@article{fdi:010080651,
  title = {{H}indcast and near real-time monitoring of green macroalgae blooms in shallow coral reef lagoons using {S}entinel-2 : a {N}ew-{C}aledonia case study},
  author = {{B}risset, {M}. and {V}an {W}ynsberge, {S}. and {A}ndr{\'e}fou{\¨e}t, {S}erge and {P}ayri, {C}laude and {S}oulard, {B}. and {B}ourassin, {E}. and {L}e {G}endre, {R}. and {C}outures, {E}.},
  editor = {},
  language = {{ENG}},
  abstract = {{D}espite 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. {M}onitoring of small tropical lagoons is challenging because they require high resolutions. {S}ince 2017, the {S}entinel-2 satellites has provided new perspectives, and the feasibility of monitoring green algae blooms was investigated in this study. {I}n the {P}oe-{G}ouaro-{D}eva lagoon, {N}ew {C}aledonia, recent {U}lva blooms are the cause of significant nuisances when beaching. {S}pectral indices using the blue and green spectral bands were confronted with field observations of algal abundances using images concurrent with fieldwork. {D}epending on seabed compositions and types of correction applied to reflectance data, the spectral indices explained between 1 and 64.9% of variance. {T}he models providing the best statistical fit were used to revisit the algal dynamics using {S}entinel-2 data from {J}anuary 2017 to {D}ecember 2019, through two image segmentation approaches: unsupervised and supervised. {T}he latter accurately reproduced the two algal blooms that occurred in the area in 2018. {T}his paper demonstrates that {S}entinel-2 data can be an effective source to hindcast and monitor the dynamics of green algae in shallow lagoons.},
  keywords = {{U}lva ; {S}entinel-2 ; satellite ; remote sensing ; algal bloom ; coral reefs ; {P}acific lagoons ; {PACIFIQUE} ; {NOUVELLE} {CALEDONIE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {13},
  numero = {2},
  pages = {211 [19 ]},
  year = {2021},
  DOI = {10.3390/rs13020211},
  URL = {https://www.documentation.ird.fr/hor/fdi:010080651},
}