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.
Authors
- Hesheng Chen (ORCID: https://orcid.org/0009-0009-5894-5318)
- Zhiyi Yu (ORCID: https://orcid.org/0000-0001-6227-0610)
- Tengfei Yao (ORCID: https://orcid.org/0000-0001-8539-0420)
- Ziyu Qin (ORCID: https://orcid.org/0000-0002-3748-1069)
- Guangcai Feng
- Bo Liu (ORCID: https://orcid.org/0000-0002-1961-960X)
- Zefa Yang (ORCID: https://orcid.org/0000-0001-9816-8562)
- Wenxin Wang (ORCID: https://orcid.org/0000-0002-5826-6405)
- Ri‐He Peng (ORCID: https://orcid.org/0009-0003-0522-3940)
Institutions
- Central South University (CN)
- Hunan Institute of Microbiology (CN)
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
Funders
- Natural Science Foundation of Hunan Province