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Article: Applying an anomaly-detection algorithm for short-term land use and land cover change detection using time-series SAR images
Title | Applying an anomaly-detection algorithm for short-term land use and land cover change detection using time-series SAR images |
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Authors | |
Issue Date | 2010 |
Citation | Giscience And Remote Sensing, 2010, v. 47 n. 3, p. 379-397 How to Cite? |
Abstract | In this study, short-term land use and land cover (LULC) changes caused by human activity were considered as spatial-temporal abnormalities in time-series images. A density-based anomaly detection (DBAD) algorithm was designed to detect the changes. Then the algorithm was applied to RADARSAT time-series images, and synchronous field surveying was performed for validation. The results showed that the DBAD algorithm was good at detecting in-progress construction and newly builtup parcels, with an error of less than 13.3%. A lower detection error was achieved for woodland areas, and a larger error for built-up areas and for some mixed-use land parcels due to the complexity of the parcels. |
Persistent Identifier | http://hdl.handle.net/10722/176296 |
ISSN | 2023 Impact Factor: 6.0 2023 SCImago Journal Rankings: 1.756 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
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dc.contributor.author | Qian, J | en_US |
dc.contributor.author | Li, X | en_US |
dc.contributor.author | Liao, S | en_US |
dc.contributor.author | Yeh, AGO | en_US |
dc.date.accessioned | 2012-11-26T09:08:17Z | - |
dc.date.available | 2012-11-26T09:08:17Z | - |
dc.date.issued | 2010 | en_US |
dc.identifier.citation | Giscience And Remote Sensing, 2010, v. 47 n. 3, p. 379-397 | en_US |
dc.identifier.issn | 1548-1603 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/176296 | - |
dc.description.abstract | In this study, short-term land use and land cover (LULC) changes caused by human activity were considered as spatial-temporal abnormalities in time-series images. A density-based anomaly detection (DBAD) algorithm was designed to detect the changes. Then the algorithm was applied to RADARSAT time-series images, and synchronous field surveying was performed for validation. The results showed that the DBAD algorithm was good at detecting in-progress construction and newly builtup parcels, with an error of less than 13.3%. A lower detection error was achieved for woodland areas, and a larger error for built-up areas and for some mixed-use land parcels due to the complexity of the parcels. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | GIScience and Remote Sensing | en_US |
dc.title | Applying an anomaly-detection algorithm for short-term land use and land cover change detection using time-series SAR images | en_US |
dc.type | Article | en_US |
dc.identifier.email | Yeh, AGO: hdxugoy@hkucc.hku.hk | en_US |
dc.identifier.authority | Yeh, AGO=rp01033 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.2747/1548-1603.47.3.379 | en_US |
dc.identifier.scopus | eid_2-s2.0-77956337678 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-77956337678&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 47 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.spage | 379 | en_US |
dc.identifier.epage | 397 | en_US |
dc.identifier.isi | WOS:000281404300005 | - |
dc.publisher.place | United States | en_US |
dc.identifier.scopusauthorid | Qian, J=18936748300 | en_US |
dc.identifier.scopusauthorid | Li, X=34872691500 | en_US |
dc.identifier.scopusauthorid | Liao, S=7401923181 | en_US |
dc.identifier.scopusauthorid | Yeh, AGO=7103069369 | en_US |
dc.identifier.issnl | 1548-1603 | - |