Markov model based on driving forces of land use change and its application
基于土地利用驱动力的马尔科夫模型及其应用

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.