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Automatic registration of a single SAR image and GIS building footprints in a large-scale urban area

Sun, Yao und Montazeri, Sina und Wang, Yuanyuan und Zhu, Xiao Xiang (2020) Automatic registration of a single SAR image and GIS building footprints in a large-scale urban area. ISPRS Journal of Photogrammetry and Remote Sensing, 170, Seiten 1-14. Elsevier. doi: 10.1016/j.isprsjprs.2020.09.016. ISSN 0924-2716.

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Offizielle URL: https://www.sciencedirect.com/science/article/pii/S092427162030263X

Kurzfassung

Existing techniques of 3-D reconstruction of buildings from SAR images are mostly based on multibaseline SAR interferometry, such as PSI and SAR tomography (TomoSAR). However, these techniques require tens of images for a reliable reconstruction, which limits the application in various scenarios, such as emergency response. Therefore, alternatives that use a single SAR image and the building footprints from GIS data show their great potential in 3-D reconstruction. The combination of GIS data and SAR images requires a precise registration, which is challenging due to the unknown terrain height, and the difficulty in finding and extracting the correspondence. In this paper, we propose a framework to automatically register GIS building footprints to a SAR image by exploiting the features representing the intersection of ground and visible building facades, specifically the near-range boundaries in the building polygons, and the double bounce lines in the SAR image. Based on those features, the two data sets are registered progressively in multiple resolutions, allowing the algorithm to cope with variations in the local terrain. The proposed framework was tested in Berlin using one TerraSAR-X High Resolution SpotLight image and GIS building footprints of the area. Comparing to the ground truth, the proposed algorithm reduced the average distance error from 5.91 m before the registration to −0.08 m, and the standard deviation from 2.77 m to 1.12 m. Such accuracy, better than half of the typical urban floor height (3 m), is significant for precise building height reconstruction on a large scale. The proposed registration framework has great potential in assisting SAR image interpretation in typical urban areas and building model reconstruction from SAR images.

elib-URL des Eintrags:https://elib.dlr.de/137998/
Dokumentart:Zeitschriftenbeitrag
Titel:Automatic registration of a single SAR image and GIS building footprints in a large-scale urban area
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Sun, YaoYao.Sun (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Montazeri, SinaSina.Montazeri (at) dlr.dehttps://orcid.org/0000-0002-6732-1381NICHT SPEZIFIZIERT
Wang, YuanyuanYuanyuan.Wang (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Zhu, Xiao Xiangxiao.zhu (at) dlr.dehttps://orcid.org/0000-0001-5530-3613NICHT SPEZIFIZIERT
Datum:Dezember 2020
Erschienen in:ISPRS Journal of Photogrammetry and Remote Sensing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:170
DOI:10.1016/j.isprsjprs.2020.09.016
Seitenbereich:Seiten 1-14
Verlag:Elsevier
ISSN:0924-2716
Status:veröffentlicht
Stichwörter:GIS building footprints, Large-scale, Registration, SAR image, Urban area
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben hochauflösende Fernerkundungsverfahren (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Methodik der Fernerkundung > EO Data Science
Hinterlegt von: Sun, Yao
Hinterlegt am:27 Nov 2020 17:44
Letzte Änderung:23 Okt 2023 13:55

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