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Article: High-resolution remote sensing mapping of global land water
Title | High-resolution remote sensing mapping of global land water |
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Authors | |
Keywords | remote sensing mapping land surface water classification method 30 m resolution global land cover |
Issue Date | 2014 |
Citation | Science China Earth Sciences, 2014, v. 57, n. 10, p. 2305-2316 How to Cite? |
Abstract | © 2014, Science China Press and Springer-Verlag Berlin Heidelberg. 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. |
Persistent Identifier | http://hdl.handle.net/10722/296744 |
ISSN | 2023 Impact Factor: 6.0 2023 SCImago Journal Rankings: 1.654 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Liao, An Ping | - |
dc.contributor.author | Chen, Li Jun | - |
dc.contributor.author | Chen, Jun | - |
dc.contributor.author | He, Chao Ying | - |
dc.contributor.author | Cao, Xin | - |
dc.contributor.author | Chen, Jin | - |
dc.contributor.author | Peng, Shu | - |
dc.contributor.author | Sun, Fang Di | - |
dc.contributor.author | Gong, Peng | - |
dc.date.accessioned | 2021-02-25T15:16:35Z | - |
dc.date.available | 2021-02-25T15:16:35Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | Science China Earth Sciences, 2014, v. 57, n. 10, p. 2305-2316 | - |
dc.identifier.issn | 1674-7313 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296744 | - |
dc.description.abstract | © 2014, Science China Press and Springer-Verlag Berlin Heidelberg. 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. | - |
dc.language | eng | - |
dc.relation.ispartof | Science China Earth Sciences | - |
dc.subject | remote sensing mapping | - |
dc.subject | land surface water | - |
dc.subject | classification method | - |
dc.subject | 30 m resolution | - |
dc.subject | global land cover | - |
dc.title | High-resolution remote sensing mapping of global land water | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/s11430-014-4918-0 | - |
dc.identifier.scopus | eid_2-s2.0-84920257035 | - |
dc.identifier.volume | 57 | - |
dc.identifier.issue | 10 | - |
dc.identifier.spage | 2305 | - |
dc.identifier.epage | 2316 | - |
dc.identifier.isi | WOS:000343363600004 | - |
dc.identifier.issnl | 1869-1897 | - |