Work

Floating kelp forest mapping using spaceborne Synthetic Aperture Radar on the British Columbia coast

Year: 2026

Type: article

Abstract: The Pacific coast of Canada is widely populated by bull kelp ( Nereocystis sp. ) and giant kelp ( Macrocystis sp. ), which create unique habitats that provide refugia and foraging opportunities for animals of all trophic levels. A recent decline in kelp forests has sparked concerns about the kelp populations' stability and the need for monitoring. Generally, optical spaceborne imagery is used to monitor kelp, but its application is limited by clouds. This study aimed to assess the correspondence between floating kelp extent determined using Synthetic Aperture RADAR (SAR) and that typically obtained using optical imagery. We evaluated three machine learning models: CATBoost, LightGBM, and XGBoost. The classification framework was based on annual changes in surface backscattering, since we observed elevated values from kelp in summertime, distinct from the surrounding waters. The XGBoost performed the best among the evaluated models, yielding a balanced accuracy of 0.76 compared with kelp extent derived from optical imagery. Our findings also revealed that data from July to September was best for mapping floating kelp using remote sensing since kelp remains consistently on the surface. This study proposes a new approach that allows observations regardless of cloud cover and captures changes in kelp forests throughout the year. This new capability opens many avenues for further research and provides new insights into the seasonal variability of the floating kelp canopy, often driven by responses to marine stressors, thus allowing managers to assess disturbance response.

Source: Ecological Informatics

DOI: 10.1016/j.ecoinf.2026.104027