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Wang, Yuanyuan und Zhu, Xiao Xiang und Zeisl, Bernhard und 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. IEEE - Institute of Electrical and Electronics Engineers. ISSN 0196-2892. (eingereichter Beitrag)
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Offizielle URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?reload=true&punumber=36
Kurzfassung
Synthetic aperture radar (SAR) interferometry is the only imaging-based method for assessing long-term millimetre-level deformation of individual building over a large area from space, credited to the availability of meter-resolution spaceborne SAR data, and the development in advanced InSAR techniques, such as SAR tomography. However, the inevitable SAR side-looking imaging geometry results in undesired occlusion and layover especially in urban areas, rendering the SAR images difficult to interpret. Aiming at a semantic-level urban infrastructure monitoring, this paper proposed an algorithm to bridge the precise deformation estimates of InSAR and good visual interpretability of optical images by a strict 3-D geometric fusion of SAR and optical images, which has not been mentioned for large urban area so far. Via the precise geometrical fusion, the semantics derived from optical image can be fused to the InSAR point clouds. The proposed approach provides the first InSAR point cloud of an entire urban area textured with optical attributes. Hence, the InSAR deformation analysis can be done systematically in a semantic level, instead of the current pixel-wised analysis and manual identification of the regions of interest. Examples on bridges and railway segments monitoring are demonstrated.
| elib-URL des Eintrags: | https://elib.dlr.de/98802/ | ||||||||||||||||||||
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| Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||
| Titel: | Fusing meter-resolution 4-D InSAR point clouds and optical images for semantic urban infrastructure monitoring | ||||||||||||||||||||
| Autoren: |
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| Datum: | 2016 | ||||||||||||||||||||
| Erschienen in: | IEEE Transactions on Geoscience and Remote Sensing | ||||||||||||||||||||
| Referierte Publikation: | Ja | ||||||||||||||||||||
| Open Access: | Nein | ||||||||||||||||||||
| Gold Open Access: | Nein | ||||||||||||||||||||
| In SCOPUS: | Ja | ||||||||||||||||||||
| In ISI Web of Science: | Ja | ||||||||||||||||||||
| Herausgeber: |
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| Verlag: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||||||||||
| ISSN: | 0196-2892 | ||||||||||||||||||||
| Status: | eingereichter Beitrag | ||||||||||||||||||||
| Stichwörter: | optical InSAR fusion, semantic classification, InSAR, SAR, infrastructure monitoring | ||||||||||||||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
| HGF - Programm: | Raumfahrt | ||||||||||||||||||||
| HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||
| DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||
| DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | R - Vorhaben hochauflösende Fernerkundungsverfahren (alt) | ||||||||||||||||||||
| Standort: | Oberpfaffenhofen | ||||||||||||||||||||
| Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > SAR-Signalverarbeitung | ||||||||||||||||||||
| Hinterlegt von: | Wang, Yuanyuan | ||||||||||||||||||||
| Hinterlegt am: | 23 Okt 2015 12:54 | ||||||||||||||||||||
| Letzte Änderung: | 08 Mär 2018 18:34 |
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- Fusing meter-resolution 4-D InSAR point clouds and optical images for semantic urban infrastructure monitoring. (deposited 23 Okt 2015 12:54) [Gegenwärtig angezeigt]
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