# An Overview of GIS-Based Assessment and Mapping of Mining-Induced Subsidence
## 3 Mine Subsidence Susceptibility/Hazard Assessment and Mapping
### Subsidence Contributory Factors  
Table 4 lists the subsidence triggering factors utilized to assess mine subsidence susceptibility within a GIS environment. Nearly 20 factors were considered in subsidence susceptibility mapping. These factors included mine cavity parameters (depth, thickness, inclination, proximity, density), the mining method, geological parameters (land use, land cover, proximity to fault, surface geology, RMR), dynamic loads (proximity to a road or railroad), hydrological parameters (surface runoff, groundwater, permeability), topological parameters (elevation, ground slope), and time parameters. This result indicated that mine subsidence can be caused by interactions among many factors, including internal geotechnical aspects, external dynamic loads, and human mining activities. The result also showed that the minimum number of the influential factors considered for each study was 3 and the maximum number was 11. Most of these studies adopted six to eight parameters to predict subsidence susceptibility.  
Figure 5: Surface subsidence (vertical displacement) map in 2005; (**a**) measured, (**b**) predicted, and (**c**) difference in the distribution between measured and predicted subsidence (modified from [PERSON] and [PERSON] [43]).  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{Reference} & \multicolumn{1}{c}{\multirow{2}{*}{Cavity}} & \multirow{2}{*}{Cavity} & \multirow{2}{*}{Cavity} & \multirow{2}{*}{Cavity} & \multirow{2}{*}{Cavity} & \multirow{2}{*}{Dultance} & \multirow{2}{*}{Cavity} & \multirow{2}{*}{Mining} & Distance & \multirow{2}{*}{Dultance} & \multirow{2}{*}{Dultance} & \multirow{2}{*}{Dultance} & \multirow{2}{*}{Dultance} & \multirow{2}{*}{Dultance} & \multirow{2}{*}{Dultance} & \multirow{2}{*}{Gallboard} & \multirow{2}{*}{Gallboard} & \multirow{2}{*}{Gallboard} & \multirow{2}{*}{Gallboard} & \multirow{2}{*}{Gallboard} & \multirow{2}{*}{Gallboard} & \multirow{2}{*}{Forensibility} & \multirow{2}{*}{Elveation} & \multirow{2}{*}{Ground} & \multirow{2}{*}{Time} \\  & & & & & & & & & & & & & & & & & & & \\ \[PERSON] [23] & \(\bullet\) & & & & & & & & \(\bullet\) & & \(\bullet\) & & \  
Distance to the nearest cavity, ground slope, and cavity depth factors were frequently used as input factors (in more than 80% of studies), followed by land use/land cover, geology, runoff/groundwater, and RMR factors (adopted in more than 50% of studies). Clearly, the influential factors frequently used in past studies have made substantial contributions to subsidence events. However, these studies have not necessarily considered that some factors are less relevant to ground subsidence because they are also affected by difficulties in collecting GIS data. Typically, the mine cavity density can be an important factor in predicting ground subsidence zoning because horizontal density or vertical overlap of underground cavities can be evaluated. In addition, the stability of the underground cavity is degraded over time, so the time factor can also be important. These problems require further research, such as numerical analysis or experiments of individual factors.  
These various mine subsidence-influencing factors support that GIS can be effectively used to derive and analyze the influential factors of mine subsidence. The mine cavity density was calculated by applying a spatial density analysis technique to mine cavity polyline data. In addition, proximity factors such as distance to a mine cavity, geological lineament, road, and railroad are newly created through the distance analysis function of GIS. In the case of RMR or permeability factors, they are compiled by applying the geostatistical interpolation method of GIS to point-type borehole data. The elevation or slope of the topography was produced via the topographic slope analysis function. These geospatial influential factors enable the evaluation and prediction of ground subsidence from diverse perspectives.