Abstract
Turbid coastal plumes carry sediments, nutrients, and pollutants. Satellite remote sensing is an effective tool for studying water quality parameters in these turbid plumes while covering a wide range of hydrological and meteorological
conditions. However, determining boundaries of turbid coastal plumes poses a
challenge. Traditionally, thresholds are the approach of choice for plume
detection as they are simple to implement and offer fast processing (especially
important for large datasets). However, thresholds are site-specific and need to
be re-adjusted for different datasets or when meteorological and
hydrodynamical conditions differ. This study compares state-of-the-art
threshold approaches with a novel algorithm (PLUMES) for detecting turbid
coastal plumes from satellite remote sensing, tested for Patos Lagoon, Brazil.
PLUMES is a semi-supervised, and spatially explicit algorithm, and does not
assume a unique plume boundary. Results show that the thresholds and PLUMES
approach each provide advantages and limitations. Compared with thresholds,
the PLUMES algorithm can differentiate both low or high turbidity plumes from
the ambient background waters and limits detection of coastal resuspension
while automatically retrieving metrics of detected plumes (e.g., area, mean
intensity, core location). The study highlights the potential of the PLUMES
algorithm for detecting turbid coastal plumes from satellite remote sensing
products, which can have significantly positive implications for coastal management. However, PLUMES, despite its demonstrated effectiveness in this
study, has not yet been applied to other study sites.
conditions. However, determining boundaries of turbid coastal plumes poses a
challenge. Traditionally, thresholds are the approach of choice for plume
detection as they are simple to implement and offer fast processing (especially
important for large datasets). However, thresholds are site-specific and need to
be re-adjusted for different datasets or when meteorological and
hydrodynamical conditions differ. This study compares state-of-the-art
threshold approaches with a novel algorithm (PLUMES) for detecting turbid
coastal plumes from satellite remote sensing, tested for Patos Lagoon, Brazil.
PLUMES is a semi-supervised, and spatially explicit algorithm, and does not
assume a unique plume boundary. Results show that the thresholds and PLUMES
approach each provide advantages and limitations. Compared with thresholds,
the PLUMES algorithm can differentiate both low or high turbidity plumes from
the ambient background waters and limits detection of coastal resuspension
while automatically retrieving metrics of detected plumes (e.g., area, mean
intensity, core location). The study highlights the potential of the PLUMES
algorithm for detecting turbid coastal plumes from satellite remote sensing
products, which can have significantly positive implications for coastal management. However, PLUMES, despite its demonstrated effectiveness in this
study, has not yet been applied to other study sites.
Original language | English |
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Article number | 1215327 |
Pages (from-to) | 1-18 |
Number of pages | 18 |
Journal | Frontiers in Marine Science |
Volume | 10 |
DOIs | |
Publication status | Published - 17 Jul 2023 |
Keywords
- ITC-GOLD
- ITC-ISI-JOURNAL-ARTICLE