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
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
, 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)
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-TextKeywords:
spectral imaging; unmanned aerial vehicles; correlation; water quality monitoring; artificial neural networks
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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.
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