Comparison of needleleaf deciduous forest and needleleaf evergreen forest in the GLCNMO with IGBP discover and GLC2000 product

2010 IEEE International Geoscience and Remote Sensing Symposium Pub Date : 2010-07-25 DOI:10.1109/IGARSS.2010.5651660

G. Tana, H. Letu, B. Erdenee, R. Tateishi

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Abstract

The Global Land Cover by National Mapping Organizations (GLCNMO) is the product of the Global Mapping Project organized by International Steering Committee for Global Mapping (ISCGM). The GLCNMO is a global 1km land cover data set produced by 16-day composite MODIS data observed in 2003. The accuracy assessment of the map has been completed by a stratified random sampling method. The overall accuracy is 76.5%. The accuracy assessment result also shows that the needleleaf evergreen forest and the needleleaf deciduous forest were misclassified into each other. With this problem in mind, Needleleaf evergreen forest and Needleleaf deciduous forest in the GLCNMO were selected for reclassification. In the new classification process, the NDVI patterns were used. Finally, the needleleaf evergreen forest and the needleleaf deciduous forest in the GLCNMO were compared with the same land cover types in other two global land cover products IGBP DISCover and GLC2000 from total pixel number, per-pixel and the ground truth data points of view.

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利用IGBP发现和GLC2000产品比较GLCNMO针叶落叶林和针叶常绿林

国家测绘组织全球土地覆盖(GLCNMO)是由全球测绘国际指导委员会(ISCGM)组织的全球测绘项目的产物。GLCNMO是由2003年观测到的16天MODIS数据合成的全球1公里土地覆盖数据集。采用分层随机抽样的方法完成了地图的精度评估。总体准确率为76.5%。准确度评价结果还表明，针叶常绿林和针叶落叶林被误分为两类。针对这一问题，选择GLCNMO的针叶常绿林和针叶落叶林进行重新分类。在新的分类过程中，采用了NDVI模式。最后，将GLCNMO的针叶常绿林和针叶落叶林与其他两个全球土地覆盖产品IGBP DISCover和GLC2000的相同土地覆盖类型从总像元数、每像元数和地面真值数据的角度进行比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2010 IEEE International Geoscience and Remote Sensing Symposium

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