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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Main Authors: Zhao Miao, Panpan Tang, Yong Zhang
Format: Article
Language:English
Published: Wiley 2022-01-01
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.
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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
work_keys_str_mv AT zhaomiao recognitionofredbedlandslidesovereasternsichuanthroughremotesensingandfieldinvestigations
AT panpantang recognitionofredbedlandslidesovereasternsichuanthroughremotesensingandfieldinvestigations
AT yongzhang recognitionofredbedlandslidesovereasternsichuanthroughremotesensingandfieldinvestigations