Abstract: [Purposes]This study intends to solve the problem of conducting effective monitoring of landslides.[Methods] Taking the “Tongshan—Pizhou” coal mining belt in Xuzhou,Jiangsu province as an example,based on the LT-1 and digital elevation model from December 2022 to July 2023,the D-InSAR algorithm is used to extract surface deformation information of the mountains within the coal mining belt.High resolution optical remote sensing satellites are combined to determine landslides,and typical landslide areas are analyzed based on soil type data.[Findings]The results show that: ①Compared with field investigation data,the method proposed in this paper can effectively identify landslide phenomena in coal mining mineralization zones,identifying a total of 114 landslide areas with an accuracy rate of 91.2%; ②More than 54.2% of surface deformation points are located at slopes greater than 30% and towards the southwest slope.As the elevation increases,the number of surface deformation points sharply decreases;③A total of 80.7% of landslide events occurred in three types of soil areas: saturated alluvial soil,saturated subsoil,and humus low activity strong acid soil,with 52,21,and 19 incidents respectively,accounting for 45.6%,18.4%,and 16.7% of the total landslide events.[Conclusions]The research results provide reference basis for landslide warning and comprehensive land improvement work in the coal mine belt of northern Jiangsu.

Key words: coal mining belt, mountain landslide, synthetic aperture radar, optical remote sensing