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

Dhafer Alqahtani, Javed Mallick, Abdulmohsen M. Alqahtani and Swapan Talukdar ()
Additional contact information
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

Sustainability, 2024, vol. 16, issue 10, 1-26

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.

Keywords: sustainable urbanization; GIS-based site selection; risk assessment; artificial intelligence; mountainous terrain; decision-making framework (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/10/4235/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/10/4235/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:10:p:4235-:d:1396891

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().