Article: A matching algorithm for detecting land use changes using case-based reasoning
| Title | A matching algorithm for detecting land use changes using case-based reasoning |
|---|---|
| Authors | Xia, L3 Yeh, AGO1 Qian, JP2 3 Ai, B3 Qi, Z1 |
| Issue Date | 2009 |
| Publisher | American 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?] |
| Abstract | The 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. |
| ISSN | 0099-1112 2011 Impact Factor: 1.048 2011 SCImago Journal Rankings: 0.050 |
| References | References in Scopus |
| dc.contributor.author | Xia, L |
|---|---|
| dc.contributor.author | Yeh, AGO |
| dc.contributor.author | Qian, JP |
| dc.contributor.author | Ai, B |
| dc.contributor.author | Qi, Z |
| dc.date.accessioned | 2010-10-31T13:36:50Z |
| dc.date.available | 2010-10-31T13:36:50Z |
| dc.date.issued | 2009 |
| dc.description.abstract | The 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. |
| dc.description.nature | Link_to_subscribed_fulltext |
| dc.identifier.citation | Photogrammetric Engineering And Remote Sensing, 2009, v. 75 n. 11, p. 1319-1332 [How to Cite?] |
| dc.identifier.epage | 1332 |
| dc.identifier.hkuros | 182888 |
| dc.identifier.issn | 0099-1112 2011 Impact Factor: 1.048 2011 SCImago Journal Rankings: 0.050 |
| dc.identifier.issue | 11 |
| dc.identifier.scopus | eid_2-s2.0-72449176358 |
| dc.identifier.spage | 1319 |
| dc.identifier.uri | http://hdl.handle.net/10722/127633 |
| dc.identifier.volume | 75 |
| dc.language | eng |
| dc.publisher | American Society for Photogrammetry and Remote Sensing. The Journal's web site is located at http://www.asprs.org/publications/pers |
| dc.publisher.place | United States |
| dc.relation.ispartof | Photogrammetric Engineering and Remote Sensing |
| dc.relation.references | References in Scopus |
| dc.title | A matching algorithm for detecting land use changes using case-based reasoning |
| dc.type | Article |
Author Affiliations
- The University of Hong Kong
- Guangzhou Institute of Geography
- Sun Yat-Sen University