Design of a dynamic land-use change probability model using spatio-temporal transition matrix

Yongjin Joo, Chulmin Jun, Soohong Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings
PublisherSpringer Verlag
Pages105-115
Number of pages11
EditionPART 1
ISBN (Print)3642121551, 9783642121555
DOIs
StatePublished - 2010
Event2010 International Conference on Computational Science and Its Applications, ICCSA 2010 - Fukuoka, Japan
Duration: 23 Mar 201026 Mar 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6016 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2010 International Conference on Computational Science and Its Applications, ICCSA 2010
Country/TerritoryJapan
CityFukuoka
Period23/03/1026/03/10

Keywords

  • Land-use change prediction
  • Markov Chain
  • Spatio-temporal transition matrix
  • Urban growth model

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