Quantitative measuring and influencing mechanism of urban and rural land intensive use in China

Abstract

Land use issue is an important constraining force to limit economic sustainable development of China. Urban and rural rapid expansion depletes valued land resources under the background of rapid urbanization. An extensive use pattern might cause a serious waste of land resources. The study on influencing mechanism of land intensive use (LIU) in China at the county level is a key tool for effective LIU practice and policy-making. This paper uses OLS model, Spatial Panel Lagged model and Spatial Panel Error model to quantitatively analyze the influencing mechanisms of five class factors and 17 variables supported by GIS (Geographic Information System) and MATLAB. And a comprehensive data set was developed including physical geography and socio-economic information of 2286 counties. Meanwhile, the spatiotemporal pattern of LIU has discussed by means of GIS. The results show that Spatial Panel Data models are slightly superior to OLS model in terms of significance and confidence level. Regression results of these models indicate that industrialization, urbanization, economic development level, location, transportation and policy have significant impact on LIU of counties. The variables of physical geography are less significant than socio-economic variables. An ignored variable of historical factor, however, became the best significant factor. In the future, the LIU at the county level should take advantage of the new situation by enhancing favorable factors and reducing disadvantageous ones, which can be acquired by improving the entire level and quality of industrialization and urbanization. We argued that an efficient and complete land market and operating system should be built to reflect market-oriented activities at the first place, then, differential LIU regulation policies and measurements should be optimized according to regional differences. In the meantime, we should pay close attention to the carrying capacity of local resources and environments when conducting LIU practices.