Urchin Colony Mapping Using AI

Study Area

The Godbout area, located in Quebec, Canada, is of significant biological interest due to its diverse ecosystems and unique flora and fauna. The area's pristine natural habitats provide important breeding grounds for birds, serve as a crucial corridor for wildlife migration, and support diverse aquatic ecosystems in its rivers and coastal waters. The Godbout area is also a key site for studying the impacts of climate change on northern ecosystems.

Key Statistics

Leveraging AI Tools

Once trained, the AI can detect urchins faster than the human eye and alleviate issues due to contrast, illumination and turbidity.

Total Running Time

Spatial Distribution

The spatial distribution of detected urchins’ positions and sizes can be readily exported as a SHP file for further analysis. Each dot represents an urchin over the seafloor’s orthomosaic.

These standardized data products can be imported into GIS software for further analysis.

Specimen Size

The AI can estimate specimen size and generate value-added data for the area of study. According to DFO guidelines, only specimens over 50mm are commercially viable.

Identifying commercially viable specimens

The algorithms yields significant value by quickly identifying commercially viable specimens automatically and extracting their distribution patterns.

This allows for drastic efficiency improvements by reducing the area to prospect specimens over 50mm.

Identifying key recruitment zones for sustainability

Identifying key recruitment areas ensures that young specimens are spared and that marine resource exploitation is compatible with sustainable development objectives.

Juvenile specimens under 30mm can be readily identified by the algorithms.

Maximizing profit while minimizing damage to the environment

Using the informations from our model, we can determine an optimal exploitation zone that directly targets commercially viable specimens while systematically avoiding immature urchins.