湖南省城镇规模扩展用地驱动因子分析及趋势预测——基于STIRPAT模型

研究目的:城镇规模扩展用地是现阶段土地利用变化研究热点之一,对城镇规模扩展用地驱动性因素进行分析及趋势预测有利于现阶段的土地集约利用与规划。研究方法:运用扩展模型,对湖南省2000~2012年城镇建设用地扩张的驱动性因素进行了分析,并运用BP神经网络模型对未来湖南省城镇建设用地需求进行了预测。研究结果:在研究期内,地区人口数、产业结构变动、城镇化水平是湖南省城镇用地扩展的主要驱动因子;运用BP神经网络模型预测2015年、2020年湖南省城镇建设用地分别增至1663.20平方千米、2030.01平方千米,城镇建设用地年扩展率为6.57%。研究结论:社会固定资产投资、地区生产总值对城镇建设用地扩张的促进作用较弱,政策性因素和人口年龄结构对城镇建设用地扩展则有一定制约作用;在"十二五"背景下湖南省两型社会的构建与城镇土地集约化使用将会存在一定压力。最后结合城镇规模扩展中建设用地驱动因子的边际贡献和预测趋势,本文提出了相关政策建议。

Trend Prediction and Some Analysis of the Driving Factors of Land Extension for Urban Construction in Hunan Province-Based on STIRPAT Model

The effect of land extension for urban constuction is currently the research focus of the land use change. In the study, based on Statistical Yearbook data of Hunan Province, and with the help of STIRPAT model, we analyze the dynamic characteristics of the urban construction land in Hunan from 2000 to 2012, and then apply BP neural network model to forecast the demand of urban construction land in the future. The results show that area population, changes of industrial structure, the level of urbanization are the main driving factors of urban land expansion; fixed asset investment, GDP have a weak promotion, policy factors and the age structure of population have restriction on the expansion of construction land. By the BP neural network model , this study predicts that construction land in 2015, 2020 will expand to 1663.2, 2030.01squarekilometers respectively, the annul rate of construction land is 6.57% per year. This article reveals that the pressure on intensive land-use and construction of two oriented society under the background of “Twelfth Five Year Plan” of Hunan. Finally, this paper puts forward some suggestions.