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Fusing Spaceborne SAR Interferometry and Street View Images for 4D Urban Modeling

Wang, Yuanyuan and Kang, Jian and Zhu, Xiao Xiang (2018) Fusing Spaceborne SAR Interferometry and Street View Images for 4D Urban Modeling. In: 2018 21st international conference on information fusion, pp. 1601-1606. FUSION 2018, 10.-13. Juli 2018, Cambridge, UK. DOI: 10.23919/ICIF.2018.8455498 ISBN 978-0-9964527-6-2

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Official URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8455498

Abstract

Obtaining city models in a large scale is usually achieved by means of remote sensing techniques, such as synthetic aperture radar (SAR) interferometry and optical image stereogrammetry. Despite the controlled quality of these products, such observation is restricted by the characteristics of their sensor platform, such as revisit time and spatial resolution. Over the last decade, the rapid development of social media has accumulated vast amount of freely available online images. Despite their uncontrolled quality, these images constitute a set of redundant spatial-temporal observations of our dynamic 3D urban environment. These images contain useful information that can complement the remote sensing data, especially the SAR images. This paper presents a preliminary study of fusing social media and SAR images, for the reconstruction of spatial-temporal (hence 4D) city models. We describe a general approach to geometrically combine the information of these two types of images that are nearly impossible to even coregister without a precise 3D city model due to their distinct imaging geometry. It is demonstrated that, one can obtain a new kind of city model that includes high resolution optical texture for better scene understanding and the dynamics of individual buildings up to the precision of millimeter retrieved from SAR interferometry.

Item URL in elib:https://elib.dlr.de/128183/
Document Type:Conference or Workshop Item (Speech)
Additional Information:so2sat
Title:Fusing Spaceborne SAR Interferometry and Street View Images for 4D Urban Modeling
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Wang, YuanyuanTUMUNSPECIFIED
Kang, JianTUMUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-LMFUNSPECIFIED
Date:June 2018
Journal or Publication Title:2018 21st international conference on information fusion
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.23919/ICIF.2018.8455498
Page Range:pp. 1601-1606
ISBN:978-0-9964527-6-2
Status:Published
Keywords:SAR, TomoSAR, structure from motion, optical images, 3D, 4D, urban model, fusion
Event Title:FUSION 2018
Event Location:Cambridge, UK
Event Type:international Conference
Event Dates:10.-13. Juli 2018
Organizer:University of Cambridge
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Wang, Yuanyuan
Deposited On:03 Jul 2019 09:41
Last Modified:31 Jul 2019 20:25

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