Utilization of Sentinel Image Multitemporal Data for Landslide Potential Identification in Pujon Sub-District

Landslides are one of the most common disasters in Indonesia. Landslides are often triggered by high rainfall and occur for several days. Unstable soil structure is very easy to experience landslides. The case study of this research is in Pujon Sub-district, Malang Regency. Pujon sub-district has a hilly and highland topography. Its hilly-mountainous relief and steep slopes cause Pujon Sub-district to experience frequent natural disasters, especially landslides. The research was conducted by processing Sentinel 1 image using DInSAR method to obtain data on land surface change and weighting scoring method to obtain information on landslide prone areas. The processing of DInSAR method produces the value of vertical land surface change. The largest increase in land surface with a displacement value of 0.2972 m. And the largest land subsidence is -0.2234 m. Such movement can be an indicator of landslide occurrence. The GIS method produces 3 classes of landslide vulnerability level, namely low, medium and high in each year in Pujon sub-district. The average landslide prone area in the last 5 years is 15081.1331 ha. The processing results of DInSAR method and weighting scoring method can describe the landslide prone areas in Pujon Sub-district which is expected to be useful for landslide mitigation efforts.