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Interacting Microsoft Visual Basic Procedures (Macros) and GIS tools in order to access optimal location and maximum use of railways and railway infrastructures


  • José Manuel Viegas


  • Helder Cristovão


  • João Filipe Camisão Caio Vieira


  • Elisabete A. Silva



Some parts of the Portuguese railway infrastructure have been neglected through time: Rural lines have been abandoned, investment in new infrastructure is sometimes delayed, and marketing strategies to keep or attract more users have not been pursued. Simultaneously, problems with urban congestion, pollution and mobility for the young, the elderly, the poor, and the handicapped are putting forward the discussion about new or more sustainable modes of transportation. Common sense of public officials, other lobbying groups, and the locals demand new, trendy train lines. And while some axes may have the potential to justify rail lines, others seem to lack population or funding to be enabled. One major problem in order to evaluate the worthiness of these rail projects has been the fact that very often the studies of travel demand and physical implantation are done separately. Travel demand analysis is done based on the four-step model (trip generation, distribution, modal split, and network assignment) using survey data and the network system, using a relatively wide zoning. The importance of interacting with other, finer, information (i.e. slope, density of population, environmental sensitivity, or other socio-economic and land use information) with the development of the travel analysis demand will enhance the analysis/results and increase the chance of proposing lines that are both optimal in location and will have the maximum use by the citizens. Off the shelf software is still unable to perform this kind of operations. Some perform the analysis using existing networks, and no information on the land is available besides the zoning system, other software propose lines accordingly to land slopes, but no trip information is included. GIS packages have the capacity to include the land information and some have some transportation analysis, but are lacking computation capabilities and algorithms to perform analysis similar to off-the-shelf transportation software. In order to develop this kind of integrated analysis it is important to have a good knowledge of the algorithms and analysis required by transportation and of the tools/opportunities offered by the GIS packages. This paper presents a methodology that integrates the transportation algorithms with the GIS functionalities, using excel macro-language. The result is an interaction of both travel demand analysis and site selection. The characteristics of the place constrain the travel demand analysis, but on its own the travel demand analysis define not only the buffer of the train line, but systematically enhance the shape of the line and the location of the stops each time the results of a phase of the travel demand analysis is outputted. This paper offers guidelines for those developing travel demand analysis including some site selection criteria, and it can be a starting point for those of whom intend to develop further application of in the GIS fields.

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  • José Manuel Viegas & Helder Cristovão & João Filipe Camisão Caio Vieira & Elisabete A. Silva, 2004. "Interacting Microsoft Visual Basic Procedures (Macros) and GIS tools in order to access optimal location and maximum use of railways and railway infrastructures," ERSA conference papers ersa04p602, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa04p602

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    References listed on IDEAS

    1. Bhat, Chandra R., 1995. "A heteroscedastic extreme value model of intercity travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 29(6), pages 471-483, December.
    2. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    3. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
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