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A Collaborative Spatial Decision Support System for Assessing Transformative Potential of Minimum Ecological Units (MEUs) in a Circular Regeneration Perspective

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Computational Science and Its Applications – ICCSA 2023 Workshops (ICCSA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14112))

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Abstract

The need to respond to the challenges of our time requires a circular reinterpretation of the cultural and ecosystem heritage of our cities. In order to foster new ways of sustainable urban regeneration, it is essential to identify public green areas in which to promote cultural-based spatial regeneration processes consistent with the Circular Economy model. Different visions of urban landscape reform give an interpretation of these issues based on the model of the ‘15-Minute City’ services and proximity logics contribute to the construction of enabling contexts, i.e. contexts in which the human beings are enabled to be active subjects, capable of pursuing their own well-being, that of their community and of their ecosystem. In particular, the ecosystem assets of cities can be read as a multitude of local proximity ecosystems or ‘Minimum Ecological Units’ (MEUs). Collaborative analysis of the use of MEUs can be the basis of Spatial Decision Support Systems (SDSS) which, through standardised techniques for accessing, understanding and interpreting data, facilitate stakeholders in decision-making processes. Starting from the results obtained by the multidisciplinary Collective “Needle Agopuntura Urbana”, in the collaborative process of urban regeneration developed within the Needle Scampia (Naples) Living Lab, the contribution proposes the integration of Multi Criteria Decision Analysis (MCDA) tools with Participatory GIS (P-GIS) collaborative spatial survey practices. The proposed methodology aims to define a SDSS able to provide decision-makers and communities with a tool capable of considering qualitative factors with respect to the transformative potential of MEUs as well as providing the possibility of balancing these factors with quantitative dimensions.

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Notes

  1. 1.

    Initiative promoted by the Directorate General for Contemporary Creativity - DGCC and MIBACT, in the context of the ‘Creative living Lab II edition’ award. The “Needle Agopuntura Urbana” collective’s members are: Abbate L., Cuntò S., Napoletano F., Pacera L., Dinardo M., Pone A., Sodano S., Diana S.. The project local partners are: Aps Jolie Rouge, Asd Stella Rossa 2006, Aps Banda Baleno, Gruppo di Risveglio dal Sonno GRIDAS, Centro Hurtado, Liceo Elsa Morante Scampia. The scientific partners are: Department of Architecture and Department of Social Sciences of University of Naples Federico II.

  2. 2.

    Needle Scampia - Collaborative Neighbourhood Uses Map, Available at: https://www.google.com/maps/d/u/0/edit?hl=it&mid=1FNBmdfqSMOvelZwreC5WCyH46T82IGIg&ll=40.899578002260625%2C14.247766710674558&z=15.

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Authors and Affiliations

  1. Department of Architecture, University of Naples Federico II, via Toledo 402, Naples, Italy

    Stefano Cuntò, Eugenio Muccio, Sabrina Sacco & Piero Zizzania

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  1. Stefano Cuntò
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  2. Eugenio Muccio
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  3. Sabrina Sacco
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  4. Piero Zizzania
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Correspondence to Stefano Cuntò .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Basilicata, Potenza, Italy

    Francesco Scorza

  6. University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

  7. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

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Cuntò, S., Muccio, E., Sacco, S., Zizzania, P. (2023). A Collaborative Spatial Decision Support System for Assessing Transformative Potential of Minimum Ecological Units (MEUs) in a Circular Regeneration Perspective. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14112. Springer, Cham. https://doi.org/10.1007/978-3-031-37129-5_20

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