Socio-Economic Impact Mechanism of Ecosystem Services Value, a PCA-GWR Approach

摘要

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.