Spring Festival travel rush is a phenomenon in China that population travel intensively surges in a short time around Chinese Spring Festival. This phenomenon, which is a special one in the urbanization process of China, brings a large traffic burden and various kinds of social problems, thereby causing widespread public concern. This study investigates the spatial-temporal characteristics of Spring Festival travel rush in 2015 through time series analysis and complex network analysis based on multisource big travel data derived from Baidu, Tencent, and Qihoo. The main results are as follows: First, big travel data of Baidu and Tencent obtained from location-based services might be more accurate and scientific than that of Qihoo. Second, two travel peaks appeared at five days before and six days after the Spring Festival, respectively, and the travel valley appeared on the Spring Festival. The Spring Festival travel network at the provincial scale did not have small-world and scale-free characteristics. Instead, the travel network showed a multicenter characteristic and a significant geographic clustering characteristic. Moreover, some travel path chains played a leading role in the network. Third, economic and social factors had more influence on the travel network than geographical location factors. The problem of Spring Festival travel rush will not be effectively improved in a short time because of the unbalanced urban-rural development and the unbalanced regional development. However, the development of the modern high-speed transport system and the modern information and communication technology can alleviate problems brought by Spring Festival travel rush. We suggest that a unified real-time traffic platform for Spring Festival travel rush should be established through the government's integration of mobile big data and the official authority data of the transportation department.

Predicting the spatio-temporal evolution characteristics and trade-off/synergy relationships of ecosystem service value (ESV) under different policy scenarios is of great significance for realizing regional sustainable development. This study established a framework and used the geographical simulation and optimization systems-future land use simulation (GeoSOS-FLUS) model and bivariate local autocorrelation analysis to stimulate and predict the impact of land use change on the ESV of Anyang City from 1995 to 2025. We also explored the trade-offs and synergy among ecosystem services under three policy scenarios (natural evolution, cultivated land protection, and ecological protection) in 2025. Results show that (1) the land use change in Anyang from 1995 to 2025 was significant, and the degree of land use change under the cultivated land and ecological protection scenarios was more moderate than that under the natural evolution scenario; (2) The total ESV decreased between 1995 and 2015, amounting to losses of 1126 million yuan, and the decline from 2015 to 2025 under the natural evolution scenario was more significant than those under the cultivated land protection and ecological protection scenarios; and (3) an obvious synergy was observed between various ecosystem services in Anyang City under different scenarios in 2025, and the most significant synergy was observed under the natural evolution scenario. In terms of spatial distribution, the agglomeration of “high–high” synergy in the west and “low–low” synergy in the central region was significant. Local areas showed “high–low” and “low–high” trade-off relationships scattered between their built land and woodland or cultivated land. The proposed framework can provide certain scientific support for regulating land use and ecosystem services in rapidly urbanized areas.

In the increasingly serious aging China, aged service is the provision of one of the most urgent and important public services to citizens, and private facilities has become an important service force with the aged service market opening in China. This study aims to explore the spatial variation in the accessibility of residential aged care facilities (RACFs) and compared the service capacity of public RACFs and private RACFs. It facilitates RACFs to be allocated rationally in the future and achieve the equalization of aged services. A village-level analysis of spatial access to public and private RACFs by the multi-catchment sizes Gaussian two-step floating catchment area (MCSG2SFCA) method was conducted through a case study in Wuhan City in Central China. The major results are as follows: (1) the accessibility of RACFs in urban areas is better than that in rural areas; (2) the public RACFs still dominate aged care services but the role of private RACFs is important as well; (3) in developed urban areas, the accessibility to private RACFs surpasses that of public ones, and the situation is opposite in rural areas; (4) the capacity of aged care services in Wuhan is not high, meanwhile there is remarkable regional disparity. The accessibility of RACFs in Wuhan is not satisfactory, and there is a significant gap between urban and rural areas. The private RACFs have significantly improved the urban capacity of aged care services, but the role in rural areas is still very weak.

In urban and rural areas under rapid urbanization, a proper understanding of the relationship between population and construction land use is important for regional sustainable development. The decoupling method is a particularly useful way to examine this relationship. However, the decoupling method only considers the current relationship between population and construction land, ignoring the initial status in the base year. Based on an improved decoupling model, vector land-use data (1:10,000 scale) from two National Land Investigations, and demographic data from the China Statistics Bureau, this paper analyzes population and construction land use change patterns as well as the types of coupling in urban and rural Hubei. The results better reflect the relationship between population and construction land use. The outcomes show that from 2009 to 2014, both the urban population and urban construction land use increased while the rural population decreased as rural settlement land use expanded. In 61 counties, the relationship between the urban population and construction land use showed expansive negative decoupling; that is, the growth rate of urban population was less than the growth rate of the urban construction land use. In 72 counties, the relationship between the rural population and rural settlement land showed a strong negative decoupling; that is, the rural population decreased while the rural settlement land use increased. The relationship between the urban–rural population and construction land use can be divided into eight types. Only nine counties are somewhat coordinated, while the other counties were all uncoordinated. Suggestions are provided by comparing per capita urban construction land and per capita rural settlement land in the base and current years with the national standard and considering the coupling types for population and construction land use change in urban and rural settings. Finally, we discuss approaches to optimize urban–rural space organization and promote coordinated urban–rural development.

China has entered a new era of comprehensive promotion of rural revitalization and integrated urban–rural development. The identification and optimization of the spatial structure of urban and rural settlements are of great significance to the realization of rural revitalization and integrated urban–rural development. This study proposes a method framework for identifying and optimizing the spatial structure of urban and rural settlements from a hierarchical network perspective. This framework includes three parts—namely, the identification, analysis, and optimization of the hierarchical network structure of these settlements. The identification of this structure is the foundation of this study. To realize the identification, for each settlement, this study finds and retains its strongest interaction with other settlements which have a stronger capacity for development. This study used Hua County in Henan, China, as an example to verify the method framework. Results showed that the spatial structure of the urban and rural settlements in Hua County identified in this study was complete and continuous, with significant hierarchical and community characteristics. Based on this, a five-level optimization system of these settlements was constructed. This study expands the method used to study the spatial structure of urban and rural settlements from the network perspective and has a theoretical and practical significance for the optimization of the spatial structure of these settlements.

This study proposes an innovative integrated method for evaluating the evacuation and rescue capabilities of open spaces through a case study in Wuhan, China. A dual-scenario network analysis model was set up to calculate travel time among communities, open spaces, and rescue facilities during peak and non-peak hours. The distribution of traffic flow was derived on the basis of a gravity model and used to construct supply-demand indexes (SDIs). SDIs such as evacuation (ESDI), rescue (RSDI), and comprehensive SDIs (CSDI) were used to evaluate the suitability of open space locations. This study drew five major findings as follows: (1) ESDI, RSDI, and CSDI can effectively evaluate the spatial suitability of open spaces when these SDIs are integrated with the gravity model. (2) The quadrant distribution analysis of ESDI can be an effective method for determining the reasons for the change in values in the two traffic scenarios and for helping planners in adjusting their policies to enhance the capability of an area. (3) The impact of the different β values on SDIs can show positive, negative, and inconspicuous correlations with large, moderate, and minimal variations, respectively. (4) The analysis of the supply-demand relationship of open spaces in Wuhan indicates a spatial mismatch in comprehensive evacuation and rescue capacities. (5) Traffic congestion can be a significant impact factor on evacuation and rescue capabilities but not on comprehensive capability.