GIS-based evaluation of mining-induced subsidence susceptibility considering 3D multiple mine drifts and estimated mined panels

This paper presents a case study of subsidence hazard mapping in the vicinity of an abandoned coal mine within geographic information system (GIS) environment. A geospatial database was constructed using mine drift maps, topographic maps, land use maps, road maps, building maps, borehole data, and subsidence inventory maps showing occurrences of past subsidence events. Six raster-type factor layers (i.e., an influential area instability (IAI) layer calculated using multiple mine drifts and estimated mined panels, land use, distance from nearest railroad, distance from nearest road, and slope gradient) were generated and extracted from the database to identify relationships between past subsidence occurrences and the factors. Two IAI factors incorporate the complex effects of ground IAI and are calculated using the depths of each underground cavity and its angle of draw. A weight of evidence model was used to establish optimal correlations, expressed as contrast values (CVs) for subsidence inventory data, and inputs of all factors. Six CV layers (one for each factor) were linearly combined to generate a subsidence hazard map representing the relative vulnerability to subsidence in the study area. The area under the cumulative frequency diagram technique was then used to verify predicted subsidence hazards by comparing estimated susceptibility rankings over the entire range of grid cells with actual subsidence occurrences; the proposed GIS analysis model showed an accuracy of 91.09 % in the prediction of subsidence occurrences. Moreover, field surveys showed buildings with severe subsidence-related damage (damage level 4 or 5, according to the National Coal Board) in regions with very high subsidence hazard indices. Finally, a factor negatively correlated with subsidence prediction (slope angle) was determined from the sensitivity analysis.