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 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.

Authors

Institutions

Publication Details

Journal
Geocarto International
Published
2025-02-07
DOI
https://doi.org/10.1080/10106049.2025.2461539
Citations
7
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
34.95
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology

Man Li, Lei Zhao, Jianyin Xiong, Chunyang Chen et al.
7 citations
Geocarto International
Synthetic Aperture Radar (SAR) Applications and Techniques
34.95
article

Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology

Man Li, Lei Zhao, Jianyin Xiong, Chunyang Chen, Renru Wang, Guangbin Yang, Tao Chen
article en
7 citations

Abstract

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.

Geocarto InternationalVol. 40(1)
Guizhou Normal University (CN), State Key Laboratory of Remote Sensing Science (CN)
Climate action
Openalex Percentile: Top 1%
Synthetic Aperture Radar (SAR) Applications and Techniques
34.95
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.