Spatiotemporal Evolution and Driving Mechanism of Production–Living–Ecological Space from 1990 to 2020 in Hunan, Central China DOI Open Access
Siliang Wu,

Wenbo Mo,

Ruochen Zhang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1703 - 1703

Published: Feb. 18, 2025

China’s rapid economic growth has increased tensions between production, living, and ecological spaces (PLES), making sustainable land-use planning difficult. Therefore, PLES evolution processes are a focus of current research. Remote sensing data with transition matrices, centroid migration, standard deviation ellipses, spatial autocorrelation, geographic detectors were used to study the dynamics in Hunan Province from 1990 2020, elucidate its mechanisms main influencing factors, provide comprehensive understanding evolutionary characteristics. The conclusions our analysis as follows: (1) Ecological space was dominant type, while production increased, putting strain on natural areas. (2) Living by 40.73% over three decades, mostly comprising manufacturing space, highlighting urban expansion. (3) Despite changes, Loudi City’s remained central. (4) Standard ellipses showed shrinkage directional stability, implying enhanced land usage within borders rather than outward growth. (5) detector that GDP, population density, slope, elevation influenced these changes. Economic prosperity drove expansion, but slope limited development accessible locations. These findings policymakers essential information for balancing urbanization preservation case design rapidly developing regions.

Language: Английский

Spatio-Temporal Evolution and Prediction of Carbon Storage in Guilin Based on FLUS and InVEST Models DOI Creative Commons
Yunlin He,

Jiangming Ma,

Zhang Changshun

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(5), P. 1445 - 1445

Published: March 4, 2023

In the context of sustainable development and dual-carbon construction, to quantify carbon storage its spatial-temporal distribution characteristics Guilin City predict in 2035 under different future scenarios, this study set four scenarios based on SDGs plan City: natural development, economic priority, ecological development. At same time, FLUS InVEST models GeoDa 1.20and ArcGIS software were used establish a coupling model land use change ecosystem simulate future. The results showed that: (1) From 2005 2020, forest was main type Guilin, cropland impervious continued expand. 2035, will be an important transformation type; (2) northwest relatively high, loss area larger than increase area. priority scenario is highest, reaching 874.76 × 106 t. aboveground (ACG) pool Guilin. Most regions with high are located northeast No matter what scenario, urban maintained at low level; (3) has strong spatial positive correlation, more hot spots cold spots. high-value areas concentrated east, whereas low-value

Language: Английский

Citations

55
Synergy/trade-offs and differential optimization of production, living, and ecological functions in the Yangtze River economic Belt, China DOI Creative Commons

Jia Zhao,

Yuluan Zhao

Ecological Indicators, Journal Year: 2023, Volume and Issue: 147, P. 109925 - 109925

Published: Jan. 23, 2023

The high-quality development of the Yangtze River Economic Belt (YREB) is a major strategy related to China's overall national development. Based on synergy/trade-offs production, living, and ecological functions (PLEFs) in YREB from 2000 2020, this paper puts forward suggestions for optimization territorial space promote YREB. mechanistic equilibrium model was applied determine synergy/trade-off relationship PLEFs, key factors affecting coordination degree were analyzed with help geographical detector geographically weighted regression (GWR) further identify trade-off zones propose differential strategies. results showed that average synergy PLEFs decreased 0.18 0.08 during study period, developed higher level, forming local patchwork "highlands" space, gradient divergence west east. land-use degree, landscape, slope, traffic, nightlight index dominant influencing their q-values 0.30, 0.27, 0.20, 0.14 order, significant spatial differences effects each factor's role. deviation three function-dominated divided, it found an evolutionary trend function domination (2000) production (2010) (2020). antagonistic dysregulated states identified, proposed targeted findings provide theoretical reference sustainable use resources regional rest country.

Language: Английский

Citations

51
Assessing the responses of ecosystem patterns, structures and functions to drought under climate change in the Yellow River Basin, China DOI
Lu Zhang,

Caiyun Deng,

Ran Kang

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 929, P. 172603 - 172603

Published: April 21, 2024

Language: Английский

Citations

15
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
Potential ecological risk assessment based on loss of ecosystem services due to land use and land cover change: A case study of Beijing-Tianjin-Hebei region DOI
Pengyan Zhang, Qianxu Wang, Yu Liu

et al.

Applied Geography, Journal Year: 2024, Volume and Issue: 171, P. 103389 - 103389

Published: Aug. 29, 2024

Language: Английский

Citations

12
Spatiotemporal Changes and Influencing Factors of the Coupled Production–Living–Ecological Functions in the Yellow River Basin, China DOI Creative Commons
Zeyu Lu, Maomao Zhang, Chunguang Hu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1909 - 1909

Published: Nov. 14, 2024

The imbalance in the “production–living–ecology” function (PLEF) has become a major issue for global cities due to rapid advancement of urbanization and industrialization worldwide. realization PLEF coupling coordination is crucial region’s sustainable development. Existing research defined concept from perspective land measured its level using relevant models. However, there still room improvement indicator system, methods, other aspects. This work builds evaluation-index system based on human habitat multi-source data order examine spatial differences influencing factors Yellow River Basin (YRB). Using modified model, Moran index, Markov chain geographically weighted random forest model were introduced analyze temporal differentiation factors. results found that (a) YRB 2010 2022 been improving, number severely imbalanced reduced 23 15, but downstream cities’ significantly higher than upstream cities. probability maintaining their own greater 50%, basically no cross-level transfer. (b) index risen 0.137 0.229, which shows significant positive clustering phenomenon continually strengthening. intercity polarization effect being enhanced as seen LISA diagram. (c) There heterogeneity between time space. In terms importance level, series per capita disposable income (0.416) > nighttime lighting (0.370) local general public budget expenditure (0.332) beds 1000 people (0.191) NO2 content air (0.110). study systematically investigates dynamic evolution coupled mechanism, great practical use.

Language: Английский

Citations

10
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

9
Spatio-temporal evolution characteristics and driving mechanisms of Urban–Agricultural–Ecological space in ecologically fragile areas: A case study of the upper reaches of the Yangtze River Economic Belt, China DOI
Wei Wei, Ning Wang, Yin Li

et al.

Land Use Policy, Journal Year: 2024, Volume and Issue: 145, P. 107282 - 107282

Published: July 26, 2024

Language: Английский

Citations

9
Agroecosystem transformation and its driving factors in karst mountainous areas of Southwest China: The case of Puding County, Guizhou Province DOI Creative Commons
Limin Yu, Yangbing Li, Mei Chen

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 80, P. 102529 - 102529

Published: Feb. 16, 2024

With the rapid socioeconomic development and urbanization, global agroecosystems (AESs) have undergone varying degrees of transformation, conducting an in-depth study on how AESs are transforming in karst mountainous areas (KMAs) is essential. To further reveal transformation process KMAs, we proposed a theoretical framework for KMAs. Following "theory construction–empirical analysis–pattern evolution–mechanism revelation" research methodology, studied trend AES evolution "typical area—typical landforms area," summarized patterns different landforms, analyzed influencing factors their transformation. The found that (1) large amount productive land (PL) was abandoned as ecological (EL) steep slopes at high altitudes while river valleys dominated by PL into economic (EEL), spatial distribution structure has evolved coordinated EL–EEL–PL, with dominance production function transformed eco-economic functions living strengthened. (2) landscapes can be four types: development, food supply, conservation, service. (3) influenced various factors, including region's particular natural environment socioeconomics. This also shows traditional extensive agriculture moving toward modern intensive remarkable win–win benefits. Our provides guidance remediation, restoration, agricultural KMAs similar to alleviate regional human–land conflicts promote sustainable

Language: Английский

Citations

8
Spatial allocation and sustainable development: a study of production-living-ecological spaces in the Yangtze River Delta DOI Creative Commons

Shangbo Li,

Yong Chen, Qinshi Huang

et al.

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 12

Published: Jan. 9, 2025

The overlap and irrational distribution of Production-Living-Ecological Spaces (PLES) has disrupted traditional urban-rural development patterns impeded regional integration. This study, focusing on the Yangtze River Delta region, introduces a PLES framework constructs classification system based multitemporal land use data. CA-Markov model was employed to simulate changes for years 2030 2040. By quantifying analyzing number, distribution, transitions categories, study identifies spatial temporal evaluates coupling coordination various components. key findings are as follows: (1) proportion Production-Living Space (PLS) increased from 9 % in 2000 14 id="m2">% 2020, with projections indicating further growth 15 id="m3">% by both 2040, while Ecological (ES) remained relatively stable; (2) between stages evolved mild disharmony weak coordination, reflecting shift localized improvements broader, more integrated development; (3) exhibited significant heterogeneity, characterized higher values eastern lower western pattern concentration north dispersion southward. These contribute deeper understanding dynamics provide strategic recommendations optimizing layout urban agglomeration, thereby promoting sustainable development.

Language: Английский

Citations

1