Automated detection of damaged buildings in post-disaster scenarios: a case study of Kahramanmaraş (Türkiye) earthquakes on February 6, 2023
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s11069-023-06154-z.pdf
Reference70 articles.
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2. Abdi G, Esfandiari M, Jabari S (2022) A deep transfer learning-based damage assessment on post-event very high-resolution orthophotos. Geomatica 75(4):237–250. https://doi.org/10.1139/geomat-2021-0014
3. Adams BJ, Mansouri B, Huyck CK (2005) Streamlining post-earthquake data collection and damage assessment for the 2003 Bam, Iran, earthquake using VIEWS™ (visualizing impacts of earthquakes with satellites). Earthq Spectra 21(S1):213–218
4. Alataş EO, Taşkın G (2019) Attribute profiles in earthquake damage identification from very high resolution post event image. In: 2019 IEEE international geoscience and remote sensing symposium, pp 9299–9302. https://doi.org/10.1109/IGARSS.2019.8899308
5. Alizadeh N, Beirami BA, Mokhtarzade M (2022) Damage detection after the earthquake using sentinel-1 and 2 images and machine learning algorithms (case study: Sarpol-e Zahab earthquake). In: 2022 12th international conference on computer and knowledge engineering (ICCKE), pp 343–347. https://doi.org/10.1109/ICCKE57176.2022.9960127
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