Visualization Analysis Of Travel Spatial And Temporal Characteristics In Nanluoguxiang Area Based On Multi-source Traffic Data

In recent decades,some burgeoning high technology industries related to the internet has gradually penetrated into and subtly affect people’s lives,for example,the Internet of Things,big data,cloud computing and so on.At the same time,it also promotes the enrichment of data resources and the gradual improvement of analysis technology,which provides theoretical support for data-driven analysis of tourists’ time and space characteristics,exploration of tourist flow pattern,extraction of related scenic spots,and discovery of potential travel needs of tourists.Compared with traditional questionnaire surveys,using big data,which is massive,diverse,and real,can effectively improve work efficiency and ensure the accuracy of data collection.Therefore,how to use big data to scientifically understand the laws of group activities in cities,accurately extract people’s behavior characteristics,and correctly judge their impact on urban development is the hot research area of geographic information science,data science and social science.Based on the foregoing background,this article collects multi-source data such as laser passenger flow monitoring in Nanluoguxiang scenic spot,ICcard records,online ride-hailings and taxis orders,and shared bicycle orders as basic research datasets to analyze the temporal and spatial distribution of people in the scenic spot,and explore more the relationship between traffic passenger flow data and scenic tourist flow,excavate the characteristics of people traveling in Nanluoguxiang scenic area,analyze the number of people in the scenic area and the proportion of people at different time periods,and finally build a visualization platform to assist the scenic area management and planning department decision-making.The main research contents are as follows:(1)Multi-source data preprocessing and classification of personnel in the research area.In order to more accurately extract and analyze the characteristics of the travel and traffic conditions of the people in the main scenic area of Nanluoguxiang area in a certain time and space,at first,we effectively pre-process multi-source tourist flow data.The data pre-processing include removing noise data,screening out data records related to the research area,and dividing and summarizing the data by hours.Since the bus and subway data records the complete travel trajectory of passengers throughout the day and has the advantage of large volume,the excavated travel characteristics are more representative.Therefore,we use k-means and DBSCAN algorithms to cluster ICcard record data to extract the travel characteristics of individual passengers from three aspects: arrive time,stay time,and the frequency,and then the passengers are divided into commuters,residents and tourists.Finally,we find the hot sites with the strongest spatial correlation with Nanluoguxiang area based on the statistical results and the heat map.(2)Multiple linear regression modeling and analysis.We analysis the tourists in Nanluoguxiang scenic spot and the multi-source public transportation passenger flow surrounding the spot from the two dimensions of time and space,and then studies the distribution differences,periodic changes and correlations among various types of transportation passenger flows.We perform a multiple linear regression analysis on the total passenger flow to the Nanluoguxiang research area and the monitored passenger flow data of the main scenic spot of Nanluoguxiang,and then obtained the impact of public subway,taxi,online ride-hailing and shared bicycle passenger flow on Nanluoguxiang.(3)Extraction of tourist travel characteristics.In order to better optimize the traffic around the scenic spot and clarify the demand for the road network around the scenic spot,we extract and analyse the travel characteristics of tourists in the scenic spot based on multi-source traffic big data,combined with statistical graphs and heat maps to analyze travel distance,travel time,and travel cost and so on.In terms of comparative analysis,the travel characteristics of tourists who choose different modes of transportation.(4)Construct a visualization platform for the tourist flow characteristics in the Nanluoguxiang area.In order to better serve the actual scenic area management,we design and develop visualization platform for population characteristics in Nanluoguxiang based on Browser/Server architecture.This platform integrates a variety of visualization methods to help managers understand the people travel laws,surrounding traffic conditions and so on more intuitively,help to comprehensively improve the management level of the scenic spot.