The urban bus service system is one of the most important components of a public transport system. Thus, exploring the spatial configuration of the urban bus service system promotes an understanding of the quality of bus services. Such an understanding is of great importance to urban transport planning and policy making. In this study, we investigated the spatial characteristics of an urban bus service system by using the complex network approach. First, a three-step workflow was developed to collect a bus operating dataset from a public website. Then, we utilized the P-space method to represent the bus service network by connecting all bus stop pairs along each bus line. With the constructed bus network, a set of network analysis indicators were calculated to quantify the role of nodes in the network. A case study of Shenzhen, China was implemented to understand the statistical properties and spatial characteristics of the urban bus network configuration. The empirical findings can provide insights into the statistical laws and distinct convenient areas in a bus service network, and consequently aid in optimizing the allocation of bus stops and routes.

China has achieved success in implementing the rural revitalization strategy and promoting the development of new urbanization. However, there are still many problems in the research and implementation on urban–rural integration development, such as insufficient research at the township level, unclear recognition of development patterns, and disconnection from land-use planning. Therefore, taking Hanchuan city in the Wuhan metropolitan area as a case study, this research constructs a comprehensive evaluation system of urban–rural integration development based on both on the current and potential level of development, and identifies the spatial characteristics and patterns in the study area. This study found that: (1) The comprehensive evaluation result of urban–rural integration development in Hanchuan City shows that a high level of development units are mainly distributed in the northeast and southwest, and gradually decreases from the northeast and southwest, indicating that towns in the central area are relatively weakly driven by the radiation of the surrounding growth poles. (2) Xiannvshan Street, Makou Town, Chenhu Town, and Xinyan Town with the highest comprehensive evaluation values were selected as the centers of urban–rural integration development in four directions. (3) Four typical patterns of urban–rural integration development, which are town gathering, agro-tourism interaction, industry-trade driven, and agricultural service, are derived by the gravity model and classification assignment method according to their respective centers. (4) According to the urban–rural integration development patterns, land-use strategies such as centralization for promoting linkage level of towns, differentiation for arranging various resources and infrastructures, and demonstration for optimization of experience to the whole area are proposed in a targeted manner. This study has important implications for the preparation and implementation of urban–rural integration development and provides effective planning guidance for promoting social equity and accessibility of facilities in the metropolitan area.

Modeling the distribution of daily and hourly human mobility metrics is beneficial for studying underlying human travel patterns. In previous studies, some probability distribution functions were employed in order to establish a base for human mobility research. However, the selection of the most suitable distribution is still a challenging task. In this paper, we focus on modeling the distributions of travel distance, travel time, and travel speed. The daily and hourly trip data are fitted with several candidate distributions, and the best one is selected based on the Bayesian information criterion. A case study with online car-hailing data in Xi’an, China, is presented to demonstrate and evaluate the model fit. The results indicate that travel distance and travel time of daily and hourly human mobility tend to follow Gamma distribution, and travel speed can be approximated by Burr distribution. These results can contribute to a better understanding of online car-hailing travel patterns and establish a base for human mobility research.

Rapid urbanization and land use changes have brought enormous pressure onto the ecological environment. Constructing ecological security patterns (ESPs) contributes to scientifically utilizing ecosystem functions, maintaining biodiversity, and protecting the ecological environment. Thus, this study proposed a regional ESP construction framework, which integrated circuit theory with an ecological security evaluation system composed of a landscape connectivity analysis, an ecosystem service evaluation, and an ecological sensitivity analysis, to generate the ESP of the national-level Chang-Zhu-Tan Metropolitan Area (CZTMA). The results showed that (1) there were 22 ecological sources mainly consisting of woodlands, grasslands, and water bodies and distributed heterogeneously from the eastern to western CZTMA; (2) 48 ecological corridors connected the large-scale ecological patches such as rivers, lakes, wetlands, and woodlands in the CZTMA, and the average distance of the east side was shorter, while the distance of the west side was longer; and (3) 13 ecological pinch nodes and 28 ecological barrier nodes were identified as important nodes. On this basis, this research constructed a multi-level ESP consisting of “one center and multiple cores, one belt and two screens, multiple corridors and multiple nodes” for the CTZMA, which not only guarantees the stability of ecosystems but also maintains their efficiency in providing ecological services and their resistance to the pressure of human activities. Moreover, a series of specific recommendations for the optimization of regional ESPs were provided, including protection of ecological sources and enhancement of their habitat quality, improvement of ecological corridor connectivity, maintenance of pinch nodes, and restoration of barrier nodes. Coordinated mechanisms at the provincial level were proposed. This study could help with ecological conservation and restoration, and strategic planning making in integrated nature–human systems that cross administrative boundaries.

Metropolitan areas in China are not only the core spatial carriers of urbanization development but also the main generators of land use carbon emission (LUCE). However, existing research lacks comparative studies on the differential patterns and impact factors of LUCE in different stages of metropolitan areas. Therefore, this paper deeply analyzes the spatial characteristics of LUCE and the coupling coordination degree (CCD) of the economy contributive coefficient (ECC) and ecological support coefficient (ESC) in three different stages of metropolitan areas in the Yangtze River Economic Belt (YREB), China. Moreover, quantitative modelling of the impact factors of LUCE in these different stages of metropolitan areas is furtherly revealed. Results show that: (1) The more mature stage of the metropolitan area, the higher the amount of LUCE, and the more districts or counties with high carbon emissions levels are clustered. (2) At the metropolitan area scale, the more mature the metropolitan area is and the lower the CCD between ECC and ESC is, while at the finer scale, more developed counties have lower CCD. (3) Resident population, per capita GDP, and urbanization rate have good explanatory effects on carbon emissions in these three metropolitan areas; however, except for the urbanization rate, which has a negative effect on LUCE in Nanchang metropolitan area (NMA), the other two factors have positive effects on LUCE in these three metropolitan areas. This study has important implications for different stages of metropolitan areas to formulate targeted LUCE reduction policies.

Understanding intra-urban travel patterns is beneficial for urban planning and transportation management, among other fields. As an emerging travel mode, online car-hailing platforms provide massive and high-precision trajectory data, thus offering new opportunities for gaining insights into human mobility. This paper aims to explore temporal intra-urban travel patterns by fitting the distributions of mobility metrics and leveraging the boxplot. The statistical characteristics of daily and hourly travel distance are relatively stable, while those of travel time and speed have some fluctuations. More specifically, most residents travel between 2 and 10 km, with travel times ranging from 6.6 to 30 min, which is fairly consistent with our daily experience. Mainly attributed to travel cost, individuals seldom use online car-hailing for too short or long trips. It is worth mentioning that a weekly pattern can be found in all mobility metrics, in which the patterns of travel time and speed are more obvious than that of travel distance. In addition, since October has more rainy days than November, travel distances and travel times in October are higher than that in November, while the opposite is true for travel speed. This paper can provide a beneficial reference for understanding temporal human mobility patterns, and lays a solid foundation for future research.