HABTRAIL is a deep learning model developed specifically to tackle harmful algal blooms (HABs) on a large scale in ocean and coastal areas at a lower cost compared to conventional in-situ methods. It comprises two data services. The first is capable of detecting and monitoring the expansion of HABs with water quality pigments derived from Sentinel-2/-3 as an alert system. The second data service, which is made available through a mobile app, can identify HABs in near-real or real time by uploading a “suspicious picture” of a body of water. Since HABs severely impact aquaculture, fisheries, and tourism, they constitute a significant threat to public health. The HABTRAIL mobile app therefore provides the public with a free tool for quickly detecting HABs with high accuracy before engaging in any marine activity.


“Habtrail has been selected the winner of the Portugal Space Atlantic Challenge because it is an idea that aims to tackle a very complex and pressing problem of our society using advanced Machine Learning technologies applied on both Satellite Imagery and in-situ data. The team behind the idea has expertise in all relevant domains ranging from the technical and scientific side to business. Furthermore, the idea of trying to detect HABs is very relevant to many Atlantic regions and has great potential to scale up as more sensors become available in the future to be able to monitor different species in different areas across the globe.”
Joan Alabart, Industrial Relations & Projects Officer, Portugal Space




Eyecon Group
Miguel Correia, Issah Suleiman, Ana Martins,
João Gonçalves