USE OF MARKOV CHAINS AND REMOTE SENSING DATA TO PREDICT LAND USE CONVERSION IN LARGE URBAN AGGLOMERATIONS
Land use change is an important component of global environmental change. Results of the analysis and forecast of some land use changes contribute to land use planning and land use management for sustainable development. In the study, land use maps of Hanoi metropolis have been created using images of SPOT-5 for 2003, 2007 and 2011. The forecast land use map of 2011generated with the use of the Markov model for land use maps of 2003 and 2007, was compared with the land use map of 2011 obtained using the SPOT-5 image. The results of the comparison show that the forecast land use map of 2011 with sufficient accuracy corresponds to factual data. Therefore, the use of Markov chains for forecasting the conversion of land use types is recomended. We used Markov model for predicting land use map of 2019 and 2027 in the metropolis.