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Area Errors Between Grid Imagery Boundaries and Vector Actual Boundaries Identifying Waterbodies from Remote Sensing Imagery

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Geo-Informatics in Resource Management and Sustainable Ecosystem ( 2015, GRMSE 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 569))

Abstract

In identifying water bodies from remote sensing imagery, a mismatch between grid data boundary and vector boundary has always existed but was seldom studied. Therefore, area errors between grid imagery boundaries and vector real boundaries are the subject of this study. A solution based on the sub-pixel classification method was developed to analyse these errors. A case study from Lake Manasarowar in China showed that the area error proposed in this study is larger than that from different interpretation methods. It was concluded that uncertainties from mixed boundary pixels were greater than that from different methods for identifying lake area using the remote sensing imagery in the study area. Overall, area error analyses for grid imagery boundaries and vector real boundaries are necessary for identifying water bodies from remote sensing imagery. It is also useful for the interpretation of other continuous bodies, such as glaciers.

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Acknowledgements

This study was supported and funded by the International Science & Technology Cooperation Program of China (2013DFA91700), National Key Technology Support Program of China (2012BAC06B02) and National Natural Science Foundation of China (41201035).

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Authors and Affiliations

  1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Zhaofei Liu & Zhijun Yao

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  1. Zhaofei Liu
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  2. Zhijun Yao
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Correspondence to Zhaofei Liu or Zhijun Yao .

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Editors and Affiliations

  1. Wuhan University , Wuhan, China

    Fuling Bian

  2. Eastern Michigan University , Ypsilanti, China

    Yichun Xie

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Liu, Z., Yao, Z. (2016). Area Errors Between Grid Imagery Boundaries and Vector Actual Boundaries Identifying Waterbodies from Remote Sensing Imagery. In: Bian, F., Xie, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2015 2015. Communications in Computer and Information Science, vol 569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49155-3_71

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  • DOI: https://doi.org/10.1007/978-3-662-49155-3_71

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