基于Logistic-Markov方法的土地利用结构变化多因素驱动预测模型研究与应用

[目的]探索土地利用结构变化的驱动规律及其预测方法,为在社会经济快速发展背景下抑制建设用地扩张、优化城乡土地利用等提供决策参考。[方法]利用主成分分析,Logistic,Markov等方法研究土地利用结构变化的驱动力,分析土地利用结构状态转移矩阵与驱动因素的数量关系,构建基于多因素驱动的土地利用结构变化预测模型。[结果]以地处"长三角"经济区的江苏省泰兴市为例,测算了城镇发展、经济发展和管理政策等土地利用结构变化驱动力,其中城镇工矿用地扩张的驱动力增加了25.85%,耕地减少的驱动力则降低了22.21%,并预测分析了2010—2020年的土地利用结构变化特征,预测精度相对提高了0.52%。[结论]多因素驱动的土地利用结构变化预测方法,能够科学地诠释土地利用结构变化及其驱动力的作用机理,可以提高预测精度,为分析区域土地利用变化规律提供一种新方法。

Application of Multiple Driving-Factors Prediction Model for Land Use Structure Change Based on Logistic-Markov Model

[Objective] The objective of the paper is to investigate the changes in land use structure and driving forces of land use change,and develop predicting method.It will provide a reference for land use decision,especially for inhibiting construction land expansion and optimizing urban & rural land use structure with social and economic development.[Methods] We used principal component analysic(PCA),Logistic and Markov methods to detect the driving forces of land use change,and developed predicting methods based on mechanism and relations of state transition probability matrix of land use structure and driving factors.[Results] At Taixing City of Jiangsu Province,which is located in the "Yangtze River Delta" economic region,we measured the multiple driving-forces of changes in land use structure including urban development,economic policy,market and management.The land expansion by the urban industrial and mining increased by 25.85％,and the cultivated land was reduced by 22.21％.We also predicted the land use structure in 2010-2020,and the prediction accuracy was increased by 0.52％ in study area.[Conclusion] The prediction model based on multiple driving-factors can explain relations between land-use change and its driving forces,improve prediction accuracy,and provide a new method for analyzing regional land use change.