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Mathematical Analysis of Urban Spatial Networks

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (18 March 2022) | Viewed by 10119

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Guest Editor
Department of Mathematics and Statistics, Texas Tech University, Box 41042 Lubbock, TX 79409-1042, USA
Interests: data analysis; stochastic nonlinear dynamics; urban studies; complexity and uncertainty in the real-world systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cities are the largest and most complex editors of human interactions that cause chief social and economic impacts on the lives of not only the present inhabitants, but also of the generations to come. Built environments constrain our visual space, thus limiting our space perception to the immediate vicinities and structuring a field of possible actions in that. Through spatial organization of a surrounding place, we can create new rules for how neighborhoods are combined into a strongly inhomogeneous network providing space where people can move and provoking chance encounters and interactions. Space structure and its impact on movement are critical to the link between the built environment and its social functioning. Many neighborhoods are cut off from other parts of the city by poor transport links and haphazard urban planning, which can often lead to social ills. Sociologists think that isolation worsens an area’s economic prospects by reducing opportunities for commerce and engenders a sense of isolation in inhabitants, both of which can fuel poverty and crime. Spatial structures creating a local situation in which there is no relation between movements inside the spatial pattern and outside it and the lack of natural space occupancy become associated with social misuse of structurally abandoned spaces.

In the proposed Special Issue, we aim to organize a broad discussion on urban morphology, urban forms, spatial networks, and structures, offering a much-needed mathematical perspective. Entropy and information theory methods would provide new insights into urban complexity and self-organization as tools and frames to disentangle the ideas that pervade arguments about form and function of the city.

Dr. Dimitri Volchenkov
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Urban morphology
  • Urban complexity and entropy
  • Swarm intelligence in urban processes
  • Urban geometry
  • Agent-based modelling of urban processes
  • Entropic force in society and urban studies

Published Papers (3 papers)

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Research

19 pages, 4203 KiB  
Article
An Integrated Fuzzy Analytic Hierarchy Process (AHP) Model for Studying Significant Factors Associated with Frequent Lane Changing
by Sarbast Moslem, Danish Farooq, Arshad Jamal, Yahya Almarhabi, Meshal Almoshaogeh, Farhan Muhammad Butt and Rana Faisal Tufail
Entropy 2022, 24(3), 367; https://0-doi-org.brum.beds.ac.uk/10.3390/e24030367 - 04 Mar 2022
Cited by 12 | Viewed by 4890
Abstract
Frequent lane changes cause serious traffic safety concerns, which involve fatalities and serious injuries. This phenomenon is affected by several significant factors related to road safety. The detection and classification of significant factors affecting lane changing could help reduce frequent lane changing risk. [...] Read more.
Frequent lane changes cause serious traffic safety concerns, which involve fatalities and serious injuries. This phenomenon is affected by several significant factors related to road safety. The detection and classification of significant factors affecting lane changing could help reduce frequent lane changing risk. The principal objective of this research is to estimate and prioritize the nominated crucial criteria and sub-criteria based on participants’ answers on a designated questionnaire survey. In doing so, this paper constructs a hierarchical lane-change model based on the concept of the analytic hierarchy process (AHP) with two levels of the most concerning attributes. Accordingly, the fuzzy analytic hierarchy process (FAHP) procedure was applied utilizing fuzzy scale to evaluate precisely the most influential factors affecting lane changing, which will decrease uncertainty in the evaluation process. Based on the final measured weights for level 1, FAHP model estimation results revealed that the most influential variable affecting lane-changing is ‘traffic characteristics’. In contrast, compared to other specified factors, ‘light conditions’ was found to be the least critical factor related to driver lane-change maneuvers. For level 2, the FAHP model results showed ‘traffic volume’ as the most critical factor influencing the lane changes operations, followed by ‘speed’. The objectivity of the model was supported by sensitivity analyses that examined a range for weights’ values and those corresponding to alternative values. Based on the evaluated results, stakeholders can determine strategic policy by considering and placing more emphasis on the highlighted risk factors associated with lane changing to improve road safety. In conclusion, the finding provides the usefulness of the fuzzy analytic hierarchy process to review lane-changing risks for road safety. Full article
(This article belongs to the Special Issue Mathematical Analysis of Urban Spatial Networks)
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23 pages, 2492 KiB  
Article
Cities on the Coast and Patterns of Movement between Population Growth and Diffusion
by Dmitry V. Kovalevsky, Dimitri Volchenkov and Jürgen Scheffran
Entropy 2021, 23(8), 1041; https://0-doi-org.brum.beds.ac.uk/10.3390/e23081041 - 13 Aug 2021
Cited by 2 | Viewed by 2200
Abstract
Sea level rise and high-impact coastal hazards due to on-going and projected climate change dramatically affect many coastal urban areas worldwide, including those with the highest urbanization growth rates. To develop tailored coastal climate services that can inform decision makers on climate adaptation [...] Read more.
Sea level rise and high-impact coastal hazards due to on-going and projected climate change dramatically affect many coastal urban areas worldwide, including those with the highest urbanization growth rates. To develop tailored coastal climate services that can inform decision makers on climate adaptation in coastal cities, a better understanding and modeling of multifaceted urban dynamics is important. We develop a coastal urban model family, where the population growth and urbanization rates are modeled in the framework of diffusion over the half-bounded and bounded domains, and apply the maximum entropy principle to the latter case. Population density distributions are derived analytically whenever possible. Steady-state wave solutions balancing the width of inhabited coastal zones, with the skewed distributions maximizing population entropy, might be responsible for the coastward migrations outstripping the demographic development of the hinterland. With appropriate modifications of boundary conditions, the developed family of diffusion models can describe coastal urban dynamics affected by climate change. Full article
(This article belongs to the Special Issue Mathematical Analysis of Urban Spatial Networks)
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16 pages, 2286 KiB  
Article
Quasi-Static Variation of Power-Law and Log-Normal Distributions of Urban Population
by Atushi Ishikawa, Shouji Fujimoto, Arturo Ramos and Takayuki Mizuno
Entropy 2021, 23(7), 908; https://0-doi-org.brum.beds.ac.uk/10.3390/e23070908 - 17 Jul 2021
Viewed by 2009
Abstract
We analytically derived and confirmed by empirical data the following three relations from the quasi-time-reversal symmetry, Gibrat’s law, and the non-Gibrat’s property observed in the urban population data of France. The first is the relation between the time variation of the power law [...] Read more.
We analytically derived and confirmed by empirical data the following three relations from the quasi-time-reversal symmetry, Gibrat’s law, and the non-Gibrat’s property observed in the urban population data of France. The first is the relation between the time variation of the power law and the quasi-time-reversal symmetry in the large-scale range of a system that changes quasi-statically. The second is the relation between the time variation of the log-normal distribution and the quasi-time-reversal symmetry in the mid-scale range. The third is the relation among the parameters of log-normal distribution, non-Gibrat’s property, and quasi-time-reversal symmetry. Full article
(This article belongs to the Special Issue Mathematical Analysis of Urban Spatial Networks)
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