Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology
Landslides present significant risks to southwest China’s mountainous regions, This study evaluates the efficacy of LT-1 satellites using InSAR technology where complex terrain and dense vegetation hinder traditional SAR detection. To identify landslides in Dafang and Nayong Counties, Guizhou Provin...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2461539 |
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| author | Junzhe Xiong Tao Chen Guangbin Yang Renru Wang Man Li Linglin Zhao Chunyang Chen |
| author_facet | Junzhe Xiong Tao Chen Guangbin Yang Renru Wang Man Li Linglin Zhao Chunyang Chen |
| author_sort | Junzhe Xiong |
| collection | DOAJ |
| description | Landslides present significant risks to southwest China’s mountainous regions, This study evaluates the efficacy of LT-1 satellites using InSAR technology where complex terrain and dense vegetation hinder traditional SAR detection. To identify landslides in Dafang and Nayong Counties, Guizhou Province, from June 2023 to June 2024. Utilizing Stacking, SBAS, and D-InSAR techniques with LT-1 and ALOS-2 data, key findings include: (1) identification of 259 landslides, (2) detection of a major landslide in Nayong County with a subsidence rate of 26 cm/year and cumulative deformation of 212 mm, (3) limited landslide detection in shadowed areas with single-orbit LT-1 data, suggesting the need for dual-orbit monitoring, and (4) LT-1 outperforming ALOS-2 in detecting small-scale landslides in sparsely vegetated areas. The study underscores LT-1's potential in landslide monitoring in challenging environments and provides insights into SAR-based detection factors. |
| format | Article |
| id | doaj-art-94da488c8f5c4f34bfbeb8df38871d74 |
| institution | Kabale University |
| issn | 1010-6049 1752-0762 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geocarto International |
| spelling | doaj-art-94da488c8f5c4f34bfbeb8df38871d742025-02-07T09:13:35ZengTaylor & Francis GroupGeocarto International1010-60491752-07622025-12-0140110.1080/10106049.2025.2461539Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technologyJunzhe Xiong0Tao Chen1Guangbin Yang2Renru Wang3Man Li4Linglin Zhao5Chunyang Chen6College of Geography and Environmental Science, Guizhou Normal University, Guiyang, Guizhou, ChinaSurveying and Mapping Data Archives of Guizhou Province, Guiyang, Guizhou, ChinaCollege of Geography and Environmental Science, Guizhou Normal University, Guiyang, Guizhou, ChinaCollege of Geography and Environmental Science, Guizhou Normal University, Guiyang, Guizhou, ChinaCollege of Geography and Environmental Science, Guizhou Normal University, Guiyang, Guizhou, ChinaCollege of Geography and Environmental Science, Guizhou Normal University, Guiyang, Guizhou, ChinaCollege of Geography and Environmental Science, Guizhou Normal University, Guiyang, Guizhou, ChinaLandslides present significant risks to southwest China’s mountainous regions, This study evaluates the efficacy of LT-1 satellites using InSAR technology where complex terrain and dense vegetation hinder traditional SAR detection. To identify landslides in Dafang and Nayong Counties, Guizhou Province, from June 2023 to June 2024. Utilizing Stacking, SBAS, and D-InSAR techniques with LT-1 and ALOS-2 data, key findings include: (1) identification of 259 landslides, (2) detection of a major landslide in Nayong County with a subsidence rate of 26 cm/year and cumulative deformation of 212 mm, (3) limited landslide detection in shadowed areas with single-orbit LT-1 data, suggesting the need for dual-orbit monitoring, and (4) LT-1 outperforming ALOS-2 in detecting small-scale landslides in sparsely vegetated areas. The study underscores LT-1's potential in landslide monitoring in challenging environments and provides insights into SAR-based detection factors.https://www.tandfonline.com/doi/10.1080/10106049.2025.2461539Southwestern mountainslandslides identificationInSARLT-1ALOS-2 |
| spellingShingle | Junzhe Xiong Tao Chen Guangbin Yang Renru Wang Man Li Linglin Zhao Chunyang Chen Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology Geocarto International Southwestern mountains landslides identification InSAR LT-1 ALOS-2 |
| title | Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology |
| title_full | Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology |
| title_fullStr | Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology |
| title_full_unstemmed | Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology |
| title_short | Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology |
| title_sort | discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of lt 1 satellite based on insar technology |
| topic | Southwestern mountains landslides identification InSAR LT-1 ALOS-2 |
| url | https://www.tandfonline.com/doi/10.1080/10106049.2025.2461539 |
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