ARCTUS offers products and services designed to meet the observation needs of users and managers. These products and services are aimed at managers of public services (government), non-profit organizations and private companies concerned with environmental protection. In addition, highly specialized algorithms, such as atmospheric corrections (GAAC), may also be of interest to the academic research community specializing in remote sensing of aquatic environments. Our team also has expertise in hydrodynamic modeling, which can meet specific coastal management needs.


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Notre soutien. Votre réussite.

Aquatic environments are dynamic, and their spatial and temporal variability increases as they approach the coast. Thanks to R&D funding, ARCTUS has developed satellite data processing chains to generate near-real-time variables used as proxies for water quality, such as turbidity and chlorophyll-a concentration (linked to algal production and eutrophication). The processing chains are based on the latest algorithm developments published in the scientific literature. We exploit free multispectral satellite data provided by Earth observation programs (e.g. Copernicus, NOAA, NASA/USGS). Our processing chains can also ingest higher-resolution satellite data sold by private suppliers (e.g. Planet Lab, Airbus, Maxar). Thanks to a collaboration with Cartovista, our products are distributed to end-users via a web platform designed for non-specialists in remote sensing or geomatics. Users can consult, analyze and explore satellite products online in an interactive way, thanks to numerous tools developed by CartoVista.

Click on the button below to access the coastal monitoring platform (an account is required) or fill in the registration form below to create an account (please allow up to 48 working hours).


L’innovation technologique au service de la connaissance

Navigation close to the coast can be risky if the presence of shoals has not been adequately mapped, or if the coast has undergone rapid geomorphological modification after the passage of a storm. However, a large proportion of the Quebec and Canadian coasts, particularly in the Arctic, have still not been mapped for bathymetry, i.e. the depth of water on nautical charts, which is usually measured by acoustic echo sounders. In addition to navigation needs, bathymetry is a fundamental variable for coastal wave modelling and coastal ecosystem management.

Bathymetric measurements in shallow coastal waters (< 10 m) are difficult to obtain by boat using traditional methods, and many coastal regions are difficult to access. The advent of constellations of Earth observation satellites equipped with optical sensors has made it possible to develop increasingly efficient algorithms for extracting water height over large areas, at relatively low cost compared with other methods. This is known as satellite-derived bathymetry, or SDB.

However, SDB estimation is complex due to the ambiguity and complexity of the optical signal measured by satellites above the Earth’s atmosphere. At ARCTUS, we have developed numerical methods based on artificial intelligence (AI) to solve a number of problems related to SDB. Our R&D projects have enabled us to develop a suite of algorithms, which we have named AI4SDB, enabling us to offer a highly customized service for the production of satellite bathymetry data.


Observer. Surveiller. Gérer. Protéger.

The concentration of pigments (chlorophyll-a) in phytoplankton can be estimated using space-based sensors based on OCR (Ocean Colour Radiometry Technology). OCR is currently the only means of obtaining near-daily synoptic maps of the biological state of the ocean and coastal zones. Other water quality parameters can also be assessed from OCR if appropriate data processing methods are used. Suspended solids (SS), dissolved and detrital organic matter (CDOM), turbidity and water transparency are other examples of water quality indicators accessible from space. Thanks to its collaboration with ACRI-st, a sister company in France, ARCTUS offers operational services (multi-sensor fusion) for real-time monitoring of bio-optical variables on the ocean surface. In particular, these data can be used to model dynamic ocean habitats and applied in the context of aquaculture management, fisheries and even marine mammals (SIMBA).


Mieux connaitre nos écosystèmes pour les aimer et les protéger

ARCTUS offers a coastal ecosystem mapping service tailored to users’ needs. In collaboration with specialists from the Université du Québec à Rimouski, ARCTUS uses machine learning-based classification methods to classify multispectral images. The team’s knowledge of coastal ecosystems along Canada’s coastline facilitates the interpretation and validation of classifications. We are working to develop a classification of sub-littoral ecosystems, made possible by the development of the GAAC and AI4SDB products.