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

Sun, Yao and Montazeri, Sina and Wang, Yuanyuan and 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, pp. 1-14. Elsevier. doi: 10.1016/j.isprsjprs.2020.09.016. ISSN 0924-2716.

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

Abstract

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.

Item URL in elib:https://elib.dlr.de/137998/
Document Type:Article
Title:Automatic registration of a single SAR image and GIS building footprints in a large-scale urban area
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Sun, YaoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Montazeri, SinaUNSPECIFIEDhttps://orcid.org/0000-0002-6732-1381UNSPECIFIED
Wang, YuanyuanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Zhu, Xiao XiangUNSPECIFIEDhttps://orcid.org/0000-0001-5530-3613UNSPECIFIED
Date:December 2020
Journal or Publication Title:ISPRS Journal of Photogrammetry and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:170
DOI:10.1016/j.isprsjprs.2020.09.016
Page Range:pp. 1-14
Publisher:Elsevier
ISSN:0924-2716
Status:Published
Keywords:GIS building footprints, Large-scale, Registration, SAR image, Urban area
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Sun, Yao
Deposited On:27 Nov 2020 17:44
Last Modified:23 Oct 2023 13:55

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