GIS-based multi-criteria railway design with spatial environmental considerations. (June 2021) - Song, Taoran; Pu, Hao; Schonfeld, Paul; Zhang, Hong; Li, Wei; Peng, Xianbao; Hu, Jianping; Liu, Wei
Abstract: Railway design is complex and closely linked to environmental concerns. To solve this problem, a two-stage method considering three categories of environmental factors (topography, ecology and geology) is proposed and demonstrated by being applied to a real-world case in China. The first stage focuses on environmental impact assessment. An elevation accessibility map is generated by determining railway spatially-reachable ranges. Then, the three categories of environmental factors are divided into 12 sub-factors and their spatial relations with railways are analyzed using a GIS. After that, an environmental suitability map is produced by combining the influences of these sub-factors with a multi-criteria analytical hierarchy process. The second stage focuses on automated railway design. The study area is first narrowed based on the two maps to determine feasible search spaces. Then, a distance transform algorithm is customized to search for railway alignments. During the search, a multi-criteria tournament decision method is integrated to optimize alignment solutions. Lastly, the application results of our two-stage method are analyzed. The outcomes reveal that the two environment-related maps provide effective descriptions of the study area. Through comparisons between the computer-generated railway and the best alternative produced by experienced designers, improvements of our method are also discussed. Highlights: A two-stage method is proposed for solving multi-criteria railway design problems. The first stage generates an elevation accessibility map of railway spatially-reachable ranges. A railway suitability map is produced with GIS and AHP on the influences of 12 environmental factors. The second stage incorporates a MTD into a LCP algorithm to solve the MCDM problem. The two-stage method shows significant improvements over traditional methods in a complex actual case.