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Developing a 3D City Digital Twin: Enhancing Walkability through a Green Pedestrian Network (GPN) in the City of Imola, Italy

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  • Mansoureh Gholami

    (Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 48, 40127 Bologna, Italy)

  • Daniele Torreggiani

    (Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 48, 40127 Bologna, Italy)

  • Patrizia Tassinari

    (Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 48, 40127 Bologna, Italy)

  • Alberto Barbaresi

    (Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 48, 40127 Bologna, Italy)

Abstract

Predominantly, dense historical cities face insufficient pedestrian-level greenery in the urban spaces. The lack of greenery impacts the human thermal comfort on the walking paths, which contributes to a considerable reduction in pedestrian flow rate. This study aims at developing a model to assess pedestrian-level thermal comfort in city environments and then evaluate the feasibility of creating a green pedestrian network (GPN). Imola, as a historical city in Italy with a compact urban pattern, is selected as the case study of this paper. To accomplish this, a three-dimensional digital twin at city scale is developed for the recognition of real-time shade patterns and for designing a GPN in this city. The 3D model of the proposed digital twin is developed in the Rhinoceros platform, and the physiological equivalence temperature (PET) is simulated through EnergyPlus, Honeybee, and Ladybug components in grasshopper. This study provides the city with a digital twin that is capable of examining pedestrian-level thermal comfort for designing a GPN based on real-time PET in the compact urban morphology of Imola. The PET model indicates that during the hottest hour of the 25th of June, pedestrians in open spaces can experience 3 °C more than on narrow shaded streets. The results are validated based on in situ datasets that prove the reliability of the developed digital twin for the GPN. It provides urban planners and policy makers with a precise and useful methodology for simulating the effects of pedestrian-level urban greenery on human thermal comfort and also guarantees the functionality of policies in different urban settings.

Suggested Citation

  • Mansoureh Gholami & Daniele Torreggiani & Patrizia Tassinari & Alberto Barbaresi, 2022. "Developing a 3D City Digital Twin: Enhancing Walkability through a Green Pedestrian Network (GPN) in the City of Imola, Italy," Land, MDPI, vol. 11(11), pages 1-13, October.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:11:p:1917-:d:955846
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    References listed on IDEAS

    as
    1. Gholami, M. & Torreggiani, D. & Tassinari, P. & Barbaresi, A., 2021. "Narrowing uncertainties in forecasting urban building energy demand through an optimal archetyping method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    2. Maja Rosi & Lora Strmsek & Dejan Dragan & Bojan Rosi, 2021. "Walkable Neighbourhoods In Smart Cities," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 21, pages 547-563.
    3. Mansoureh Gholami & Alberto Barbaresi & Patrizia Tassinari & Marco Bovo & Daniele Torreggiani, 2020. "A Comparison of Energy and Thermal Performance of Rooftop Greenhouses and Green Roofs in Mediterranean Climate: A Hygrothermal Assessment in WUFI," Energies, MDPI, vol. 13(8), pages 1-15, April.
    4. Martina Artmann & Olaf Bastian & Karsten Grunewald, 2017. "Using the Concepts of Green Infrastructure and Ecosystem Services to Specify Leitbilder for Compact and Green Cities—The Example of the Landscape Plan of Dresden (Germany)," Sustainability, MDPI, vol. 9(2), pages 1-26, February.
    5. Bolund, Per & Hunhammar, Sven, 1999. "Ecosystem services in urban areas," Ecological Economics, Elsevier, vol. 29(2), pages 293-301, May.
    6. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
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