Abstract
The movement and transport of people and goods is spatial by its very nature. Thus, geospatial fundamentals of transport systems need to be adequately considered in transport models. Until recently, this was not always the case. Instead, transport research and geography evolved widely independently in domain silos. However, driven by recent conceptual, methodological and technical developments, the need for an integrated approach is obvious. This paper attempts to outline the potential of Geographical Information Systems (GIS) for transport modeling. We identify three fields of transport modeling where the spatial perspective can significantly contribute to a more efficient modeling process and more reliable model results, namely, geospatial data, disaggregated transport models and the role of geo-visualization. For these three fields, available findings from various domains are compiled, before open aspects are formulated as research directions, with exemplary research questions. The overall aim of this paper is to strengthen the spatial perspective in transport modeling and to call for a further integration of GIS in the domain of transport modeling.
Highlights
Transport is a function of moving objects in the two dimensions of physical time and space
We have argued that the relevance of geospatial information for transport modeling is significant, but not yet adequately considered in most cases
The role of geospatial information in transport models will be necessarily further strengthened. This is mainly due to fundamental shifts in the transport modeling domain: from data scarcity to a data deluge, from expanding infrastructure to smart management, and from aggregated to disaggregated models
Summary
Transport is a function of moving objects (e.g., people or goods) in the two dimensions of physical time and space. Spatial characteristics and relations are highly abstracted in standard transport modeling frameworks, while GIS was primarily used as tool for data preparation and, to a lesser degree, for visualization [9]. Geo-Inf. 2016, 5, 84 relations are highly abstracted in standard transport modeling frameworks, while GIS was primarily used as tool for data preparation and, to a lesser degree, for visualization [9]. TTAAZZ ffoorrmm tthhee ssppaattiiaall rreeffeerreennccee ffoorr ddeemmaanndd--bbaasseedd ttrraannssppoorrtt mmooddeellss,, wwhheerree tthhee nnuummbbeerrss ooff ttrriippss ffrroomm,, ttoo and through these zones are estimated. For these estimations, various socio-demographic, and through these zones are estimated. In order to deal with spatial heterogeneity, several techniques have been developed and implemented in GIS applications, such as the Geographically Weighted Regression Analysis (GWR) by Brunsdon et al [27], that can be used for determining and weighting parameters of transport models
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