基于土地利用驱动力的马尔科夫模型及其应用

马尔科夫模型在土地利用变化的预测中已经得到了广泛的应用,但如何通过区域社会经济指标对马尔科夫模型进行修正,提高其预测精度是一个值得研究的科学问题。本文解译1995,2001,2005,2008四个时相的TM遥感影像得到太仓土地利用结构图,构建基于土地利用驱动力分析的加权马尔科夫模型,对2013年太仓市的土地利用结构(农用地,建设用地等)进行预测。改进后的模型将1995—2001年,2001—2005两阶段转移矩阵作为加权马尔科夫模型的加权因子;再根据GDP、非农人口数量、二产比重的自相关系数确定两阶段转移矩阵的权重,建立基于土地利用驱动力分析的加权马尔科夫模型,以此对2013年土地利用结构进行预测。同时基于城市土地利用现状(2008年)分析,对比上述加权马尔科夫模型预测结果,证明加权马尔科夫模型预测精度较高。

Markov model based on driving forces of land use change and its application

Markov model has been widely applied in the prediction of urban landscape change, however, it can be amended though the regional socio-economic indicators to improve its forecast accuracy. Based on TM satellite images in different years (1995, 2001, 2005 and 2008), urban land-use change maps were created and analyzed in Taicang County of Jiangsu Province, then a weighed Markov model was established based on the driving force of urban land-use change to predict the urban landscape structure ( agricultural land, constructive land, etc. ) in 2013. Based on the analysis of driving forces of land-use change, the periods of driving forces were divided into 1995 - 2001 and 2001 - 2005 two stages. The transfer matrixes were used as the weighted factors of Markov model whose weights were calculated to constitute the model in order to build a transfer matrix more in line with the urban landscape change in the stage from 2008 to 2013, then the structure of the urban landscape in 2013 was predict. On the basis of status value (2008) of urban landscape, the weighted Markov model was more reasonable than the non-weighted Markov model.