[Statistical properties of Markov chain in land use and landscape study]

Markov chain has been widely applied in the study of land use and landscape changes, but its statistical properties were less tested. Based on the land use change data monitored in Beijing, and with Pearson chi-squared goodness-of-fit test, this paper examined the time stability and time independence of Markov chain of land use change. The results indicated that the hypothesis of time stationary and Markov property is not tenable, which meant that the land use change in Beijing was an un-stationary and highly order Markov chain. Pearson chi-squared test was not as restricted a the likelihood ratio test, its transitional probabilities being allowed to be greater than zero, and thus, could be more useful in testing the assumption of homogeneity and independence.