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Volume 18
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10.3390/s18010159
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Open AccessTechnical Note

Proposal of a Method to Determine the Correlation between Total Suspended Solids and Dissolved Organic Matter in Water Bodies from Spectral Imaging and Artificial Neural Networks

by
Maurício R. Veronez
1,2,3,*,
Lucas S. Kupssinskü
3,
Tainá T. Guimarães
4,
Emilie C. Koste
1,
Juarez M. Da Silva
3,
Laís V. De Souza
2,
William F. M. Oliverio
3,
Rogélio S. Jardim
3,
Ismael É. Koch
3,
Jonas G. De Souza
3,
Luiz Gonzaga, Jr.
1,3,
Frederico F. Mauad
4,
Leonardo C. Inocencio
1 and
Fabiane Bordin
1
1
Advanced Visualization & Geoinformatics Lab—VizLab, Unisinos University, São Leopoldo 93022-750, Brazil
2
Graduate Programme in Geology, Unisinos University, São Leopoldo 93022-750, Brazil
3
Graduate Programme in Applied Computing, Unisinos University, São Leopoldo 93022-750, Brazil
4
Graduate Programme in Environmental Engineering Sciences, São Carlos Engineering School, University of São Paulo, São Carlos 13566-590, Brazil
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(1), 159; https://doi.org/10.3390/s18010159
Received: 16 November 2017 / Revised: 3 January 2018 / Accepted: 5 January 2018 / Published: 9 January 2018
(This article belongs to the Special Issue Analysis of Multispectral and Hyperspectral Data)
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Abstract

Water quality monitoring through remote sensing with UAVs is best conducted using multispectral sensors; however, these sensors are expensive. We aimed to predict multispectral bands from a low-cost sensor (R, G, B bands) using artificial neural networks (ANN). We studied a lake located on the campus of Unisinos University, Brazil, using a low-cost sensor mounted on a UAV. Simultaneously, we collected water samples during the UAV flight to determine total suspended solids (TSS) and dissolved organic matter (DOM). We correlated the three bands predicted with TSS and DOM. The results show that the ANN validation process predicted the three bands of the multispectral sensor using the three bands of the low-cost sensor with a low average error of 19%. The correlations with TSS and DOM resulted in R2 values of greater than 0.60, consistent with literature values. View Full-Text
Keywords: spectral imaging; unmanned aerial vehicles; correlation; water quality monitoring; artificial neural networks spectral imaging; unmanned aerial vehicles; correlation; water quality monitoring; artificial neural networks
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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
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MDPI and ACS Style

R. Veronez, M.; Kupssinskü, L.S.; T. Guimarães, T.; Koste, E.C.; Da Silva, J.M.; De Souza, L.V.; Oliverio, W.F.M.; Jardim, R.S.; Koch, I.É.; De Souza, J.G.; Gonzaga, L., Jr.; Mauad, F.F.; Inocencio, L.C.; Bordin, F. Proposal of a Method to Determine the Correlation between Total Suspended Solids and Dissolved Organic Matter in Water Bodies from Spectral Imaging and Artificial Neural Networks. Sensors 2018, 18, 159. https://doi.org/10.3390/s18010159

AMA Style

R. Veronez M, Kupssinskü LS, T. Guimarães T, Koste EC, Da Silva JM, De Souza LV, Oliverio WFM, Jardim RS, Koch IÉ, De Souza JG, Gonzaga L Jr., Mauad FF, Inocencio LC, Bordin F. Proposal of a Method to Determine the Correlation between Total Suspended Solids and Dissolved Organic Matter in Water Bodies from Spectral Imaging and Artificial Neural Networks. Sensors. 2018; 18(1):159. https://doi.org/10.3390/s18010159

Chicago/Turabian Style

R. Veronez, Maurício; Kupssinskü, Lucas S.; T. Guimarães, Tainá; Koste, Emilie C.; Da Silva, Juarez M.; De Souza, Laís V.; Oliverio, William F.M.; Jardim, Rogélio S.; Koch, Ismael É.; De Souza, Jonas G.; Gonzaga, Luiz, Jr.; Mauad, Frederico F.; Inocencio, Leonardo C.; Bordin, Fabiane. 2018. "Proposal of a Method to Determine the Correlation between Total Suspended Solids and Dissolved Organic Matter in Water Bodies from Spectral Imaging and Artificial Neural Networks" Sensors 18, no. 1: 159. https://doi.org/10.3390/s18010159

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