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

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