The Nexus of UG-ESs in the Chinese Loess Plateau using CL-CA and Ecological Assessment Models

Urban growth (UG) in the Chinese Loess Plateau has increased rapidly, impacting regional ecosystem services (ESs). Accurate evaluations of UG-ESs have become a challenge for the development of simulation models. To address long-term spatiotemporal dependencies in grid neighborhood interactions, this...

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Bibliographic Details
Main Authors: Liang Youjia, Su Zichong, Liu Lijun
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/128/e3sconf_icaeer2024_02009.pdf
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Summary:Urban growth (UG) in the Chinese Loess Plateau has increased rapidly, impacting regional ecosystem services (ESs). Accurate evaluations of UG-ESs have become a challenge for the development of simulation models. To address long-term spatiotemporal dependencies in grid neighborhood interactions, this study enhances land-use simulation accuracy using a method combining machine learning algorithms and cellular automata (CL-CA) to model competitive relationship between urban growth and other land-use types during 2000-2050, and then, ESs supply was simulated with ecological assessment models under three landuse scenarios: business as usual, ecological priority, and economic priority. Key findings include: (1) Growth rates and land-use patterns are influenced by policies and natural environments, with an expected urban growth rate of 3%-6%, shifting from leapfrog to marginal growth post-2030; (2) Forests and grasslands primarily impact ESs; and (3) The EP scenario optimally balances sustainable urban development and ES enhancement.
ISSN:2267-1242