Empowering Urban Resilience: Sustainable Smart Solutions and Advanced Technologies for Community-Centric Development

A special issue of Urban Science (ISSN 2413-8851).

Deadline for manuscript submissions: closed (1 November 2024) | Viewed by 3046

Special Issue Editors


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Guest Editor
Sustainable Smart Cities Research Center, University of Alabama at Birmingham, Birmingham, AL, USA
Interests: urban and coastal resiliency; water resources and environment; stormwater management and assessing the impact of extreme weather events on the built environment
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Guest Editor
Department of Civil and Architectural Engineering, Sultan Qaboos University, P.O. Box 33, PC 123, AL Khoudh Street, Muscat, Oman
Interests: machine learning and data science; reservoirs; groundwater and river and water quality modeling; application of remote sensing (RS) in water resources and environmental management; water quality monitoring and water resources systems analysis and planning; optimization and simulation techniques and water quality assessment; integration with numerical, hydrological and climate change models for different water resource and water quality assessments; floods; seawater intrusion; costal management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid pace of urbanization and the challenges posed by climate change necessitate innovative approaches to enhancing urban resilience. This Special Issue explores the intersection of sustainable smart solutions, advanced technologies, and community-centric development with the aim of empowering urban resilience. By focusing on the synergy between technological advancements, sustainable strategies, and community engagement, this issue sheds light on effective potential pathways toward building resilient and thriving cities.

Scope and Topics: This Special Issue invites contributions that explore the multifaceted aspects of empowering urban resilience through sustainable smart solutions and advanced technologies within a community-centric framework. Topics include but are not limited to the following:

  1. Smart Infrastructure Integration: Examining the incorporation of smart infrastructure, such as IoT-enabled systems, renewable energy integration, and efficient waste management, in order to bolster urban resilience.
  2. Advanced Data Analytics for Urban Resilience: Exploring the role of big data, artificial intelligence, and predictive modeling in enhancing resilience strategies, our preparedness for disasters, and the mitigation of risk in urban settings.
  3. Community Engagement and Co-Creation: Investigating innovative approaches to involving local communities in co-creating and implementing sustainable smart solutions, thereby fostering ownership and resilience at the grassroots level.
  4. Climate-Responsive Urban Design: Discussion of design principles that integrate technology and sustainability to create climate-resilient and adaptive urban spaces through considering factors such as green infrastructure and low-impact development.
  5. Governance and Policy Frameworks: Analyzing effective governance structures and policy frameworks that support the adoption and scaling-up of sustainable smart solutions, thus ensuring inclusivity and equitable access.
  6. Resilient Social Systems: Examining how advanced technologies and community-driven initiatives build social resilience, address social inequalities, and foster cohesive and connected communities.
  7. Case Studies and Best Practices: Presenting real-world case studies showcasing successful implementation of sustainable smart solutions and advanced technologies in fostering urban resilience, highlighting lessons learned and transferable models.

Submission Guidelines: Authors are invited to submit original research articles, reviews, and case studies aligned with the themes of this Special Issue. Submissions will undergo a rigorous peer-review process to ensure their quality and relevance.

Expected Impact: This Special Issue aims to serve as a platform for interdisciplinary discussions and knowledge exchange, fostering innovation and practical strategies to enhance urban resilience. It aspires to create more resilient, inclusive, and sustainable urban environments by emphasizing community-centric development and integrating sustainable smart solutions with advanced technologies.

Timeline:

  • Call for papers: 15th of March 2024
  • Submission deadline: 1st of November 2024
  • Peer-review process: 2 months

We invite researchers, practitioners, policymakers, and experts who are passionate about urban resilience and community-centric development to contribute their expertise to this Special Issue. Please feel free to reach out with any inquiries or suggestions for potential contributions.

Dr. Rouzbeh Nazari
Dr. Mohammad Reza Nikoo
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. Urban Science 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 1600 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 resilience
  • urban design
  • smart infrastructure
  • climate-responsive design

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Published Papers (3 papers)

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Research

23 pages, 9644 KiB  
Article
Modeling Urban Microclimates for High-Resolution Prediction of Land Surface Temperature Using Statistical Models and Surface Characteristics
by Md Golam Rabbani Fahad, Maryam Karimi, Rouzbeh Nazari and Mohammad Reza Nikoo
Urban Sci. 2025, 9(2), 28; https://doi.org/10.3390/urbansci9020028 - 28 Jan 2025
Viewed by 665
Abstract
Surface properties in complex urban environments can significantly impact local-level temperature gradients and distribution on several scales. Studying temperature anomalies and identifying heat pockets in urban settings is challenging. Limited high-resolution datasets are available that do not translate into an accurate assessment of [...] Read more.
Surface properties in complex urban environments can significantly impact local-level temperature gradients and distribution on several scales. Studying temperature anomalies and identifying heat pockets in urban settings is challenging. Limited high-resolution datasets are available that do not translate into an accurate assessment of near-surface temperature. This study developed a model to predict land surface temperature (LST) at a high spatial–temporal resolution in urban areas using Landsat data and meteorological inputs from NLDAS. This study developed an urban microclimate (UC) model to predict air temperature at high spatial–temporal resolution for inner urban areas through a land surface and build-up scheme. The innovative aspect of the model is the inclusion of micro-features in land use characteristics, which incorporate surface types, urban vegetation, building density and heights, short wave radiation, and relative humidity. Statistical models, including the Generalized Additive Model (GAM) and spatial autoregression (SAR), were developed to predict land surface temperature (LST) based on surface characteristics and weather parameters. The model was applied to urban microclimates in densely populated regions, focusing on Manhattan and New York City. The results indicated that the SAR model performed better (R2 = 0.85, RMSE = 0.736) in predicting micro-scale LST variations compared to the GAM (R2 = 0.39, RMSE = 1.203) and validated the accuracy of the LST prediction model with R2 ranging from 0.79 to 0.95. Full article
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11 pages, 212 KiB  
Article
African American Farmers’ Attitudes and Perceptions Towards an Urban Agriculture Certificate Program
by Theoneste Nzaramyimana, Kathryn Orvis, Nathan Shoaf, Sait Sarr and Tamara Benjamin
Urban Sci. 2024, 8(4), 256; https://doi.org/10.3390/urbansci8040256 - 17 Dec 2024
Viewed by 615
Abstract
Farmers’ training through experiential learning plays a crucial role in the success of their farming businesses. Aspiring farmers seek crucial skill sets, including financial management, marketing strategies, pricing, budgeting, whole-farm planning, and long-term decision-making. The objective of this study was to assess African [...] Read more.
Farmers’ training through experiential learning plays a crucial role in the success of their farming businesses. Aspiring farmers seek crucial skill sets, including financial management, marketing strategies, pricing, budgeting, whole-farm planning, and long-term decision-making. The objective of this study was to assess African American farmers’ attitudes and perceptions towards an urban agriculture certificate program launched to equip them with farming skills to help them become more successful in an urban setting. A mixed-method (qualitative and quantitative) research approach was used to evaluate the impact of this certificate program. Pre- and post-survey questionnaires and interviews were administered to assess farmers’ prior urban farming knowledge and skills and if there were any changes after the certificate program was launched. Eighteen participants (n = 18) who participated and completed the program were surveyed to measure knowledge and skills gained. Results showed that African American farmers participating in the Gary Urban Agriculture Certificate Program significantly (p < 0.03) increased their skill sets and knowledge about farming in comparison to their mean scores from pre- and post-certificate program. When participants were asked to summarize the impact of the course, several mentioned that it helped them develop a comprehensive approach to planning, planting, maintaining, and harvesting the produce of their farms. Narratives from interview discussions also support the survey results in which the majority expressed a positive impact of the certificate in helping them learn about the useful farming resources around them and gain skills in running a farm. Key findings support the concept that the urban agriculture certificate program administered by Purdue University impacted participant knowledge and provided a positive attitude towards farming. This study helped us understand the impact of the certificate program. Results provided greater awareness of creating programs to support the development of Gary urban farmers’ ability to become more knowledgeable and successful in their farming endeavors. Full article
20 pages, 5090 KiB  
Article
Urban–Rural Continuum in the Gonda District, India: Quantifying Rurality Using Modified Fuzzy AHP
by Ashutosh Shukla and Hiroko Ono
Urban Sci. 2024, 8(4), 168; https://doi.org/10.3390/urbansci8040168 - 10 Oct 2024
Viewed by 919
Abstract
This article is the first attempt to understand and develop an effective tool to support decision-makers in defining actions aimed at the development of rural areas in view of the global rationalization and optimization of resources. The objective was to create a rurality [...] Read more.
This article is the first attempt to understand and develop an effective tool to support decision-makers in defining actions aimed at the development of rural areas in view of the global rationalization and optimization of resources. The objective was to create a rurality index (RI) to assist in resource allocation and policy design by considering the unique characteristics of India addressing a critical gap in regional development studies. A modified Fuzzy Analytical Hierarchy Process (F-AHP) was used to develop an RI tailored to the Gonda district in India. A comprehensive survey of 1300 experts guided the selection and prioritization of 21 factors across six domains: education, infrastructure, employment, agriculture, healthcare, and social index. These factors were then applied to assess 1214 villages in 16 development blocks. This methodology facilitated the ranking and zoning of the areas, resulting in 16 distinct zones, which enhanced the interpretability of the results. Rupaideeh and Itiyathok emerged at the top of the combined domain rankings, while Babhanjot and Chapiya occupied the bottom positions. The developed index provides a robust framework for guiding resource allocation and designing targeted interventions, thereby promoting more equitable development across communities. The results underscored the complex interplay of factors influencing village development across the assessed regions. Moreover, this model demonstrated the potential for adaptation and application in diverse localities, subject to appropriate modifications of parameters to suit local contexts. The index’s versatility and comprehensive approach offers valuable insights for policymakers and development practitioners seeking to address regional disparities effectively. Full article
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