Weiming Liao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Weiming Liao has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Guangcai Feng
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
1 shared publication - Haiyan Wang
The Chongqing 208 Geological Environment Research Institute Company, Ltd., Chongqing 400799, China
1 shared publication - Pengfei Liu
Chongqing Institute of Geological Environment Monitoring, Chongqing 401122, China
1 shared publication - Shangwei Liu
Chongqing Institute of Geological Environment Monitoring, Chongqing 401147, China
1 shared publication - Wei Li
Chongqing 208 Geological Environment Research Institute Co., Ltd., Chongqing 400700, China
1 shared publication - Xiaoting Liu
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
1 shared publication
Latest Publications
- Open Access
Applicability of Multi-Sensor and Multi-Geometry SAR Data for Landslide Detection in Southwestern China: A Case Study of Qijiang, Chongqing
The southwestern mountainous region of China (SMRC), characterized by complex geological environments, experiences frequent landslide disasters that pose significant threats to local residents. This study focuses on the Qijiang District of Chongqing, where we conduct a systematic evaluation of wavelength and observation geometry effects on InSAR-based landslide monitoring. Utilizing multi-sensor SAR imagery (Sentinel-1 C-band, ALOS-2 L-band, and LUTAN-1 L-band) acquired between 2018 and 2025, we integrate time-series InSAR analysis with geological records, high-resolution topographic data, and field investigation findings to assess representative landslide-susceptible zones in the Qijiang District. The results indicate the following: (1) L-band SAR data demonstrates superior monitoring precision compared to C-band SAR data in the SMRC; (2) the combined use of LUTAN-1 ascending/descending orbits significantly improved spatial accuracy and detection completeness in complex landscapes; (3) multi-source data fusion effectively mitigated limitations of single SAR systems, enhancing identification of small- to medium-scale landslides. This study provides critical technical support for multi-source landslide monitoring and early warning systems in Southwest China while demonstrating the applicability of China’s SAR satellites for geohazard applications.
Open AccessApplicability of Multi-Sensor and Multi-Geometry SAR Data for Landslide Detection in Southwestern China: A Case Study of Qijiang, Chongqing
The southwestern mountainous region of China (SMRC), characterized by complex geological environments, experiences frequent landslide disasters that pose significant threats to local residents. This study focuses on the Qijiang District of Chongqing, where we conduct a systematic evaluation of wavelength and observation geometry effects on InSAR-based landslide monitoring. Utilizing multi-sensor SAR imagery (Sentinel-1 C-band, ALOS-2 L-band, and LUTAN-1 L-band) acquired between 2018 and 2025, we integrate time-series InSAR analysis with geological records, high-resolution topographic data, and field investigation findings to assess representative landslide-susceptible zones in the Qijiang District. The results indicate the following: (1) L-band SAR data demonstrates superior monitoring precision compared to C-band SAR data in the SMRC; (2) the combined use of LUTAN-1 ascending/descending orbits significantly improved spatial accuracy and detection completeness in complex landscapes; (3) multi-source data fusion effectively mitigated limitations of single SAR systems, enhancing identification of small- to medium-scale landslides. This study provides critical technical support for multi-source landslide monitoring and early warning systems in Southwest China while demonstrating the applicability of China’s SAR satellites for geohazard applications.