AI-Driven Land Use Planning for Sustainable Cities
A special issue of Urban Science (ISSN 2413-8851). This special issue belongs to the section "Urban Planning and Design".
Deadline for manuscript submissions: 6 October 2026 | Viewed by 619
Special Issue Editors
Interests: land use planning; public policy; planning support system; territorial monitoring; indicators; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: sustainable urban development; public policies; planning process; land-use changes; energy transition; net zero carbon cities; green infrastructures and nature-based solutions
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Rapid urbanization and increasing complexity in city management demand innovative tools to support sustainable urban planning. This Special Issue, entitled “AI-Driven Land Use Planning for Sustainable Cities”, focuses on the integration of artificial intelligence (AI) and advanced planning support systems (PSSs) to enhance territorial monitoring, evaluation, and decision-making processes. Urban land use planning, when combined with AI-driven methodologies, enables continuous, data-driven assessment of policies, helping cities adapt dynamically to social, economic, and environmental changes.
The scope of this Special Issue includes the development and application of automated and intelligent systems for urban planning, such as AI-based dashboards, real-time territorial indicators, and automated generation of state of territorial planning reports. It emphasizes approaches that promote sustainability, transparency, and evidence-based decision-making, while bridging gaps between static planning instruments and dynamic urban realities.
This Special Issue will supplement the existing literature by offering insights into how AI and automation can transform traditional urban planning processes into adaptive, proactive, and scalable frameworks. Contributions are encouraged on topics including automated urban monitoring, AI-enabled decision support, integration of territorial and environmental data, planning evaluation and feedback loops, and policy implications for sustainable land use.
By gathering research at the intersection of urban planning, AI, and sustainability, this Special Issue aims to advance theoretical understanding, provide practical tools, and inspire innovative practices for resilient and health-oriented cities.
We look forward to receiving your contributions.
Dr. António Ribeiro Amado
Dr. Francesca Poggi
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 250 words) can be sent to the Editorial Office for assessment.
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 1800 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
- AI in urban planning
- planning support systems
- land use monitoring
- territorial indicators
- sustainable cities
- automated planning
- smart city technologies
- dynamic urban evaluation
- decision support systems
- public policy assessment
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