Classification of Chlorophyll Concentrations in Coastal Water Using Linear Regression with THEOS Imagery

International Journal of Applied Physics

© 2020 by SSRG - IJAP Journal

Volume 7 Issue 1

Year of Publication : 2020

Authors : Ahmed Asal Kzar, Hayder Saad Abdulbaqi, M. Z. MatJafri, H. S. Lim

10.14445/23500301/IJAP-V7I1P120

How to Cite?

Ahmed Asal Kzar, Hayder Saad Abdulbaqi, M. Z. MatJafri, H. S. Lim, "Classification of Chlorophyll Concentrations in Coastal Water Using Linear Regression with THEOS Imagery," SSRG International Journal of Applied Physics, vol. 7,  no. 1, pp. 142-150, 2020. Crossref, https://doi.org/10.14445/23500301/IJAP-V7I1P120

Abstract:

The increasing of water pollutants in the coastline has caused environment problem by the widely usage of the region’s resources for their life. The waters surrounding areas is one of the most effected from these areas especially by chlorophyll. In this study, using of the linear regression for classification then mapping of chlorophyll concentrations through finding the relationship between the chlorophyll concentration and the digital number of an individual band represented by red or green or blue of the adopted satellite (THEOS) for Penang strait, Penang, Malaysia. The validation data were measured from the study area simultaneously with the satellite image acquisition. The results were by selecting one of the three relationships of the three bands. As result, the red band had the best relationship through given the highest coefficient of determination (0.967) that calculated between the two groups of the chlorophyll concentrations: measured (validation data) and calculated by the linear regression. In addition, we tested the new algorithm with noise, it has proved its steadfastness with noisy images over a range of noise levels. Therefore, chlorophyll mapping of water pollution in the adopted study area can be achieved by the linear regression with the based THEOS satellite image.

Keywords:

Chlorophyll; environment; THEOS; image classification; water quality mapping.

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