Economic development and natural amenity: An econometric analysis of urban green spaces in China

Rapid urbanization and spontaneous economic development has brought about profound changes in urban landscapes throughout the world. The task of managing transforming urban landscapes, particularly urban green spaces, so as to provide sufficient natural amenity for increasing urban populations, is one of the critical challenges facing policy makers. However, little empirical evidence exists about the evolving path of urban green spaces along with economic development and urbanization. This study attempts to fill in this knowledge gap through an econometric analysis of panel data across 285 Chinese cities during a period of rapid urbanization and economic growth (2001–2010). The results point to the existence of an N-shaped environmental Kuznets curve (EKC) for an important aspect of environmental quality: urban green spaces. Urban green space coverage increases at the initial stage of economic development, and then it starts to decrease as GDP per capita exceeds RMB50,855 and then increases again at a high GDP per capita level (RMB107,558). Large elasticity (>1) is expected as GDP per capita grows to a higher level (beyond RMB128,095). By the end of 2010, 30% of Chinese cities are still located on the downward-sloping path and only four cities have attained elasticities greater than one. The findings present a challenging and pressing call for policy makers to effectively manage the tradeoffs between continuous economic development and better natural amenities.     

Effects of vegetation structure and environmental characteristics on pollinator diversity in urban green spaces

With accelerating urbanization, insect pollinators in urban ecosystems face challenges such as reduced pollen sources, habitat fragmentation, and damage to the nesting environment. Urban green spaces (UGS) are essential for the stability of pollinator communities. However, little is known about the relationship between vertical layer heterogeneity and horizontal layer complexity of vegetation structure in UGS and pollinator communities. The present study aimed to assess how vegetation structure and environmental characteristics shape the insect pollinator community in UGS. To this end, this study was conducted with seven typical vegetation types which were selected according to the biotope mapping classification system (BMCS) in the ring parks around Hefei City, in Anhui province, China. A total of 11,401 pollinators belonging to 6 orders and 34 families were identified during the eight-month survey. Among the seven habitats under the BMCS, mainly successional short-cut shrub and partly open green space, trees two- or multi-layered broad-leaved mixed forest and partly closed green space, and mainly successional tall grass and partly open green space were identified as high-quality insect pollinator habitats. According to the results of the generalized linear regression, the explanatory power of the four best-fitting generalised linear models is relatively high (over 77%). In four optimal models, the effect of vegetation structure on pollinator community was greater than that of environmental characteristics. The redundancy discriminant analysis showed that the flowering abundance of nectar plants, herb richness, and shrub coverage rate were the three most important factors influencing insect pollinator communities, with a cumulative explanatory power of up to 78.8%. Pollinator abundance was positively influenced by spontaneous herbs and low-intensity management. However, high-intensity management, low diversity of plants, low nectar plant richness, ignoring seasonal nectar plant configuration, and dense tree distribution could limit pollinator reproduction and population growth. These results reflect the status of insect pollinator community in UGS in Hefei city and present a possible direction for improving urban green habitats and plant configurations.     

A general grass growth model for urban green spaces management in tropical regions: A case study with bahiagrass in southeastern Brazil

Urban green spaces (UGS) positively impact the population, providing essential ecosystem services and improving public health. Urban vegetation management needs to optimize mowing process costs and reducing impacts on the natural ecosystem. Thus, we implemented a general grass growth model suitable for UGS management in tropical areas, focused on lawns, public parks and squares, roadsides, and around waterways. The model incorporates local edaphoclimatic conditions to simulates the daily dynamics of leaf area index (LAI), biomass, evapotranspiration, and soil water content, going under mowing processes or not, with spatialization capability which might be integrated within geographic information system (GIS) environments. A case study assessing bahiagrass (Paspalum notatum Flüggé) vegetation species in São Carlos, southeastern Brazil, is presented, considering two scenarios to demonstrate the spatial capabilities of the model: (i) UGS as a single area, and (ii) several areas independently. For model validation, vegetation indices calculated based on data from an unmanned aerial vehicle (UAV) and CubeSat imagery (PlanetScope) were used to retrieve LAI time series, calibrated with spectral signatures from leaf ground sampling. For performance analysis, LAI time series from the model and LAI retrieved from both sensors were compared via determination coefficient (R²⁾ and root mean square error (RMSE). Our findings suggest that the proposed model is accurate, and due to its spatialization capability and integration with a GIS, its application may help government administrations to optimize UGS mowing processes.     

Advancing research on urban greenspace experiences and perceptions in disadvantaged communities: A social housing perspective

Empirical assessments of the experiences and perceptions of urban green space (UGS) in a social housing context are scant. Studying UGS perception in these contexts is important to understand how people experience and derive benefits from UGS in disadvantaged communities. This short communication provides interdisciplinary and methodological guidance on how to conduct empirical assessment of UGS experience and perception in social housing neighborhoods. For conducting these types of studies, we suggest researchers go beyond simply calculating UGS abundance around communities and consider assessing UGS experiences and perceptions. We suggest designing studies that account for the mixed nature of many social housing communities and that develop useful UGS perception measures that can be associated with wellbeing and community indicators. Finally, we also recommend: (1) designing studies at the local scale and developing strong relationsihps with the social housing communities before and while conducting these studies; (2) considering safety as a key component of UGS perception measures; (3) considering the association between UGS perception measures and wellbeing and community experience indicators to strengthen existing models of UGS benefit provision.     

Refining the accessibility evaluation of urban green spaces with multiple sources of mobility data: A case study in Shenzhen,China

Urban green space (UGS) is an important component of urban resources which contributes to human physical and mental health. Studies on the accessibility of UGS under the two-step floating catchment (2SFCA) framework have recently received much attention. However, the effects of people’s actual mobility patterns have not been fully considered in current studies. Proposed in this study is an improved accessibility model called AM-Ga2SFCA, which refines the traditional Gaussian 2SFCA method with the actual mobility information extracted from mobile phone big data and online map. A new attractiveness index of UGS is implemented by combining the popularity evaluated by the PageRank algorithm and the actual utilisation based on buffer analysis. In addition, realistic travel time between each demand point and UGS is retrieved from the online map, which is further introduced into AM-Ga2SFCA as the travel cost. A case study is conducted in Shenzhen, China to validate the proposed model. Results show that the accessibility of UGS is strongly correlated with regional urbanization level, for example, higher accessibility generally occurred in the region with developed transportation and rich green resources. From the perspective of age groups and travel modes, we found that the environmental justice issue had already occurred in Shenzhen especially for the non-elderly: under the walk mode, nearly 80% of the non-elderly only shared 20% of UGS whilst approximately 80% of the elderly shared 30% of UGS. However, taxi or private vehicles can effectively alleviate the aforementioned phenomenon by reducing the Gini index to less than 0.5. The proposed model is expected to advance the understanding of UGS accessibility and facilitate effective planning to reduce environmental justice.