Shi, Yilei and Bamler, Richard and Wang, Yuanyuan and Zhu, Xiao Xiang (2021) Generation of large scale 3-D city models using InSAR and optical data. In: International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2931-2934. IEEE. IGARSS 2021, 2021-07-11 - 2021-07-16, Brussels, Belgium. doi: 10.1109/IGARSS47720.2021.9553691. ISBN 978-1-6654-0369-6. ISSN 2153-7003.
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Official URL: https://ieeexplore.ieee.org/document/9553691
Abstract
Interferometric synthetic aperture radar (InSAR) techniquesare powerful tool for reconstructing the 3-D position of scat-terers, especially for the urban areas. Since the estimationaccuracy depends on the inverse of number of interferogramsand signal-to-noise ratio (SNR), it is necessary to use as manyas possible interferograms in order to achieve more accurateresult. However, the number of interferograms of TanDEM-Xdata is generally limited for most areas. Therefore, in orderto maintain the estimation accuracy, one feasible way is toincrease the SNR. In this work, we proposed a novel frame-work, which integrates the non-local procedure into SARtomography inversion and combines the robust estimation.A large-scale demonstration has been carried out with fiveTanDEM-X bistatic data, which covers the entire city of Mu-nich, Germany. Quantitative evaluation of the reconstructedresult with the LiDAR reference exhibits the standard devi-ation of the height difference is within two meters, whichimplies the proposed framework has great potential for highquality large-scale 3-D urban modeling.
| Item URL in elib: | https://elib.dlr.de/146249/ | ||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||||||
| Additional Information: | So2Sat | ||||||||||||||||||||
| Title: | Generation of large scale 3-D city models using InSAR and optical data | ||||||||||||||||||||
| Authors: |
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| Date: | 12 October 2021 | ||||||||||||||||||||
| Journal or Publication Title: | International Geoscience and Remote Sensing Symposium (IGARSS) | ||||||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||||||
| Open Access: | Yes | ||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||||||
| DOI: | 10.1109/IGARSS47720.2021.9553691 | ||||||||||||||||||||
| Page Range: | pp. 2931-2934 | ||||||||||||||||||||
| Publisher: | IEEE | ||||||||||||||||||||
| ISSN: | 2153-7003 | ||||||||||||||||||||
| ISBN: | 978-1-6654-0369-6 | ||||||||||||||||||||
| Status: | Published | ||||||||||||||||||||
| Keywords: | 3-D urban models, InSAR, TomoSAR,TanDEM-X, global mapping | ||||||||||||||||||||
| Event Title: | IGARSS 2021 | ||||||||||||||||||||
| Event Location: | Brussels, Belgium | ||||||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||||||
| Event Start Date: | 11 July 2021 | ||||||||||||||||||||
| Event End Date: | 16 July 2021 | ||||||||||||||||||||
| Organizer: | IEEE | ||||||||||||||||||||
| 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 - Artificial Intelligence | ||||||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||||||
| Institutes and Institutions: | Remote Sensing Technology Institute > EO Data Science Remote Sensing Technology Institute > Leitungsbereich MF | ||||||||||||||||||||
| Deposited By: | Wang, Yuanyuan | ||||||||||||||||||||
| Deposited On: | 29 Nov 2021 08:13 | ||||||||||||||||||||
| Last Modified: | 24 Apr 2024 20:45 |
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