NASA Space Apps - Harmful Algae Bloom

HABIT: Detecting Harmful Algae Blooms before they happen.

I participated in the NASA Space Apps 2020, where the challenge was to identify and shape a solution for sustainable applications using NASA, ESA, JAXA, CNES, or CSA Earth Observation datasets, products, or resources. I lead the team comprising a biologist, a designer, a satellite expert, an IT developer and a creative technologist. Together we proposed solution that provides access to Harmful Algae Bloom early warnings and predictive models so they can be acted upon in time. 


 Earth Observation via Satellite provides early detection of massive-scale areas, which combined with data captured from local coastal communities and research institutes, can in turn refine and build into the model. Our solution works on early detection and prevention based on HAB markers and provides early access to the relevant authorities and organizations, but also to coastal businesses in order to save money, time, ecology and improve the environmental quality to encourage biodiversity.

Addressing the challenge

Current solutions detect the algae blooms too late. Measures are taken when the problem has already caused damages, leading to the death of fish and other wildlife. Our proposed detection system uses predictive monitoring to identify where algae blooms might could occur based on observed environmental conditions and AI-powered learning.

We use Sentinel I to train the AI engine with historic HAB markers (Algae cover, Temperature, Nitrogen content, Turbidity and Water movement) on high definition satellite imagery/data to create a correlation model of these markers. Sentinel II uses this first trigger to capture high-definition imagery and data, to confirm and send warnings so action can be taken. A typical action is to add nitrogen-eating bacteria to the water, to reduce the conditions for HABs to happen.

After detection we monitor the impact of the treatment to control the HAB and assess its effectiveness, to correlate treatment measures and type of algae (and conditions) to propose more effective solutions in the future.


To find a business case, we initially looked at tracking animal behaviour as a marker for cataclysms. We noticed an exception in which a cataclysm that animals cannot foresee is toxic algae, which causes whale embankments and is responsible for the death of seals, fish, shellfish and countless marine life. Looking at the economic impacts we saw it affects tourism, fishing, recreation and a many other activities that lead to extensive money loss.
After analyzing the pictures that satellites took of the algae, we realised that getting an overview of the conditions that cause algae could provide with a predictive analysis of HAB occurrence in a given area, to prevent it.
A brief situation analysis revealed the sectors which would benefit from having access to this information, and companies like Bgtechs that can provide HAB management solutions. To improve pre-existing methods we also will track the effectiveness of the cure and correlate it the condition and the 300 species of HAB .

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