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[1]LIU Jie,LI Hong,MA Yong-gang.Analysis and Prediction of Land Use Change in Typical City of Central Asia Based on CA-Markov Model[J].Research of Soil and Water Conservation,2014,21(03):51-56.

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Analysis and Prediction of Land Use Change in Typical City of Central Asia Based on CA-Markov Model

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 21 Number of periods: 2014 03 Page number: 51-56 Column: Public date: 2014-06-28

Title:: Analysis and Prediction of Land Use Change in Typical City of Central Asia Based on CA-Markov Model

Author(s):: LIU Jie, LI Hong, MA Yong-gang; Xinjiang Uygur Autonomous Region Center for Remote Sensing, Urumqi 830011, China

Keywords:: land use; CA-Markov model; Dushanbe; trend prediction

CLC:: F301.24

DOI:: -

Abstract:: Dushanbe is the capital of Tajikistan. It is one of the typical cities in Central Asia. Supported by the technology of remote sensing and GIS, using three periods of Landsat remote sensing image (1989 TM, 2001 TM, 2011 ETM), Dushanbe is supervised classification. Land-use change in 2011 was simulated based on the the results of the 1989 and 2001 classification with CA-Markov model and the results of classification data. The simulation result was analyzed and compared with the observed data of 2011. In 1989—2001, the land use change accorded with the applied conditions of CA-Markov model, verifying that the CA-Markov process is feasible. The variation characteristics of land use in horizontal (spatial structure) and vertical (time-series) between the years of 1989—2011 were systematically analyzed.The results reflecting the increase in the size of the city are very significant trends, the area of vegetation and unused land significantly change, the area of artificial rivers and water changes is extremely small. The status of land use change in 2020 was simulated and predicted by the 1989—2001 and 2001—2011 probabilistic transfer matrixes. Two land use status data in 2020 (2020A & 2020B) are acquired by the predicted different time periods. These predicted data from the space and the number characteristic were analyzed. They not only have a remarkable consistency, but also have an obvious difference which can be seen through the analysis of these data. Dushanbe construction land of main city grows significantly to the west, 2020B growth is more significant, the main city in the northeast of the growth is not obvious. Around the main city construction land area of 2020B grows more slowly than 2020A. Vegetation area forecast results are consistent, but construction land and unused land prediction results are significantly different, there are still minor differences in the prediction results of artificial water and river area. The reason is that under these two different time periods, its various types of land use and the way the transfer direction are different, there are also differences in the extent of the transfer. In addition, the classification accuracy, model uncertainties and other factors have an impact on the predicted results.

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