SeaBee is being proven in the field through different applications and subprojects. ZosMap is a SeaBee subproject with focus on developing applications for seagrass mapping and monitoring using drones (Unoccupied Aerial Vehicles, UAVs), high-resolution aerial imaging, and Machine Learning (ML) technology for image analysis and thematic mapping.
The aim is to explore the possibilities of measuring seagrass distribution, biomass, carbon content, and health status using flying drones. Not only are seagrass meadows essential to sustain marine biodiversity and provide nursery grounds for fish, but they also host large amount of organic carbon bound in living biomass and in the sediments below the seagrass meadows.
Mapping seagrass mission
In mid-June, a team of NIVA researchers and drone pilots once again went to map seagrass meadows and explore the amount of organic carbon that is stored in these vital coastal habitats.
The fieldwork is part of an annual monitoring campaign with drone missions flown every month. Five researchers from NIVA participated in this fieldwork. In addition, engineering researchers and two Master students from NTNU are involved in the project work.
A bit outside Larvik, around Ølbergholmen in the Oslofjord, ZosMap has a test ground for developing methods and testing out new hypotheses. Two small bays define the test area that hosts both dense and sparse seagrass meadows, rockweed beds, sandy sediments with microalgae, and a few scattered kelp occurrences.
Over four days in June the team flew multiple drone missions for collecting imaging data covering both a larger overview of the region (at high altitude) and high-resolution images for detailed studies (at low altitude). To assess the meaning of pixel resolution for seagrass and organic carbon mapping drone mission were flown at altitudes from 20 to 100 m.
A DJI Matrice 300 drone was deployed equipped with an RGB camera (SeaBee Tech) and a multispectral spectral (MSI) camera (Micasense Altum). In addition a DJI M600 drone was deployed with a hyperspectral (HSI) sensor (SPECIM AFX-10). The RGB images will be used primarily for image annotation and provide good true color overview image, while MSI and HIS image data will be used for generating thematic vegetation maps and quantifying seagrass biomass, organic carbon content and ecosystem health status.
In addition to drone data collection, the team was busy collecting ground truth data using traditional techniques in order to annotate (categorise) image data and to build a database for training of machine learning algorithms.
The algorithms will in turn be able to identify seagrass and other coastal vegetated habitats automatically from drone data, in the same way as a smart phone identifies the face of its owner.
In June we found the seagrass meadows of the Larvik region to be both well developed, in good ecological condition and rich in organic carbon hosted in its dense seagrass canopies – Kasper Hancke, NIVA
Importance for seagrass meadows
Seagrass meadows in the Oslofjord are often under strong pressure from anthropogenic stressors, so it was great to experience healthy and live seagrass meadows in these areas. These areas are not only a SeaBee/ZosMap test ground, but are also a well-visited recreational area for beach drifters, picnic groups, kayakers and many others.
Next steps are to analyse the images further in the SeaBee data pipeline. The results will be published when the data and laboratory samples have been processed.
For more information on how SeaBee works with coastal habitat mapping, visit ‘What We Do’