APPLICATION OF THE GCOM-C ALGORITHM FOR ESTIMATION OF CHLOROPHYLL CONCENTRATION ON THE BEACHES OF THE NORTH OF FLORIANÓPOLIS ISLAND

Authors

DOI:

https://doi.org/10.21575/25254782rmetg2025vol10n42462

Keywords:

Google Earth Engine, Chlorophyll-a, Computational Modeling, Bathing, Water Quality

Abstract

The bathing water quality of beaches in major coastal cities has been a persistent challenge in Brazil and worldwide. Monitoring and analyzing the environmental variables that influence water quality involves slow, costly, and logistically complex processes. This study aimed to estimate Chlorophyll-a concentrations at nine points along the northern beaches of Florianópolis Island between 2018 and 2025, using chlorophyll dissolved in water as an indicator of bathing water quality. The algorithms GCOM-C/L3/OCEAN/CHLA/V2 and GCOM-C/L3/OCEAN/CHLA/V2V3, based on satellite sensor data, were applied through the Google Earth Engine (GEE) platform using data from the Global Change Observation Mission – Climate (GCOM-C). Results indicate that chlorophyll peaks coincide with periods of higher population density and with viral outbreak events recorded in the northern region of Santa Catarina Island. The findings highlight the deficiencies in sewage and urban drainage systems, as well as the sensitivity of local water bodies, which often reflect the irregular discharge of domestic sewage into drainage channels and rivers. These factors are critical for municipal management to address in maintaining safe bathing conditions. Over the past two years, a reduction in chlorophyll peaks was observed at Ingleses, Santinho, and Canasvieiras beaches, where sewage treatment systems were expanded and domestic networks were regularized. Although the satellite product showed limitations in spatial resolution, the approach proved to be a viable medium- and long-term tool for monitoring bathing areas on a regional and even national scale.

Author Biographies

  • Bento Almeida Gonzaga, Federal University of Rio Grande

    He holds an M.Sc. in Coastal Management (2020), postgraduate specializations in Project Management (2017) and Mechatronic Systems (2016), and a degree in Industrial Automation Technology (SENAI, 2014). His experience includes electronics, automation, embedded systems, and microcontroller programming. He has taught technical courses and serves as a volunteer researcher at IFRS and IFSC, developing low-cost sensors for environmental and agricultural monitoring. He also works with digital image processing and risk mapping for flood-prone urban areas.

  • Dinalva Aires de Sales, Federal University of Rio Grande

    She holds a Bachelor’s degree in Mathematics and an M.Sc. in Physics and Astronomy (Univap), and earned her Ph.D. in Physics from UFRGS. She was a NASA Postdoctoral Fellow at the Rochester Institute of Technology and a DOCFIX postdoctoral researcher (FAPERGS/CAPES). Since 2019, she has been a CNPq Productivity Fellow (Level 2). An Assistant Professor at IMEF-FURG, she is a faculty member of the Graduate Programs in Physics and Computational Modeling, having also held several leadership roles, including Director of Research at PROPESP-FURG (2025). She coordinates PDI projects at iTec/FURG–EMBRAPII and works transdisciplinarily in AstroBioGeoChemistry, with expertise in signal processing and modeling, astrophysics, astrochemistry, remote sensing, and quantum computing. She received the 2020 Carolina Nemes Award from the Brazilian Physical Society.

  • Jean Marcel Espinoza, IFSC Campus Garopaba

    He holds a Ph.D. and M.Sc. in Remote Sensing (UFRGS) and bachelor’s degrees in Physics and Medical Physics (FURG). His work focuses on remote sensing applied to glaciological studies, digital image and signal processing, and reflectance radiometry, with emphasis on radar. He is a member of research groups in Geotechnologies and Environment (IFRS), Coastal Environmental Management (FURG), and Remote Sensing (UFRGS). He is currently a faculty member at IFSC – Garopaba Campus, teaching Physics and Environmental Management.

  • Isadora Bicho Emmendorfer, Federal University of Rio Grande

    She holds a Bachelor's and a Master's degree in Oceanology from FURG and a technical degree in Geoprocessing (IFRS). He is currently a Ph.D. candidate in Computational Modeling, a member of the AstroESUL project, and a Licentiate student in Biological Sciences. His work focuses on geoprocessing and remote sensing applied to water resources and coastal geomorphology, including shoreline evolution analysis and coastal flood mapping.

  • Victor Huggo Lessa Rosolem, Federal University of Rio Grande

    He holds an M.Sc. in Computational Modeling and a Bachelor’s degree in Physics with an emphasis on Oceans (FURG). His experience includes work in Physics and Physical Oceanography, focusing on the cryosphere, glacier dynamics, climate change, remote sensing, and environmental modeling.

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Published

2025-12-15

Issue

Section

Edição Especial do XII ERMAC RS