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Ghanbari, Marjan, Karimi, Mohammad, Claramunt, Christophe, Lagesse, Claire. (1402). Identifying Critical Locations in Urban Transportation Networks Using Network Kernel Density Estimation (Net-KDE): A Spatial Analysis. , 7(1), -. doi: 10.22059/eoge.2024.368046.1144
Marjan Ghanbari; Mohammad Karimi; Christophe Claramunt; Claire Lagesse. "Identifying Critical Locations in Urban Transportation Networks Using Network Kernel Density Estimation (Net-KDE): A Spatial Analysis". , 7, 1, 1402, -. doi: 10.22059/eoge.2024.368046.1144
Ghanbari, Marjan, Karimi, Mohammad, Claramunt, Christophe, Lagesse, Claire. (1402). 'Identifying Critical Locations in Urban Transportation Networks Using Network Kernel Density Estimation (Net-KDE): A Spatial Analysis', , 7(1), pp. -. doi: 10.22059/eoge.2024.368046.1144
Ghanbari, Marjan, Karimi, Mohammad, Claramunt, Christophe, Lagesse, Claire. Identifying Critical Locations in Urban Transportation Networks Using Network Kernel Density Estimation (Net-KDE): A Spatial Analysis. , 1402; 7(1): -. doi: 10.22059/eoge.2024.368046.1144

Identifying Critical Locations in Urban Transportation Networks Using Network Kernel Density Estimation (Net-KDE): A Spatial Analysis

Earth Observation and Geomatics Engineering
مقاله 6، دوره 7، شماره 1، شهریور 2023
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22059/eoge.2024.368046.1144
نویسندگان
Marjan Ghanbari1؛ Mohammad Karimi* 2؛ Christophe Claramunt3؛ Claire Lagesse4
1GIS Department, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
2Kntu
3Naval Academy Research Institute, Lanvéoc- Poulmic, France
4Burgundy Franche-Comté University, France
چکیده
In the realm of urban transportation management, identifying critical locations within transportation networks is paramount for efficient urban planning, crisis management, and infrastructure development. This study investigates the effectiveness of the Network Kernel Density Estimation (Net-KDE) method in identifying these critical locations. The Net-KDE method is chosen for its inherent capacity to consider spatial patterns and path length between sample and estimation points, making it well-suited for capturing the complexities of urban transportation networks. The approach is experimented with a series of control maps applied to Tehran city. Overall, Net-KDE provides valuable and agreeable outputs that show its potential. The findings underscore the crucial role of scenario customization in enhancing the method's accuracy. Remarkably, featuring adaptive bandwidth and strategic sampling emerges as the most effective in identifying critical locations. This research has a broader impact on crisis responders, urban developers, and city planners in addition to improving our knowledge of urban network dynamics.
کلیدواژه‌ها
Network Kernel Density Estimation؛ Urban Transportation Network؛ Critical Locations؛ Sampling Strategy؛ Urban Planning
آمار
تعداد مشاهده مقاله: 80


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