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Article: A matching algorithm for detecting land use changes using case-based reasoning

TitleA matching algorithm for detecting land use changes using case-based reasoning
Authors
Issue Date2009
PublisherAmerican Society for Photogrammetry and Remote Sensing. The Journal's web site is located at http://www.asprs.org/publications/pers
Citation
Photogrammetric Engineering And Remote Sensing, 2009, v. 75 n. 11, p. 1319-1332 How to Cite?
AbstractThe paper deals with change detection using time series SAR images. SAR provides a unique opportunity for detecting land-use changes within short intervals (e.g., monthly) in tropical and sub-tropical regions with cloud cover. Traditional change detection methods mainly rely on per-pixel spectral information but ignore per-object structural information. In this study, a new method is presented that integrates object-oriented analysis with case-based reasoning (CBR) for change detection. Object-oriented analysis is carried out to retrieve a variety of features, such as tone, shape, texture, area, and context. An incremental segmentation technique is proposed for deriving change objects from multi-temporal Radarsat images. Feature selection based on genetic algorithms is carried out to determine the optimal set of features for change detection. A CBR matching algorithm is developed to identify the temporal positions and the kind of changes. It is based on the weighted k-Nearest Neighbor classification using an accumulative similarity measure. The comparison of the four combinations of change detection methods, object-based or pixel-based plus case-based or rule-based, is carried out to validate the performance of this proposed method. The analysis shows that this integrated approach has provided an efficient way of detecting land-use changes at monthly intervals by using multi-temporal SAR images. © 2009 American Society for Photogrammetry and Remote Sensing.
Persistent Identifierhttp://hdl.handle.net/10722/127633
ISSN
2014 Impact Factor: 1.608
2014 SCImago Journal Rankings: 1.114
References

 

DC FieldValueLanguage
dc.contributor.authorXia, Len_HK
dc.contributor.authorYeh, AGOen_HK
dc.contributor.authorQian, JPen_HK
dc.contributor.authorAi, Ben_HK
dc.contributor.authorQi, Zen_HK
dc.date.accessioned2010-10-31T13:36:50Z-
dc.date.available2010-10-31T13:36:50Z-
dc.date.issued2009en_HK
dc.identifier.citationPhotogrammetric Engineering And Remote Sensing, 2009, v. 75 n. 11, p. 1319-1332en_HK
dc.identifier.issn0099-1112en_HK
dc.identifier.urihttp://hdl.handle.net/10722/127633-
dc.description.abstractThe paper deals with change detection using time series SAR images. SAR provides a unique opportunity for detecting land-use changes within short intervals (e.g., monthly) in tropical and sub-tropical regions with cloud cover. Traditional change detection methods mainly rely on per-pixel spectral information but ignore per-object structural information. In this study, a new method is presented that integrates object-oriented analysis with case-based reasoning (CBR) for change detection. Object-oriented analysis is carried out to retrieve a variety of features, such as tone, shape, texture, area, and context. An incremental segmentation technique is proposed for deriving change objects from multi-temporal Radarsat images. Feature selection based on genetic algorithms is carried out to determine the optimal set of features for change detection. A CBR matching algorithm is developed to identify the temporal positions and the kind of changes. It is based on the weighted k-Nearest Neighbor classification using an accumulative similarity measure. The comparison of the four combinations of change detection methods, object-based or pixel-based plus case-based or rule-based, is carried out to validate the performance of this proposed method. The analysis shows that this integrated approach has provided an efficient way of detecting land-use changes at monthly intervals by using multi-temporal SAR images. © 2009 American Society for Photogrammetry and Remote Sensing.en_HK
dc.languageengen_HK
dc.publisherAmerican Society for Photogrammetry and Remote Sensing. The Journal's web site is located at http://www.asprs.org/publications/persen_HK
dc.relation.ispartofPhotogrammetric Engineering and Remote Sensingen_HK
dc.titleA matching algorithm for detecting land use changes using case-based reasoningen_HK
dc.typeArticleen_HK
dc.identifier.emailYeh, AGO: hdxugoy@hkucc.hku.hken_HK
dc.identifier.authorityYeh, AGO=rp01033en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-72449176358en_HK
dc.identifier.hkuros182888en_HK
dc.identifier.hkuros218399-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-72449176358&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume75en_HK
dc.identifier.issue11en_HK
dc.identifier.spage1319en_HK
dc.identifier.epage1332en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridXia, L=34874194600en_HK
dc.identifier.scopusauthoridYeh, AGO=7103069369en_HK
dc.identifier.scopusauthoridQian, JP=18936748300en_HK
dc.identifier.scopusauthoridAi, B=35306437300en_HK
dc.identifier.scopusauthoridQi, Z=35307702300en_HK

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