资助
【CateGory Index】: X87
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