As a fundamental component of trajectory processing and analysis, trajectory map-matching can be used for urban traffic management and tourism route planning, among other applications. While there are many trajectory map-matching methods, urban high-sampling-frequency GPS trajectory data still depend on simple geometric matching methods, which can lead to mismatches when there are multiple trajectory points near one intersection. Therefore, this study proposed a novel segmented trajectory matching method in which trajectory points were separated into intersection and non-intersection trajectory points. Matching rules and processing methods dedicated to intersection trajectory points were developed, while a classic “Look-Ahead” matching method was applied to non-intersection trajectory points, thereby implementing map matching of the whole trajectory. Then, a comparative analysis between the proposed method and two other new related methods was conducted on trajectories with multiple sampling frequencies. The results indicate that the proposed method is not only competent for intersection matching with high-frequency trajectory data but also superior to two other methods in both matching efficiency and accuracy.

With the rapid pace of urbanization, enhancing the quality of life has become an urgent demand for the general public in both developed and developing countries. This study addresses the pressing need to understand the spatial distribution and underlying mechanisms of urban leisure activity participation. To achieve this, we propose a novel methodological framework that integrates diverse big data sources, including mobile phone signaling data, urban geospatial data, and web-crawled data. By applying this framework to the urban area of Nanjing, our study reveals both the temporal and spatial patterns of urban leisure activity participation in the city. Notably, leisure activity participation is significantly higher on weekends, with distinctive daily peaks. Moreover, we identify spatial heterogeneity in leisure activity participation across the study area. Leveraging the OLS regression model, we design and quantify a comprehensive set of 12 internal and external indicators to explore the formation mechanisms of leisure participation for different leisure activity types. Our findings offer valuable guidance for urban planners and policymakers to optimize the allocation of resources, enhance urban street environments, and develop leisure resources in a rational and inclusive manner. Ultimately, this study contributes to the ongoing efforts to improve the quality of urban life and foster vibrant and sustainable cities.

The Tourist Oriented Directional Signs (TODS) system is an essential and important project in constructing and planning scenic areas. At present, the placement of directional signs generally depends on the personal experience of the tour manager to identify important positions and display the name of critical scenic spots on a signboard. Few studies have focused on how to generate the location and display the content of directional signs automatically. This article proposes a method for directional sign location selection and automatic generation of content in a scenic area based on the tourist spatial behavior theory and network analysis algorithm. Junction nodes of the road in a scenic area are used as the candidate locations of the directional signs to be placed. The main steps of the method in this paper include tourist route simulation, betweenness centrality calculation, location selection, and content generation. The Ming Tomb in Nanjing, China, is selected as the experimental area. The evaluation indexes of the traveled distance and the number of errors were adopted. The random walk algorithm is applied to compare the generated scheme with the existing scheme in the experimental scenic area. The generated scheme is also verified through questionnaires and interviews. The results show that the method proposed in this paper can select relevant and appropriate junction nodes where to deploy directional signs and automatically generate displayed content more prominently. The comparison shows that the generated scheme in this method is significantly better than the actual placement scheme. It can optimize the actual placement scheme in the experimental area, and it also can reduce the traveled distance and number of errors.