# Applicability of Multi-Sensor and Multi-Geometry SAR Data for Landslide Detection in Southwestern China: A Case Study of Qijiang, Chongqing

**Authors:** Haiyan Wang, Xiaoting Liu, Guangcai Feng, Pengfei Liu, Wei Li, Shangwei Liu, Weiming Liao

PMC · DOI: 10.3390/s25144324 · 2025-07-10

## TL;DR

This study evaluates how different satellite radar data can detect landslides in mountainous southwest China, finding that L-band radar and combined satellite data improve accuracy.

## Contribution

The study introduces a novel evaluation of multi-sensor and multi-geometry SAR data for landslide detection in complex geological regions.

## Key findings

- L-band SAR data provides better monitoring precision than C-band in the SMRC.
- Combining LUTAN-1 ascending and descending orbits improves spatial accuracy in complex landscapes.
- Multi-source data fusion enhances detection of small- to medium-scale landslides.

## Abstract

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.

## Full-text entities

- **Diseases:** deformations (MESH:D009140), SMRC (MESH:D000532), injury to (MESH:D014947)
- **Chemicals:** LT-1 (-), Sentinel (MESH:C093628)
- **Species:** Homo sapiens (human, species) [taxon 9606]
- **Cell lines:** ALOS-2 — Homo sapiens (Human), Colon carcinoma, Cancer cell line (CVCL_A628), -1 — Mus musculus (Mouse), Hybridoma (CVCL_C7RB)

## Figures

13 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12299697/full.md

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Source: https://tomesphere.com/paper/PMC12299697