Assessing the Landslide Identification Capability of LuTan-1 in Hilly Regions: A Case Study in Longshan County, Hunan Province

China’s first L-band fully polarimetric Synthetic Aperture Radar (SAR) constellation, LuTan-1 (LT-1), was designed for terrain mapping and geohazard monitoring. This study evaluates LT-1’s capability in identifying landslides in the southern hilly regions of China, focusing on Longshan County, Hunan Province. Using both ascending and descending orbit data from LT-1, we conducted landslide identification experiments. First, deformation was obtained using Differential Interferometric SAR (D-InSAR) technology, and the deformation rates were derived through the Stacking technique. A landslide identification method that integrates C-index, slope, and ascending/descending orbit deformation information was then applied. The identified landslides were validated against existing geohazard points and medium-to-high-risk slope and gully unit data. The experimental results indicate that LT-1-ascending orbit data identified 88 landslide areas, with 39.8% corresponding to geohazard points and 65.9% within known slope units. Descending orbit data identified 90 landslide areas, with 37.8% matching geohazard points and 61.1% within known slope units. The identification results demonstrated good consistency with existing data. Comparative analysis with Sentinel-1 data revealed that LT-1’s combined ascending and descending orbit data outperformed Sentinel-1’s single ascending orbit data. LT-1’s L-band characteristics, comprehensive ascending and descending orbit coverage, and high-precision deformation detection make it highly promising for landslide identification in the southern hilly regions. This study underscores LT-1’s robust technical support for early landslide identification, highlighting its potential to enhance geohazard monitoring and mitigate risks in challenging terrains.

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Publication Details

Journal
Remote Sensing
Published
2025-03-08
DOI
https://doi.org/10.3390/rs17060960
Citations
3
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
7.27

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article

Assessing the Landslide Identification Capability of LuTan-1 in Hilly Regions: A Case Study in Longshan County, Hunan Province

Hesheng Chen, Zhiyi Yu, Tengfei Yao, Ziyu Qin et al.
3 citations
Remote Sensing
Landslides and related hazards
7.27
article

Assessing the Landslide Identification Capability of LuTan-1 in Hilly Regions: A Case Study in Longshan County, Hunan Province

Hesheng Chen, Zhiyi Yu, Tengfei Yao, Ziyu Qin, Guangcai Feng, Bo Liu, Zefa Yang, Wenxin Wang, Ri‐He Peng
article en
3 citations

Abstract

China’s first L-band fully polarimetric Synthetic Aperture Radar (SAR) constellation, LuTan-1 (LT-1), was designed for terrain mapping and geohazard monitoring. This study evaluates LT-1’s capability in identifying landslides in the southern hilly regions of China, focusing on Longshan County, Hunan Province. Using both ascending and descending orbit data from LT-1, we conducted landslide identification experiments. First, deformation was obtained using Differential Interferometric SAR (D-InSAR) technology, and the deformation rates were derived through the Stacking technique. A landslide identification method that integrates C-index, slope, and ascending/descending orbit deformation information was then applied. The identified landslides were validated against existing geohazard points and medium-to-high-risk slope and gully unit data. The experimental results indicate that LT-1-ascending orbit data identified 88 landslide areas, with 39.8% corresponding to geohazard points and 65.9% within known slope units. Descending orbit data identified 90 landslide areas, with 37.8% matching geohazard points and 61.1% within known slope units. The identification results demonstrated good consistency with existing data. Comparative analysis with Sentinel-1 data revealed that LT-1’s combined ascending and descending orbit data outperformed Sentinel-1’s single ascending orbit data. LT-1’s L-band characteristics, comprehensive ascending and descending orbit coverage, and high-precision deformation detection make it highly promising for landslide identification in the southern hilly regions. This study underscores LT-1’s robust technical support for early landslide identification, highlighting its potential to enhance geohazard monitoring and mitigate risks in challenging terrains.

Remote SensingVol. 17(6)
Central South University (CN), Hunan Institute of Microbiology (CN)
Natural Science Foundation of Hunan Province
Openalex Percentile: Top 4%
Landslides and related hazards
7.27
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