水土保持通报2017，Vol.37Issue(1)：149-154,160,7.DOI:10.13961/j.cnki.stbctb.2017.01.027
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
Application of Multiple Driving-Factors Prediction Model for Land Use Structure Change Based on Logistic-Markov Model
摘要
Abstract
[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.关键词
土地利用结构变化/主成分分析/Logistic-Markov model/多因素驱动/预测模型Key words
land use structure change/principal component analysis/Logistic-Markov model/multiple driving forces/prediction model分类
管理科学引用本文复制引用
余德贵,吴群..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[J].水土保持通报,2017,37(1):149-154,160,7.基金项目
国家自然科学基金(重点)项目“我国土地资源效率提升能力与系统建设研究:基于转变经济发展方式的视角”(71233004) （重点）
南京农业大学中央业务费专项“互联网+背景下的江苏现代农业发展模式与增效途径”(SKZK2015008) （SKZK2015008）
江苏省科技计划“基于全供应链协同的东台市绿色食品电子商务平台”(BN2014156). （BN2014156）
