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Lidar-based change detection and change-type determination in urban areas

dc.citation.epage981en_US
dc.citation.issue3en_US
dc.citation.spage968en_US
dc.citation.volume34en_US
dc.citation.woscount5
dc.contributor.authorTeo, Tee-Annen_US
dc.contributor.authorShih, Tian-Yuanen_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.department生物科技學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.date.accessioned2014-12-08T15:28:10Z
dc.date.available2014-12-08T15:28:10Z
dc.date.issued2013en_US
dc.description.abstractChange detection of objects, such as buildings, is essential for map updating. Traditionally, detection is usually performed through spectral analysis of multi-temporal images. This article proposes a method that employs multi-temporal interpolated lidar data. The objective of this study is to perform change detection and change-type determination via geometric analysis. A shape difference map is generated between the digital surface models in two different time periods. The areas with small shape differences are treated as non-changed areas and are excluded from the segmentation. The object's properties are then applied to determine the change types. Experimental results demonstrate that the proposed scheme achieves accuracy as high as 80%. Most of the errors from this study occurred in small or vegetation areas.en_US
dc.identifier.doi10.1080/01431161.2012.714504en_US
dc.identifier.issn0143-1161en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF REMOTE SENSINGen_US
dc.identifier.urihttp://dx.doi.org/10.1080/01431161.2012.714504en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/20387
dc.identifier.wosnumberWOS:000309710900014
dc.language.isoen_USen_US
dc.titleLidar-based change detection and change-type determination in urban areasen_US
dc.typeArticleen_US

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