Urban area change detection using time series aerial images

Basit Öğe Kaydı
dc.contributor.authorAltuntas C.
dc.date.accessioned2020-03-26T20:11:52Z
dc.date.available2020-03-26T20:11:52Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description2018 ISPRS TC II Mid-term Symposium "Towards Photogrammetry 2020" -- 4 June 2018 through 7 June 2018 -- 136782en_US
dc.description.abstractThe urban area should be imaged in three-dimensional (3D) for planning, inspection and management. In addition fast urbanisation requires detection the urban area changes which have been occurred with new buildings, additional floor to current buildings and excavations. 3D surface model of urban area enables to extracting high information from them. On the other hand high density spatial data should be measured to creating 3D digital terrain surface model. The dense image matching method makes 3D measurement with high density from the images in a short time. The aim of this study is detection the urban area changes via comparison of time series point cloud data from historical stereoscopic aerial images. The changes were detected with the difference of these digital elevation models. The study area was selected from Konya city in Turkey, and it has a large number of new buildings and changes in topography. Dense point cloud data were created from historical aerial images belong to years of 1951, 1975 and 2010. Every three-dimensional point cloud data were registered to global georeferenced coordinate system with ground control points created from the imaged objects such as building corner, fence, wall and etc. Then urban changes were detected with comparing the dense point cloud data by exploiting the iterative closest point (ICP) algorithm. Consequently, the urban changes were detected from point to surface distances between image based point clouds. © Authors 2018.en_US
dc.description.sponsorshipBritish Association for Psychopharmacologyen_US
dc.description.sponsorshipThis study was supported for the project (17401062) by Scientific Research Found (BAP) of Selcuk University.en_US
dc.identifier.doi10.5194/isprs-archives-XLII-2-29-2018en_US
dc.identifier.endpage34en_US
dc.identifier.issn1682-1750en_US
dc.identifier.issue2en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage29en_US
dc.identifier.urihttps://dx.doi.org/10.5194/isprs-archives-XLII-2-29-2018
dc.identifier.urihttps://hdl.handle.net/20.500.12395/37253
dc.identifier.volume42en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInternational Society for Photogrammetry and Remote Sensingen_US
dc.relation.ispartofInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archivesen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectAerial imageen_US
dc.subjectDense point clouden_US
dc.subjectHistorical imageen_US
dc.subjectPhotogrammetryen_US
dc.subjectUrban change detectionen_US
dc.titleUrban area change detection using time series aerial imagesen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu