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Building an aging-friendly city is necessary, considering the unprecedented demographic shift of the aging population. It is necessary to study the built environment conditions surrounding the elderly’s residential areas. This study examines the density, diversity, and design (3D) features around the two typical elderly communities, which are community-based care and the nursing home. Then, the equity analysis is conducted from the social and spatial perspective. We use the 3D framework to measure the built environment around elderly communities. The essential features of an aging-friendly community are used to assess the built environment around the elderly communities. Moreover, we analyze the social and spatial equity of the elderly communities from the facility level and the town level. From the facility level, the 3D features of the elderly communities and the whole communities are compared to identify the social disparity among groups. From the town level, the average values of the 3D features are aggregated to each town, and then the attribute values of the towns are compared to reveal the spatial gaps and spatial mismatch areas. Results found that the spatial distributions of the 3D features around elderly communities present the center-periphery patterns. This study also found that a social disparity exists between the elderly communities and the whole communities. Moreover, there is a spatial mismatch between the diversity of facilities, road connections, and the number of elderly. Towns located in the fringe area are with a high number of elderly, but with a low diversity and road connections. The findings of this study can help planners and decision-makers to optimize the living facilities for old people and inform the gap in planning an aging-friendly city.

China’s development zones have been enjoying a process of dramatic growth and restructuring since the start of the new millennium, which has been extensively documented in the literature. The growth stems from the increased scope and expansion in demand created by China’s economic growth, as well as gradual global economic reconfiguration, which has, in itself, become a factor in advancing the country’s spiraling economic growth. This article examines the trajectory of the growth and restructuring of China’s development zones since 1984, by reviewing critical policies and their measures and effects, as well as academic research in this field, focusing on transitional stages, features and mechanisms. Based on different academic viewpoints, the work sets out a three-pronged conceptual framework composed of institutional transition, industrial evolution and land use transformation to systematize the growth process. In recent years, the restructuring of development zones has come to be considered as a comprehensive and complex issue, and its main challenges arise from factors such as overcoming outdated institutional arrangements, strengthening market participation, promoting high-end industrial agglomeration and breaking the bottleneck of inefficient land use. This article uses a multi-dimensional, logical approach to address the growth of development zones, and examines relevant practices and studies so as to explore the deeply rooted correlations between different dimensions in more depth and to examine the innate and unchanged logic involved in the restructuring of development zones.

Greenspace exposure (GSE) may have a positive impact on mental health. However, existing research lacks a classification analysis of the influence pathways of different GSE on mental health. Meanwhile, the research method is limited to the measurement of the green space ratio (GSR) based on remote sensing data, which ignores people’s real perception of greenspace. This paper aims to further expand the measurement method of GSE, taking Hangzhou, China as an example, and to reveal the influence mechanism of different GSE modes on mental health. We obtained the personal information, mental health, physical activity, and other data of the interviewees through a questionnaire (n = 461). Combined with a remote sensing satellite and the Baidu Street view database, the method of image interpretation and deep learning was used to obtain the GSR, green visual ratio (GVR), and green visual exposure (GVE). The structural equation model is used to analyze the relationship between different variables. The results showed that: (1) GSE has a certain positive effect on mental health; (2) there are differences in the influence mechanism of multiple measures of GSE on mental health—the GVR and GVE measures based on the interaction perspective between human and greenspace make the influence mechanism more complicated, and produce direct and indirect influence paths; and (3) greenspace perception, sense of community, and physical activity can act as mediators, and have indirect effects. Finally, we call for expanding the measurement index and methods of GSE and integrating them into the management and control practices of urban planning to promote the healthy development of communities and even cities.