Photo by Kushagra Kevat on Unsplash

The UK Hydrographic Office Data Science team research and develop machine learning for coastal and marine habitat mapping from satellite imagery. We mostly work with European Space Agency Sentinel-2 Level-1C satellite data, which is downloaded as radiometrically and geometrically corrected top-of-atmosphere (TOA) imagery.

TOA imagery has some issues:

  • a certain ‘haziness’ is mostly caused by molecular and aerosol scattering in the atmosphere, meaning that TOA imagery contains a lot of Remote Sensing Reflectances (Rrs) values incorporating the atmosphere rather than solely land or water surface Rrs.
  • the ‘adjacency effect’: when high radiance values from one pixel are incorporated into another…

On Wednesday 29th to Friday 31st May 2019 I attended the ITU, XPRIZE and ACM organised AI for Good Global Summit . The goals of the AI for Good Global Summit are to connect AI innovators with problem owners, to identify practical applications of AI to accelerate progress toward the UN Sustainable Development Goals, and to ensure trusted, safe and inclusive development of AI technologies and equitable access to their benefits.

UN Sustainable Development Goals to meet by 2030

The Summit held 5 action-oriented breakthrough sessions designed to generate AI for Good projects; AI Education and Learning, Good Health and Wellbeing, AI for Human Dignity and Inclusive Societies…

Rachel Keay

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