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.
PDF
- Published version
19MB |
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: |
| ||||||||||||||||||||
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 |
Repository Staff Only: item control page