This study aims to analyze land use patterns using time-series satellite images of Seoul Metropolitan Area for the past 30 years, and present a macroscopic model for predicting future land use patterns using Markov Chain based probability model, and finally examine its applicability to Korea. Several Landsat MSS and TM images were used to acquire land-use change patterns and dynamic land-use change patterns were categorized from the classified images. Finally, spatio-temporal transition matrices were constructed from the classified images and applied them into a Markov Chain based model to predict land-use changes for the study area. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Joo, Y., Jun, C., & Park, S. (2010). Design of a dynamic land-use change probability model using spatio-temporal transition matrix. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6016 LNCS, pp. 105–115). Springer Verlag. https://doi.org/10.1007/978-3-642-12156-2_8
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