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Sun, Yao und Wang, Yi und Eineder, Michael (2024) Post-Earthquake SAR-Optical Dataset for Quick Damaged-Building Detection. In: 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024, Seiten 3787-3790. IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) 2024, 2024-07-07 - 2024-07-12, Athen, Griechenland. doi: 10.1109/IGARSS53475.2024.10641601. ISBN 979-8-3503-6032-5. ISSN 2153-7003.
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Offizielle URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10641601
Kurzfassung
This work introduces a dataset for automated earthquake-damaged building detection from post-event satellite imagery. Using very high-resolution Synthetic Aperture Radar (SAR) and optical data from the 2023 Turkey-Syria earthquakes, the dataset includes over four thousand co-registered building footprints and patches. The task is framed as a binary image classification problem, serving as a reference for researchers to expedite algorithm development for rapid damaged building detection in future events. The dataset and codes together with detailed explanations will be made publicly available at https://github.com/ya0-sun/PostEQ-SARopt-BuildingDamage.
| elib-URL des Eintrags: | https://elib.dlr.de/208979/ | ||||||||||||||||
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| Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||
| Titel: | Post-Earthquake SAR-Optical Dataset for Quick Damaged-Building Detection | ||||||||||||||||
| Autoren: |
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| Datum: | 2024 | ||||||||||||||||
| Erschienen in: | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 | ||||||||||||||||
| Referierte Publikation: | Ja | ||||||||||||||||
| Open Access: | Nein | ||||||||||||||||
| Gold Open Access: | Nein | ||||||||||||||||
| In SCOPUS: | Ja | ||||||||||||||||
| In ISI Web of Science: | Nein | ||||||||||||||||
| DOI: | 10.1109/IGARSS53475.2024.10641601 | ||||||||||||||||
| Seitenbereich: | Seiten 3787-3790 | ||||||||||||||||
| ISSN: | 2153-7003 | ||||||||||||||||
| ISBN: | 979-8-3503-6032-5 | ||||||||||||||||
| Status: | veröffentlicht | ||||||||||||||||
| Stichwörter: | building damage detection, convolutional neural network (CNN), remote sensing imagery, synthetic aperture radar (SAR), earthquake | ||||||||||||||||
| Veranstaltungstitel: | IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) 2024 | ||||||||||||||||
| Veranstaltungsort: | Athen, Griechenland | ||||||||||||||||
| Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
| Veranstaltungsbeginn: | 7 Juli 2024 | ||||||||||||||||
| Veranstaltungsende: | 12 Juli 2024 | ||||||||||||||||
| Veranstalter : | IEEE | ||||||||||||||||
| 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 - SAR-Methoden | ||||||||||||||||
| Standort: | Oberpfaffenhofen | ||||||||||||||||
| Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > SAR-Signalverarbeitung | ||||||||||||||||
| Hinterlegt von: | Eineder, Prof. Dr. Michael | ||||||||||||||||
| Hinterlegt am: | 26 Nov 2024 14:44 | ||||||||||||||||
| Letzte Änderung: | 26 Nov 2024 14:44 |
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