The value of a cultural ecosystem service depends on the perception of different cultural service categories. However, the data sources used in research on the perception of cultural service have limitations that mainly depend on social investigation, leading to slow progress in cultural service evaluation. With the advent of the era of network big data, social media provides a new data source for the study of cultural ecosystem service perception, so that the study of these services is expected to make new breakthroughs. Using search crawler software, this paper reviewed 7257 online comments related to 19 city parks in Xuzhou City, China. With the help of Rost Content mining semantic analysis software, the comment sentences were divided into keywords, and the Delphi expert method was used to classify these keywords. Thus, a cultural service perception database was established. Through statistical analysis, with the help of ArcGIS software, various cultural services were analyzed. The results showed that (1) the cultural services of urban parks could be divided into seven types (i.e., aesthetics, recreation, sports, inspiration, education, cultural heritage, and spiritual satisfaction) using social network comment data. (2) High-frequency keywords of online comment data can serve as the core basis during an analysis of the perception of cultural services by visitors of city parks. However, a large gap exists in the number of high frequency keywords in different parks. For example, Yunlong Lake Park has 2887 keywords, while Kuaizai Ting Park has only 33. (3) Differences exist in the perception of cultural service in urban parks, the park’s scale, and characteristics determine the visitor’s cultural service perception level. The aesthetic and recreation types were the most easily perceived, and 68% and 63% parks have the above two perceptual records, respectively. Therefore, the social media comment data has the ability to document perception of each park’s cultural service type and its differences, which can serve as the cultural ecosystem service perception as well as the valuation data source, to supplement the social investigation.

Taking China’s industrial land transfer data as the data source, this study quantitatively analyzes the transfer structure and spatial distribution of China’s industrial land from 2010 to 2019. By constructing the information entropy and the equilibrium degree model of industrial land-use structure, this study evaluates the transfer characteristics of industrial land of different functional types in various provinces of China, analyzes the scale advantages of various types of transferred industrial land by using the land transfer scale advantage index, and summarizes the spatial distribution characteristics of different types of industrial land transfer in China through the spatial center of gravity analysis and cold/hot spot regional distribution mapping. The following results were obtained. (1) There are significant differences in the transfer scale of industrial land among provinces in China. The transfer scale of Eastern and Central China is large, whereas that of Western China is small. (2) From the perspective of land-use structure, the transfer scale of industrial land in the central and western regions is more balanced than that in the east. (3) From the gravity center distribution of the standard deviation ellipse, the land transfer direction of the energy industry, and the mining industry, and other types of industries is more significant than that of the culture and sports hygiene industries, modern manufacturing industry, and high-tech industry. (4) From the analysis of cold and hot spots, the mining industry, the energy industry, and other types of industries in the western region with rich mineral resources are the hot spots of industrial land transfer, and the southeast coast is the cold spot; the eastern coastal area is a hot area for land transfer of modern manufacturing, the high-tech industry, and the culture and sports hygiene industries. The results reveal the regional differences and spatial distribution characteristics of industrial transfer in China and provide a reference for authorities to formulate industrial planning and industrial land collection, storage, and transfer plans.

As a unique ecosystem with multiple ecological functions but high fragility, grassland in arid areas is very vulnerable to changes in the natural environment or human activities, resulting in various ecological and environmental problems. In order to study the degree and spatial extent of the influence of climatic conditions and human activities, especially mining activities, on grasslands in arid regions, we used remote sensing data to monitor the vegetation of the Xilin Gol grassland over a long period. The significant greening and browning areas of Xilin Gol grassland vegetation from 2000 to 2020 were extracted by a time series analysis. At the same time, the correlation analysis method was used to obtain the response of the Xilin Gol grassland vegetation to climatic factors and social and economic factors. In addition, we propose a new method based on buffer analysis and correlation analysis to calculate the influence range of vegetation degradation due to mining. We used this method to determine the influence range of vegetation degradation in the main mining area of the Xilin Gol grassland. The results showed that the vegetation condition of the Xilin Gol grassland were slightly improved from 2000 to 2020. Its vegetation was significantly affected by precipitation, and more than 50% of the area’s vegetation changes were highly correlated with precipitation changes. However, the area with the most serious vegetation degradation was mainly affected by human factors, and this part accounted for about 0.13% of the total area. In the form of direct damage and indirect effects (pulling population and economic growth to expand built-up areas), coal mining has become the main driving factor in the most significant areas of vegetation damage in the study area. Vegetation coverage in areas with significant greening and significant browning was highly correlated with economic factors, indicating that the vegetation changes were significantly affected by economic development. This study can reflect the vegetation changes and main driving factors in the overall and key areas of the Xilin Gol League and is a meaningful reference for the local balance of economic development and environmental protection.

The overlapped areas of cropland and coal resources play a fundamental role in promoting economic and social progress. However, intensive mining operations in high water-level areas have brought significant spatial–temporal heterogeneity and ecological problems. From the dual dimensions of the ecosystem service value (ESV) and ecological risk (ER), it is of great significance to explore the influence characteristics of underground mining on the landscape, such as above-ground cultivated land, which is valuable to achieving regional governance and coordinated development. In this study, taking Peixian as the research area, a multiple-dimensional correlation framework was constructed based on the revised ESV and ER, integrating the grey relational degree, spatial–temporal heterogeneity, disequilibrium, and inconsistency index to explore the ESV and ER assessment and correlation characteristics from 2010 to 2020. The results show that (1) the ESV showed a high agglomerated distribution pattern in the east, with a net decrease of 13.61%. (2) The ER decreased by 78.18 and was concentrated in the western and southern regions, with overall contiguous and local agglomeration characteristics. This indicates that the ecological security of the region has improved. (3) The comprehensive grey correlation between the cultural service value and the ecological risk index was the highest. Furthermore, the spatial–temporal heterogeneity of the ESV and ER weakened, and the disequilibrium rose and then fell, indicating that the ecosystem gradually tended to be stable. The study is crucial for overlapped cropland and coal resource areas to maintain stability and sustainable development. The multivariate correlation framework provides practical value for ecosystem management and risk control.

Lead (Pb), as one of the main pollution elements, has resulted in large-scale soil pollution around the world. Even if phytoremediation can solve this problem, the selection of restoration potential plants has always been a scientific problem. As a multifunctional repair plant, Neyraudia reynaudiana can rehabilitate both polluted soils and slopes. N. reynaudiana has been widely used in terrain restoration in southern China before. This study was the first to study the growth and Pb absorption and enrichment capacity of N. reynaudiana in Xuzhou, north of the Yangtze River. In this study, N. reynaudiana was planted in soils with different lead concentrations, and the change of lead content in roots, shoots, and soils, as well as the redox enzyme, was tested and analyzed during each growth stage. The results showed that the roots could absorb Pb and transfer 79.45% to the shoots at most. With the growth of the plant, the ability to accumulate and transfer gradually increased. Moreover, when the soil Pb concentration was above 800 mg kg⁻¹, the ability to accumulate by N. reynaudiana was significantly restrained. Furthermore, superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), and peroxidase (POD) first acted on the redox response in the initial phase, while increasing the pollutant concentration or the growth of N. reynaudiana in the later stage, and the glutathione reductase (GR) redox system continued to feed back on the lead stress. This study proved that N. reynaudiana is a kind remediation plant for lead pollution soil and could repair soil with a lead pollution concentration lower than 800 mg kg⁻¹. The results provide a theoretical reference for clarifying the action mechanism and threshold value of N. reynaudiana in rehabilitating soil lead pollution and provide practical guidance for the planting proportion of N. reynaudiana.

Ecosystem services (ES) serve as a critical link between ecosystems and the sustainable development goals (SDGs). Exploring the relationship between ES and SDGs is of great significance for promoting regional sustainable development. This study proposes a conceptual framework to examine the interlinkages between ES and SDGs. First, the equivalent factor method is employed to estimate the county-level ES value in Jiangsu Province from 2005 to 2020. Second, the entropy-weighted TOPSIS model is used to assess SDG performance. Third, the coupling coordination degree model is applied to quantify the synergistic relationship between ES and SDGs, based on which regional typologies are constructed. Finally, a geographically and temporally weighted regression (GTWR) model is utilized to investigate the spatial–temporal impacts of various ecosystem service functions on SDGs. The results reveal that (1) over the past 15 years, the value of ES in Jiangsu Province has shown an overall upward trend, with a peak followed by a slight decline; (2) that the SDGs performance exhibited an increasing trend until 2015, after which it began to decline; (3) the coupling coordination degree between ES and SDGs has increased annually and that, based on the coupling results, four types of regions are identified: potential development zones, ecological deficit zones, priority improvement zones, and high-quality synergy zones; and (4) that the relationship between different ecosystem service functions and SDGs demonstrates significant regional heterogeneity. Future efforts should focus on enhancing provisioning services in counties within the Yi-Shu-Si River Basin, balancing economic development and ecological protection in the Yangtze River Basin, and improving cultural services in western counties of both the Yangtze River Basin and the Taihu Lake Basin. The findings offer insights for regional SDG strategies from the perspective of ES in Jiangsu Province.