In order to explore the travel characteristics and space-time distribution of different groups of bikeshare users,an online analytical processing(OLAP)tool called data cube was used for treating and displaying multi-d...In order to explore the travel characteristics and space-time distribution of different groups of bikeshare users,an online analytical processing(OLAP)tool called data cube was used for treating and displaying multi-dimensional data.We extended and modified the traditionally threedimensional data cube into four dimensions,which are space,date,time,and user,each with a user-specified hierarchy,and took transaction numbers and travel time as two quantitative measures.The results suggest that there are two obvious transaction peaks during the morning and afternoon rush hours on weekdays,while the volume at weekends has an approximate even distribution.Bad weather condition significantly restricts the bikeshare usage.Besides,seamless smartcard users generally take a longer trip than exclusive smartcard users;and non-native users ride faster than native users.These findings not only support the applicability and efficiency of data cube in the field of visualizing massive smartcard data,but also raise equity concerns among bikeshare users with different demographic backgrounds.展开更多
Rail transit plays a crucial role in improving urban sustainability and livability.In many Chinese cities,the planning of rail transit routes and stations is focused on facilitating new developments rather than revita...Rail transit plays a crucial role in improving urban sustainability and livability.In many Chinese cities,the planning of rail transit routes and stations is focused on facilitating new developments rather than revitalizing existing built-up areas.This approach reflects the local governments’expectations of substantial growth to reshape the urban structure.However,existing research on transit-oriented development(TOD)rarely explores the spatial interactions between individual transit stations and investigates how they can be integrated to achieve synergistic effects and balanced development.This study proposes that rail transit systems impact urban structure through two“forces”:the provision of additional and reliable carrying capacity and the reduction of travel time between locations.Metro passenger flow is used as a proxy for these forces,and community detection techniques are employed to identify the actual and optimal spatial clusters in Wuhan,China.The results reveal that the planned sub-centers align reasonably well with the optimal spatial clusters in terms of spatial configuration.However,the actual spatial clusters tend to have longer internal travel times compared to the optimal clusters.Further exploration suggests the need for equalizing land use density within planned spatial clusters served by the metro system.Additionally,promoting concentrated,differentiated,and mixed functional arrangements in metro station areas with low passenger flows within the planned clusters could be beneficial.This paper presents a new framework for investigating urban spatial clusters influenced by a metro system.展开更多
基金Supported by Projects of International Cooperation and Exchange of the National Natural Science Foundation of China(51561135003)Key Project of National Natural Science Foundation of China(51338003)Scientific Research Foundation of Graduated School of Southeast University(YBJJ1842)
文摘In order to explore the travel characteristics and space-time distribution of different groups of bikeshare users,an online analytical processing(OLAP)tool called data cube was used for treating and displaying multi-dimensional data.We extended and modified the traditionally threedimensional data cube into four dimensions,which are space,date,time,and user,each with a user-specified hierarchy,and took transaction numbers and travel time as two quantitative measures.The results suggest that there are two obvious transaction peaks during the morning and afternoon rush hours on weekdays,while the volume at weekends has an approximate even distribution.Bad weather condition significantly restricts the bikeshare usage.Besides,seamless smartcard users generally take a longer trip than exclusive smartcard users;and non-native users ride faster than native users.These findings not only support the applicability and efficiency of data cube in the field of visualizing massive smartcard data,but also raise equity concerns among bikeshare users with different demographic backgrounds.
文摘Rail transit plays a crucial role in improving urban sustainability and livability.In many Chinese cities,the planning of rail transit routes and stations is focused on facilitating new developments rather than revitalizing existing built-up areas.This approach reflects the local governments’expectations of substantial growth to reshape the urban structure.However,existing research on transit-oriented development(TOD)rarely explores the spatial interactions between individual transit stations and investigates how they can be integrated to achieve synergistic effects and balanced development.This study proposes that rail transit systems impact urban structure through two“forces”:the provision of additional and reliable carrying capacity and the reduction of travel time between locations.Metro passenger flow is used as a proxy for these forces,and community detection techniques are employed to identify the actual and optimal spatial clusters in Wuhan,China.The results reveal that the planned sub-centers align reasonably well with the optimal spatial clusters in terms of spatial configuration.However,the actual spatial clusters tend to have longer internal travel times compared to the optimal clusters.Further exploration suggests the need for equalizing land use density within planned spatial clusters served by the metro system.Additionally,promoting concentrated,differentiated,and mixed functional arrangements in metro station areas with low passenger flows within the planned clusters could be beneficial.This paper presents a new framework for investigating urban spatial clusters influenced by a metro system.
