Hindcast and Near Real-Time Monitoring of Green Macroalgae Blooms in Shallow Coral Reef Lagoons Using Sentinel-2: A New-Caledonia Case Study

Type Article
Date 2021-01
Language English
Author(s) Brisset Maele1, Van Wynsberge Simon1, Andréfouët SergeORCID2, Payri Claude2, Soulard BenoitORCID1, Bourassin EmmanuelORCID1, Le Gendre RomainORCID1, Coutures Emmanuel3
Affiliation(s) 1 : Institut Français de Recherche pour l’Exploitation de la Mer, UMR 9220 ENTROPIE (Institut de Recherche pour le Développement, Université de la Réunion, IFREMER, Université de la Nouvelle-Calédonie, Centre National de la Recherche Scientifique), Nouméa 98800, New Caledonia
2 : Institut de Recherche pour le Développement, UMR 9220 ENTROPIE (Institut de Recherche pour le Développement, Université de la Réunion, IFREMER, Université de la Nouvelle-Calédonie, Centre National de la Recherche Scientifique), BP A5, Nouméa CEDEX 98848, New Caledonia
3 : Direction du Développement Durable des Territoires, Province Sud, Nouméa 98849, New Caledonia
Source Remote Sensing (2072-4292) (MDPI AG), 2021-01 , Vol. 13 , N. 2 , P. 211 (19p.)
DOI 10.3390/rs13020211
WOS© Times Cited 4
Note This article belongs to the Special Issue Remote Sensing of the Aquatic Environment
Keyword(s) Ulva, Sentinel-2, satellite, remote sensing, algal bloom, coral reefs, Pacific lagoons
Abstract

Despite the necessary trade-offs between spatial and temporal resolution, remote sensing is an effective approach to monitor macroalgae blooms, understand their origins and anticipate their developments. Monitoring of small tropical lagoons is challenging because they require high resolutions. Since 2017, the Sentinel-2 satellites has provided new perspectives, and the feasibility of monitoring green algae blooms was investigated in this study. In the Poé-Gouaro-Déva lagoon, New Caledonia, recent Ulva blooms are the cause of significant nuisances when beaching. Spectral indices using the blue and green spectral bands were confronted with field observations of algal abundances using images concurrent with fieldwork. Depending on seabed compositions and types of correction applied to reflectance data, the spectral indices explained between 1 and 64.9% of variance. The models providing the best statistical fit were used to revisit the algal dynamics using Sentinel-2 data from January 2017 to December 2019, through two image segmentation approaches: unsupervised and supervised. The latter accurately reproduced the two algal blooms that occurred in the area in 2018. This paper demonstrates that Sentinel-2 data can be an effective source to hindcast and monitor the dynamics of green algae in shallow lagoons

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How to cite 

Brisset Maele, Van Wynsberge Simon, Andréfouët Serge, Payri Claude, Soulard Benoit, Bourassin Emmanuel, Le Gendre Romain, Coutures Emmanuel (2021). Hindcast and Near Real-Time Monitoring of Green Macroalgae Blooms in Shallow Coral Reef Lagoons Using Sentinel-2: A New-Caledonia Case Study. Remote Sensing, 13(2), 211 (19p.). Publisher's official version : https://doi.org/10.3390/rs13020211 , Open Access version : https://archimer.ifremer.fr/doc/00668/77968/