ORIGINAL RESEARCH
Exploring the Human-Land Nexus in China’s Xin’an River Basin: Remote Sensing Analysis of Ecosystem Services Variability and Synergy
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Xin Su 2
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1
Social Innovation Design Research Centre, Anhui University, Hefei, 203106, China
 
2
Community Development Research Center, Anhui University, Hefei, 203106, China
 
3
Faculty of Arts and Social Sciences, Lancaster University, UK, Lancaster, UK
 
 
Submission date: 2024-04-11
 
 
Final revision date: 2024-05-28
 
 
Acceptance date: 2024-06-12
 
 
Online publication date: 2024-10-21
 
 
Corresponding author
Xin Su   

Community Development Research Center, Anhui University, Hefei, 203106, China
 
 
Yanlong Guo   

Social Innovation Design Research Centre, Anhui University, Hefei, 203106, China
 
 
 
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ABSTRACT
This study scrutinized the Xin’an River Basin from 2017 to 2022, employing refined methodologies such as updated ecosystem service value tables, welfare assessment systems encompassing material, health, and public well-being metrics, human-environment coupling models, and advanced remote sensing technologies for land use patterns and satellite data analysis. Key findings revealed that: (1) The valuation of ecosystem services exhibited periods of equilibrium followed by slight declines, with a spatial distribution pattern described as ‘rising at the periphery, diminishing at the core’, culminating in a modest overall depreciation. (2) Human settlement welfare demonstrated a distinct geographical trend of ‘enhancement in the southeast, reduction in the northwest’, highlighting exceptional welfare in Jiande City, Shexian, and Chun’an County. (3) Over the observation period, the dynamic interplay between ecosystem services and human settlement welfare fluctuated, reaching its zenith in 2018 and its nadir in 2020. This interaction displayed a spatial gradient of ‘excellent in the southeast, subpar in the central regions, and favorable in the northwest’, indicating an overall moderate level of integration. The results underscore a mutual adjustment and a clear convergence towards minimal functional discord between the two systems.
eISSN:2083-5906
ISSN:1230-1485
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