Analysis of spatial variability in factors contributing to vegetation restoration in Yan'an, China

Abstract

Abstract As a typical ecologically fragile region, the Loess Plateau of China has much improved in the ecological environment in the past two decades. In order to achieve a more efficient implementation of ecological projects in the future, it is of great importance to study the influencing factors and the driving mechanism of vegetation restoration based on past vegetation restoration practices. However, human activity and natural factors may show different coupling effects in contributing to the vegetation restoration in different locations because of their spatial heterogeneity. In that case, the traditional global regression based on the Ordinary Least Squares is at risk of failure. With Yan'an as the study area, vegetation index data in 2000 and 2011 were used to calculate the vegetation improvement map during the ecological projects; taking this map as the dependent variable, and the topographical, meteorological, socio-economic, and policy factors as independent variables, Geographically Weighted Regression model which can well deal with spatial heterogeneity, together with the Ordinary Least Squares model, was applied in this study. The results show: (1) most of the variables selected in this research have significant impacts on the vegetation restoration, while meteorological and socio-economic factors make greater contributions; (2) the effect of factors contributing to vegetation coverage improvement varies substantially across the study site, with climatic and physical factors dominating, and socio-economic/policy factors playing either positive or negative roles in different parts of the study area. It could be concluded that spatial variability in factors contributing to vegetation restoration should be well considered when performing ecological policy evaluation, and Geographically Weighted Regression method has unparalleled advantages of Ordinary Least Squares model in this aspect since it provides scientific reference for policymakers to make effective decisions according to local conditions and maximize the effectiveness of ecological policies.