Integrating mining district data into ecological security pattern identification: a case study of Chenzhou DOI Creative Commons

Jiawei Hui,

Yongsheng Cheng

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

Published: May 6, 2025

Resource-intensive cities face significant ecological challenges due to mining activities, which degrade landscapes, pollute ecosystems, and disrupt security patterns. This study proposes a process for identifying patterns (ESP) in cities, integrating landscape risk assessment, remote sensing quality evaluation, district spatial data. We introduce the source index (ECSI) identify sources Chenzhou construct an resistance surface (ERS) by incorporating locations. Using circuit theory, we map key corridors nodes, establishing framework Chenzhou. Our findings show 2,903 km² of primary sources, 1,735 secondary ES, 2,124 tertiary along with 90 (1,183.66 km), 22 inactive (983.37 3 major river corridors, 68 pinch points, 80 barriers. The are organized "dominant multiple subsidiary cores" structure, connected "three horizontal four vertical" corridor network. Ecological primarily located east, while barriers concentrated west. Barriers mainly urban areas, zones, farmland, points occur narrow sections, especially near towns areas. Mining activities cause localized shifts fragmentation corridors. propose recommendations management, such as implementing strict approval processes, constructing artificial expanding channel boundaries point clusters. These provide essential guidance restoration sustainable development resource-dependent cities.

Language: Английский

Dynamic monitoring and drivers of ecological environmental quality in the Three-North region, China: Insights based on remote sensing ecological index DOI Creative Commons

Leyi Zhang,

Li Xia, Xiuhua Liu

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: unknown, P. 102936 - 102936

Published: Dec. 1, 2024

Language: Английский

Citations

5
Analysis of the spatial pattern and causes of ecological environmental quality in Myanmar based on the RSEI model and the Geodetector-GCCM method DOI Creative Commons

Shuangfu Shi,

Shuangyun Peng,

Zhiqiang Lin

et al.

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13

Published: Feb. 11, 2025

Facing the challenges brought about by global climate change and biodiversity loss, accurately assessing ecological environmental quality (EEQ), its driving factors are crucial for formulating effective strategies protection restoration. However, there remains limited understanding of interactions causal relationships between multiple factors, with existing studies mainly focusing on impact individual EEQ their correlations. This study took Myanmar as research area, employing a Remote Sensing Ecological Index (RSEI) model spatial autocorrelation analysis to quantitatively evaluate distribution characteristics Myanmar’s in 2020 reveal dependence. Furthermore, innovatively integrating Geodetector Geographical Convergent Cross Mapping (GCCM) methods, this systematically analyzed impacts various spatiotemporal differentiation EEQ. The results indicate that: (1) overall was relatively good, but is significant heterogeneity; (2) Local revealed clear clustering pattern Myanmar; (3) identified DEM, slope, Net Primary Productivity (NPP), land use, human footprint dominant influencing EEQ, among these factors; (4) GCCM further verified effects NPP, while temperature, precipitation, use weaker. established technical framework analyzing causes unveiling mechanisms evolution driven natural factors. It enriched human-environment within coupled systems delved into complex system. These insights enhanced our intricate providing valuable references sustainable development Myanmar.

Language: Английский

Citations

0
Monitoring and Evaluation of Ecological Environment Quality in the Tianshan Mountains of China Using Remote Sensing from 2001 to 2020 DOI Open Access
Yuting Liu, Zhifang Chai, Qifei Zhang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1673 - 1673

Published: Feb. 17, 2025

High-altitude mountainous regions are highly vulnerable to climate and environmental shifts, with the current global change exerting a profound influence on ecological landscape of Tianshan Mountains in China. This study assesses security quality China from 2001 2020 by employing various remote sensing techniques such as Remote Sensing Ecological Index (RSEI) for evaluation, Normalized Difference Vegetation (NDVI) fractional vegetation cover (FVC) analysis, CASA model estimating primary productivity (NPP), carbon source/sink calculating net ecosystem (NEP) vegetation. The research also delves into evolutionary trends impact mechanisms environment using land use meteorological data. findings reveal that RSEI’s principal component (PC1) exhibits significant explanatory power, showing notable increase 5.90% 2020. Despite relatively stable changes RSEI over past two decades covering 61.37% area, there is prevalent anti-persistence pattern at 72.39%. Notably, NDVI, FVC, NPP display upward characteristics. While most areas continue emit carbon, marked NEP, signifying an enhanced absorption capacity. partial correlation coefficients between temperature, well precipitation, demonstrate statistically relationships (p < 0.05), encompassing 6.36% 1.55% respectively. Temperature displays predominantly negative 98.71% significantly correlated zones, while precipitation positive correlation. An in-depth analysis how affects provides crucial insights strategic interventions enhance regional protection promote sustainability.

Language: Английский

Citations

0
Integrating mining district data into ecological security pattern identification: a case study of Chenzhou DOI Creative Commons

Jiawei Hui,

Yongsheng Cheng

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

Published: May 6, 2025

Resource-intensive cities face significant ecological challenges due to mining activities, which degrade landscapes, pollute ecosystems, and disrupt security patterns. This study proposes a process for identifying patterns (ESP) in cities, integrating landscape risk assessment, remote sensing quality evaluation, district spatial data. We introduce the source index (ECSI) identify sources Chenzhou construct an resistance surface (ERS) by incorporating locations. Using circuit theory, we map key corridors nodes, establishing framework Chenzhou. Our findings show 2,903 km² of primary sources, 1,735 secondary ES, 2,124 tertiary along with 90 (1,183.66 km), 22 inactive (983.37 3 major river corridors, 68 pinch points, 80 barriers. The are organized "dominant multiple subsidiary cores" structure, connected "three horizontal four vertical" corridor network. Ecological primarily located east, while barriers concentrated west. Barriers mainly urban areas, zones, farmland, points occur narrow sections, especially near towns areas. Mining activities cause localized shifts fragmentation corridors. propose recommendations management, such as implementing strict approval processes, constructing artificial expanding channel boundaries point clusters. These provide essential guidance restoration sustainable development resource-dependent cities.

Language: Английский

Citations

0