An essential part of urban natural systems, urban green spaces play a crucial role in mitigating the urban heat island effect (UHI). The UHI effect refers to the phenomenon where the temperature within a city is higher than that of the surrounding rural areas. The effects of the spatial composition and configuration of urban green spaces on urban land surface temperature (LST) have recently been documented. However, few studies have examined the effects of the directionality and distribution of green spaces on LST. In this study, we used a landscape index to describe the change in pattern of heat island intensity for the city of Baotou, China. We then used a semi-variable function and nearest neighbor algorithm to analyze the cooling effects of green spaces. We found that: (1) the cooling distance of an urban green space was not only influenced by its size, vegetation cover, and shape, but also showed anisotropy. In general, the larger the area of the urban green space and the higher the value of Normalized Difference Vegetation Index (NDVI; a measure of plant photosynthetic activity), the larger the cooling distance within a certain threshold. Green spaces with more regular shapes displayed higher LST mitigation; however, the cooling distance was directional, and cooling effects depended on the semi-major axis and semi-minor axis of the green space. (2) The distribution of the urban green space within the landscape played a key role in mitigating the UHI effect. Within a certain area, the cooling effect of green spaces that are evenly distributed was greater than that which was associated with either green spaces that were large in area or where greens spaces were aggregated in the landscape. Therefore, within urban areas, where space is limited, urban planning should account for green spaces that are relatively scattered and evenly distributed to maximize cooling effects. The results of this study have key implications for sustainable urban planning and development; to mitigate urban heat island effects it is important to not only increase canopy cover or the size of urban green spaces, but also to optimize their spatial configuration.

Ecosystem services management should often expect to deal with non-linearities due to trade-offs and synergies between ecosystem services (ES). Therefore, it is important to analyze long-term trends in ES development and utilization to understand their responses to climate change and intensification of human activities. In this paper, the region of Uxin in Inner Mongolia, China, was chosen as a case study area to describe the spatial distribution and trends of 5 ES indicators. Changes in relationships between ES and driving forces of dynamics of ES relationships were analyzed for the period 1979–2016 using a stepwise regression. We found that: the magnitude and directions in ES relationships changed during this extended period; those changes are influenced by climate factors, land use change, technological progress, and population growth.

This study introduces risk theory of environmental science into human settlement science using 2004–2013 statistics, remote sensing data, and thematic maps. The entropy weight method and risk-index model are both used to study the characteristics of the time course and spatial pattern of human settlement risk in 31 provincial regions in China. In addition, influential mechanisms of vulnerability, functionality, stress, and adaptability on environmental risks are analyzed. Three primary results are obtained. First, for temporal characteristics, environmental risks of human settlements increased significantly from 2003 to 2012. The year 2006 marked both a sudden change and the cut-off point after which human settlements in China experienced qualitative changes and new risks. Second, for spatial characteristics, the risk index of human settlements decreased gradually from the southwestern to the northeastern, northwestern, and northern parts of China. The risk index of human settlement spaces differed significantly, with obvious block aggregation of spatial-distribution characteristics. Third, for relevant factor characteristics, between 2003 and 2012, the temporal change in vulnerability is relatively stable, with a slight increase in functionality and a slight decrease in adaptability. Spatially, Qinghai, Tibet, southwestern China, Guangdong, Guangxi, Beijing, and Tianjin had relatively high vulnerability in human settlements; Beijing, Tianjin, Jiangsu, and Zhejiang had the best functionality; Hunan and Sichuan had relatively high stress; and Guangdong, Jiangsu, and Zhejiang had relatively stronger adaptability. Further consideration and discussion are required on the environmental risks for different social groups and at different geographical scales, as well as on the uncertainty and long-term features of environmental risks in addition to environmental justice issues.