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Investigación de vangarda para o desenvolvemento sostible

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Investigación de vangarda para o desenvolvemento sostible

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2020

Cillero-Castro, Carmen; Domínguez-Gómez, Jose Antonio; Delgado-Martín, Jordi; Hinojo-Sánchez, Boris Alejandro; Cereijo-Arango, José Luis; Tuya, Federico Andrés Cheda; Díaz-Varela, Ramon

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

In: Remote Sensing, vol. 12, no. 9, pp. 1514, 2020, ISSN: 2072-4292.

Abstract | Links | BibTeX | Etiquetas: eutrophication, Monitoring, multispectral imagery, satellite, UAV, Water quality

@article{cillero_castro_uav_2020,

title = {An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs},

author = {Carmen Cillero-Castro and Jose Antonio Domínguez-Gómez and Jordi Delgado-Martín and Boris Alejandro Hinojo-Sánchez and José Luis Cereijo-Arango and Federico Andrés Cheda Tuya and Ramon Díaz-Varela},

url = {https://www.mdpi.com/2072-4292/12/9/1514},

doi = {10.3390/rs12091514},

issn = {2072-4292},

year  = {2020},

date = {2020-01-01},

urldate = {2026-08-06},

journal = {Remote Sensing},

volume = {12},

number = {9},

pages = {1514},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {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.},

keywords = {eutrophication, Monitoring, multispectral imagery, satellite, UAV, Water quality},

pubstate = {published},

tppubtype = {article}

}