Eco-Environmental Effects of Changes in Territorial Spatial Pattern and Their Driving Forces in Qinghai, China (1980–2020)

Wu, Xinyan; Ding, Jinmei; Lu, Bingjie; Wan, Yuanyuan; Shi, Linna; Wen, Quan

doi:10.3390/land11101772

Cited by 9 publications

(5 citation statements)

References 60 publications

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“…The land space is the place and environment where humans live. The interac tween humans and the natural environment in the land space changes the functio regional land space through changes in land use types and shaping the PLES is an e means of ecological civilization construction and spatial planning [31,32]. It classifi…”

Section: Discussionmentioning

confidence: 99%

“…The land space is the place and environment where humans live. The interaction between humans and the natural environment in the land space changes the function of the regional land space through changes in land use types and shaping the PLES is an effective means of ecological civilization construction and spatial planning [31,32]. It classifies land space based on different land use functions to optimize development patterns, control development intensity, and adjust the spatial structure of the land space [33].…”

Section: Discussionmentioning

confidence: 99%

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Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

et al. 2023

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Rapid economic and social development has triggered competition for limited land space from different industries, accelerating the evolution of Beijing’s urban landscape types. The increase in impermeable surfaces and the decrease in ecological land have led to an increase in the impact on the urban thermal environment. Since previous studies have mainly focused on the impact of a single urban landscape on the urban thermal environment and lacked an exploration of the combined impact of multiple landscapes, this study applied standard deviation ellipses, Pearson correlation analysis, land surface temperature (LST) profile analysis, and hot spot analysis to comprehensively explore the influence of the evolving production–living–ecological space (PLES) pattern on LST. The results show that the average LST of various spaces continued to increase before 2009 and decreased slowly after 2009, with the highest average temperature being living space, followed by production space, and the lowest average temperature being ecological space for each year. The spatiotemporal shift path of the thermal environment is consistent with the shift trajectory of the living space center of gravity in Beijing; LST is positively correlated with living space (LS) and negatively correlated with production space (PS) and ecological space (ES). LST is positively correlated with LS and negatively correlated with PS and ES. Influenced by the change in bedding surface type, the longitudinal thermal profile curve of LST shows a general trend of “low at both ends and high in the middle”. With the change in land space type, LST fluctuates significantly, and the horizontal thermal profile curve shows a general trend of “first decreasing, followed by increasing and finally decreasing”. In addition, the hot spot analysis shows that the coverage area of very hot spots, hot spots, and warm spots increased by 0.72%, 1.13%, and 2.03%, respectively, in the past 30 years, and the main expansion direction is southeast, and very cold spots and cold spots are distributed in the northwest ecological space, and the area change first decreases and then increases.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

et al. 2023

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“…The application of the multi-agent method to land use change simulations is a research hotspot [34,35]. The advantages of MAS have attracted many researchers' attention for its application in agricultural systems and communities to enhance the administrative result [36][37][38][39][40][41][42][43][44]. Although multi-agent systems are very suitable for simulating the interaction between human behavior and geographical landscapes, the application of MAS in man-earth coupling systems in mining areas still faces many challenges.…”

Section: Discussionmentioning

confidence: 99%

Uncovering Stakeholders’ Participation to Better Understand Land Use Change Using Multi-Agent Modeling Approach: An Example of the Coal Mining Area of Shanxi, China

Guo

Zhang

Cui

et al. 2022

Land

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Recent decades have witnessed increasing human disruption and the acceleration of fragile natural habitats, especially in coal mining areas in developing countries or regions, which will inevitably lead to sharp land use and cover change (LUCC). Most LUCC models focus more on the research of “land” than “human” in human-land coupled systems, while the simulation and prediction of LUCC involving stakeholders are still deficient. Aiming to reveal the shaping process of LUCC through the stakeholders’ participation, we conducted an in-depth interview in a typical coal mining area of Shanxi, China, and developed an agent-based model by quantifying the stakeholders’ land-use decision-making rules to simulate and predict land use change in different scenarios. The analysis illustrated that the stakeholders’ participation in different periods had shaped the land use pattern in the coal mine area. The area of cultivated land has decreased from 272.34 hm2 to 118.89 hm2, while industrial and mining land increased dramatically by 78.66 hm2 from 2012 to 2019. The attitude and willingness of farmers towards land use varied greatly and were affected by livelihood capital. Part-time farmers whose agricultural income only accounted for 20–80% of the total income were in favor of farmland requisition by coal mining enterprises compared to full-time farmers. We quantified the rules between the attributes of the stakeholders at the micro level and land use changes at the macro level and proposed the multi-agent simulation model, which was effective and verified by a fitting test where the overall accuracy of the Kappa coefficient was 0.83 and could be used to predict future LUCC in research areas by setting the decision parameters in specific scenarios. These outcomes provided a scientific reference for landscape simulation and the prediction of a human-land coupling system while promoting the effectiveness of spatial planning policies.

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“…land use transfer areas. These two methods can reflect the eco-environmental quality status of different land types and clarify the main land use transformations that cause changes in the overall eco-environmental quality of the region [39][40][41]. Given the broad application of this method in China [42][43][44], this study adopted the EI and the ecological impact rate of PLEL change (EIR) to explore the eco-environmental response to PLEL transformation comprehensively.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Evolution of Production–Living–Ecological Land and Its Eco-Environmental Response in China’s Coastal Zone

Yang

Wang

et al. 2023

Remote Sensing

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High-intensity human activities have caused dramatic transformations of land function in China’s coastal zone, putting enormous pressure on the region’s ecological environment. It is urgent to fully understand the spatiotemporal evolution of the land-use function in the coastal zone to promote sustainable development. Therefore, based on CNLUCC data for 2000, 2010, and 2020, this study quantitatively explored the spatiotemporal evolution of production–living–ecological land (PLEL) and its eco-environmental response in China’s coastal zone by using multiple land-use analysis methods, gradient analysis, and the eco-environmental quality index. The results showed that over the past 20 years, the production land (PL) continued to decrease, whereas the living land (LL) and blue ecological land (BEL) increased. In the vertical direction, PL and the ecological land (EL) dominated in the northern and the southern coastal zone, respectively. In the horizontal direction, with increasing distance from the coastline, the green ecological land (GEL) increased, whereas it was the opposite for BEL. The transformations of PLEL were high and low frequency in the north and south, respectively. From 2000 to 2020, the eco-environmental quality of China’s coastal zone slightly degraded, with conditions that were “excellent in the south and poor in the north”. The eco-environmental qualities of each sub-coastal zone gradually improved with increasing distance from the coastline. The main transformation types that led to eco-environmental improvement and degradation were from other production lands (OPL) to blue ecological land (BEL) and BEL to OPL, respectively. The findings will guide PLEL planning, eco-environmental protection, and science-based land usage.

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Eco-Environmental Effects of Changes in Territorial Spatial Pattern and Their Driving Forces in Qinghai, China (1980–2020)

Cited by 9 publications

References 60 publications

Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

Effects of Production–Living–Ecological Space Patterns Changes on Land Surface Temperature

Uncovering Stakeholders’ Participation to Better Understand Land Use Change Using Multi-Agent Modeling Approach: An Example of the Coal Mining Area of Shanxi, China

Spatiotemporal Evolution of Production–Living–Ecological Land and Its Eco-Environmental Response in China’s Coastal Zone

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