Beach wrack monitoring using image dataset with artificial intelligence

As part of production exported from Blue Carbon ecosystems (BCEs), detached macrophytes are washed up onshore and deposited as beach wrack. In addition to providing habitat and food for coastal fauna, beach wrack is considered as one of the largest parts of carbon exported from BCEs, serving a significant role in carbon cycle of BCEs. However, beach wrack becomes a source of greenhouse gas emission during decomposition and is a
nuisance for local residence. Hence, exploring the fate of beach wrack is essential for quantifying its ecological value. Compared to the investigation of carbon burial in BCEs, it remains a challenge to track this exported part. Due to limited time- and spatial- resolutions, satellite image acquired by traditional monitoring method of satellite remote sensing (RS) can neither meet the requirement for flexible data collection, nor can it capture detailed information of land objects at beach-scale. Therefore, this thesis firstly explored the potential of Unmanned Aerial Vehicles (UAVs) and camera trap to investigate the deposition pattern of beach wrack (Manuscript 1 and 2). The capabilities of machine learning (ML) to classify aerial images (overall classification accuracy > 75 %, Manuscript 1) and deep learning (DL) to efficiently identify beach wrack from various beach scenes captured in camera images (accuracy > 60 %, 187 images analyzed in 5 minutes, Manuscript 2) indicated that with
application of artificial intelligence (AI) in analyzing image dataset, UAVs and camera trap can be developed into practical tools for beach wrack monitoring as well as for coastal environmental management. Furthermore, the in-situ decomposition experiment showed that mass loss and change of total phosphorus (P) of beach wrack were significantly affected by
wrack species and deposition scenario (Manuscript 3). In future work, biomass information of beach wrack can be collected with more functional sensors mounted on UAVs and camera trap. By combining beach wrack biomass with its deposition and decomposition patterns, the contribution of beach wrack to carbon and nutrient cycles in coastal systems can be estimated.