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Sustainability
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Advanced Modelling Tools to Support Urban and Regional Planning
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Advanced Modelling Tools to Support Urban and Regional Planning

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 14623

Special Issue Editors

Dr. Federico Amato

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Guest Editor
EPFL Swiss Data Science Center (SDSC), Lausanne, Switzerland
Interests: environmental data mining; machine learning; spatial planning
Special Issues, Collections and Topics in MDPI journals
Dr. Sabrina Lai

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Guest Editor
Department of Civil and Environmental Engineering, and Architecture, Università di Cagliari, 9124 Sardinia, Italy
Interests: spatial planning; spatial modeling; natural protected areas; ecosystem services
Special Issues, Collections and Topics in MDPI journals
Dr. Alessandro Marucci

E-Mail Website
Guest Editor
Department DICEAA, University of L’Aquila, 67100 L’Aquila, Italy
Interests: environmental planning; spatial analysis; advanced technologies for fast planning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Beniamino Murgante

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Guest Editor
School of Engineering, University of Basilicata, 85100 Potenza, Italy
Interests: urban planning; spatial analysis; computational intelligence; e-learning; environment; sustainable development; sustainability; mapping; urban sustainability; modeling; simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Lorena Fiorini

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Guest Editor
Department of Civil, Construction-Architectural and Environmental Engineering (DICEAA) University of L’Aquila, Via G. Gronchi, 18, 67100 L’Aquila, Italy
Interests: environmental analysis and management; urban planning; land use change; geographic information system; indicator engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Despite covering only 2% of the Earth’s surface, cities are responsible for the consumption of about 78% of the world’s energy and the production of more than 60% of greenhouse gas emissions [1]. In terms of resource flows, a prominent role is played by urban–rural connections, which entail various kinds of exchanges, such as flows of people (e.g., migrations, commuting), goods (e.g., food and energy) and, in modern society, knowledge.

Moreover, in recent decades, urban areas have been growing at an unprecedented pace, and such growth sometimes takes place in absence of any planning or is accompanied by poor or ineffective planning, which has been creating both socioeconomic and environmental problems. On the socioeconomic side, ineffective and unfair urban policies have spurred urban poverty and social inequalities. On the environmental side, urban growth (especially in the form of urban sprawl) worldwide has been increasing air pollution, waste production, energy consumption, land take, and soil sealing, which generates biodiversity loss and affects the hydrological cycle by hindering infiltration and ultimately results in increased frequency and severity of natural hazard phenomena, including floods and landslides.

A possible way forward to address such issues is to tackle the rural–urban imbalance and pursue an integrated rural–urban development through appropriate and effective local/city-level policies and plans. This is also reinforced by the fact that global-level policies (such as, for instance, the United Nation 2030 Agenda for Sustainable Development with its 17 Sustainable Development Goals, or the UN-Habitat position documents) indicate required or desired directions of changes while identifying the urban, or suburban scale as the optimum scale at which such changes can, or should, reasonably be pursued through local policies.

This Special Issue will collect papers that present both theoretical and empirical studies aimed at supporting integrated regional and urban planning. Authors are expected to contribute through the introduction of novel quantitative approaches to address the aforementioned issues with particular reference to their space–time dimension. Advanced algorithms, platforms, and frameworks to describe, model, and visualize these complex geographical phenomena are especially welcome.

References:

  1. United Nations. Department of Economic and Social Affairs, Population Division (2019). World Urbanization Prospects: The 2018 Revision (ST/ESA/SER.A/420); United Nations: New York, NY, USA.

Dr. Federico Amato
Dr. Sabrina Lai
Dr. Alessandro Marucci
Prof. Dr. Beniamino Murgante
Dr. Lorena Fiorini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • environmental modelling
  • geocomputation
  • urban and regional planning

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Published Papers (5 papers)

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Research

52 pages, 12111 KiB  
Article
Exploring Options for Public Green Space Development: Research by Design and GIS-Based Scenario Modelling
by Philip Stessens, Frank Canters and Ahmed Z. Khan
Sustainability 2021, 13(15), 8213; https://doi.org/10.3390/su13158213 - 22 Jul 2021
Cited by 7 | Viewed by 3390
Abstract
Green spaces have a positive influence on human well-being. Therefore, an accurate evaluation of public green space provision is crucial for administrations to achieve decent urban environmental quality for all. Whereas inequalities in green space access have been studied in relation to income, [...] Read more.
Green spaces have a positive influence on human well-being. Therefore, an accurate evaluation of public green space provision is crucial for administrations to achieve decent urban environmental quality for all. Whereas inequalities in green space access have been studied in relation to income, the relation between neighbourhood affluence and remediation difficulty remains insufficiently investigated. A methodology is proposed for co-creating scenarios for green space development through green space proximity modelling. For Brussels, a detailed analysis of potential interventions allows for classification according to relative investment scales. This resulted in three scenarios of increasing ambition. Results of scenario modelling are combined with socio-economic data to analyse the relation between average income and green space proximity. The analysis confirms the generally accepted hypothesis that non-affluent neighbourhoods are on average underserved. The proposed scenarios reveal that the possibility of reaching a very high standard in green space proximity throughout the study area if authorities would be willing to allocate budgets for green space development that go beyond the regular construction costs of urban green spaces, and that the types of interventions require a higher financial investment per area of realised green space in non-affluent neighbourhoods. Full article
(This article belongs to the Special Issue Advanced Modelling Tools to Support Urban and Regional Planning)
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14 pages, 3701 KiB  
Article
Advanced Modelling Tools to Support Planning for Sand/Gravel Quarries
by Filippo Carlo Pavesi, Anna Richiedei and Michele Pezzagno
Sustainability 2021, 13(11), 6380; https://doi.org/10.3390/su13116380 - 4 Jun 2021
Cited by 3 | Viewed by 2577
Abstract
Sand and gravel quarry planning must guarantee the public interest in the procurement of raw materials while ensuring environmental sustainability. An Analyzing Planning Support System for sand and gravel quarry plan can assist decision-makers during the planning process. The proposed Analyzing PSS uses [...] Read more.
Sand and gravel quarry planning must guarantee the public interest in the procurement of raw materials while ensuring environmental sustainability. An Analyzing Planning Support System for sand and gravel quarry plan can assist decision-makers during the planning process. The proposed Analyzing PSS uses integrating geologic, economic, environmental, and geographic information to quantify raw materials and the size of quarries. This kind of tool is useful to support public authority decisions. The study provides the results of an experience conducted in the province of Brescia (NUT 3 in Northern Italy). Full article
(This article belongs to the Special Issue Advanced Modelling Tools to Support Urban and Regional Planning)
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13 pages, 2272 KiB  
Article
A Study of Multiregional Economic Correlation Analysis Based on Big Data—Taking the Regional Economy of Cities in Shaanxi Province, China, as an Example
by Shouheng Tuo and Hong He
Sustainability 2021, 13(9), 5121; https://doi.org/10.3390/su13095121 - 3 May 2021
Cited by 5 | Viewed by 2112
Abstract
To enhance the sustainability of the regional economy, this study attempts to integrate historical big data of multiregional and multi-industry economic indicators, aiming to explore and discover the correlations among regions, industries, or cross-regional economic indicators. In this paper, two correlation analysis models [...] Read more.
To enhance the sustainability of the regional economy, this study attempts to integrate historical big data of multiregional and multi-industry economic indicators, aiming to explore and discover the correlations among regions, industries, or cross-regional economic indicators. In this paper, two correlation analysis models (the 2-order correlation model and the elastic-net regularized generalized linear model) are used to conduct a correlation analysis study of multiregional and multi-industry economies, and 20 years of historical data from 9 prefecture-level cities in Shaanxi (778 indicators in total) are analyzed empirically. The results show that the proposed method can mine complex correlations from economic big data. Full article
(This article belongs to the Special Issue Advanced Modelling Tools to Support Urban and Regional Planning)
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18 pages, 726 KiB  
Article
Local and Application-Specific Geodemographics for Data-Led Urban Decision Making
by Amanda Otley, Michelle Morris, Andy Newing and Mark Birkin
Sustainability 2021, 13(9), 4873; https://doi.org/10.3390/su13094873 - 26 Apr 2021
Viewed by 2433
Abstract
This work seeks to introduce improvements to the traditional variable selection procedures employed in the development of geodemographic classifications. It presents a proposal for shifting from a traditional approach for generating general-purpose one-size-fits-all geodemographic classifications to application-specific classifications. This proposal addresses the recent [...] Read more.
This work seeks to introduce improvements to the traditional variable selection procedures employed in the development of geodemographic classifications. It presents a proposal for shifting from a traditional approach for generating general-purpose one-size-fits-all geodemographic classifications to application-specific classifications. This proposal addresses the recent scepticism towards the utility of general-purpose applications by employing supervised machine learning techniques in order to identify contextually relevant input variables from which to develop geodemographic classifications with increased discriminatory power. A framework introducing such techniques in the variable selection phase of geodemographic classification development is presented via a practical use-case that is focused on generating a geodemographic classification with an increased capacity for discriminating the propensity for Library use in the UK city of Leeds. Two local classifications are generated for the city, one a general-purpose classification, and the other, an application-specific classification incorporating supervised Feature Selection methods in the selection of input variables. The discriminatory power of each classification is evaluated and compared, with the result successfully demonstrating the capacity for the application-specific approach to generate a more contextually relevant result, and thus underpins increasingly targeted public policy decision making, particularly in the context of urban planning. Full article
(This article belongs to the Special Issue Advanced Modelling Tools to Support Urban and Regional Planning)
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18 pages, 6321 KiB  
Article
A Modeling Framework: To Analyze the Relationship between Accessibility, Land Use and Densities in Urban Areas
by Amila Jayasinghe, N. B. S. Madusanka, Chethika Abenayake and P. K. S. Mahanama
Sustainability 2021, 13(2), 467; https://doi.org/10.3390/su13020467 - 6 Jan 2021
Cited by 11 | Viewed by 2921
Abstract
The study proposes a framework to model the three-dimensional relationship among density, land use, and accessibility in urban areas constructively contributing to overcome the limitations noted in the domains of urban planning and transport planning. First, most of the existing studies have focused [...] Read more.
The study proposes a framework to model the three-dimensional relationship among density, land use, and accessibility in urban areas constructively contributing to overcome the limitations noted in the domains of urban planning and transport planning. First, most of the existing studies have focused on the topological characteristics in capturing the accessibility, but a limited attention has been given on measuring the accessibility by considering both topological and roadway characteristics. Second, the existing research studies have acknowledged the relationship among density, land use, and accessibility while a limited attention has been given to develop a modeling framework to capture the three-dimensional relationship. The modelling framework was tested in three urban areas in Sri Lanka. The research first analyzed the three-dimensional relationship among density, land use, and accessibility in the case studies. Then, the study developed a set of regression models to capture the density from the land use and accesability. The proposed model recorded a satisfactory level of accuracy (i.e., R2 > 0.70) on a par with internationally accepted standards. The relationship was further elaborated through a decision tree analysis and 4D plot diagrams. Findings of the study can be utilized to model the density of a given land use and the correspondent accessibility scenarios. The proposed model is capable of quantifying the impact of the changes in the density correspondent to the accessibility and land use. Therefore, the study concludes that this will be an effective tool for decision-makers in the fields of land-use planning and transport planning for scenario building, impact analysis, and the formulation of land use zoning and urban development plans aiming at the overarching sustainability of future cities. Full article
(This article belongs to the Special Issue Advanced Modelling Tools to Support Urban and Regional Planning)
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