Automatic selection of weights for GIS-based multicriteria decision analysis: site selection of transmission towers as a case study
Veronesi, F., Schito, J., Grassi, S. and Raubal, M. (2017) Automatic selection of weights for GIS-based multicriteria decision analysis: site selection of transmission towers as a case study. Applied Geography, 83. pp. 78-85.
|
Text
Fabio Veronesi Automatic selection upload.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (629kB) | Preview |
Abstract
Transmission line (TL) siting consists of finding suitable land to build transmission towers. This is just one of the numerous complex geographical problems often solved using GIS-based multicriteria decision analysis (MCDA), which is a set of techniques that weight several geographical features to identify suitable locations. This technique is mostly employed using expert knowledge to identify the correct set of weights; thus adding a certain amount of subjectivity to the analysis, meaning that for the same problem if we change the experts involved, we may reach different results. This research is a first attempt to try and solve this issue. We employed a statistical analysis to quantitatively calculate these weights and we tested our method on a case study about transmission line siting in Switzerland. We compared the distances between each sample in our dataset, in this case study these are location of transmission towers, with each geographical feature, e.g. distance from water features. Then we calculate the same distances but for random points, sampled throughout the study area. The reasoning behind this method is that if samples present a distance from a geographic feature statistically different from the random, it means that the feature played an important role in dictating the location of the sample. In this case for instance, high-voltage transmission towers are purposely built as far away as possible from urban areas. Random points are on the contrary by definition sampled without any constraint. Therefore, when comparing the two datasets, we should find that transmission towers have a larger average distance from urban areas than random points. This allows us to determine that this criterion (i.e. distance from urban centers) is important for planning new TL. The results indicate that this method can successfully weight and rank the most important criteria to be considered for an MCDA analysis, in line with weights proposed in the literature. The advantage of the proposed technique is that it completely excludes human factors, thus potentially increasing the social acceptance of the MCDA results.
Item Type: | Article |
---|---|
Keywords: | Multicriteria decision analysis, Transmission line siting Statistical analysis, Geographic information system |
Divisions: | Crop and Environment Sciences (to 31.07.20) |
Depositing User: | Ms Kath Osborn |
Date Deposited: | 08 Jun 2018 10:27 |
Last Modified: | 12 Oct 2018 04:10 |
URI: | https://hau.repository.guildhe.ac.uk/id/eprint/17282 |
Actions (login required)
Edit Item |