Prediction of Principle Factors Effect for Avoiding Field Desolation by Markov Chain Estimation Algorithm

Abstract

The finite Markov chain was employed for the prediction of progressively expandingdesolated fields of settlements. It is well known that the Markov chains are commonly used in connection with time series. In this study it was found that a Markov chain is adaptable and useful for evaluating the principal factors of desolated fields, though it is not time series. One hundred and five settlements were selected from large rural areas with progressively desolated fields in Japan, and were classified into 5 groups by the fuzzy set theory. The effect of single principal factor on the multiple social aspects was discussed. For example, from the results of the finite Markov chain, it was found that the road conditions are very important factor of land use planning in restraining of the advance of desolated fields, the increase in the length of the paved road is more desirable than the increase in the length of the road wider than 3.5m. These results were consistent with the study cited above, and were confirmed by concrete cases. From this study a model for a Dynamic Land Use Planning may be developed.