As public service facilities, urban parks offer many benefits for daily life and social activities for residents. However, the accessibility of public parks to urban residents is often unevenly distributed in spaces that cannot be utilized fully. Here, we used the urban parks in Beijing, China as a case study and examined the relationship between urban park accessibility and population distribution at different administrative levels. Gini coefficient and Lorenz curve were used to evaluate the social equity of urban park accessibility, and the location quotient was used to identify the spatial difference between urban parks and resident population. The results of our study show that the urban park accessibility varies at district and subdistrict levels and that places with more urban parks usually have higher accessibility. Very importantly, the spatial equity is different from the social equity, a mismatch exists between the spatial distribution of urban parks and population, particularly for the elderly residents. These results generate valuable insights, as, in China and many developing countries, current urban public green space planning only uses the ratio of public green space to urban construction land and the per capita public green area.

The urban heat island (UHI) effect has been recognized as one of the most significant terrestrial surface climate-related consequences of urbanization. However, the traditional definition of the urban–rural (UR) division and the newly established local climate zone (LCZ) classification for UHI and urban climate studies do not adequately express the pattern and intensity of UHI. Moreover, these definitions of UHI find it hard to capture the human activity-induced anthropogenic heat that is highly correlated with urban functional zones (UFZ). Therefore, in this study, with a comparison (theory, technology, and application) of the previous definition (UR and LCZ) of UHI and integration of computer programming technology, social sensing, and remote sensing, we develop a new urban functional zone-based urban temperature zoning system (UFZC). The UFZC system is generally a social-based, planning-oriented, and data-driven classification system associated with the urban function and temperature; it can also be effectively used in city management (e.g., urban planning and energy saving). Moreover, in the Beijing case, we tested the UFZC system and preliminarily analyzed the land surface temperature (LST) difference patterns and causes of the 11 UFZC types. We found that, compared to other UFZCs, the PGZ (perseveration green zone)-UFZC has the lowest LST, while the CBZ (center business district zone)-UFZC and GCZ (general commercial zone)-UFZC contribute the most and stable heat sources. This implies that reducing the heat generated by the function of commercial (and industrial) activities is an effective measure to reduce the UHI effect. We also proposed that multi-source temperature datasets with a high spatiotemporal resolution are needed to obtain more accurate results; thus providing more accurate recommendations for mitigating UHI effects. In short, as a new and finer urban temperature zoning system, although UFZC is not intended to supplant the UR and LCZ classifications, it can facilitate more detailed and coupled urban climate studies.

The effects of land use and socioeconomic changes on urban landscape patterns and functional zones have been increasingly investigated around the world; however, our knowledge on these effects is still inadequate for sustainably managing urban ecosystems. The urban functional zone (UFZ) refers to a kind of regional space that provides specific functions for human activities and reflects the land use type in a city. They are important for urban planning and exploring urban texture dynamics. UFZs improve understanding of sustainable development for urban ecosystems with extreme environments and unique social backgrounds. However, the identification methods for UFZs are incomplete because of a lack of socioeconomic attributes, as well as their hierarchical relations. Here, we present a hierarchical weighted clustering model to identify UFZs based on the entropy weight method. The data included points of interest (POIs), land use type data, road network data, socioeconomic data, and population density. We found that the adjusted cosine metric and the average criterion were the optimal distance metric and linkage strategy, respectively, to cluster urban zone data. The performance with weighted data was better than that with raw data, and the level of the POI classification scheme and landscape pattern affected the accuracy of identification UFZs. The research indicated that the hierarchical weighted clustering model was a useful method to classify UFZs in order to improve urban planning and environmental management schemes.

The Yellow River Basin (YRB) serves as a critical ecological functional and economic zone in China. However, due to the rapid economic and social development, the YRB has encountered dual pressure from the anthropogenic disturbances and climate change, leading to intensified conflicts among production, living, and ecological spaces (PLES). In this study, we examined the spatiotemporal evolution pattern and transition mode of the PLES from 1980 to 2020 at the county level, evaluated the eco-environmental effects, and identified the key driving factors. The results indicate that land-use changes in the YRB are marked by a continuous increase in living space, while ecological spaces initially decreased before increasing, and production spaces initially increased before decreasing, with the year 2000 serving as a pivotal point in these transitions. At the county level, land-use transformations in the YRB have significant spatial differentiation. The north region of the Hu Line is predominantly characterized by a reduction in ecological space, whereas the south primarily exhibits declines in production space and increases in living space in the downstream region. Consequently, the environmental quality index (EQI) also exhibits a trend of an initial decline followed by an increase. Frequent mutual conversions between production and ecological spaces influenced by major national ecological conservation policies after 2000, as well as pressure from living spaces on production spaces influenced by population and GDP growth, have been the primary manifestations of spatial transformation in the region. These findings suggest that with the implementation of appropriate governance measures, exploring the transformation of PLES at a finer county level can provide a clearer pattern of spatiotemporal changes, supporting detailed basin management for sustainable development.

Environmental sustainability and high-quality development are global issues since soil deterioration and potential desertification are caused by human activities and global climate change, especially in arid and semi-arid areas. The Loess Plateau is one of the most severely eroded regions in the world. Since the “Grain for Green Program” was established on the Loess Plateau in the late 1990s as a result of the degradation of the soil, it has been an important state policy and demonstration project for ecological protection and sustainable development in China. Therefore, understanding the spatiotemporal changes of soil wind erosion, such as yearly and monthly fluctuations in various periods, under the scenarios of global climate change and human activities, is crucial for carrying out soil conservation initiatives in the Yellow River basin. The revised wind erosion equation (RWEQ) model was applied in this study to evaluate the dynamics of soil wind erosion on the Loess Plateau, China. The soil wind erosion was evaluated on the Loess Plateau from 1981 to 2019 to provide a creative idea for managing ecosystems at the regional scale. By examining the case of the Loess Plateau, we hope to be better able to comprehend the significance of putting environmental protection projects into action to enhance the ecological environment and the well-being of locals, as well as to offer recommendations for the future creation of effective and sustainable development strategies.