Routeing of power lines through least-cost path analysis and multicriteria evaluation to minimise environmental impacts

被引:110
作者
Bagli, Stefano [2 ]
Geneletti, Davide [1 ,3 ]
Orsi, Francesco [3 ]
机构
[1] Harvard Univ, Ctr Int Dev, Cambridge, MA 02138 USA
[2] GECOsistema Srl, I-47023 Cesena, Italy
[3] Univ Trent, Dept Civil & Environm Engn, I-38050 Trento, Italy
关键词
GIS; Power line; Multicriteria evaluation; Least-cost path; Sensitivity analysis; EXPOSURE; FIELDS;
D O I
10.1016/j.eiar.2010.10.003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Least-cost path analysis (LCPA) allows designers to find the "cheapest" way to connect two locations within a cost surface, which can be computed by combining multiple criteria, and therefore by accounting for different issues (environmental impact, economic investment, etc.). This procedure can be easily implemented with modern Geographic Information System (GIS) technologies, and consequently it has been widely employed to support planning and design of different types of linear infrastructures, ranging from roads to pipelines. This paper presents an approach based on the integration of multicriteria evaluation (MCE) and LCPA to identify the most suitable route for a 132 kV power line. Criteria such as cost, visibility, population density, and ecosystem naturalness were used for the analysis. Firstly, spatial MCE and LCPA were combined to generate cost surfaces, and to identify alternative paths. Subsequently, MCE was used to compare the alternatives, and rank them according to their overall suitability. Finally, a sensitivity analysis allowed the stability of the results to be tested and the most critical factors of the evaluation to be detected. The study found that small changes in the location of the power line start and end points can result in significantly different paths, and consequently impact levels. This suggested that planners should always consider alternative potential locations of terminals in order to identify the best path. Furthermore, it was shown that the use of different weight scenarios may help making the model adaptable to varying environmental and social contexts. The approach was tested on a real-world case study in north-eastern Italy. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:234 / 239
页数:6
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