The accurate delineation of urban agglomeration boundary is conductive to not only the better understanding of the development relationship between cities in urban agglomeration but also to the guidance of regional functions as well as the formulation of regional management policies. At the same time, the fusion of land relations and urban internal relations can greatly improve the accuracy of the delineation of urban agglomeration boundary. Still, for all that, previous studies delineated the boundary only from the perspective of land relations. In this study, firstly, wavelet transform is used to fuse Night-time Light data (NTL), POI (Point of Interest) data and Tencent Migration data, respectively. Then, the image is segmented by multiresolution segmentation to delineate the urban agglomeration boundary of GBA. Finally, the results are verified. The results show that the accuracy of urban agglomeration boundary delineated by NTL data is 85.57%, with the Kappa value as 0.6256, respectively. While, after fusing POI data, the accuracy is 88.97%, with the Kappa value as 0.7011, respectively. What is more, the accuracy of delineating urban agglomeration boundary by continuous fusion of population movement data reaches 93.60%, and that of Kappa value as 0.8155. Therefore, it can be concluded that compared with delineating the boundary of urban agglomeration only based on land relations, the fusion of population movement data of urban agglomerations by wavelet transform strengthens the interconnection between cities in urban agglomeration and contributes to the accurate division of urban agglomeration boundaries. What is more, such accurate delineation not only has important practical value for optimizing the spatial structure of urban agglomerations, but also assists in the formulation of regional management and development planning policies.

With the development of society, an increasing number of educational institutions have adopted field environmental education activities rather than classroom education. Field education can not only enhance students’ environmental awareness but also enable them to fully understand environmental protection knowledge. Ecological protection areas are important bases for educational institutions to organize students to implement field environmental education. Focusing on Zhuhai City, this study explored spatial relationships between educational institutions and ecological protection zones using Kernel density estimation, the two-step floating catchment area method, and Thiessen polygons. Specific actions included measuring transportation accessibility and dividing the service scopes of ecological protection zones to provide field environmental education for educational institutions. These actions provided a helpful reference for educational institutions to conduct field environmental education activities effectively. The results showed the following: (1) Schools in Zhuhai City were mainly located in subdistricts and presented a spatial layout of “one primary and two secondary.” Students were mainly concentrated in villages and towns and presented a spatial layout of “one core and two centers.” Ecological protection zones were scattered in the township area; their spatial relationships with educational institutions were scattered. Meanwhile, their spatial relationship with the number of students was relatively concentrated. (2) In terms of the accessibility of educational institutions to ecological protection zones, the educational institutions in the northeast of Xiangzhou District and the middle of Doumen District had higher accessibility, while the educational institutions in the middle and south of Zhuhai City had lower accessibility, and the educational institutions in the middle of Xiangzhou District had the lowest accessibility. (3) Based on accessibility, the service scopes of field environmental education activities in ecological protection zones were divided into 15 blocks. Here, the educational institutions located in Xiangzhou District, the western part of Jinwan District, and western, middle, and eastern parts of Doumen District had relatively strong spatial dispersions with the ecological protection zones within their blocks, while the educational institutions located in the central and eastern parts of Jinwan District and northern and southern parts of Doumen District had relatively weak spatial dispersions with the ecological protection zones within their blocks.

This study used the two-step floating catchment area method and potential model to calculate facility accessibility and potential service scope of public health infrastructure distribution, and to evaluate its spatial equity. We applied the Gini coefficient to measure the spatial equilibrium at each level of public health infrastructure in Doumen District, Guangdong, China, from different perspectives. The following results were obtained: (1) Significant spatial differences were observed in the accessibility of public health facilities among different levels; the higher the health facility level, the greater the difference in spatial accessibility. Spatial differences in the accessibility of public health infrastructure at the primary level and higher were distributed in a block-like pattern, while spatial differences in the accessibility of rural health stations were distributed in a circular pattern. Administrative villages tended to have the highest and lowest accessibility of tertiary and secondary hospitals, but not of primary hospitals and rural health stations. The frequencies for administrative villages with the highest and lowest accessibility were 32.8% and 49.6% of the total number of villages in the district, respectively, for tertiary hospitals; 39.2% and 48.8% for secondary hospitals; 19.2% and 24.8% for primary hospitals; 16.8% and 21.6% for rural health stations. (2) The potential service scope was spatially dissociative for tertiary hospitals, and differed more significantly in terms of space for secondary hospitals; the potential service scope of the two overlapped. The potential service scope of primary hospitals was relatively balanced, with strong spatial continuity, while that of rural health service centers was spatially fragmented. The service scope of rural health service centers was mostly consistent with their respective village-level administrative divisions. (3) The higher the level of public health infrastructure, the less balanced its spatial layout. Conversely, the lower the level of public health infrastructure, the more balanced its spatial layout.

Appropriate spatial distribution of primary and secondary schools for relocated children of migrant workers (RCMW) is extremely valuable to ensure the fair education of special groups and improve the quality of their education. This study used concentration analysis, kernel density estimation (KDE), and coefficient of variation (CV) to measure the spatial agglomeration of these children and their primary and secondary schools in the districts and counties of Liaoning Province from 2008 to 2017 based on government surveys. The results showed that the number of RCMW children in primary and secondary schools increased during the research period and the growth rate of children in primary schools was higher than that of children in junior high schools. The number of primary and secondary schools has changed very little, while the number of secondary schools has dropped sharply. The spatial distribution of RCMW and that of their primary and secondary schools were characterized by a “dual-core” distribution and a three-level (county, city, and provincial capital) gradient aggregation. In addition, kernel density evolved from a balanced distribution to polar nucleus-shaped, clustered, and discretized distributions, respectively. Specifically, the “large” and “super-large” schools were mainly concentrated in cities, showing a clustered pattern. “Medium-sized” and “small” schools were mainly distributed in counties, presenting a discretized pattern. In addition, when the CV of the number of RCMW increased, the imbalanced distribution of schools became more significant. Furthermore, the spatial differentiation of primary and secondary schools for RCMW appeared to be affected by economic development, population size, and related policies in the region.

Against the background of social digitalization, networking, and intelligent development, the relationship between China’s digital economy and regional factors is increasingly close. This study systematically cards the relevant references of the digital economy, regional factors, and population based on the six perspectives of industry, residents’ income, urban human settlement environment, infrastructure, the real economy, and government management level to explore the influence of the digital economy on regional factors and regional factors on population. The results show that: 1) the digital economy has a bidirectional influence on the population. Digital economy can both attract population and lead to population outflow through relevant regional factors. 2) Digital economy can indirectly affect the spatial layout of population attributes by giving digital connotations to regional elements. We analyze the influence of China’s digital economic development on the population, build the influence of the digital economy on the population research framework, and put forward the research prospect of the impact of the digital economy on the population to provide a new research perspective on digital economic geography and population, as well as provide significant reference to guide the reasonable population flow and narrow the digital divide gap.