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Optimizing Residential Construction Site Selection in Mountainous Regions Using Geospatial Data and eXplainable AI

Author

Listed:
  • Dhafer Alqahtani

    (Department of Civil Engineering, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia)

  • Javed Mallick

    (Department of Civil Engineering, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia)

  • Abdulmohsen M. Alqahtani

    (Department of Civil Engineering, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia)

  • Swapan Talukdar

    (Department of Geography, Asutosh College, University of Calcutta, Kolkata 700026, India)

Abstract

The rapid urbanization of Abha and its surrounding cities in Saudi Arabia’s mountainous regions poses challenges for sustainable and secure development. This study aimed to identify suitable sites for eco-friendly and safe building complexes amidst complex geophysical, geoecological, and socio-economic factors, integrating natural hazards assessment and risk management. Employing the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), the study constructed a suitability model incorporating sixteen parameters. Additionally, a Deep Neural Network (DNN) based on eXplainable Artificial Intelligence (XAI) conducted sensitivity analyses to assess the parameters’ influence on optimal location decision making. The results reveal slope as the most crucial parameter (22.90%), followed by altitude and land use/land cover (13.24%), emphasizing topography and environmental considerations. Drainage density (11.36%) and rainfall patterns (9.15%) are also significant for flood defense and water management. Only 12.21% of the study area is deemed “highly suitable”, with “no-build zones” designated for safety and environmental protection. DNN-based XAI demonstrates the positive impact of variables like the NDVI and municipal solid waste generation on site selection, informing waste management and ecological preservation strategies. This integrated methodology provides actionable insights for sustainable and safe residential development in Abha, aiding informed decision making and balancing urban expansion with environmental conservation and hazard risk reduction.

Suggested Citation

  • Dhafer Alqahtani & Javed Mallick & Abdulmohsen M. Alqahtani & Swapan Talukdar, 2024. "Optimizing Residential Construction Site Selection in Mountainous Regions Using Geospatial Data and eXplainable AI," Sustainability, MDPI, vol. 16(10), pages 1-26, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4235-:d:1396891
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    References listed on IDEAS

    as
    1. Al Garni, Hassan Z. & Awasthi, Anjali, 2017. "Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia," Applied Energy, Elsevier, vol. 206(C), pages 1225-1240.
    2. Alex Dunne & Yuriy Kuleshov, 2023. "Drought risk assessment and mapping for the Murray–Darling Basin, Australia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(1), pages 839-863, January.
    3. Javed Mallick, 2021. "Municipal Solid Waste Landfill Site Selection Based on Fuzzy-AHP and Geoinformation Techniques in Asir Region Saudi Arabia," Sustainability, MDPI, vol. 13(3), pages 1-29, February.
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