This study compares global and local analyses of non-car commuting modes and the probability of increasing modes use in different urban and rural areas for a case study in Yorkshire, UK, with commuter residence areas used as the response variable. The analyses compared Generalized Linear Models of commuting by bus, cycling and walking to estimate the probability of increasing sustainable modes use in commuters in urban areas, relative to rural areas. The three variables were found to be significant predictors for the models and indicate differential odds of commuting from urban areas relative to rural ones. An analysis of the non-stationarity of was undertaken using a Geographically Weighted Regression analysis, which showed how the probability of residing in a particular type of urban and rural area, as described by commuting patterns, varied spatially within the study region. The local analyses provide a critical information able to support and guide local policy in its ambition to increase sustainable transport modes and to reduce car dependence in both rural and urban areas.
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