4.7 Article

Automatic Detection of Floating Macroalgae via Adaptive Thresholding Using Sentinel-2 Satellite Data with 10 m Spatial Resolution

Journal

REMOTE SENSING
Volume 15, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/rs15082039

Keywords

adaptive thresholding method; floating algae area estimation; Otsu's method; satellite remote sensing; Sentinel-2 satellite

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Extensive floating macroalgae from the East China Sea have drifted to Japan's offshore area, and field observation is not sufficient to track their spatial and temporal changes. High-spatial-resolution satellite data with multiple spectral bands have improved remote sensing analysis. This study proposes an adaptive thresholding method using Sentinel-2 satellite data to detect floating macroalgae. By comparing different methods, the most advantageous approach for automatic detection of floating macroalgae using NDVI, NDWI, and FAI images is determined. The spatial coverage and reproducible combination for automatic detection of floating macroalgae in Kagoshima, Japan are examined.
Extensive floating macroalgae have drifted from the East China Sea to Japan's offshore area, and field observation cannot sufficiently grasp their extensive spatial and temporal changes. High-spatial-resolution satellite data, which contain multiple spectral bands, have advanced remote sensing analysis. Several indexes for recognizing vegetation in satellite images, namely, the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and floating algae index (FAI), are useful for detecting floating macroalgae. Thresholds are defined to separate macroalgae-containing image pixels from other pixels, and adaptive thresholding increases the reliability of image segmentation. This study proposes adaptive thresholding using Sentinel-2 satellite data with a 10 m spatial resolution. We compare the abilities of Otsu's, exclusion, and standard deviation methods to define the floating macroalgae detection thresholds of NDVI, NDWI, and FAI images. This comparison determines the most advantageous method for the automatic detection of floating macroalgae. Finally, the spatial coverage of floating macroalgae and the reproducible combination needed for the automatic detection of floating macroalgae in Kagoshima, Japan, are examined.

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