Analysis of Landsat 5 TM Data of Malaysian Land Covers Using ISODATA Clustering Technique

Asmala, A. and Sufahani, Suliadi Firdaus (2012) Analysis of Landsat 5 TM Data of Malaysian Land Covers Using ISODATA Clustering Technique. IEEE Asia-Pasific Conference on Applied Electromagnetics. pp. 92-97. ISSN 978-1-4673-3115-9


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This study presents a detailed analysis of Iterative Self Organizing Data Analysis (ISODATA) clustering for multispectral data classification. ISODATA is an unsupervised classification method which assumes that each class obeys a multivariate normal distribution, hence requires the class means and covariance matrices for each class. In this study, we use ISODATA to classify a diverse tropical land covers recorded from Landsat 5 TM satellite. The classification is carefully examined using visual analysis, classification accuracy, band correlation and decision boundary. The results show that ISODATA is able to detect eight classes from the study area with 93% agreement with the reference map. The behavior of mean and standard deviation of the classes in the decision space is believed to be one of the main factors that enable ISODATA to classify the land covers with relatively good accuracy.

Item Type: Article
Uncontrolled Keywords: ISODATA, Landsat, Classification
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics
Divisions: Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User: Dr. Asmala Ahmad
Date Deposited: 18 Dec 2012 06:55
Last Modified: 26 Jan 2022 10:16
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