Automated analysis of drone data
- Department BAMJO
- Fields involved Earth observation, Climate and Environment
- Industries involved Ocean, Climate and environment, Technology and industry
SeaBee is a Norwegian infrastructure project for drone-based research services for coastal and aquatic studies. It facilitates research, mapping and monitoring of habitats, animal communities and human-made impacts in these environments.
AI-based tools for easy and reliable analysis
The project aims to streamline data collection and analysis using aerial drones. Automating these processes will ensure cost-effective, high-quality data management, and offer a cutting-edge tool to address ongoing environmental challenges.
SeaBee provides:
- drones, equipment, and personnel for data collection,
- AI-based tools that enable easy and reliable image analysis,
- cloud-based storage and visualisation tools for easy access and inspection of drone images and analysis products.
Object detection and thematic mapping
SeaBee supports all kinds of image data, including multi-spectral, hyper-spectral and colour images (RGB). NR heads the development of AI algorithms, specifically deep learning, that enables automatic analysis of the data.
Our AI pipeline supports two main tasks: object detection and pixel-wise thematic mapping. Using advanced deep learning algorithms, the framework can be adapted to solve specific tasks, offering a large degree of flexibility with accurate results. Typical outputs include maps of marine habitats in coastal areas and automated recognition of marine mammals and sea birds.
Project: SeaBee – Norwegian Infrastructure for drone-based research, mapping and monitoring in the coastal zone
Partners: The Norwegian Institute for Water Research (NIVA), the Norwegian University of Science and Technology (NTNU), the Norwegian Institute for Nature Research (NINA), the Institute of Marine Research (IMR) and GRID-Arendal
Funding: The Research Council of Norway
Period: 2020-2024
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