Please use this identifier to cite or link to this item: https://doi.org/10.1109/36.718845
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dc.titleApplication of multitemporal ers-2 synthetic aperture radar in delineating rice cropping systems in the mekong river delta, vietnam
dc.contributor.authorLiew, S.C.
dc.date.accessioned2014-11-28T07:57:16Z
dc.date.available2014-11-28T07:57:16Z
dc.date.issued1998
dc.identifier.citationLiew, S.C. (1998). Application of multitemporal ers-2 synthetic aperture radar in delineating rice cropping systems in the mekong river delta, vietnam. IEEE Transactions on Geoscience and Remote Sensing 36 (5 PART 1) : 1412-1420. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/36.718845" target="_blank">https://doi.org/10.1109/36.718845</a>
dc.identifier.issn01962892
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/112828
dc.description.abstractIn this paper, we report the use of multitemporal ERS-2 satellite synthetic aperture radar (SAR) images in delineating and mapping areas under different rice cropping systems in the Mekong River Delta, Vietnam. Change index maps were generated from seven images acquired between May and December 1996. Using a 3-dB threshold, the pixels in each change index (CI) map were classified into one of three classes: increasing, decreasing, or constant backscattering. Five of the CI maps were used to generate a composite map with 243 possible change classes. These change classes were grouped into thematic categories of rice cropping systems using two methods: human visual inspection and a semiautomatic hierarchical clustering algorithm. The derived thematic maps were compared with SPOT scenes acquired during the same rice seasons. © 1998 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/36.718845
dc.sourceScopus
dc.subjectAgriculture
dc.subjectClustering methods
dc.subjectImage classification
dc.subjectRemote sensing
dc.subjectSynthetic aperture radar (sar)
dc.subjectVegetation mapping
dc.typeArticle
dc.contributor.departmentCTR FOR REM IMAGING,SENSING & PROCESSING
dc.description.doi10.1109/36.718845
dc.description.sourcetitleIEEE Transactions on Geoscience and Remote Sensing
dc.description.volume36
dc.description.issue5 PART 1
dc.description.page1412-1420
dc.description.codenIGRSD
dc.identifier.isiutNOT_IN_WOS
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