城市建设用地需求预测方法研究——以湖南省长沙市为例

Study on Methods of Prodicting Land Demand for Construction Use——A Case of changsha city Hunan Province

本文以城市建设用地需求量预测为研究对象,对多种预测方法进行比较分析,选取合适研究区建设用地的预测方法。本研究选择湖南省长沙市城市建设用地需求量预测作为实例,文中结合1996—2013年研究区的经济社会发展统计资料和土地利用的时空变化数据,分别利用多元线性回归、灰色系统GM(1,1)模型和RBF(Radial Basis Function)神经网络模型,并借助了SPSS、Excel、Matlab等软件对长沙市建设用地需求量进行预测,并将所得预测结果进行比较分析,优化预测方法,得出RBF神经网络模型的预测精度最高。此外,通过预测值与规划值的比较分析,可知长沙市建设用地增长速度过快,应加强城市内涵挖掘,对城市土地利用及其规划制定具有一定的科学指导意义。

The paper utilizes the urban cons truction land demand forecast as the research object, compares and analyze many kinds of prediction methods,and choose the most suitable prdiction method.Taking the demand predict of Changsha as an example, combined with the socio-economic development statistical data and space-time change data land utilize from 1996 to 2013.This research constructs the construction land demand5 changes predicting model of multiple linear regression model, gray systemGM（l5l） prediction model, and RBF（Radial Basis Function） neural network forecasting model with the help of SPSS,Excal,Matlab and other software to predict the construction land demand in Changsha City.Besides,the forecast results are made a comparative analysis,and then to improve the rationality and accuracy of prediction. The results of prediction dearly shows that the accuracy of RBF neural network is the best.Besides,by the comparison of predicted and actual values, Changsha develops faster than expected.Hence we should use land effectively and provide scientific reference for urban land use planning.