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Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images

Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 21000 Split, Croatia
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Academic Editor: Chiman Kwan
Electronics 2021, 10(23), 3004; https://doi.org/10.3390/electronics10233004
Received: 12 October 2021 / Revised: 22 November 2021 / Accepted: 29 November 2021 / Published: 2 December 2021
(This article belongs to the Section Artificial Intelligence)
In this paper, we describe a method for the prediction of concentration of chlorophyll-a (Chl-a) from satellite data in the coastal waters of Kaštela Bay and the Brač Channel (our case study areas) in the Republic of Croatia. Chl-a is one of the parameters that indicates water quality and that can be measured by in situ measurements or approximated as an optical parameter with remote sensing. Remote sensing products for monitoring Chl-a are mostly based on the ocean and open sea monitoring and are not accurate for coastal waters. In this paper, we propose a method for remote sensing monitoring that is locally tailored to suit the focused area. This method is based on a data set constructed by merging Sentinel 2 Level-2A satellite data with in situ Chl-a measurements. We augmented the data set horizontally by transforming the original feature set, and vertically by adding synthesized zero measurements for locations without Chl-a. By transforming features, we were able to achieve a sophisticated model that predicts Chl-a from combinations of features representing transformed bands. Multiple Linear Regression equation was derived to calculate Chl-a concentration and evaluated quantitatively and qualitatively. Quantitative evaluation resulted in R2 scores 0.685 and 0.659 for train and test part of data set, respectively. A map of Chl-a of the case study area was generated with our model for the dates of the known incidents of algae blooms. The results that we obtained are discussed in this paper. View Full-Text
Keywords: Chlorophyll-a; multiple linear regression; ridge regression; Sentinel-2; data set augmentation Chlorophyll-a; multiple linear regression; ridge regression; Sentinel-2; data set augmentation
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MDPI and ACS Style

Ivanda, A.; Šerić, L.; Bugarić, M.; Braović, M. Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images. Electronics 2021, 10, 3004. https://doi.org/10.3390/electronics10233004

AMA Style

Ivanda A, Šerić L, Bugarić M, Braović M. Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images. Electronics. 2021; 10(23):3004. https://doi.org/10.3390/electronics10233004

Chicago/Turabian Style

Ivanda, Antonia, Ljiljana Šerić, Marin Bugarić, and Maja Braović. 2021. "Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images" Electronics 10, no. 23: 3004. https://doi.org/10.3390/electronics10233004

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