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Fusing meter-resolution 4-D InSAR point clouds and optical images for semantic urban infrastructure monitoring

Wang, Yuanyuan and Zhu, Xiao Xiang and Zeisl, Bernhard and Pollefeys, Marc (2016) Fusing meter-resolution 4-D InSAR point clouds and optical images for semantic urban infrastructure monitoring. IEEE Transactions on Geoscience and Remote Sensing, 55 (1), pp. 14-26. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2016.2554563. ISSN 0196-2892.

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Official URL: http://ieeexplore.ieee.org/document/7587405/


Using synthetic aperture radar (SAR) interferometry to monitor long-term millimeter-level deformation of urban infrastructures, such as individual buildings and bridges, is an emerging and important field in remote sensing. In the state-of-the-art, deformation parameters are retrieved and monitored on a pixel-basis solely in the SAR image domain. But the inevitable side-looking imaging geometry of SAR results in undesired occlusion and layover in urban area, rendering the current method less competent for a semantic-level monitoring of different urban infrastructures. This paper presents a framework of a semantic-level deformation monitoring by linking the precise deformation estimates of SAR interferometry and the semantic classification labels of optical images via a 3-D geometric fusion and semantic texturing. The proposed approach provides the first “SARptical” point cloud of an urban area, which is the TomoSAR point cloud textured with attributes from optical images. This opens a new perspective of InSAR deformation monitoring. Interesting examples on bridge and railway monitoring are demonstrated.

Item URL in elib:https://elib.dlr.de/105768/
Document Type:Article
Title:Fusing meter-resolution 4-D InSAR point clouds and optical images for semantic urban infrastructure monitoring
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Zeisl, BernhardETH ZürichUNSPECIFIED
Pollefeys, MarcETH ZürichUNSPECIFIED
Date:October 2016
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1109/TGRS.2016.2554563
Page Range:pp. 14-26
EditorsEmailEditor's ORCID iD
Plaza, Antonio J.aplaza@unex.esUNSPECIFIED
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Keywords:optical InSAR fusion, coregistration, semantic classification, InSAR, SAR, urban infrastructure monitoring
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 > SAR Signal Processing
Deposited By: Wang, Yuanyuan
Deposited On:18 Aug 2016 15:33
Last Modified:31 Jul 2019 20:03

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