Markov Chain Modeling of Multinomial Land-Cover Classes

摘要

Quantitatively modeling the spatial distribution and uncertainties of land-cover classes is crucial in geographic information science. However, currently suitable methods for modeling multinomial categorical variables for geographical analyses are rare because of the complex spatial interdependence of multinomial classes. In this paper we use a recently presented two-dimensional Markov chain model to simulate multinomial land-cover classes and to estimate occurrence probability vectors for spatial uncertainty representation. Simulated results indicate that the model may provide a potential method for predictive mapping at higher resolutions possibly over large areas and for spatial uncertainty analyses of land-cover classes.