ABSTRACT
Jogging has become a popular urban outdoor recreational activity because it is inexpensive and easy. Although there are positive responses to leisure-route planning from many regions, the routes with features preferred by joggers are not commonly considered in urban planning. This article explores and evaluates methods for determining optimal urban jogging routes while considering joggers’ preferences. This study combines information about road width, green space, riverbank scenery, and various points of interest with jogging heat map data and uses a decision tree analysis to study joggers’ preferences. Next, routes with high potential considering three different patterns of points of interest and road width are selected using the vehicle routing problem analysis in ArcGIS. This method for preference-based route selection can be used to identify which links in urban road networks are attractive to runners and provide policymakers with useful information for designing built environments.
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Notes on contributors
Yumeng Huang
Yumeng Huang completed her degree in the Master’s Program in Risk Engineering at the Graduate School of Systems and Information Engineering, University of Tsukuba. Her research focuses on spatial planning for public health.
Sunyong Eom
Sunyong Eom is an associate professor in the Division of Policy and Planning Sciences, Institute of Systems and Information Engineering, University of Tsukuba. He received his doctoral degree in engineering from the University of Tsukuba in 2018. His research interests cover spatial information science, land use planning, facility location planning, and Big Data analysis. His recent research contributes to creating sustainable urban spaces, emphasizing the dynamics of human movement.
Tsutomu Suzuki
Tsutomu Suzuki is a professor in the Division of Policy and Planning Sciences, Institute of Systems and Information Engineering, University of Tsukuba. He earned a doctoral degree in engineering from the University of Tokyo in 1995. His research topics range from location analysis, spatial analysis, and urban structure to transportation modeling.