Automatic Generation of Station Catchment Areas: A comparison of Euclidean distance transform algorithm and location-allocation methods
|dc.contributor.author||Xia, Jianhong (Cecilia)|
|dc.identifier.citation||Lin, T. and Palmer, R. and Xia, J. and McMeekin, D. 2014. Automatic Generation of Station Catchment Areas: A comparison of Euclidean distance transform algorithm and location-allocation methods, in 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Aug 19-21 2014. Xiamen, China: IEEE.|
A train station catchment area can be generated in two ways: by surveying train users or by modelling methods. The former method is time consuming and labor intensive. In this paper attention was given to develop methods that automatically generate station catchment areas. This study’s aim was to compare two modelling methods: the Euclidean Distance Transform / Voronoi Diagram Generation method and a location and allocation method for automatically generating station catchment areas. A case study of the Perth Metropolitan area, in Western Australia, was used to implement these two methods. The results from these two methods are consistent and the methods demonstrate robustness for understanding the nature of station catchment areas and provide useful insights for public transport planning in Perth.
|dc.subject||Location and allocation|
|dc.subject||Station catchment area|
|dc.subject||Euclidean distance trnasform|
|dc.title||Automatic Generation of Station Catchment Areas: A comparison of Euclidean distance transform algorithm and location-allocation methods|
|dcterms.source.title||2014 ICNC-FSKD Conference|
|dcterms.source.series||2014 ICNC-FSKD Conference|
|dcterms.source.conference||2014 ICNC-FSKD Conference|
|dcterms.source.conference-start-date||Aug 19 2014|
Copyright © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
This research was supported by an Australian Research Council Linkage grant (LP110201150)
|curtin.department||Department of Spatial Sciences|