GIS-Based Visualization and Analysis of Urban Distribution Network

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Urban logistics is becoming an increasingly important urban function due to the expansion of e-commerce and the concentration of urban populations. However, it also faces many challenges, including traffic congestion, rising delivery costs, and increased CO₂ emissions. To solve these problems, the optimal placement of logistics hubs and the construction of efficient delivery networks are essential. Geographic Information Systems (GIS) are attracting attention as a core technology for this.
GIS integrates diverse spatial data, such as road networks, traffic volume, population distribution, commercial facilities, and warehouse locations, to visualize logistics activities on a map. This makes it possible to analyze areas where delivery demand is concentrated and locations prone to traffic congestion, and to scientifically select optimal logistics hub candidates.
In particular, by utilizing GIS platforms such as GISBox, advanced logistics analysis using not only 2D but also 3D urban spaces can be achieved. For example, it is possible to grasp building density, road width, and elevation differences in three dimensions, and simulate the passability of large vehicles and delivery efficiency. Furthermore, analyzing the distance and transportation time between multiple logistics centers can lead to the optimization of delivery routes and reduction of transportation costs.
Furthermore, GIS can support dynamic logistics management by integrating with real-time traffic data and IoT sensors. By instantly reflecting traffic congestion and accident information and flexibly changing delivery routes, delivery delays can be minimized. This contributes not only to the efficiency of urban logistics but also to reducing environmental impact.
In addition, consistency with disaster prevention and urban planning is crucial when locating urban logistics hubs. Using GIS, it's possible to analyze the relationship with flood risk areas and evacuation routes, enabling safe hub placement. Moreover, it allows for the prior assessment of noise and traffic impacts that logistics facilities will have on the surrounding residential environment.
Thus, GIS is a vital technology supporting spatial analysis, route optimization, real-time management, and risk assessment in the placement of urban logistics hubs. By utilizing GISBox, logistics data can be managed comprehensively, enabling the construction of an efficient and sustainable urban logistics system. Moving forward, with the development of smart cities, the importance of GIS-based logistics optimization is expected to increase even further.
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