Analysis of landsat 5 TM data of Malaysian Land covers using ISODATA clustering technique

Ahmad, Asmala and Sufahani, Suliadi Firdaus Analysis of landsat 5 TM data of Malaysian Land covers using ISODATA clustering technique. Proceeding IEEE . pp. 92-97. ISSN 978-1-4673-3114-2 (ISBN)


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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; lendsat; chssifieation
Subjects:Q Science > QA Mathematics > QA297 Numerical analysis. Analysis
Divisions:Faculty of Science, Technology and Human Development > Department of Science and Mathematics
ID Code:4319
Deposited By:Normajihan Abd. Rahman
Deposited On:15 Mar 2015 15:51
Last Modified:15 Mar 2015 15:51

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