Computational Urban Science (Nov 2024)
Measuring integrated accessibility for sustainable mobility: a fuzzy set approach case study
Abstract
Abstract Sustainable transportation is vital to climate justice and social equity. Despite the efforts to achieve sustainability, there is still a lack of adequate measurement that integrates land use and transportation systems, which can be barriers to planning implementation. With methodological improvements in fuzzy theory application, this study develops an integrated index to measure the sustainability of multimodal accessibility. We do so by defining a fuzziness degree based on the different trip purposes and modes of transportation with a case study in Isfahan, Iran. Sustainable accessibility indicators were developed for walking, biking, and public transportation to represent the performance of each transportation system, considering the integration with land-use patterns. We analyze transportation modes and the accessibility to five main urban activities, including employment opportunities, education, healthcare, shopping, and recreation services, based on the travel distances, followed by a statistical integration method with Principal Components Analysis (PCA) for each travel mode. The outcome provides insights for urban planners and transportation planners to effectively evaluate the degree of integration between transportation and land-use systems and contribute to enhancing sustainable accessibility.
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