Construction of Long-Term Grid-Scale Decoupling Model: A Case Study of Beijing-Tianjin-Hebei Region DOI Creative Commons

Xvlu Wang,

Minrui Zheng, Dongya Liu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1853 - 1853

Published: Nov. 6, 2024

Against the backdrop of rapid global economic development, Beijing-Tianjin-Hebei (BTH) region, a pivotal hub and environmentally sensitive area in China, faces significant challenges sustaining its landscape ecosystem. Given region’s strategic importance vulnerability to environmental pressures, this study investigated intricate relationships between ecological risk, urban expansion, growth (EG) BTH region. Utilizing as focal point, we constructed decoupling model at grid scale explore relationship risk index (ERI), construction (CAG), EG. The results showed that (1) distinct stages regional disparities were observed trends ERI, CAG, EG within hot cold spot patterns for these factors did not align consistently. (2) From 1995 2019, coupling region underwent fluctuating transition, initially moving from an undesirable state ideal state, subsequently reverting state. Although overall some convergence, there notable spatial distribution differences. (3) heterogeneity two was relatively poor. Further analysis revealed evolution closely intertwined with policy shifts adjustments.

Language: Английский

Lessons Learnt from the Influencing Factors of Forested Areas’ Vulnerability under Climatic Change and Human Pressure in Arid Areas: A Case Study of the Thiès Region, Senegal DOI Creative Commons
Bonoua Faye, Guoming Du, Quanfeng Li

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(6), P. 2427 - 2427

Published: March 13, 2024

Understanding the factors influencing vulnerability of forested areas is crucial for human well-being and effective governance ecosystem supply demand. Based on remote sensing data, this study also considered ten natural variables as indexes to explore main that may impact Thies region’s areas. The 2005, 2010, 2015, 2020 satellite image data were processed using ArcGIS 10.6 ENVI 5.1 software. methodology includes transfer matrix approach calculating geographic landscape index describe dominant morphology Furthermore, a mixed linear regression model was built establish connection between potential contributing components. Our revealed led relative fragmentation, with an average 88 patches Aggregation Index (AI), 3.25 Largest Patch (LPI), 2.50 Density (PD), 112 Landscape Shape (LSI) 2005 2020. In addition, indicated loss forestry about −78.8 km2 agricultural land, −127.8 bare −65.3 artificial surfaces. most critical influenced manufactural added value, rainfall (p < 0.05), slope, distance road, sown area 0.001). Overall, investigation has management in region requires understandable assessment. It observed both anthropogenic significantly contribute decline

Language: Английский

Citations

9
Impact of Urban Expansion on Carbon Emissions in the Urban Agglomerations of Yellow River Basin, China DOI Creative Commons
Zhenwei Wang, Yi Zeng, Xiaochun Wang

et al.

Land, Journal Year: 2024, Volume and Issue: 13(5), P. 651 - 651

Published: May 10, 2024

Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the agglomerations of Yellow River Basin (UAYRB), China. In this regard, study introduced kernel density analysis, Gini coefficient, and Markov chains to reveal patterns intensity (CEI) UAYRB at county level, explored spatial heterogeneity impact on CEI with geographically temporally weighted regression model. The results show that both showed steady growing trend during period. revealed was weakening, while rate continuously slowed down. coefficients region were high levels, indicating obvious imbalance. transfer probability matrix time span five years growth will still occur over next years, more obvious. Meanwhile, counties coefficient higher than 0 covered majority, distribution pattern remained quite stable. different landscape metrics varied greatly; except shape index, aggregation interspersion juxtaposition patch overall positive. These findings can advance policy enlightenment high-quality development Basin.

Language: Английский

Citations

4
Assessing landscape fragmentation and its driving factors in arid regions: A case study of the Manas River, China DOI Creative Commons
Jiaji Li, Jinxuan Wang, Yonghua Du

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113253 - 113253

Published: Feb. 1, 2025

Language: Английский

Citations

0
Analysis of the Distribution Pattern and Driving Factors of Bald Patches in Black Soil Beach Degraded Grasslands in the Three-River-Source Region DOI Creative Commons

Weitao Jing,

Zhou Wang,

Guowei Pang

et al.

Land, Journal Year: 2025, Volume and Issue: 14(5), P. 1050 - 1050

Published: May 12, 2025

The degradation of ‘black soil beach’ (BSB) ecosystems in the Three-River-Source region, characterized by widespread bald patches and severe erosion, poses a critical threat to regional ecological security sustainable pastoralism. This study aims elucidate spatial distribution patterns driving factors BSB degraded grasslands within Guoluo Tibetan Autonomous Prefecture, providing scientific basis for targeted restoration strategies. Utilizing multi-source remote sensing data (Landsat 8–9 OLI, UAV imagery, Google Earth), we employed Multiple Endmember Spectral Mixture Analysis (MESMA) method identify patches, combined with landscape pattern index autocorrelation quantify their heterogeneity. Geographical detector analysis was applied assess influence natural anthropogenic factors. results indicate following: (1) are bounded Yellow River, showing ‘high west low east’. total area reached 32,222.11 km2, accounting 43.43% among which Maduo County Dari had highest rate. (2) With aggravation degradation, patch density each county increased first then decreased, while aggregation shape continued decrease. (3) Spatial bare strengthens severity (Moran’s I 0.6543→0.7999). LISA identified two clusters: high–high agglomeration north Maduo–Dari low–low southeast Jiuzhi–Banma, revealing heterogeneity process. (4) mainly affected annual average precipitation actual stocking capacity, synergistic effect significantly higher than that single factor. combination 4491–4708 m high altitude area, 0–5° gentle slope zone, texture (clay 27–31%, silt 43–100%) has risk. multi-factor coupling explains limitations traditional factor provides new perspective accurate repair.

Language: Английский

Citations

0
Analyzing Spatial–Temporal Characteristics and Influencing Mechanisms of Landscape Changes in the Context of Comprehensive Urban Expansion Using Remote Sensing DOI Creative Commons
Yu Li,

Weina Zhen,

Bibo Luo

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(12), P. 2113 - 2113

Published: June 11, 2024

The phenomena of global climate change and comprehensive urban expansion have precipitated significant unprecedented transformations in landscape patterns. To enhance the assessment these spatio−temporal changes their driving forces at a regional level, we developed index (CLI) to quantify patterns conducted detailed analysis variations Minnesota over last two decades. Our CLI was by examining both its quantitative relationships spatial distribution findings indicate consistent increase Minnesota’s this period, marked an escalation fragmentation diversity, alongside decline connectivity. Temporally, experienced notable shift 2010. Spatially, clustering characteristics largely remained stable. reveals that is most sensitive total population (POP) gross domestic product (GDP) factors, underscoring impact human activity on Notably, explanatory capacity interactions between factors substantially greater than individual with GDP vegetation structure (VS) interaction demonstrating greatest influence This highlights critical role interplay socio−economic coverage shaping configurations.

Language: Английский

Citations

2
Spatiotemporal characteristics and robustness analysis of the thermal network in Beijing, China DOI
Xiang Cao,

Fei Feng,

Chengyang Xu

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 106092 - 106092

Published: Dec. 1, 2024

Language: Английский

Citations

2
Construction of Long-Term Grid-Scale Decoupling Model: A Case Study of Beijing-Tianjin-Hebei Region DOI Creative Commons

Xvlu Wang,

Minrui Zheng, Dongya Liu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1853 - 1853

Published: Nov. 6, 2024

Against the backdrop of rapid global economic development, Beijing-Tianjin-Hebei (BTH) region, a pivotal hub and environmentally sensitive area in China, faces significant challenges sustaining its landscape ecosystem. Given region’s strategic importance vulnerability to environmental pressures, this study investigated intricate relationships between ecological risk, urban expansion, growth (EG) BTH region. Utilizing as focal point, we constructed decoupling model at grid scale explore relationship risk index (ERI), construction (CAG), EG. The results showed that (1) distinct stages regional disparities were observed trends ERI, CAG, EG within hot cold spot patterns for these factors did not align consistently. (2) From 1995 2019, coupling region underwent fluctuating transition, initially moving from an undesirable state ideal state, subsequently reverting state. Although overall some convergence, there notable spatial distribution differences. (3) heterogeneity two was relatively poor. Further analysis revealed evolution closely intertwined with policy shifts adjustments.

Language: Английский

Citations

1