Research On The Driving Forces Of Urban Hot Spots Based On Exploratory Analysis And Binary Logistic Regression Model

The hot spots of people's activities are an important part of urban spatial structure research, and the analysis of the driving forces of urban hot spots can provide a scientific basis for urban planning. The determination of urban hot spots is affected by the heterogeneity of the analysis data, resulting in differences in the hot spot driving factors. To analyze the spatial distributions of urban hot spots, this article conducted a series of exploratory spatial analyses on spatiotemporal travel data and further applied a binary logistic regression (BLR) model to analyze the driving factors affecting the distribution of urban hot spots to accurately characterize the distribution pattern of urban hot spots. First, a spatial autocorrelation test was performed on the trajectory data. Based on the test results, the Getis-Ord Gi* statistical method was used to calculate the distribution area of urban hot spots. Second, considering the internal and external factors that affect the distribution of urban hot spots, 10 driving factors in the categories of terrain, socioeconomics, and road and transportation facility accessibility were selected as the independent variables in the regression model of the hot spot distribution. Third, a BLR model was used to establish a driving force model that altered the distribution of hot spots in cities to explore the influencing factors and the degree of the hot spot distribution. Finally, the accuracy of the hot spot driving force model was evaluated according to the receiver operating characteristic (ROC) curve. Taking Wuhan as an example, the results show that the area under the ROC curve of the hot spot model established in this article reaches 0.918, and the model has a good fit. The formation of urban hot spots is a combination of internal driving factors such as terrain and socioeconomics as well as external driving factors such as the accessibility of roads and transportation facilities. Among these factors, transportation facility accessibility contributes most to the hot spot distribution.