A stochastic modeling algorithm for the long-term land cover change forecasting

The peculiarities of a stochastic algorithm for the long-term land cover change modeling are considered. Its components are identified which affect a predictability of the modeling process and increase its computational expense. The techniques to reduce computational expenses of the algorithm are developed. It is based on the processing of the most important elements of the expected transition areas matrix. An example of the algorithm approbation using the proposed techniques demonstrating dramatic decreases of its computational expense for the long-term modeling is presented.