Abstract：Abstract ： Research purposes ： The main landform types along a passenger dedicated railway in central China are low mountains and hilly areas， where developed the fault structures and the unfavorable geological conditions， such as landslide， collapse， etc. In order to improve the survey quality and optimize engineering geological mapping work， the multi - scale 3D remote sensing interpretation technology was utilized for unfavorable geological condition survey along the railway.
Research conclusions ：( 1) Based on the aerospace，satellite, DEM and geological data, combined with the autonomous development software named railway 3D remote sensing interpretation and quantitative analysis system，we built a multi - scale 3D remote sensing scene for interpreting the fault structures and the unfavorable geological conditions along the railway. (2) Through detailed interpretation and field verification， more than 50 fault structures， 27 landslides， 17 potential unstable rocks，4 slides were checked out with the accuracy rate above 80 percent. The fault structures are mainly distributed in the Taiyue low mountainous areas and the Changzhi hilly areas，furthermore， the main strike of fault structures is northeast in the Taiyue low mountainous areas， and east - west in the Changzhi hilly areas. The landslides are mainly distributed in the Taiyue low mountainous areas and the low hilly areas， and most of them developed at both sides of the slopes in the valley. (3 ) The practice shows that the multi - scale 3D remote sensing interpretation technology can fulfil the different needs of geological investigation, and effectively improve the remote sensing interpretation accuracy, furthermore, reduce the workload of field investigation. (4 ) The study results can be used in the railway engineering geology investigation, especially in mountainous areas.
刘桂卫. 多尺度三维遥感技术在某铁路地质勘察中应用[J]. 铁道工程学报, 2016, 33(8): 40-43.
LIU Gui – wei. Application of Multi - scale 3 D Remote Sensing Technology for Geological Investigation in Railway. Journal of Railway Engineering Society, 2016, 33(8): 40-43.
2016, Vol. 33 
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