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Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data
The damage caused by natural disasters in rural areas differs in nature extent, landscape, and structure, from the damage caused in urban environments. Previous and current studies have focused mainly on mapping damaged structures in urban areas after catastrophic events such as earthquakes or tsuna...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788353/ https://www.ncbi.nlm.nih.gov/pubmed/36560367 http://dx.doi.org/10.3390/s22249998 |
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author | Havivi, Shiran Rotman, Stanley R. Blumberg, Dan G. Maman, Shimrit |
author_facet | Havivi, Shiran Rotman, Stanley R. Blumberg, Dan G. Maman, Shimrit |
author_sort | Havivi, Shiran |
collection | PubMed |
description | The damage caused by natural disasters in rural areas differs in nature extent, landscape, and structure, from the damage caused in urban environments. Previous and current studies have focused mainly on mapping damaged structures in urban areas after catastrophic events such as earthquakes or tsunamis. However, research focusing on the level of damage or its distribution in rural areas is lacking. This study presents a methodology for mapping, characterizing, and assessing the damage in rural environments following natural disasters, both in built-up and vegetation areas, by combining synthetic-aperture radar (SAR) and optical remote sensing data. As a case study, we applied the methodology to characterize the rural areas affected by the Sulawesi earthquake and the subsequent tsunami event in Indonesia that occurred on 28 September 2018. High-resolution COSMO-SkyMed images obtained pre- and post-event, alongside Sentinel-2 images, were used as inputs. This study’s results emphasize that remote sensing data from rural areas must be treated differently from that of urban areas following a disaster. Additionally, the analysis must include the surrounding features, not only the damaged structures. Furthermore, the results highlight the applicability of the methodology for a variety of disaster events, as well as multiple hazards, and can be adapted using a combination of different optical and SAR sensors. |
format | Online Article Text |
id | pubmed-9788353 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97883532022-12-24 Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data Havivi, Shiran Rotman, Stanley R. Blumberg, Dan G. Maman, Shimrit Sensors (Basel) Article The damage caused by natural disasters in rural areas differs in nature extent, landscape, and structure, from the damage caused in urban environments. Previous and current studies have focused mainly on mapping damaged structures in urban areas after catastrophic events such as earthquakes or tsunamis. However, research focusing on the level of damage or its distribution in rural areas is lacking. This study presents a methodology for mapping, characterizing, and assessing the damage in rural environments following natural disasters, both in built-up and vegetation areas, by combining synthetic-aperture radar (SAR) and optical remote sensing data. As a case study, we applied the methodology to characterize the rural areas affected by the Sulawesi earthquake and the subsequent tsunami event in Indonesia that occurred on 28 September 2018. High-resolution COSMO-SkyMed images obtained pre- and post-event, alongside Sentinel-2 images, were used as inputs. This study’s results emphasize that remote sensing data from rural areas must be treated differently from that of urban areas following a disaster. Additionally, the analysis must include the surrounding features, not only the damaged structures. Furthermore, the results highlight the applicability of the methodology for a variety of disaster events, as well as multiple hazards, and can be adapted using a combination of different optical and SAR sensors. MDPI 2022-12-19 /pmc/articles/PMC9788353/ /pubmed/36560367 http://dx.doi.org/10.3390/s22249998 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Havivi, Shiran Rotman, Stanley R. Blumberg, Dan G. Maman, Shimrit Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data |
title | Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data |
title_full | Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data |
title_fullStr | Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data |
title_full_unstemmed | Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data |
title_short | Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data |
title_sort | damage assessment in rural environments following natural disasters using multi-sensor remote sensing data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788353/ https://www.ncbi.nlm.nih.gov/pubmed/36560367 http://dx.doi.org/10.3390/s22249998 |
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