Asmala, A. and Shaun, Quegan (2016) The Effects of Haze on the Accuracy of Maximum Likelihood Classification. Applied Mathematical Sciences, 10 (39). pp. 1935-1944. ISSN 1312-885X
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Abstract
This study aims to investigate the effects of haze on the accuracy of Maximum Likelihood classification. Data containing eleven land covers recorded from Landsat 5 TM satellite were used. Two ways of selecting training pixels were considered which are choosing from the haze-affected and haze-free data. The accuracy of Maximum Likelihood classification was computed based on confusion matrices where the accuracy of the individual classes and the overall accuracy were determined. The result of the study shows that classification accuracies declines with faster rate as visibility gets poorer when using training pixels from clear compared to hazy data.
Item Type: | Article |
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Uncontrolled Keywords: | Haze, Landsat, Classification Accuracy, Training Pixels |
Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
Divisions: | Faculty of Information and Communication Technology > Department of Industrial Computing |
Depositing User: | Dr. Asmala Ahmad |
Date Deposited: | 30 Jun 2016 02:06 |
Last Modified: | 05 Sep 2021 16:32 |
URI: | http://eprints.utem.edu.my/id/eprint/16729 |
Statistic Details: | View Download Statistic |
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