Evaluating the spatiotemporal land ecological changes in the Yangtze-to-Huaihe Water Diversion Project area DOI
Beibei Guo, Wei Li,

Xuemin Kong

et al.

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Language: Английский

Research on the evolution characteristics, driving mechanisms and multi-scenario simulation of habitat quality in the Guangdong-Hong Kong-Macao Greater Bay based on multi-model coupling DOI
Yufan Wu, Jiangbo Wang, Aiping Gou

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 924, P. 171263 - 171263

Published: Feb. 28, 2024

Language: Английский

Citations

17
Detection of long-term land use and ecosystem services dynamics in the Loess Hilly-Gully region based on artificial intelligence and multiple models DOI
Yansui Liu, Xinxin Huang, Yaqun Liu

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 447, P. 141560 - 141560

Published: Feb. 29, 2024

Language: Английский

Citations

16
Dynamics Analysis of Spatial Distribution and Landscape Pattern of Wetlands in the Weihe River Basin from 1980 to 2020 DOI Open Access

An-Min Wu,

Jun-Bao Li, Dan Zhang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(2), P. 544 - 544

Published: Jan. 12, 2025

The wetland ecosystem is one of the most important carbon sinks on Earth, biodiverse ecological landscape in nature, and living environments for human beings. Weihe River located Guanzhong Plain urban agglomeration, with extreme climate expansion having a great impact its dynamic changes. Revealing characteristics trends dynamics Basin key to protecting maintaining healthy development wetlands. This paper analyzed changing land use types patterns wetlands using data from six periods 1980 2020 explored spatial temporal distribution changes Basin. results showed following: (1) Wetlands Basin, dominated by rivers, saw area fluctuations an initial decline followed increase. Land slow–fast–slow trend. (2) From 2020, frequent conversions among were observed. primary transformation was conversion marshes into lakes (18.05 km2) reservoirs/ponds (17.98 km2). Approximately 0.06 km2 transformed canals/channels. (3) patches have largest area, while canals/channels smallest. patch density (PD) shape index (LSI) fluctuate significantly, reduction leads 3.46% decrease aggregation (AI). Shannon’s diversity (SHDI) has decreased 5.41%. (4) centroid experiences significant changes, river are complex. along southeast–northwest line. Canals/watercourses remain stable. Lakes exhibit longest migration. study provides robust scientific support protection, policy formulation, social sustainable conducting in-depth analysis change

Language: Английский

Citations

2
The impact of land-use change on the ecological environment quality from the perspective of production-living-ecological space: A case study of the northern slope of Tianshan Mountains DOI Creative Commons
Yu Cao, Mingyu Zhang, Zhengyong Zhang

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 83, P. 102795 - 102795

Published: Aug. 25, 2024

Language: Английский

Citations

12
Effects of land utilization transformation on ecosystem services in urban agglomeration on the northern slope of the Tianshan Mountains, China DOI Creative Commons
Xiaojun Song, Fu Chen, Yan Sun

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 162, P. 112046 - 112046

Published: April 21, 2024

Land utilization transformation (LUT) is a key factor affecting ecosystem services (ESs). The urban agglomeration on the Northern Slope of Tianshan Mountains (UATM) located in typical arid region with extremely fragile ecological environment. However, impact LUT spatial pattern ESs over past 20 years not clear. This study aimed to explore characteristics UATM using land transfer matrix, information entropy, intensity, and dynamic degree. Various indexes were quantitatively measured Integrated Valuation Ecosystem Services Trade-offs (InVEST) model, effect was revealed through geographic detector auto-correlation analyses. results this led following conclusions: First, between 2000 2020, primary types arable land, grassland, bare significant cross-transformations occurring among these types. Meanwhile, showed marked differences different regions. changed rapidly significantly central region; contrast, slower slight changes observed northern southern Second, during research period, habitat maintenance, water yield carbon sequestration decreased, soil retention function increased. accelerated development second decade more rapid ESs. Finally, both structure intensity strongest explanatory capability for Different dimensions interactions Therefore, it advisable guide scientifically, promote vegetation restoration projects, alleviate impacts human activities climate change ESs, enhance safety environmental sustainability even regions Central Asia.

Language: Английский

Citations

11
The difference in ecological environmental quality impact factors between human activity zone and non-human activity zone in arid regions: A case study of the northern slope of the Tianshan Mountains DOI Creative Commons
Yu Cao, Jiayi Zhang, Zhengyong Zhang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113226 - 113226

Published: Feb. 1, 2025

Language: Английский

Citations

1
Exploring the supply and demand imbalance of carbon and carbon-related ecosystem services for dual‑carbon goal ecological management in the Huaihe River Ecological Economic Belt DOI
Dehu Yang, Changming Zhu, Jianguo Li

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 912, P. 169169 - 169169

Published: Dec. 10, 2023

Language: Английский

Citations

17
Dynamic variation and driving mechanisms of land use change from 1980 to 2020 in the lower reaches of the Yangtze River, China DOI Creative Commons

Shouwei Shang,

Tingting Cui,

Yintang Wang

et al.

Frontiers in Environmental Science, Journal Year: 2024, Volume and Issue: 11

Published: Jan. 4, 2024

To systematically explore land use/cover change (LUCC) trends and driving mechanisms at the large watershed scale under background of climate rapid urbanization. Taking lower reaches Yangtze River (LRYR) as research object, based on use remote sensing monitoring data from 1980 to 2020, spatial temporal evolution characteristics LUCC in LRYR were analyzed by adopting methods dynamics degree (LUDD) hotspot analysis used geospatial detectors quantitatively assess intensity role drivers LRYR. The results show that: 1) land-use types dominated arable woodland, accounting for more than 70% total area. During study period, construction area increased 11,835 km 2 , became third largest type after 2010 formed a typical urban contiguous zone along route Nanjing Shanghai. 2) comprehensive index (LUDCI) each stage is 270.91, 270.88, 272.22, 272.72, 274.00, 275.57, 276.93 280.37, respectively. has become dramatic, there significant heterogeneity. Shanghai always been hot Huangshan Chizhou are cold spots LUCC. 3) mechanism can be divided into three stages. In these stages, secondary industry output value, precipitation, elevation important factors affecting interaction between significant. strongest value ∩ above 0.6. great significance promoting sustainable development this region.

Language: Английский

Citations

6
Driving mechanisms and multi-scenario simulation of land use change based on National Land Survey Data: a case in Jianghan Plain, China DOI Creative Commons
Heng Zhou,

Mingdong Tang,

Jun Huang

et al.

Frontiers in Environmental Science, Journal Year: 2024, Volume and Issue: 12

Published: July 24, 2024

The Jianghan Plain is simultaneously responsible for ecological protection, food security and urbanization, land use conflicts are prominent. Revealing the driving mechanism of use/cover change (LUCC) simulating pattern can help to coordinate in future. Utilizing National Land Survey Data (NLSD) Jiangling County (2011–2020) patch-generating simulation (PLUS) model, this paper analyzed characteristics evolution, applied random forest classification (RFC) analyze mechanism, simulated 2035 under three scenarios natural development, planning guidance protection through Markov Cellular Automaton based on multiple seeds (CARS) models, proposed several countermeasures. study found that: 1) From 2011 2020, town construction increased, village land, agricultural decreased. 2) factors LUCC were socio-economic factors, spatial descending order. 3) In scenarios, trend expansion, encroachment inevitable by 2035. 4) It imperative actively advocate large-scale mechanization informatization production, encourage repurposing idle inefficiently used facilitate multi-purpose utilization, implement a policy locally balancing occupation compensation cultivated land. 5) When employing PLUS model simulate LUCC, using continuous NLSD yielded more accurate results than remote sensing image interpretation data. This offers theoretical basis coordinated development Plain, presents method enhance accuracy model.

Language: Английский

Citations

6
Unstable changes in ecological quality of the four major sandy lands in northern China based on Google Earth Engine DOI Creative Commons

Haowen Ma,

Yongfang Wang,

Enliang Guo

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113195 - 113195

Published: Feb. 1, 2025

Language: Английский

Citations

0