Kongtianyuan made progress in SAR remote sensing monitoring technology research before landslide disaster

【 Instrument R&D of Instrument Network 】Recently, the research of SAR remote sensing monitoring technology before the disaster of landslide has made progress in the Department of Aerospace Microwave Remote Sensing of the Institute of Aerospace Information Innovation, Chinese Academy of Sciences. His related research result "Improved Offset Tracking for Predisaster Deformation Monitoring of the 2018 Jinsha River Landslide (Tibet, China)" was published in the field of remote sensing. The journal Remote Sensing of Environment ("Environmental Remote Sensing").

Synthetic Aperture Radar (SAR) remote sensing technology is widely used for long-term surface monitoring in landslide-prone areas due to the advantages of all-weather and all-weather observation. The traditional offset tracking technology is based on the similarity monitoring of the signal intensity of the same target in two SAR images in the same area to calculate the offset of the same target between the two SAR images. It is a monitoring method of surface deformation. It is suitable for large-scale deformation monitoring, such as high-speed landslide (more than tens of centimeters/year). However, the traditional offset tracking technology also has certain limitations, including the high dependence of the estimation window design on experience, the conflict between single-point accuracy and overall efficiency, and the low confidence caused by heterogeneous samples within the window.

Facing the above landslide monitoring and processing requirements, researchers have proposed a homogeneous adaptive non-coherent spot tracking method (AISOT-HS) for non-significant areas, which reduces the experience of traditional offset tracking technology in the estimation window design. Highly dependent and effectively improve the overall efficiency and confidence of the results under the same precision requirements; the "pre-separation" step to distinguish feature matching and spot matching is proposed to optimize the existing processing process for natural scenes and effectively improve the processing of the offset tracking algorithm effectiveness.

Researchers used the technology to process multiple SAR data before the Jinsha River landslide (in Tibet, China) in 2018, and studied the evolution of the landslide. Compared with traditional methods, this method improves the operation efficiency and reduces the uncertainty of the results. The SAR data comes from China's Gaofen-3 (GF-3) satellite and Japan Land Observation Satellite (ALOS PALSAR-2), and the GF-3 satellite SAR payload was developed by the Aerospace Microwave Remote Sensing System Department of the Institute of Aerospace Information Innovation. The article also analyzes the space-time displacement model of the landslide, and speculates that the Jinshajiang landslide is probably a pushover landslide. This study proves the role of SAR remote sensing in global landslide monitoring, especially when the ground truth data is scarce.

The research results were supported by the National Key Research and Development Program "New System Spaceborne SAR Integrated Environmental Monitoring Technology", the National Natural Science Foundation of China, and the National Outstanding Youth Science Foundation.