Analyzing Spatial Location Preference of Urban Activities with Mode-Dependent Accessibility Using Integrated Land Use–Transport Models

Raza, Asif; Muhammad, Safdar; Zhong, Ming; Hunt, John Douglas

doi:10.3390/land11081139

Cited by 20 publications

(10 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the study was limited to one city (Djibouti, Africa), where the phenomenon of car-sharing is relatively new. The observed preferences were much similar to another study from Pakistan [32] where car-sharing has been a wellestablished mode of mobility since 2012. Another study from a developing country [33], apart from the attributes already mentioned, reveals also waiting time and privacy concerns as significant, influential factors in the adoption of car-sharing.…”

Section: Reducing Costssupporting

confidence: 87%

Towards a Smart City—The Study of Car-Sharing Services in Poland

Pawełoszek

2022

Energies

View full text Add to dashboard Cite

In recent years, Mobility-as-a-Service (MaaS) has attracted much attention in the context of smart city development. One of the models of intelligent mobility is car-sharing, a modern and convenient form of renting vehicles through a mobile application. Car-sharing is a solution that can help to mitigate the effects of excessive traffic congestion, noise, and air pollution in cities. In Poland, car-sharing has developed in recent years. To increase its popularity, it is necessary to look at the barriers from the user’s perspective. The presented study is a diagnosis of car-sharing problems based on customer reviews. The reviews were obtained from the Google Play store and cover the applications of Poland’s three largest car-sharing service providers. Descriptive statistics and sentiment analysis were used to identify the problems. The study of users’ comments made it possible to establish that car-sharing has gained tremendous popularity in recent years, reflected in the number of reviews. Moreover, car-sharing services are assessed positively by the majority of users. Women perceive services more positively than men, although they are a minority among car-sharing users. The main problems described in the comments relate to the operation of the application, in particular, the registration of new users and the unclear payment policy.

show abstract

Section: Reducing Costssupporting

confidence: 87%

Towards a Smart City—The Study of Car-Sharing Services in Poland

Pawełoszek

2022

Energies

View full text Add to dashboard Cite

show abstract

“…In existing research, most scholars focus on the unidirectional influence of urban rail transit and urban business centers [26], with fewer studies on their mutual interaction and even fewer examining their coupling relationship from the perspective of complex networks. This study uses a method combining complex networks and Geographic Information Systems (GIS) to investigate their coupling relationship, expanding the research perspective on urban rail transit networks.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial Coupling of Mass Transit Networks and Business Centers in China's Megacities: A Complex Network Theory Approach

Wen¹

2023

JUDM

View full text Add to dashboard Cite

As fundamental nodal elements in urban spatial structures, the coupling and coordinated development of urban business centers and urban rail transit contributes to the optimization of these structures. Utilizing complex network theory, a model for the urban rail transit network was constructed. The importance and hub nature of urban rail transit stations were evaluated from different angles, including degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. These metrics examined the station's degree, closeness to other nodes, number of shortest paths, and centrality of neighboring nodes. The coupling relationship between urban rail transit and urban business centers was taken into account, leading to the creation of a coupling and coordination degree model for urban rail transit stations and urban business centers. An analysis of the spatio-temporal evolution of the coupling relationship between urban rail transit and business centers in Beijing, Shanghai, and Guangzhou from 2000 to 2020 was conducted. The findings indicated an interactive and mutually influencing coupling relationship between the urban rail transit network and urban business centers. Over time, the coupling and coordination degree of urban rail transit stations and urban business centers trended from being uncoordinated towards preliminary, moderate, and good coordination. Spatial heterogeneity existed in the coupling and coordination status of different circles, with the best coupling and coordination conditions being in the core area. There was a degree of variance in the coupling and coordination development situation of rail transit stations and business centers in the core areas of different cities. Among them, Shanghai's core area had the best spatial coupling and coordination development situation, Beijing's core area lagged in business center development compared to the construction of the urban rail transit network, while Guangzhou's core area saw urban rail transit network development lag behind its mature business centers. The application of these research findings aids in promoting sustainable urban development. While this study primarily measured the importance of urban rail transit network stations from the node centrality perspective, future studies could further examine the spatial coupling of urban rail transit and business centers from the viewpoints of accessibility and passenger flow.

show abstract

“…Well-planned transportation infrastructure facilitates the integration of diverse land use types, while MLU development increases transportation accessibility by reducing travel distances and promoting sustainable transportation alternatives. This symbiotic relationship contributes to the development of vibrant, connected, and sustainable communities [30,31]. For instance, Aygoren [32], suggests that if there are two primary uses, it should be classified as MLU.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Impact of Transportation Infrastructure-Based Accessibility on the Development of Mixed Land Use Using Deep Neural Networks: Evidence from Jiang’an District, City of Wuhan, China

Almansoub,

Zhong,

Safdar

et al. 2023

Sustainability

Self Cite

View full text Add to dashboard Cite

Mixed land use (MLU) plays a crucial role in fostering a sustainable urban development, vibrant communities, and efficient land utilization, providing a viable solution for smart growth, inclusive public transit, and urban sustainability. This study employs deep neural network (DNN) models: multilayer perceptron (MLP), and long short-term memory (LSTM), to analyze the effect of the transportation infrastructure-based accessibility on the prevalence of MLU patterns, based on the following data: infrastructure-based accessibility measures represented by the logsum (or transport supply), MLU patterns at the parcel level, and floor space prices by space type, for the years 2012 and 2015. Furthermore, the proposed methods are applied to the Jiang’an District of the city of Wuhan, China, at the parcel level as the case study. The study results reveal that MLU is predominantly accessible in areas close to the city center, characterized by a high density, and is relatively scarce on the city outskirts. Notably, parcels exhibiting mixed residential–commercial and residential land-use patterns underwent significant changes between 2012 and 2015, particularly in regions with robust accessibility via non-motorized modes and public transit, specifically in the central and southern parts of Jiang’an District. This transition is evident under scenario 3 (walk, bike, bus, subway) and scenario 6 (walk, bus, car) considered in this study. Furthermore, the study observed a substantial expansion in mixed commercial–residential and commercial districts, significantly near the high-transit accessibility area of subway line 1, as demonstrated in scenario 7 (bike, subway, taxi). The results from the MLP models show a mean relative error (MRE) of 4.7–14.08% for the MLU, and the LSTM models show an MRE of 3.74–10.38% for the MLU. More importantly, both the training and forecasting errors of the above models are lower, in most cases, than those reported in the literature. Moreover, these results indicate that the transportation supply or the infrastructure-based accessibility (represented by logsum) significantly influences MLU patterns.

show abstract

Analyzing Spatial Location Preference of Urban Activities with Mode-Dependent Accessibility Using Integrated Land Use–Transport Models

Cited by 20 publications

References 51 publications

Towards a Smart City—The Study of Car-Sharing Services in Poland

Towards a Smart City—The Study of Car-Sharing Services in Poland

Spatial Coupling of Mass Transit Networks and Business Centers in China's Megacities: A Complex Network Theory Approach

Modeling Impact of Transportation Infrastructure-Based Accessibility on the Development of Mixed Land Use Using Deep Neural Networks: Evidence from Jiang’an District, City of Wuhan, China

Contact Info

Product

Resources

About