High-resolution remote sensing mapping of global land water

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• 作者：AnPing Liao ; LiJun Chen ; Jun Chen ; ChaoYing He ; Xin Cao…
• 关键词：global land cover ; land surface water ; 30 m resolution ; classification method ; remote sensing mapping
• 刊名：Science China Earth Sciences
• 出版年：2014
• 出版时间：October 2014
• 年：2014
• 卷：57
• 期：10
• 页码：2305-2316
• 全文大小：3,072 KB
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• 作者单位：AnPing Liao (1)
  LiJun Chen (1)
  Jun Chen (1)
  ChaoYing He (1)
  Xin Cao (2)
  Jin Chen (2)
  Shu Peng (1)
  FangDi Sun (3)
  Peng Gong (4)
  
  1. National Geomatics Center of China, Beijing, 100830, China
  2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
  3. International Institute of Earth System Science, Nanjing University, Nanjing, 210093, China
  4. The Earth System Science Center, Tsinghua University, Beijing, 100084, China
  
• ISSN：1869-1897

文摘

Land water, one of the important components of land cover, is the indispensable and important basic information for climate change studies, ecological environment assessment, macro-control analysis, etc. This article describes the overall study on land water in the program of global land cover remote sensing mapping. Through collection and processing of Landsat TM/ETM+, China’s HJ-1 satellite image, etc., the program achieves an effective overlay of global multi-spectral image of 30 m resolution for two base years, namely, 2000 and 2010, with the image rectification accuracy meeting the requirements of 1:200000 mapping and the error in registration of images for the two periods being controlled within 1 pixel. The indexes were designed and selected reasonably based on spectral features and geometric shapes of water on the scale of 30 m resolution, the water information was extracted in an elaborate way by combining a simple and easy operation through pixel-based classification method with a comprehensive utilization of various rules and knowledge through the object-oriented classification method, and finally the classification results were further optimized and improved by the human-computer interaction, thus realizing high-resolution remote sensing mapping of global water. The completed global land water data results, including Global Land 30-water 2000 and Global Land 30-water 2010, are the classification results featuring the highest resolution on a global scale, and the overall accuracy of self-assessment is 96%. These data are the important basic data for developing relevant studies, such as analyzing spatial distribution pattern of global land water, revealing regional difference, studying space-time fluctuation law, and diagnosing health of ecological environment.