Empowering a wave of technological change to support
cleanup organizations and save our oceans.
REVOLUTIONISE CLEANUPS Developing state-of-the-art technology, including ocean currents models, machine learning, and remote sensing, we provide accessible open-source technology for coastal cleanup NGOs to use their resources effectively. Through partnering, we offer them the essential technological tool to find optimal cleanup locations which maximises cost-effectiveness and impact.
CHANGE MINDSETS Sharing this same technology with the public to further understanding, we incentivize collective action and combat the public's mistrust through algorithmic and scientific transparency.
If you are a cleanup organization, contact us for support!
Splastic predicts the movement of ocean pollution patches by running ocean currents models, informing NGOs where most pollutants originate from.
By running our ocean model backwards in time, we locate
coastal areas where the most trash comes from, maximizing the
impact of cleanup efforts.
At the moment, we feed in many randomized pollution patch locations to the model. We hope to use SeaVision for getting this info!
We work independently with NGOs to inform them their best plan of action, but you can try out our visualization platform! Based around South-East China's coast, you can see where pollution patches originate or end up!
SeaVision applies machine learning to remotely-sensed high-resolution marine satellite images, locating marine plastic pollution patches.
We aim to map areas of polluted coasts to show the scale of
To feed the most accurate marine pollution location data into Splastic, we need to first know where the pollution patches currently are!
Due to the limited number of real-time satellite images we can purchase, we are unable to display the data.