Urbanization leads to the occupation of green areas, directly contributing to a high level of fragmentation of urban green spaces, which, in turn, results in numerous socioeconomic and environmental problems. Consequently, an understanding of the relationships between patterns of urban green spaces and urbanization processes is essential. Although previous quantitative studies have examined this relationship, they have not included an exploration of spatial heterogeneities in the effects of urbanization on the spatial patterns of urban green areas. We therefore applied a spatiotemporal perspective to examine the above relationship, while considering the wider planning context. First, we quantified the extent of fragmentation of urban green spaces using landscape metrics comprising the largest patch index (LPI) and landscape shape index (LSI). Next, using the calculated spatial metrics and nighttime light data (NTL) for central Beijing for the period 1992–2016, we applied a geographically weighted regression model to assess variations in the spatiotemporal effects of urbanization on the fragmentation of urban green spaces. The results showed that urbanization initially occurred mainly in the northern parts of Beijing, whereas urbanization of southern urban fringe areas occurred after 2008. The reduction in green spaces along with increasing fragmentation and complex spatial patterns are indicative of issues relating to Beijing’s rapid urbanization and planning policies. This study contributes to an understanding of how urbanization influences fragmentation of urban green spaces and offers insights for the planning of urban green spaces from the perspective of promoting sustainability.

Urban green spaces encourage outdoor activity and social communication that contribute to the health of local residents. Examining the relationship between the use of urban green spaces and factors influencing their utilization can provide essential references for green space site selection in urban planning. In contrast to previous studies that focused on internal factors, this study highlights the external factors (traffic convenience, population density and commercial facilities) contributing to the use of urban green spaces. We conducted a spatiotemporal analysis of the distribution of visitors in 208 selected green spaces in central Beijing. We examined the relationship between the spatial pattern of visitor distribution within urban green spaces and external factors, using the Gini coefficient, kernel density estimation, and geographical detectors. The results of the study were as follows. The spatial distribution of visitors within central Beijing’s green spaces was concentrated, forming different agglomerations. The three examined external factors are all associated with the use of green spaces. Among them, commercial facilities are the important external factor associated with the use of green spaces. For the selection of sites for urban green spaces, we recommend consideration of external factors in order to balance urban green space utilization.

Forest Ecological Security (FES) means coordinated development of forest ecosystems, social economies, and the forest environment. In this paper, we evaluate FES in Beijing under different designed scenarios using a dynamic systems model and find that first, the initial FES index value (in Scenario 0) increased to its highest level of 0.529 in 2012, but declined slightly to 0.485 by 2020. Second, in Scenarios 1–4, the FES index value reached 0.545, 0.516, 0.585 and 0.637 respectively in 2020, which was enhanced in varying degrees when compared with Scenario 0. The simulation shows the implementation of forest management policies, socioeconomic development and environmental management combine to affect the FES in Beijing. The FES could develop into a good state when the productivity of forest resources, the stability of forest environments and the orderly development of the social economy are carefully maintained (in Scenario 4). This research could provide decision-making in support of the overall improvement of forest conditions while promoting sustainable forestry in Beijing.

Greater contradiction and conflict among urban green space, the development of social economy and the environment have occurred in Beijing. However, few studies have been conducted that consider the three subsystems as a whole. In this study, we defined sustainable development of green space (SDGS) as the coordinated development of the urban green system, social economy, and environment. Based on the datasets from 2000 to 2015, we forecast the SDGS in Beijing under multiple scenarios based on real-world policies using a system dynamics model. We found that the historical SDGS value increased to its highest level in 2012, but declined slightly by 2015. Second, the forecasted SDGS values declined over time in all scenarios, but the decline was greater in scenarios placing a high priority on economic development. In these scenarios, the performance of the indices only improved in certain subsystems. The simulation shows the implementation of the four policies proposed by the government failed to improve the overall level of SDGS in Beijing. This study could provide support for decision-making designed to improve the overall condition of urban green space in Beijing through integrated forecast and scenario simulation.

Net primary productivity (NPP) is an important index with which to evaluate the safety and quality of regional carbon sinks. Based on the improved CASA model, climate data, social data, remote-sensing ecological data, and other multi-source data types, this article took a Chinese city, Yangzhou, as the research object, used Theil–Sen medium-trend analysis and the Hurst index to analyze its spatial–temporal-evolution characteristics and future change trends, and used geographical detectors to analyze the impact of climate, social, ecological, and other factors on the change in NPP in the study area, with the intention of providing a theoretical exploration and practical basis for achieving the “dual carbon” goals in the region. The results showed that the annual average NPP levels of the vegetation in Yangzhou in the five sampling years were 445.343 gc/m²·a, 447.788 gc/m²·a, 427.763 gc/m²·a, 398.687 gc/m²·a, and 420.168 gc/m²·a, respectively, exhibiting a trend that first decreases and then increases, with a slight overall decrease from 2000 to 2020. The area in which the vegetation in Yangzhou had the higher grades of NPP increased by 203,874 km², and an increase of 321,769 km² in the lower levels was observed. The NPP level of vegetation showed polarization, with relatively high levels in the surrounding farmland and mountain–forest areas and relatively low levels in densely populated urban areas. The ranking was highest in Baoying and lowest in Gaoyou. From the average NPP of all the land types in the study area, the following trend was exhibited: forest land > farmland > bare soil > impermeable surface > water. The future change in vegetation NPP in Yangzhou City will mainly follow the trend of the past 20 years, with a slow decrease. The NDVI (q = 0.728) and LUCC (q = 0.5601) were the leading driving factors of vegetation NPP change in Yangzhou City, and the interaction effect of double driving factors was greater than that of single driving factors.