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

Yongjin Joo; Chulmin Jun; Soohong Park

doi:10.1007/978-3-642-12156-2_8

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

Yongjin Joo
, Chulmin Jun
, Soohong Park

Department of Geoinformatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Computational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings
Publisher	Springer Verlag
Pages	105-115
Number of pages	11
Edition	PART 1
ISBN (Print)	3642121551, 9783642121555
DOIs	https://doi.org/10.1007/978-3-642-12156-2_8
State	Published - 2010
Event	2010 International Conference on Computational Science and Its Applications, ICCSA 2010 - Fukuoka, Japan Duration: 23 Mar 2010 → 26 Mar 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6016 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2010 International Conference on Computational Science and Its Applications, ICCSA 2010
Country/Territory	Japan
City	Fukuoka
Period	23/03/10 → 26/03/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Keywords

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

Access to Document

10.1007/978-3-642-12156-2_8

Cite this

Joo, Y., Jun, C., & Park, S. (2010). Design of a dynamic land-use change probability model using spatio-temporal transition matrix. In Computational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings (PART 1 ed., pp. 105-115). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6016 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-642-12156-2_8

Joo, Yongjin ; Jun, Chulmin ; Park, Soohong. / Design of a dynamic land-use change probability model using spatio-temporal transition matrix. Computational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings. PART 1. ed. Springer Verlag, 2010. pp. 105-115 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Design of a dynamic land-use change probability model using spatio-temporal transition matrix",

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.",

keywords = "Land-use change prediction, Markov Chain, Spatio-temporal transition matrix, Urban growth model",

author = "Yongjin Joo and Chulmin Jun and Soohong Park",

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Joo, Y, Jun, C & Park, S 2010, Design of a dynamic land-use change probability model using spatio-temporal transition matrix. in Computational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6016 LNCS, Springer Verlag, pp. 105-115, 2010 International Conference on Computational Science and Its Applications, ICCSA 2010, Fukuoka, Japan, 23/03/10. https://doi.org/10.1007/978-3-642-12156-2_8

Design of a dynamic land-use change probability model using spatio-temporal transition matrix. / Joo, Yongjin; Jun, Chulmin; Park, Soohong.
Computational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings. PART 1. ed. Springer Verlag, 2010. p. 105-115 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6016 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Design of a dynamic land-use change probability model using spatio-temporal transition matrix

AU - Joo, Yongjin

AU - Jun, Chulmin

AU - Park, Soohong

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Land-use change prediction

KW - Markov Chain

KW - Spatio-temporal transition matrix

KW - Urban growth model

UR - https://www.scopus.com/pages/publications/77952296311

U2 - 10.1007/978-3-642-12156-2_8

DO - 10.1007/978-3-642-12156-2_8

M3 - Conference contribution

AN - SCOPUS:77952296311

SN - 3642121551

SN - 9783642121555

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 105

EP - 115

BT - Computational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings

PB - Springer Verlag

T2 - 2010 International Conference on Computational Science and Its Applications, ICCSA 2010

Y2 - 23 March 2010 through 26 March 2010

ER -

Joo Y, Jun C, Park S. Design of a dynamic land-use change probability model using spatio-temporal transition matrix. In Computational Science and Its Applications - ICCSA 2010 - International Conference, Proceedings. PART 1 ed. Springer Verlag. 2010. p. 105-115. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-12156-2_8

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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