Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data
The northwest part of Hubei Province, China, is characterized by steep topography, complex geological structures, and intense precipitation, providing ideal natural conditions for landslide disasters. To address the lack of integration of synthetic aperture radar interferometry (InSAR) and geologica...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2025.1531615/full |
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| author | Shunyao Wang Shunyao Wang Shunyao Wang Qingbin Fan Hui Li |
| author_facet | Shunyao Wang Shunyao Wang Shunyao Wang Qingbin Fan Hui Li |
| author_sort | Shunyao Wang |
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| description | The northwest part of Hubei Province, China, is characterized by steep topography, complex geological structures, and intense precipitation, providing ideal natural conditions for landslide disasters. To address the lack of integration of synthetic aperture radar interferometry (InSAR) and geological data for the identification of latent landslide hazards, in this study, we incorporated InSAR technology and geological data to identify potential landslides in Fang County, northwest Hubei Province. With the aid of 10 ALOS-2 data scenes and high-precision digital elevation models of the study area, a displacement rate map with a maximum value of −70.6 mm/a was extracted. Then, according to the displacement rate and optical images, the suspected latent landslide area was delineated, and a comprehensive analysis of the slope map and fault and watershed buffer zone map was performed to obtain the final results. Compared to the existing latent landslide recognition method, the proposed method integrating InSAR and geological data can eliminate areas where landslides are geologically unlikely to occur, thereby enhancing the efficiency and accuracy of latent landslide hazard identification. The results were verified using geological and optical image features, which confirmed its effectiveness for identifying latent landslide hazards. The results of this research can contribute to the prediction and early warning of landslides and guide field investigations of geological disasters. |
| format | Article |
| id | doaj-art-0dd32315c8a24069950a32205f3c79a8 |
| institution | Kabale University |
| issn | 2296-6463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Earth Science |
| spelling | doaj-art-0dd32315c8a24069950a32205f3c79a82025-01-20T07:20:27ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632025-01-011310.3389/feart.2025.15316151531615Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological dataShunyao Wang0Shunyao Wang1Shunyao Wang2Qingbin Fan3Hui Li4School of Geography and Tourism, Nanyang Normal University, Nanyang, ChinaKey Laboratory of Natural Disaster and Remote Sensing of Henan Province, Nanyang Normal University, Nanyang, ChinaEngineering Research Center of Environmental Laser Remote Sensing Technology and Application of Henan Province, Nanyang Normal University, Nanyang, ChinaSchool of Geography and Tourism, Nanyang Normal University, Nanyang, ChinaSchool of Geography and Tourism, Nanyang Normal University, Nanyang, ChinaThe northwest part of Hubei Province, China, is characterized by steep topography, complex geological structures, and intense precipitation, providing ideal natural conditions for landslide disasters. To address the lack of integration of synthetic aperture radar interferometry (InSAR) and geological data for the identification of latent landslide hazards, in this study, we incorporated InSAR technology and geological data to identify potential landslides in Fang County, northwest Hubei Province. With the aid of 10 ALOS-2 data scenes and high-precision digital elevation models of the study area, a displacement rate map with a maximum value of −70.6 mm/a was extracted. Then, according to the displacement rate and optical images, the suspected latent landslide area was delineated, and a comprehensive analysis of the slope map and fault and watershed buffer zone map was performed to obtain the final results. Compared to the existing latent landslide recognition method, the proposed method integrating InSAR and geological data can eliminate areas where landslides are geologically unlikely to occur, thereby enhancing the efficiency and accuracy of latent landslide hazard identification. The results were verified using geological and optical image features, which confirmed its effectiveness for identifying latent landslide hazards. The results of this research can contribute to the prediction and early warning of landslides and guide field investigations of geological disasters.https://www.frontiersin.org/articles/10.3389/feart.2025.1531615/fulllandslideInSARgeological datahazard recognitionFang County |
| spellingShingle | Shunyao Wang Shunyao Wang Shunyao Wang Qingbin Fan Hui Li Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data Frontiers in Earth Science landslide InSAR geological data hazard recognition Fang County |
| title | Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data |
| title_full | Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data |
| title_fullStr | Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data |
| title_full_unstemmed | Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data |
| title_short | Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data |
| title_sort | latent landslide hazard recognition in fang county using synthetic aperture radar interferometry and geological data |
| topic | landslide InSAR geological data hazard recognition Fang County |
| url | https://www.frontiersin.org/articles/10.3389/feart.2025.1531615/full |
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