Application of Fuzzy-AHP in GIS in Finding E-Scooter Trail for Street Art

• Published in: REVUE INTERNATIONALE DE GEOMATIQUE
• Main Authors: Annuar, Muhammad Salahuddin Mohamad Shahrul; Naharudin, Nabilah; Azmi, Nur Aina Adiela; Khalid, Nafisah
• Format: Article
• Language: English
• Published: TECH SCIENCE PRESS 2025
• Subjects: Remote Sensing
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001401232100001
• ISSN: 1260-5875; 2116-7060
• DOI: 10.32604/rig.2025.058078

Tourism trails connect destinations, points of interest, and travel-related businesses. By enhancing connectivity, these trails reduce travel time, allowing tourists to maximize their exploration of sites, leading to more efficient and satisfying travel experiences. The rising popularity of e-scooters in urban areas has highlighted the need to identify safe and accessible routes, particularly in cities where safety concerns have led to restrictions. Multi- Criteria Decision Analysis (MCDA) and Geographic Information System (GIS) network analysis can be employed to determine optimal paths by considering multiple criteria. This study focuses on finding an optimal street art trail for e-scooters in Bukit Bintang using Fuzzy-AHP (FAHP) and GIS. The objectives of this study are to identify the criteria of optimal pathway conditions for e-scooters and to develop a framework to find potential trails for escooters by using FAHP and GIS. FAHP was used to compute criterion weights based on expert input, revealing Path Facility as the most critical factor (weight: 0.495), followed by Slope (0.194), Traffic Speed (0.172), and Obstruction (0.139). These weights were integrated into a GIS-based network model, with the Travelling Salesperson Problem (TSP) method applied to identify the optimal e-scooter route. The resulting map showcases the ideal e-scooter trail connecting street art locations, alongside details on path conditions, street art sites, nearby train stations, and escooter rental stations. This methodology effectively combines FAHP and GIS to determine optimal routes, aiding authorities in improving e-scooter infrastructure. Additionally, the map can be integrated into e-scooter-sharing applications or displayed at key transportation hubs to guide riders.