Spatial and Temporal Matching Measurement of Ecosystem Service Supply, Demand and Human Well-Being and Its Coordination in the Great Rivers Economic Belt—Evidence from China’s Yangtze River Economic Belt DOI Open Access
Zhijun Luo,

Songkai Luo,

F. Zhang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7487 - 7487

Published: Aug. 29, 2024

Understanding the complex relationship between ESSD and human well-being is of paramount significance to protecting regional ecology, enhancing achieving sustainable development. We take Yangtze River Economic Belt as an example use multi-source data analyse land cover change, well spatiotemporal evolution well-being. explore reveal coupling coordination The results show that from 2000 2020, overall trend in ESs region improved significantly, supply notably increased, whereas demand growth rate was even more pronounced. supply–demand ratio for water yield soil conservation showed little with variations <10%. However, carbon sequestration declined significantly by 41.83%, food increased 42.93%. spatial pattern presented a mismatch, which characterised ‘low high eastern low western region’. Overall, remained stable line level socio-economic development, thereby exhibiting distinct ‘polarisation rich poor’. Well-being higher central urban agglomerations lower plateau mountainous areas. Over 20 years, degree 0.0107, gradually transitioned moderate imbalance coordination. Spatially, Hubei Province, Chongqing Municipality Delta were main ‘high–high’ agglomeration areas, Sichuan Basin Yunnan-Guizhou Plateau ‘low–low’ Based on these findings, we propose following management recommendations other related great river economic belts: optimise structure, rationally allocate natural resources, strengthen external connections promote coordinated enhance implementation policies ecological environmental protection, establish compensation mechanisms coordinate protection full scope focus harmonising human–land relationships, build multi-stakeholder collaborative governance mechanism elevation

Language: Английский

Dynamic assessment of eco-environmental quality in Xiong’an new area, China using WB-RSEI new model DOI Creative Commons

Yinqiao Zhou,

Wei Cao, Jiandong Zhou

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 4, 2025

Language: Английский

Citations

0

Analysis of Ecological Environment in the Shanxi Section of the Yellow River Basin and Coal Mining Area Based on Improved Remote Sensing Ecological Index DOI Creative Commons

Huabin Chai,

Yuqiao Zhao,

Hui Xu

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(20), P. 6560 - 6560

Published: Oct. 11, 2024

As a major coal-producing area, the Shanxi section of Yellow River Basin has been significantly affected by coal mining activities in local ecological environment. Therefore, an in-depth study evolution this region holds great scientific significance and practical value. In study, Basin, including its planned was selected as research subject. An improved remotely sensed index model (NRSEI) integrating (RSEI) net primary productivity (NPP) vegetation constructed utilizing Google Earth Engine platform. The NRSEI time series data from 2003 to 2022 were calculated, Sen + Mann-Kendall analysis method employed comprehensively assess environment quality evolutionary trends area. findings paper indicate following data: (1) contribution first principal component is more than 70%, average correlation coefficient higher 0.79. effectively integrates information multiple indicators enhances applicability regional evaluation. (2) Between 2022, showed overall upward trend, with value experiencing phases fluctuation, increase, decline, stabilization. values non-coal areas consistently remained those areas. (3) Over 60% have conditions, especially (4) impact on significant within 6 km radius, while effects gradually diminish 10 range. This not only offers reliable methodology for evaluating large scale over long but also guiding restoration sustainable development

Language: Английский

Citations

2

Spatial and Temporal Matching Measurement of Ecosystem Service Supply, Demand and Human Well-Being and Its Coordination in the Great Rivers Economic Belt—Evidence from China’s Yangtze River Economic Belt DOI Open Access
Zhijun Luo,

Songkai Luo,

F. Zhang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7487 - 7487

Published: Aug. 29, 2024

Understanding the complex relationship between ESSD and human well-being is of paramount significance to protecting regional ecology, enhancing achieving sustainable development. We take Yangtze River Economic Belt as an example use multi-source data analyse land cover change, well spatiotemporal evolution well-being. explore reveal coupling coordination The results show that from 2000 2020, overall trend in ESs region improved significantly, supply notably increased, whereas demand growth rate was even more pronounced. supply–demand ratio for water yield soil conservation showed little with variations <10%. However, carbon sequestration declined significantly by 41.83%, food increased 42.93%. spatial pattern presented a mismatch, which characterised ‘low high eastern low western region’. Overall, remained stable line level socio-economic development, thereby exhibiting distinct ‘polarisation rich poor’. Well-being higher central urban agglomerations lower plateau mountainous areas. Over 20 years, degree 0.0107, gradually transitioned moderate imbalance coordination. Spatially, Hubei Province, Chongqing Municipality Delta were main ‘high–high’ agglomeration areas, Sichuan Basin Yunnan-Guizhou Plateau ‘low–low’ Based on these findings, we propose following management recommendations other related great river economic belts: optimise structure, rationally allocate natural resources, strengthen external connections promote coordinated enhance implementation policies ecological environmental protection, establish compensation mechanisms coordinate protection full scope focus harmonising human–land relationships, build multi-stakeholder collaborative governance mechanism elevation

Language: Английский

Citations

0