On Markov Process and Simulation of Land Use Change

Abstract

Land use is a major activity happening in many parts of the world, hence several rules and regulations have been implemented to minimize the cause of destruction and over-usage of the land. Remote Sensing and GIS technologies have been the common technique of absorbing data for land use but these methods are costly and time-consuming. Other studies produce the transition matrices through cross-tabulation. In this study, the transition matrices of the actual land use data gathered from the Cagayan de Oro Socio-Economic Profile were computed through Simulation using the statistical software. The transition probability matrix with the least error was taken as the predictor of the state vector. The future land use of Cagayan de Oro was then projected by an application of stochastic modeling through the use of a Markov process. The results indicate that for the next seven years there will be a substantial agricultural and forest land loss, and an increase in urban land and other land types. The results also indicate a stabilization of land use. Hence, the Markov process is a useful tool in forecasting land use change. To better acquire observed data, it is suggested to use GIS technologies and remote sensing.