Landslide inventory using InSAR and ancillary datasets for susceptibility

Producing a landslide susceptibility (LS) map using the statistical techniques such as the density ratio heavily relies on an existing inventory dataset. In the absence of the data in Western Area, Sierra Leone (Africa), the SBAS-InSAR technique was applied for detecting the ground deformation using multi-temporal Sentinel-1 SAR datasets from July 2015 to August 2017. The derived slope displacements coupled with the geomorphological evidence in the ancillary data are used to map the possible landslides in the area. The density ratio technique was used to generate landslide parameter class values. The values are aggregated to create the LS map and the result validated using the degree of fit and the error index. This paper, therefore, highlights a method of creating the landslide inventory and susceptibility in areas where the inventory data are limited or even absent.