Sun, Yao and Wang, Yi and Eineder, Michael (2024) Post-Earthquake SAR-Optical Dataset for Quick Damaged-Building Detection. In: 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024, pp. 3787-3790. 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.
Full text not available from this repository.
Official URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10641601
Abstract
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.
| Item URL in elib: | https://elib.dlr.de/208979/ | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||
| Title: | Post-Earthquake SAR-Optical Dataset for Quick Damaged-Building Detection | ||||||||||||||||
| Authors: |
| ||||||||||||||||
| Date: | 2024 | ||||||||||||||||
| Journal or Publication Title: | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 | ||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||
| Open Access: | No | ||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||
| DOI: | 10.1109/IGARSS53475.2024.10641601 | ||||||||||||||||
| Page Range: | pp. 3787-3790 | ||||||||||||||||
| ISSN: | 2153-7003 | ||||||||||||||||
| ISBN: | 979-8-3503-6032-5 | ||||||||||||||||
| Status: | Published | ||||||||||||||||
| Keywords: | building damage detection, convolutional neural network (CNN), remote sensing imagery, synthetic aperture radar (SAR), earthquake | ||||||||||||||||
| Event Title: | IGARSS 2024 | ||||||||||||||||
| Event Location: | Athen, Griechenland | ||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||
| Event Start Date: | 7 July 2024 | ||||||||||||||||
| Event End Date: | 12 July 2024 | ||||||||||||||||
| 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 - SAR methods | ||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||
| Institutes and Institutions: | Remote Sensing Technology Institute > SAR Signal Processing | ||||||||||||||||
| Deposited By: | Eineder, Prof. Dr. Michael | ||||||||||||||||
| Deposited On: | 26 Nov 2024 14:44 | ||||||||||||||||
| Last Modified: | 25 Feb 2025 15:02 |
Repository Staff Only: item control page