This paper comprehensively used three methods to explore the global and local impact mechanism of socioeconomic on ecosystem services value in Beijing-Tianjin-Hebei region, which included principal component analysis (PAC), ordinary least square (OLS) and geographic weighted regression (GWR). The results suggested that, the primary industry related factors were the main socioeconomic factors, while factors such as the second industry, the third industry, the fiscal revenue and so on, had little effect on it. Socioeconomic factors can affect or change the value of ecosystem services to a certain extent. The comprehensive factor of primary industry had a negative effect, and the negative effect of the total population factor was weaker than the comprehensive factor, meanwhile, the effect of the simplification factor of the primary industry was positive or negative. The local model of a PCA-GWR can better solve the spatial non-stationarity of the dependent and the independent variables, and the local model was better than the global model of OLS and PCA-OLS. A standard GWR model can be further improved to reflect the local differences of the impact mechanism in more detail.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.