Machine learning in modelling the urban thermal field variance index and assessing the impacts of urban land expansion on seasonal thermal environment

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 106, P. 105345 - 105345

Published: March 14, 2024

Language: Английский

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Assessing the relative contributions, combined effects and multiscale uncertainty of future land use and climate change on water-related ecosystem services in Southwest China using a novel integrated modelling framework

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 106, P. 105400 - 105400

Published: April 1, 2024

Language: Английский

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Detection of long-term land use and ecosystem services dynamics in the Loess Hilly-Gully region based on artificial intelligence and multiple models

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

Published: Feb. 29, 2024

Language: Английский

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Spatio‑temporal analysis and driving forces of urban ecosystem resilience based on land use: A case study in the Great Bay Area

Ecological Indicators, Journal Year: 2024, Volume and Issue: 159, P. 111769 - 111769

Published: Feb. 1, 2024

Ecosystem resilience plays a vital role for security and in the urban system which experiences combined effects of anthropogenic activities natural disasters. Nonetheless, there is currently no unified indicator assessing resilience. Therefore, this study aims to examine changes ecosystem Guangdong-Hong Kong-Macao Great Bay Area (GBA) based on land use, using framework resistance, adaption, elasticity. The study's results revealed that between 2000 2020, increase peripheral GBA cities outpaced decrease central cities, leading yearly rise overall Nighttime light (NL), population density (PD), urbanization rate (UR), normalized difference vegetation index (NDVI) were primary driving factors influencing resistance elasticity GBA, thereby shaping Findings from multi-scale geographical weighted regression (MGWR) analysis demonstrated decreased as NL, PD, UR increased, while it exhibited an areas with higher NDVI. This contributes improvement by providing targeted strategies, expediting development resilient offering theoretical insights management, planning, policy formulation.

Language: Английский

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Climate and land use changes impact the trajectories of ecosystem service bundles in an urban agglomeration: Intricate interaction trends and driver identification under SSP-RCP scenarios

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 944, P. 173828 - 173828

Published: June 10, 2024

Language: Английский

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Promoting Balanced Ecological-economic Development in Ecologically Vulnerable Regions: Spatio-temporal Variation and Driving Factors

Environmental Management, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Language: Английский

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Assessment and multi-scenario prediction of ecosystem services in the Yunnan-Guizhou Plateau based on machine learning and the PLUS model

Frontiers in Ecology and Evolution, Journal Year: 2025, Volume and Issue: 13

Published: Feb. 18, 2025

Introduction Machine learning techniques, renowned for their ability to process complex datasets and uncover key ecological patterns, have become increasingly instrumental in assessing ecosystem services. Methods This study quantitatively evaluates individual services—such as water yield, carbon storage, habitat quality, soil conservation—on the Yunnan-Guizhou Plateau years 2000, 2010, 2020. A comprehensive service index is employed assess overall capacity, revealing spatiotemporal variations services exploring trade-offs synergies among them. Additionally, machine models identify drivers influencing services, informing design of future scenarios. The PLUS model used project land use changes by 2035 under three scenarios—natural development, planning-oriented, priority. Based on simulation results these scenarios, InVEST applied evaluate various Results During 2000-2020, exhibited significant fluctuations, driven synergies. Land vegetation cover were primary factors affecting with priority scenario demonstrating best performance across all Discussion research integrates model, providing more efficient data interpretation precise design, offering new insights methodologies managing optimizing Plateau. These findings contribute development effective protection sustainable strategies, applicable both plateau similar regions.

Language: Английский

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Analysis of the evolution of ecosystem service value and its driving factors in the Yellow River Source Area, China

Ecological Indicators, Journal Year: 2023, Volume and Issue: 158, P. 111344 - 111344

Published: Dec. 2, 2023

The Yellow River Source Area (YRSA) functions as an ecological barrier within the Basin, playing a significant role in providing indispensable ecosystem services. Analyzing service value (ESV) of YRSA holds great significance establishing protection awareness and promoting actions. In this study, we reveal spatial temporal characteristics ESV from 2000 to 2020 based on land use change equivalent factor method, explore driving mechanisms behind heterogeneity using geographical detector. results showed that 2020, increased significantly, with average increase rate 9.12 × 1021seJ/5a, showing distribution pattern low northwest high southeast, imbalance is gradually weakening. annual contribution grassland reached 45 %, followed by water bodies (23 %). Ecosystem services are mainly dominated regulating services, among which hydrological dominated, more than 40 %. Supply regulation, support cultural both form strong correlation synergy. Climate factors main drivers ESV, further illustrating sensitivity climate change. Moreover, our accentuate integral furnishing broader provides theoretical basis reference for decision makers assess security zones.

Language: Английский

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Identifying the drivers of land expansion and evaluating multi-scenario simulation of land use: A case study of Mashan County, China

Ecological Informatics, Journal Year: 2023, Volume and Issue: 77, P. 102201 - 102201

Published: July 12, 2023

Language: Английский

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Scenario modeling of ecosystem service trade-offs and bundles in a semi-arid valley basin

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 896, P. 166413 - 166413

Published: Aug. 18, 2023

Language: Английский

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