There are few existing studies from a spatial perspective that explore the mechanism of the living environment, relocated direction and relocated distance on the elderly’s physical and mental health. Based on the 2019 household survey questionnaire data, this study utilizes a binomial logistic regression model and residents’ in-depth interviews to study relocated behavior in Nanjing. We analyzed the spatial–temporal characteristics of relocated behaviors, the accumulation effect at different stages and the influence of relocated intention on physical and mental health among the elderly. The findings are as follows: (1) The mode of relocation among the elderly includes long-term cumulative effects and short-term effects. Frequent relocation has a cumulative negative impact on the physical and mental health of the elderly. (2) The elderly relocated in the short-term had a great negative impact on their mental health but had no significant impact on their physical health. (3) In the last relocation, active relocation had a significantly positive impact on physical health. The “centrifugal relocation” from the main urban area to the surrounding new cities has a significant positive impact on mental health. Moreover, long-distance relocations adversely affected mental health.

The popularisation of mobile information technology has provided access to the living habits and activity trajectories of residents and enabled the accurate measurement of the impact of urban haze disasters on residents’ lives, supporting urban haze risk response. Using the main urban area of Gaoyou City as a case study, this study identifies the spatial range and trajectory characteristics of the daily activities of residents in a haze disaster environment, based on air pollution monitoring and resident travel positioning data. We constructed an evaluation index system to measure the corresponding relationship between residential activities and haze disasters. The results indicate that the interference with residential activities and the adaptability of built environments are key indicators for evaluating urban resilience in haze environments, with weights of 0.57 and 0.43, and correlation indices of 0.67 and 0.81, respectively. The interference with residential activities and the adaptability of built environments exhibit spatial characteristics of cold and hot ‘multi-core’ agglomeration and ‘strip’ agglomeration, respectively. Specific indicators show that the residential activity exposure index is significantly influenced by the built environment factor index, with the vegetation coverage index showing a significant positive correlation (0.837) and the public transportation facility accessibility index showing a significant negative correlation (−1.242). Planning should focus on improving the adaptability of the built environment or reducing the interference with residential activities and enhancing the matching degree of the two at the spatial facility level.

Studies on urban shrinkage in eastern China lack relevant contributions. This study investigates population dynamics in Jiangsu Province, focusing on county-level cities to understand the factors influencing urban population size. It developed a multidimensional indicator system per 2014, 2017, 2020, and 2023 statistical data, incorporating road network accessibility, socio-economic levels, resident income, public services, and the built environment. Employing static fixed effects models and dynamic panel regression models, it analyses trends and evolutionary patterns of permanent population changes. The findings indicate an overall increase in the permanent population over the past decade, although the growth rate has slowed in the last five years. Notably, there is a significant spatial clustering of population growth and contraction, often aligned with high-speed transportation corridors. Unlike existing research findings, the urban shrinkage pattern in Jiangsu Province is unique. Some cities in northern Jiangsu exhibit a ‘relative contraction’ pattern, where population decline coexists with high economic growth and spatial expansion. Key short-term factors influencing population size include the city’s economic level and residents’ disposable income, while long-term factors encompass city level, industrial structure, and transportation networks. Small towns exhibit ‘close-range mobility’, with primary short-term influences stemming from residents’ income, public service quality, and intercity transportation accessibility. Indeed, long-term factors primarily reflect economic development quality and urban employment rates.

Low-visibility air pollution frequently occurs in the major cities of China and affects residents’ physical and mental health. This study, using Gaoyou City as a case study, selected 10 typical residential communities with different locations and types and conducted a questionnaire survey for two consecutive weeks to measure commuting behavior characteristics and health effects among residents in environments with different degrees of air pollution from November to December 2022. Concerning commuting distance, the average straight distance for short-distance commuting was 1.4 km, and the median commuting distance was 13.2 km. In air-polluted environments, residents’ commuting times were mainly concentrated within 1.5 h, with a majority taking 20 min to 30 min. The working and living spaces presented a circular core distribution pattern, with low-visibility air pollution significantly affecting the choice of commuting mode and having an indirect impact on health. The proportion of people who chose bus commuting significantly increased as air pollution changed from mild to moderate, whereas the proportion of people choosing slower commuting, such as walking, significantly decreased. While no significant fluctuations in physical health levels occurred, psychological health levels significantly decreased. In high air pollution environments, residents’ sleep quality, attitudes towards life, emotional states, and other assessed factors exhibited an inverted U-shaped correlation with commuting patterns. Low-visibility air pollution indirectly damaged the health of residents by affecting their commuting patterns, reducing their physical activity intensity and commuting options, and increasing their psychological stress and anxiety.

With the improvement in residents’ living standards, non-commuting has gradually become an important daily transportation behaviour for residents. The intensity of non-commuting flow can reflect the level of urban functional services and external attractiveness and can intuitively characterise the interconnection pattern and relationship among various cities within the metropolitan area. Related research is also a key topic in the fields of urban planning and transportation geography from a humanistic perspective. Taking the Shanghai Metropolitan Area as an example, this study explored the characteristics of the non-commuting flow of residents in the region and between cities and its nonlinear influencing factors with the help of the mobile phone signalling data and the gradient lifting decision tree model. Three conclusions were identified: first, non-commuting flow within each city in the metropolitan area was concentrated in the central urban area, while non-commuting flow between cities was concentrated in the central urban area of the urban border and strong core cities. Second, the built environment had a nonlinear impact on residents’ non-commuting flow. Different types of large-scale service facilities had different impact mechanisms on non-commuting flow, and public service facilities and transportation infrastructure jointly affected residents’ non-commuting flow. Third, transportation facilities had a more significant impact on the non-commuting flow between cities. Large tourism, cultural, and medical service facilities had a more significant impact on non-commuting flow within cities, with upper or lower thresholds according to the type of facility. The planning strategy needs to conduct targeted planning, regulation, and facility configuration based on the area’s actual needs. In addition, this study identified the characteristics of non-commuter flow differentiation in street towns and the nonlinear impact of the built environment.

Research on public service facility evaluation has mainly focused on spatial accessibility and facility quality from a supply perspective, but has rarely focused on the evaluation of service facilities from a usage perspective. Researchers can observe the service quality, frequency of use, functional connotation, satisfaction level, and other aspects of facilities from the user’s perspective, effectively compensating for the disadvantage of insufficient precision in traditional macro statistical data. This study proposes a new method for evaluating medical facility usage and service quality based on residents’ activity data. We established an evaluation index system from the perspective of residents’ activity by measuring intensity, frequency, and service satisfaction through network grading data and online comments context. Then, we evaluated the supply and demand relationship of medical facilities, identifying the influencing factors of medical satisfaction. We have also proposed specific strategies for sustainable optimization of medical services. The results show that (1) the service attitude (0.024, 0.002**), service efficiency (0.133, 0.001*), and service quality (0.017, 0.001**) of medical institutions are the core factors that affect medical satisfaction, followed by the convenience of residents in accessing medical resources, showing a significant positive correlation (p < 0.01, Total R² = 0.9061); and (2) the medical service level in Nanjing City is generally balanced, although spatial heterogeneity exists in the Qixia and Jiangning boroughs.