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Sensors 2016, 16(7), 1075; doi:10.3390/s16071075

Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree

1
Department of Civil Engineering, Kangwon National University, Chuncheon 200-701, Korea
2
LX Korea Cadastral Surveying Corporation, 141 Uisadang-daero Yeodeungpo-gu, Seoul 150-911, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Thomas B. Messervey
Received: 21 March 2016 / Revised: 4 July 2016 / Accepted: 7 July 2016 / Published: 12 July 2016
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Abstract

Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size. View Full-Text
Keywords: Landsat 8; OLI sensor; J48 decision tree; water body identification; Gandwon-do Landsat 8; OLI sensor; J48 decision tree; water body identification; Gandwon-do
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Acharya, T.D.; Lee, D.H.; Yang, I.T.; Lee, J.K. Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree. Sensors 2016, 16, 1075.

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