Abstract: Karst studies employ high-resolution satellite images and geospatial data to identify and delineategeomorphic features that are critical to karst development and related hazard. This paper aims to determine the efficiency of Interferometric Synthetic Aperture Radar-derived Digital Elevation Model (IFSAR-DEM) to identify,quantify and characterize karst depressions using ArcGIS 10. 0. The semi-automated karst depression/sinkhole detection method used water flow simulation approach that incorporated a)watershed delineation;b) sink-and-fill to extract depression features;c)sink-depth measurements and classification;and d)validation of detected karst depressions using Hyperspectral Google Satellite Image of 2013-2014 and Digital Terrain Model. The method was pre-tested in the assessment conducted in the Municipality of Panglao,Bohol. Initial closed-depression analysis using 1991 National Mapping and Resource Information Authority 1:50,000 scale topographic map counted 15 sinkholes in Panglao. Using 5 m high resolution IFSAR-DEM,there are 820 sinkholes detected,424 of which were delineated through detailed ground truth to validate the presence of karst depressions. Ground truth included basic morphometric analysis,such as common sinkhole size,shape and depth,to eliminate false positives. Threshold values in sink depth of >1. 0 m and aperture size of >10 m were designated to distinguish true sinkholes with maximum accuracy. This GIS-based tool is deemed helpful to generate high-resolution karst subsidence susceptibility map that will guide local planners and engineers,as well as policy-makers,in land use and development planning.