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• W4285384493 startingPage "109165" @default.
• W4285384493 abstract "Sufficient research on cultural ecosystem services (CESs) helps decision makers realize developmental and environmental goals in urban planning, budget allocation, and municipal service provision. The Bayesian belief network (BBN), as a semi-quantitative model, can be used to infer the supply and demand match for CESs. Taking Shenzhen as the study area, we evaluated the CES supply and demand. We used a BBN to simulate the CES supply and demand and identify the key influencing factors affecting the CES budget. CES budget expectations were created to indicate the CES supply and demand balance. The main conclusions are as follows. (1) Considering the community as the evaluation unit, the satisfaction rate of CES demand was 62.5% in Shenzhen. (2) Communities with a high possibility of a CES deficit are primarily distributed in Futian, Nanshan, Luohu, and Bao’an Districts, accounting for 7.45% of the area of Shenzhen. (3) The population density, CES supply potential, and CES supply opportunity jointly determined the CES supply and demand balance. (4) The CES budget expectation results demonstrate that communities with a high risk of imbalance are widely distributed, and balanced communities are primarily concentrated in the Guangming, Pingshan, and Dapeng New Areas. (5) It is necessary to enhance the fairness of CES supply in Shenzhen through the promotion of green space, improvement of infrastructure, and interconnection of communities. By combining BBN with CES as an exercise, this study aims to enrich the methods for evaluating the CES supply and demand balance, providing scientific suggestions for Shenzhen to build a livable city and achieve the Sustainable Development Goals." @default.
• W4285384493 created "2022-07-14" @default.
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• W4285384493 date "2022-09-01" @default.
• W4285384493 modified "2023-09-30" @default.
• W4285384493 title "Evaluating the supply-demand balance of cultural ecosystem services with budget expectation in Shenzhen, China" @default.
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• W4285384493 doi "https://doi.org/10.1016/j.ecolind.2022.109165" @default.
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