ECO-SET2025: ECO-SET: A Multidisciplinary approach to plan ECOsystem SErvices for cities in Transition |
Website | https://sites.google.com/unisa.it/eco-set |
Submission link | https://easychair.org/conferences/?conf=ecoset2025 |
The ECO-SET: A Multidisciplinary approach to plan ECOsystem SErvices for cities in Transition workshop explores how data-driven models and geospatial technologies can inform urban ecosystem planning. Grounded in the ECO-SET research project funded under PRIN PNRR, it aims to bridge Human-Computer Interaction (HCI), environmental planning, and civic engagement using spatial tools like QGIS, Urban Atlas data, and CO₂ prediction models.
Topic
Authors are invited to submit articles that fall under topics such as, but not limited to:
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Participatory and interactive tools for ecological scenario planning and green infrastructure co-design
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HCI methodologies to engage citizens and stakeholders in environmental decision-making using digital platforms and spatial simulations
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AI-assisted spatial analysis for identifying ecological patterns and optimizing and use at multiple scales
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Data storytelling and visualization techniques to support ecological literacy and urban policy design
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Ethical and governance considerations in the use of AI for spatial planning
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Co-creation and knowledge transfer between human experts (e.g., urban planners, ecologists) and AI-driven systems in sustainability initiatives
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Case studies on climate-resilient cities, showcasing how computational models, GIS, and participatory design can converge to foster actionable change
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Behavioral and perceptual dimensions of ecological data interaction, including how users interpret and respond to spatial environmental information
Submission Guidelines
We invite and welcome two distinct types of contributions for the ECO-SET workshop:
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Full Papers: minimum of 10 standard pages*, plus an appropriate number of references
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Short Papers: between 5 and 9 standard pages*
*one standard page corresponds to 2,500 characters.
All submissions will undergo a single-blind peer review and should follow the official CEUR template, available in both LaTeX and Microsoft Word formats.
Contact
All questions about submissions should be emailed to carmelina.bevilacqua@uniroma1.it