LANDSLIDES MONITORING WITH TIME SERIES OF SENTINEL-1 IMAGERY IN YEN BAI PROVINCE-VIETNAM
- 1Dept. of Geomatics and Land Adminnistration, HUMG, HaNoi University of Mining and Geology, No 18 Vien Street, Bac Tu Liem, Hanoi, Vietnam
- 2Dept. of Information Technology, HUNRE, HaNoi University of Natural Resources and Environment, No 41 A Phu Dien Street, Bac Tu Liem district, Hanoi, Vietnam
- 3Institute of Geological Sciences, Vietnam Academy of Science and Technology, No. 84 Chua Lang Street, Dong Da, Hanoi, Vietnam
- 4Department of Civil and Environmental Engineering (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan, Italy
- 5Vasil Levski National Military University, Veliko Tarnovo, Bulgaria
Keywords: Landslide, PSInSAR, Vanyen-Yenbai, Sentinel-1
Abstract. This paper presents an application of PS-InSAR method for determining landslide displacement velocity in Van Yen district, Yen Bai province, Vietnam. The used tools for processing data is a combination of two free software, SNAP 7.0 and STaMPS 4.1. With 27 Sentinel-1A images in descending direction acquired from 11th January 2019 to 1st March 2021, the landslide displacement values were calculated and exported. There were locations in which landslides correctly appeared, such as Lang Thip, Xuan Tam, Chau Que Ha, Phong Du Thuong communes and along provincial road 151. Landslide rate is determined from SAR image series with average value less than 16.5 mm/y in places with high terrain and steep slope. The distribution of permanent scatter (PS) points for landslides often appeared along the road slopes, especially the inter-communal and inter-provincial roads that have not been reinforced with structural mitigation measures. In 2013 a field survey was conducted by the Vietnam Institute of Geosciences and Mineral Resources for this area which was used to validate the results from SAR processing. Landslide velocity charts at certain landslide sites were derived. The current study demonstrated the feasibility of the method as well as the usage of Sentinel-1 data for land deformation monitoring in the mountainous area.