Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field Investigations
Red-bed soft rock, characterized by the gentle slope, low intensity, and weak weathering resistance, is widely distributed over the Eastern Sichuan Province, China, threatening many lives of people, economy development, and urbanization progress. In this study, Multi-Temporal Synthetic Aperture Rada...
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Format: | Article |
Language: | English |
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Wiley
2022-01-01
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Series: | Geofluids |
Online Access: | http://dx.doi.org/10.1155/2022/9385352 |
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author | Zhao Miao Panpan Tang Yong Zhang |
author_facet | Zhao Miao Panpan Tang Yong Zhang |
author_sort | Zhao Miao |
collection | DOAJ |
description | Red-bed soft rock, characterized by the gentle slope, low intensity, and weak weathering resistance, is widely distributed over the Eastern Sichuan Province, China, threatening many lives of people, economy development, and urbanization progress. In this study, Multi-Temporal Synthetic Aperture Radar interferometry (MTInSAR) techniques and detailed field investigations were carried out to detect the potential red-bed landslides. The strategies of small baselines, phase optimization, and atmospheric delay removal were proved to be effective in improving the deformation results. Finally, dozens of slow-moving slopes were found and attributed to frequent human activities, and the applicability of various monitoring tools and the comparisons of their results were discussed. This research is aimed at proving the applicability of remote sensing measures in the monitoring of landslides, increasing the efficiency of this method, and helping the hazard prevention in Southwest China. |
format | Article |
id | doaj-art-2668e372cea74f8e833b2d05f62199b0 |
institution | Kabale University |
issn | 1468-8123 |
language | English |
publishDate | 2022-01-01 |
publisher | Wiley |
record_format | Article |
series | Geofluids |
spelling | doaj-art-2668e372cea74f8e833b2d05f62199b02025-02-03T01:22:26ZengWileyGeofluids1468-81232022-01-01202210.1155/2022/9385352Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field InvestigationsZhao Miao0Panpan Tang1Yong Zhang2Institute of Exploration TechnologyResearch Center of Big Data TechnologyInstitute of Exploration TechnologyRed-bed soft rock, characterized by the gentle slope, low intensity, and weak weathering resistance, is widely distributed over the Eastern Sichuan Province, China, threatening many lives of people, economy development, and urbanization progress. In this study, Multi-Temporal Synthetic Aperture Radar interferometry (MTInSAR) techniques and detailed field investigations were carried out to detect the potential red-bed landslides. The strategies of small baselines, phase optimization, and atmospheric delay removal were proved to be effective in improving the deformation results. Finally, dozens of slow-moving slopes were found and attributed to frequent human activities, and the applicability of various monitoring tools and the comparisons of their results were discussed. This research is aimed at proving the applicability of remote sensing measures in the monitoring of landslides, increasing the efficiency of this method, and helping the hazard prevention in Southwest China.http://dx.doi.org/10.1155/2022/9385352 |
spellingShingle | Zhao Miao Panpan Tang Yong Zhang Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field Investigations Geofluids |
title | Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field Investigations |
title_full | Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field Investigations |
title_fullStr | Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field Investigations |
title_full_unstemmed | Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field Investigations |
title_short | Recognition of Red-Bed Landslides over Eastern Sichuan through Remote Sensing and Field Investigations |
title_sort | recognition of red bed landslides over eastern sichuan through remote sensing and field investigations |
url | http://dx.doi.org/10.1155/2022/9385352 |
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