The Production of China Land Cover Data for Version 1.0 Global Map
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摘要: 介绍了全球地图第一版中国土地覆盖分类产品的遥感数据源、数据处理方法及结果,详细介绍了非监督聚类和决策树分类相结合的区域级土地覆盖分类方法及处理步骤,并以2003年全年的MODIS/TERRA16d合成产品MOD43B4为主要遥感数据源,采用先进行影像聚类,然后以聚类结果为处理单元进行多时相多特征决策树分类,得到了覆盖全国、约1km分辨率的土地覆盖分类结果。采用室内精度评定和外业验证两种方法对分类结果进行了检验,生成的中国土地覆盖分类产品的精度为89.14%。Abstract: This paper describes the production of China land cover data for version 1.0 Global Map with the emphasis on the developed land cover classification methodology-a combination of unsupervised image clustering and supervised decision tree classification. The 23 MODIS/TERRA 16 d composites (MOD43B4 product) acquired over the whole year of 2003 are the main remote sensing data sources. Firstly,the composite in the period of August 13 to 28 which corresponds to the greenest image of the year was segmented with unsupervised clustering algorithm. The output class number is set to 60 in order to keep any subtle difference between different land cover types. Further clustering is performed to the time average of four composites starting on July 12 and ending on Sept. 13 with output class numbers reduced to 40. The polygons output from the two-round clustering are then classified into 16 land cover types using a decision tree classifier. The MODIS spectral reflectance and two indexes of multiple MODIS composites consist of the variables of the decision tree. The accuracy of the final classification result was evaluated by comparison to existing 1∶500 000 China land use map and 1∶1 000 000 China vegetation map and other high resolution images. This evaluation indicates the overall accuracy of China land cover product is 89.14%. At the same time,22 filed sites were selected around Beijing as check points to compare the classification result with the ground truth,which suggests a similar evaluation of the accuracy.
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Keywords:
- MODIS /
- land cover /
- image classification /
- decision tree /
- unsupervised clustering
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