CHANGE DETECTION IN MULTI-TEMPORAL IMAGES USING MULTISTAGE CLUSTERING FOR DISASTER RECOVERY PLANNING

Soleh, Muhamad; Arymurthy, Aniati Murni; Wiguna, Sesa

doi:10.21609/jiki.v11i2.623

Jurnal SINTA 2

CHANGE DETECTION IN MULTI-TEMPORAL IMAGES USING MULTISTAGE CLUSTERING FOR DISASTER RECOVERY PLANNING

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 11 No. 2 (2018) · pp. 110–117

DOI: 10.21609/jiki.v11i2.623
ISSN: 2502-9274, 2088-7051
Published: 2018-06-29
Publisher: Faculty of Computer Science - Universitas Indonesia
Language: eng

Abstract

Change detection analysis on multi-temporal images using various methods have been developed by many researchers in the field of spatial data analysis and image processing. Change detection analysis has many benefit for real world applications such as medical image analysis, valuable material detector, satellite image analysis, disaster recovery planning, and many others. Indonesia is one of the most country that encounter natural disaster. The most memorable disaster was happened in December 26, 2004. Change detection is one of the important part management planning for natural disaster recovery. This article present the fast and accurate result of change detection on multi-temporal images using multistage clustering. There are three main step for change detection in this article, the first step is to find the image difference of two multi-temporal images between the time before disaster and after disaster using operation log ratio between those images. The second step is clustering the difference image using Fuzzy C means divided into three classes. Change, unchanged, and intermediate change region. Afterword the last step is cluster the change map from fuzzy C means clustering using k means clustering, divided into two classes. Change and unchanged region. Both clustering’s based on Euclidian distance.

Keywords

Collaboration network of the authors

21 authors · 37 co-authorship links · 6 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

University of Indonesia
University of Auckland
RWTH Aachen University
The University of Melbourne
Affiliation unknown

Different organisations
Same organisation
Affiliation unknown
Thicker line = more joint articles · bigger circle = more articles

Show as table

Co-author	Organisation	Joint articles
Edward Citrahadi	Affiliation unknown	1
Tieta Antaresti	University of Indonesia	1
Vina Ayumi	University of Indonesia	1
L. M. Rasdi Rere	University of Indonesia	1
Mohamad Ivan Fanany	University of Indonesia	1
Yohanes Gultom	University of Indonesia	1
Rian Josua Masikome	RWTH Aachen University	1
Muhammad Hafizhuddin Hilman	The University of Melbourne	1
Grafika Jati	University of Indonesia	1
Yuni Arti	University of Indonesia	1
Hans Timothy Wijaya	University of Indonesia	1
Juan Thomas Wijaya	University of Indonesia	1
Yohanes Fridolin Hestrio	University of Indonesia	1
Bayu Satria Persada	University of Indonesia	1
Frederic Morado Saragih	University of Indonesia	1
Muhammad Yusuf Kardawi	University of Indonesia	1
Wisnu Aryo Jatmiko	University of Indonesia	1
Herwanto Herwanto	Affiliation unknown	1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.

Original metadata (oai_dc)

<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">CHANGE DETECTION IN MULTI-TEMPORAL IMAGES USING MULTISTAGE CLUSTERING FOR DISASTER RECOVERY PLANNING</dc:title>
	<dc:creator>Soleh, Muhamad</dc:creator>
	<dc:creator>Arymurthy, Aniati Murni</dc:creator>
	<dc:creator>Wiguna, Sesa</dc:creator>
	<dc:subject xml:lang="en-US">Change Detection</dc:subject>
	<dc:subject xml:lang="en-US">Multistage Clustering</dc:subject>
	<dc:subject xml:lang="en-US">Disaster Recovery Planning</dc:subject>
	<dc:subject xml:lang="en-US">Fuzzy C Means</dc:subject>
	<dc:subject xml:lang="en-US">K-Means</dc:subject>
	<dc:description xml:lang="en-US">Change detection analysis on multi-temporal images using various methods have been developed by many researchers in the field of spatial data analysis and image processing. Change detection analysis has many benefit for real world applications such as medical image analysis, valuable material detector, satellite image analysis, disaster recovery planning, and many others. Indonesia is one of the most country that encounter natural disaster. The most memorable disaster was happened in December 26, 2004. Change detection is one of the important part management planning for natural disaster recovery. This article present the fast and accurate result of change detection on multi-temporal images using multistage clustering. There are three main step for change detection in this article, the first step is to find the image difference of two multi-temporal images between the time before disaster and after disaster using operation log ratio between those images. The second step is clustering the difference image using Fuzzy C means divided into three classes. Change, unchanged, and intermediate change region. Afterword the last step is cluster the change map from fuzzy C means clustering using k means clustering, divided into two classes. Change and unchanged region. Both clustering’s based on Euclidian distance.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2018-06-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/623</dc:identifier>
	<dc:identifier>10.21609/jiki.v11i2.623</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 11 No. 2 (2018): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 110-117</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v11i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/623/400</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 Jurnal Ilmu Komputer dan Informasi</dc:rights>
</oai_dc:dc>