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Spatial Point Pattern Analysis of Inbound Logistics Activities Based on GPS Trajectory Data

The agglomeration and dissipation behaviors of large-scale logistics activities lead to significant traffic congestion and delays. In order to reveal the operation and movement rules of logistics vehicles in the urban road network, this paper studies the spatial distribution characteristics of inbound logistics clusters based on the GPS trajectory data. Firstly, the kernel density estimation method with road network constraints is employed to extract the spatial characteristics of inbound logistics enterprises. Secondly, the weighted kernel density estimation method is adopted to analyze the point aggregation characteristics of inbound logistics transportation demand. Besides, the Moran index is applied to analyze the spatial autocorrelation characteristics of inbound logistics activities in the urban road network.