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As more satellite-derived land cover products used in the study of global change,especially climate modeling,assessing their quality has become vitally important.In this study,we developed a distance metric based on the parameters used in weather research and forecasting(WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme(IGBP) classification scheme.We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer(MODIS) products,and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model.Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes,while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes.The degree of disagreement varied significantly among seven regions of China.The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly.High accuracy and fuzzy agreement occurred in the following classes:water,grassland,cropland,and barren or sparsely vegetated.Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals.Some classes need to be improved further;the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling.Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.  相似文献   
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 随着全球气候变化的日益加剧,全球变化研究对全球土地覆盖数据的需要也越来越迫切。目前全球土地覆盖数据产品主要包括由欧洲和美国生产的5类数据产品,其中,美国波士顿大学生产的全球土地覆盖数据产品(即MODIS数据集)和欧洲空间局通过全球合作生产的全球土地覆盖数据产品(即Globcover数据集)具有较好的实效性,应用越来越广泛。由于数据来源、分类系统和分类方法不同,两个数据集在土地覆盖类型的数量和空间分布上有明显的差异。本研究从数据使用者的角度,对比了MODIS和Globcover数据集在黑龙江流域上数量和空间分布的差异,并采用LANDSAT TM/ETM+影像随机采样和野外照片验证两种方式对两个数据集的分类精度进行了验证。结果表明,在黑龙江流域,两个数据集数量和空间分布差异较大。在数量上,两个数据集一级土地覆盖类型均以森林和农田为主,草地次之,但二级土地覆盖类型差异较大。在空间上,二级类空间一致性区域和一级类空间一致性的区域分别仅占流域的22.5%和53.6%。两个数据集精度均不高,一级土地覆盖类型精度约为60%,Globcover数据较MODIS数据破碎化明显,整体精度略低于MODIS数据集,不同的二级土地覆盖类型精度不同。考虑到黑龙江流域的代表性,我们认为Globcover数据集和MODIS数据集可满足较低要求的土地覆盖分析需求。本研究为全球气候变化研究选择合适的数据集提供了基础。  相似文献   
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