【正文】 883 36 94.83– 1,042 20 12– 1,167 28 17– 874 32 20– 1,015 36 24– 922 52 27– 1,144 4 34– 893 76 43– 887 48 Distance from drift (m) 0 16,135 960 0.01– 10,182 892 2.01– 5,839 584 4.01– 4,601 328 6.01– 4,133 248 8.60– 4,966 220 13.29– 4,820 16 19.93– 4,680 0 30.47– 4,378 0 50.01–100 4,382 0 Depth of groundwater (m) 2.72– 6,188 0 9.60– 6,523 112 10.30– 6,813 100 11.38– 6,606 828 12.33– 7,128 564 12.65– 6,194 1024 12.90– 6,823 400 13.22– 6,459 0 13.79– 5,856 108 14.87– 5,668 112 RMR 2.400– 4,473 108 2.440– 7,140 100 2.450– 4,140 12 2.460– 7,268 144 2.466–10,900 1,280 2.470– 10,411 1,392 2.480– 6,276 100 2.510– 4,697 48 2.650– 4,514 64 2.850– 4,439 16 中文譯文 以 GIS 為基礎的煤礦開采沉陷危機分析 摘要 煤礦開采導致周圍地面的沉陷會導致很多人的死亡以及各種不幸。 Coal Industry Promotion Board 1997), including the depth and height of mine cavities, excavation method, degree of inclination of the excavation, scope of mining, structural geology, flow of groundwater and the mechanical characteristics represented by the rock mass rating (RMR). In this study, locations of ground subsidence and factors governing the occurrence of ground subsidence were collected in a vectortype spatial database and then represented on a grid using the ArcGIS software package. The spatial database is shown in Table 1 . The database included a 1:5,000 ground subsidence map, 1:50,000 geological map, 1:5,000 topographic map, 1:5,000 land use map, 1:1,200 mine tunnel map, borehole data and satellite imagery with 1 m resolution. The site Jeongahm was chosen for investigation in this study. Reliable accuracy of the spatial database is indispensable in a GIS environment. For this reason, accurate maps authorized by national anizations such as the Coal Industry Promotion Board for ground subsidence, the National Geographic Information Institute for topography and land use, the Mine Reclamation Corp. for mine tunnels and boreholes and the Korea Institute of Geoscience and Mineral Resources for geology were assembled even though the scales of the maps differed. Eight variables as shown in Fig. 5 , extracted from the constructed spatial database, were considered as factors of ground subsidence when calculating the probability. Contours (5 m intervals) and survey base points of elevation were extracted from the topographic map, and triangulated irregular work was made using the elevations. The angle of slope was obtained from the digital elevation map. Areas of buildings, mountains, railways, fields, rivers, hybrids, roads and miscellaneous use were extracted from the land use map. Most literature states that the major factor in ground subsidence is the scope of mine cavities. Therefore, constructing a database for the depths and widths of mine cavities was important. To achieve this, (1) GPS measurements were used to determine the exact positions of mine heads, (2) these positions were used to vectorize a hard copy of the mine tunnel map and (3) the vectorized mine tunnel map was converted to an ASCII grid file and subtracted from the digital elevation map raster data. There were 13 boreholes at the study site, but four boreholes did not have RMR values and groundwater levels. An inversedistance weighting interpolation was used to contour the RMR and groundwater level. Geological data were extracted from the 1:50,000 geological map. A lineament was detected from IKONOS imagery with 1m resolution by a structural geologist. The d