Multi-Sourced Data Integration for Detecting and Mapping the 30th July 2017 Adaklu Mountain Landslide in the Volta Region of Ghana

• Multi-source remote sensing reveals deformation patterns of the 2017 Adaklu landslide • Vegetation loss and increased bare land weakened slope conditions prior to failure • Moderate but persistent rainfall and elevated antecedent moisture triggered instability • DInSAR detects coherent downslope deformation across crown, body, and toe zones • AHP susceptibility mapping highlights relative instability in mid-slope terrain Landslides are recurrent hazards in Ghana’s mountainous environments but remain poorly characterised in terms of spatial drivers and physical impacts. This study investigates the 30 th July 2017 Adaklu Mountain landslide using an integrated geospatial framework that combines event-scale deformation evidence with susceptibility zoning to support decision-oriented interpretation in a data-scarce region. Event-scale LOS deformation from two-pass Sentinel-1A DInSAR was explicitly linked to a factor-screened AHP susceptibility index and evaluated using an event-based ROC/AUC test (AUC = 0.691) together with field-consistency checks. Analyses are presented in two parts: (i) event characterisation using rainfall conditions, two-pass DInSAR deformation patterns, and field indicators of instability; and (ii) susceptibility mapping based on screened conditioning factors. Land-cover change (2017–2018) indicates substantial vegetation loss (forest −33.7%, shrubland −32.7%) and increased bare land (+32.1%). The event occurred during a period of moderate but persistent rainfall, with several late-July days reaching ∼45–50 mm and elevated 7–15-day antecedent rainfall prior to failure; rainfall on the landslide day itself was modest (5.1 mm). Two-pass Sentinel-1A DInSAR indicates spatially coherent line-of-sight (LOS) displacement of approximately −13 to +29 mm. AHP-based susceptibility mapping highlights relatively high susceptibility along the eastern, northern, and southern district margins. Field observations (fracturing, persistent moisture, moss colonisation, and roots exploiting fractures) are consistent with the mapped instability patterns.