Conference Paper

Design of a Dynamic Land-Use Change Probability Model Using Spatio-Temporal Transition Matrix

DOI: 10.1007/978-3-642-12156-2_8 Conference: Computational Science and Its Applications - ICCSA 2010, International Conference, Fukuoka, Japan, March 23-26, 2010, Proceedings, Part I
Source: DBLP


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.

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