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Multiscale Digital Landscape Reconstructions for Resilient Mountain Inner Areas

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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

Lacking, declining, marginal, inner areas overlap worldwide with intermediate, rural and mountain territories where climate change and inherent social-spatial vulnerabilities inhibit a smart, sustainable, and inclusive development. Within this framework, the present contribution addresses the lack of methodologies for engaging and empowering community resilience in the case of Italian mountain inner areas by investigating the integrated application of digital tools, technologies and techniques for their planning, design, and management.

In a landscape-scale perspective, this work adopts an interdisciplinary and multiscale approach towards the development of rapid and low-cost workflows for 3D reconstructions to support information management activities. Connecting a wide range of methods and tools (i.e., GIS mapping, photogrammetry, point cloud modeling), two research explorations conducted in the Autonomous Province of Trento (Italy) are presented as complementary approaches towards the digital representation of fragile landscapes at different spatial scales of action: the territorial scale of municipal planning in Val di Sole, where 2.5D visualizations of cartographic information in a GIS environment and 3D models relying on satellite data are identified; and the tree scale of forest management in the Mesiano University park, where low-cost alternatives for under-storey vegetation 3D mapping (i.e., Apple iPad Pro with LiDAR sensor and Ricoh Theta V 360° camera) are tested.

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Acknowledgments

This work is part of an ongoing PhD research financially supported by the Department of Civil, Environmental and Mechanical Engineering (DICAM) of the University of Trento and by the Italian Ministry of University and Research (MUR) in the frame of “B4R–Branding4Resilience. Tourist Infrastructure as a Tool to Enhance Small Villages by Drawing Resilient Communities and New Open Habitats” (Project number: 201735N7HP). The latter is a research project of relevant national interest (PRIN 2017—Youth Line) coordinated by the Università Politecnica delle Marche (Principal Investigator Prof. Maddalena Ferretti) and involves as partners the Università degli Studi di Palermo (Local Coordinator Prof. Barbara Lino), the Università degli Studi di Trento (Local Coordinator Prof. Sara Favargiotti), and the Politecnico di Torino (Local Coordinator Prof. Diana Rolando).

The author acknowledges her supervisors, Prof. Sara Favargiotti and Prof. Giovanna A. Massari (University of Trento), for their essential contribution to the development and the outcome of the overall research.

With regard to the acquisition of data in the Mesiano University park, the author also acknowledges Prof. Giovanna A. Massari and Prof. Alfonso Vitti (University of Trento) for the free loan of the instrumentation used in the survey campaigns, and Prof. Marco Ciolli, PhD candidates Chiara Frungillo, Anna Maragno, Angelica Pianegonda, Research fellow Andrea Biotti (Univerisity of Trento) for their operative contributions during the acquisitions.

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Authors and Affiliations

  1. Department of Civil, Environmental and Mechanical Engineering (DICAM), University of Trento, 38123, Trento, Italy

    Chiara Chioni

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  1. Chiara Chioni
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Correspondence to Chiara Chioni .

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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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Chioni, C. (2023). Multiscale Digital Landscape Reconstructions for Resilient Mountain Inner Areas. 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_2

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  • DOI: https://doi.org/10.1007/978-3-031-37129-5_2

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  • Online ISBN: 978-3-031-37129-5

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