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Article

An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs

1
R&D Department, 3edata Environmental Engineering L. C., 27004 Lugo, Spain
2
Departamento de Física Matemática y de Fluidos, Facultad de Ciencias, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain
3
Civil Engineering School, University of A Coruña, 15008 A Coruña, Spain
4
Botany Department, Higher Politechnic School, GI-1809-BIOAPLIC, University of Santiago de Compostela, 27002 Lugo, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(9), 1514; https://doi.org/10.3390/rs12091514
Received: 7 March 2020 / Revised: 4 May 2020 / Accepted: 5 May 2020 / Published: 9 May 2020
(This article belongs to the Special Issue She Maps)
A multi-sensor and multi-scale monitoring tool for the spatially explicit and periodic monitoring of eutrophication in a small drinking water reservoir is presented. The tool was built with freely available satellite and in situ data combined with Unmanned Aerial Vehicle (UAV)-based technology. The goal is to evaluate the performance of a multi-platform approach for the trophic state monitoring with images obtained with MultiSpectral Sensors on board satellites Sentinel 2 (S2A and S2B), Landsat 8 (L8) and UAV. We assessed the performance of three different sensors (MultiSpectral Instrument (MSI), Operational Land Imager (OLI) and Rededge Micasense) for retrieving the pigment chlorophyll-a (chl-a), as a quantitative descriptor of phytoplankton biomass and trophic level. The study was conducted in a waterbody affected by cyanobacterial blooms, one of the most important eutrophication-derived risks for human health. Different empirical models and band indices were evaluated. Spectral band combinations using red and near-infrared (NIR) bands were the most suitable for retrieving chl-a concentration (especially 2 band algorithm (2BDA), the Surface Algal Bloom Index (SABI) and 3 band algorithm (3BDA)) even though blue and green bands were useful to classify UAV images into two chl-a ranges. The results show a moderately good agreement among the three sensors at different spatial resolutions (10 m., 30 m. and 8 cm.), indicating a high potential for the development of a multi-platform and multi-sensor approach for the eutrophication monitoring of small reservoirs. View Full-Text
Keywords: satellite; water quality; multispectral imagery; UAV; eutrophication; monitoring satellite; water quality; multispectral imagery; UAV; eutrophication; monitoring
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MDPI and ACS Style

Cillero Castro, C.; Domínguez Gómez, J.A.; Delgado Martín, J.; Hinojo Sánchez, B.A.; Cereijo Arango, J.L.; Cheda Tuya, F.A.; Díaz-Varela, R. An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs. Remote Sens. 2020, 12, 1514. https://doi.org/10.3390/rs12091514

AMA Style

Cillero Castro C, Domínguez Gómez JA, Delgado Martín J, Hinojo Sánchez BA, Cereijo Arango JL, Cheda Tuya FA, Díaz-Varela R. An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs. Remote Sensing. 2020; 12(9):1514. https://doi.org/10.3390/rs12091514

Chicago/Turabian Style

Cillero Castro, Carmen, Jose A. Domínguez Gómez, Jordi Delgado Martín, Boris A. Hinojo Sánchez, Jose L. Cereijo Arango, Federico A. Cheda Tuya, and Ramon Díaz-Varela. 2020. "An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs" Remote Sensing 12, no. 9: 1514. https://doi.org/10.3390/rs12091514

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