Study Of Spatial Interaction Network In Urban Hotspot Areas

The area in a city with a high concentration of high traffic and crowd heat is called urban hotspot area,which is both a reflection of intensive travel of urban residents and a frequent area of urban traffic problems such as traffic congestion.Extracting the urban hotspot areas and studying the spatial interaction between the areas and the influencing factors can help test the rationality of urban traffic planning and provide suggestions for traffic control and planning of traffic management departments,so that traffic control measures can be set up in the peak areas in advance to reduce the possibility of traffic problems caused by the gathering of crowds or vehicles;it also provides help for urban residents to choose their destinations before traveling and travel during It also provides reference for city residents to choose their destinations before travel and avoid the peak.Big data of urban spatio-temporal trajectory is the data containing rich spatio-temporal information of traffic trajectory,and the rich information it contains can reflect the evolution pattern and law of urban traffic,compared with the dynamic spatiotemporal travel trajectory,the static traffic facilities also have the role of measuring the rationality of urban traffic planning,so the research of gathering hotspot areas generated by multi-source spatio-temporal location data and analyzing the interaction pattern and law between hotspot areas This paper uses multi-source spatio-temporal trajectory data.This paper uses multi-source spatio-temporal trajectory data,extracts hotspot areas from shared bicycle data,cab data and multi-type traffic POI data based on the weighted spatio-temporal data field method,analyzes the spatio-temporal distribution patterns of hotspots,and represents hotspot areas by nodes and multi-source travel flows by edges,completes the construction of spatial interaction network of hotspot areas,and then analyzes the interaction patterns and interaction modes between hotspot areas based on a series of network analysis methods.Then,based on a series of network analysis methods,the interaction patterns and interaction modes between hotspot areas are analyzed.Finally,by constructing a stochastic exponential graph model,a series of data of factors that will have an impact on travel are introduced into the model,and the degree of influence of each factor on the interaction between urban hotspot areas is analyzed qualitatively and quantitatively.The main work of this paper is as follows:(1)Urban hot spot area extraction and analysis.In this paper,we propose a weighted spatio-temporal data field to solve the lack of processing capability of multi-source data in previous data field methods,and extract hotspot areas based on shared bicycle trajectory data,cab trajectory data and other traffic-related multisource data.The hotspot areas are visualized and analyzed using the kernel density analysis method and the grid division method,and the scope of the hotspot areas and their distribution patterns are explored for the reference of urban planning and residents’ travel.(2)Spatial interaction network interaction analysis of hotspot regions.Based on the complex network theory,the network nodes represent the hotspot areas,the connected edges between the nodes represent the connection and interaction between the areas,and the weight of the edges is the size of the interaction quantity,and the hotspot area interaction network is constructed.After the network is constructed,a number of network statistical indicators are selected to analyze the network and study the spatial and temporal characteristics of network interaction.The spatial and temporal distribution patterns of the two important characteristics of "flow" and "direction of flow" are explored,so as to understand the influence of each area in the city and explore the travel patterns of residents.(3)Study on the factors influencing the spatial interaction network of urban hotspot areas.The ERGM model is constructed to select and analyze the influencing factors of urban multi-source travel based on the research results and experiences of previous travel influencing factors,and then introduce the influencing factors into the model,calculate the regression parameters through the network statistical model,analyze the regression parameters of the influencing factors to explain the intrinsic causes of spatial interaction,and further explore the intrinsic laws and causes of spatial interaction in urban hotspot areas.