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Land subsidence analysis using synthetic aperture radar data
Land subsidence is considered a threat to developing cities and is triggered by several natural (geological and seismic) and human (mining, groundwater withdrawal, oil and gas extraction, constructions) factors. This research has gathered datasets consisting of 80 Sentinel-1A ascending and descendin...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033746/ https://www.ncbi.nlm.nih.gov/pubmed/36967928 http://dx.doi.org/10.1016/j.heliyon.2023.e14690 |
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author | Bokhari, Rida Shu, Hong Tariq, Aqil Al-Ansari, Nadhir Guluzade, Rufat Chen, Ting Jamil, Ahsan Aslam, Muhammad |
author_facet | Bokhari, Rida Shu, Hong Tariq, Aqil Al-Ansari, Nadhir Guluzade, Rufat Chen, Ting Jamil, Ahsan Aslam, Muhammad |
author_sort | Bokhari, Rida |
collection | PubMed |
description | Land subsidence is considered a threat to developing cities and is triggered by several natural (geological and seismic) and human (mining, groundwater withdrawal, oil and gas extraction, constructions) factors. This research has gathered datasets consisting of 80 Sentinel-1A ascending and descending SLC images from July 2017 to July 2019. This dataset, concerning InSAR and PS-InSAR, is processed with SARPROZ software to determine the land subsidence in Gwadar City, Balochistan, Pakistan. Later, the maps were created with ArcGIS 10.8. Due to InSAR’s limitations in measuring millimeter-scale surface deformation, Multi-Temporal InSAR techniques, like PS-InSAR, are introduced to provide better accuracy, consistency, and fewer errors of deformation analysis. This remote-based SAR technique is helpful in the Gwadar area; for researchers, city mobility is constrained and has become more restricted post-Covid-19. This technique requires multiple images acquired of the same place at different times for estimating surface deformation per year, along with surface uplifting and subsidence. The InSAR results showed maximum deformation in the Koh-i-Mehdi Mountain from 2017 to 2019. The PS-InSAR results showed subsidence up to −92 mm/year in ascending track and −66 mm/year in descending track in the area of Koh-i-Mehdi Mountain, and up to −48 mm/year in ascending track and −32 mm/year in descending track in the area of the deep seaport. From our experimental results, a high subsidence rate has been found in the newly evolving Gwadar City. This city is very beneficial to the country’s economic development because of its deep-sea port, developed by the China-Pakistan Economic Corridor (CPEC). The research is associated with a detailed analysis of Gwadar City, identifying the areas with significant subsidence, and enlisting the possible causes that are needed to be resolved before further developments. Our findings are helpful to urban development and disaster monitoring as the city is being promoted as the next significant deep seaport with the start of CPEC. |
format | Online Article Text |
id | pubmed-10033746 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-100337462023-03-24 Land subsidence analysis using synthetic aperture radar data Bokhari, Rida Shu, Hong Tariq, Aqil Al-Ansari, Nadhir Guluzade, Rufat Chen, Ting Jamil, Ahsan Aslam, Muhammad Heliyon Research Article Land subsidence is considered a threat to developing cities and is triggered by several natural (geological and seismic) and human (mining, groundwater withdrawal, oil and gas extraction, constructions) factors. This research has gathered datasets consisting of 80 Sentinel-1A ascending and descending SLC images from July 2017 to July 2019. This dataset, concerning InSAR and PS-InSAR, is processed with SARPROZ software to determine the land subsidence in Gwadar City, Balochistan, Pakistan. Later, the maps were created with ArcGIS 10.8. Due to InSAR’s limitations in measuring millimeter-scale surface deformation, Multi-Temporal InSAR techniques, like PS-InSAR, are introduced to provide better accuracy, consistency, and fewer errors of deformation analysis. This remote-based SAR technique is helpful in the Gwadar area; for researchers, city mobility is constrained and has become more restricted post-Covid-19. This technique requires multiple images acquired of the same place at different times for estimating surface deformation per year, along with surface uplifting and subsidence. The InSAR results showed maximum deformation in the Koh-i-Mehdi Mountain from 2017 to 2019. The PS-InSAR results showed subsidence up to −92 mm/year in ascending track and −66 mm/year in descending track in the area of Koh-i-Mehdi Mountain, and up to −48 mm/year in ascending track and −32 mm/year in descending track in the area of the deep seaport. From our experimental results, a high subsidence rate has been found in the newly evolving Gwadar City. This city is very beneficial to the country’s economic development because of its deep-sea port, developed by the China-Pakistan Economic Corridor (CPEC). The research is associated with a detailed analysis of Gwadar City, identifying the areas with significant subsidence, and enlisting the possible causes that are needed to be resolved before further developments. Our findings are helpful to urban development and disaster monitoring as the city is being promoted as the next significant deep seaport with the start of CPEC. Elsevier 2023-03-20 /pmc/articles/PMC10033746/ /pubmed/36967928 http://dx.doi.org/10.1016/j.heliyon.2023.e14690 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Bokhari, Rida Shu, Hong Tariq, Aqil Al-Ansari, Nadhir Guluzade, Rufat Chen, Ting Jamil, Ahsan Aslam, Muhammad Land subsidence analysis using synthetic aperture radar data |
title | Land subsidence analysis using synthetic aperture radar data |
title_full | Land subsidence analysis using synthetic aperture radar data |
title_fullStr | Land subsidence analysis using synthetic aperture radar data |
title_full_unstemmed | Land subsidence analysis using synthetic aperture radar data |
title_short | Land subsidence analysis using synthetic aperture radar data |
title_sort | land subsidence analysis using synthetic aperture radar data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033746/ https://www.ncbi.nlm.nih.gov/pubmed/36967928 http://dx.doi.org/10.1016/j.heliyon.2023.e14690 |
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