GIS-Based Analytical Tools for Transport Planning: Spatial Regression Models for Transportation Demand Forecast

Abstract

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Reviewing the use of Geographic Information System (GIS) to measure Sustainable Urban Transport performance

“…For instance, classification method used to identify level of accessibility to health care facilities (A. and to identify level of accessibility to health care facilities (Lopes et al, 2014). Table 2 show the matrix of classification GIS tools in previous studies as discussed at below.…”

“…It is calculated from length of public transport routes in meters divided by geographical area of district in hectares. Then, the paper by (Lopes et al, 2014) used GIS based to spatial regression models to forecast travel demand in correlation with transportation infrastructure supply, also used GIS-T software to analyse the changes produced in the models with the inclusion of spatial variables. Performances of transportation infrastructure also as main factor which affected the sustainable urban transport.…”

Proposal of a Geostatistical Procedure for Transportation Planning Field

“…However, these traditional models of trip generation forecasting assume that the observed data have no association with the spatial location (Lopes et al, 2014). It is understood that urban travel issues are associated with individual and household features, as well as the spatial location of each household, destination and the activities distribution in the urban environment (Páez et al, 2013).…”

A Comparative Analysis of the Distributions of KFC and McDonald’s Outlets in China

“…Technically, spatial autocorrelation examines the relationship between similarities and distance [17][18][19]. The phenomenon that near things are more related than distant things is universal.…”