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Multi-Scenario Simulation of Ecosystem Service Value in Xiangjiang River Basin, China, Based on the PLUS Model

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成果类型:
期刊论文
作者:
Tang, Lisha;Li, Jingzhi;Xie, Chenmei;Wang, Miao
通讯作者:
Li, JZ
作者机构:
[Tang, Lisha] Hunan First Normal Univ, Sch Business, Changsha 410205, Peoples R China.
[Tang, Lisha] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
[Wang, Miao; Li, Jingzhi; Xie, Chenmei] Changsha Univ Sci & Technol, Coll Architecture, Changsha 410076, Peoples R China.
[Li, Jingzhi] Key Lab Dongting Lake Aquat Ecoenvironm Control &, Changsha 410114, Peoples R China.
通讯机构:
[Li, JZ ] C
Changsha Univ Sci & Technol, Coll Architecture, Changsha 410076, Peoples R China.
Key Lab Dongting Lake Aquat Ecoenvironm Control &, Changsha 410114, Peoples R China.
语种:
英文
关键词:
ecosystem service value;PLUS model;multi-scenario simulation;spatial–temporal evolution
期刊:
Land
ISSN:
2073-445X
年:
2025
卷:
14
期:
7
页码:
1482-
基金类别:
Conceptualization, L.T. and J.L.; methodology, L.T.; software, L.T. and C.X.; validation, L.T., J.L., C.X. and M.W.; formal analysis, L.T. and J.L.; investigation, L.T. and J.L.; resources, L.T. and J.L.; data curation, L.T., J.L. and C.X.; writing—original draft preparation, L.T. and J.L.; writing—review and editing, L.T., J.L., C.X. and M.W.; visualization, L.T., C.X. and M.W.; supervision, L.T. and J.L.; project administration, L.T.; funding acquisition, L.T. and J.L. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China (42101214); Hunan Provincial Natural Science Foundation (2023JJ30023).
机构署名:
本校为通讯机构
院系归属:
建筑学院
摘要:
With rapid socio-economic development, excessive anthropogenic consumption and the exploitation of natural resources have impaired the self-healing, supply, and carrying capacities of ecosystems. The assessment and prediction of ecosystem service values (ESVs) are crucial for the coordinated development of ecology and economy. This research examines the Xiangjiang River Basin and combines land use data from 1995 to 2020, Landsat images, meteorological data, and socio-economic data. These data are incorporated into the PLUS model to simulate land use patterns in 2035 under the following five sc...

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