AI for Earth Monitoring

This course, produced by Imperative space, is currently hosted on FutureLearn you can access the course using the 'Take this course’ button below.

This is a fast-changing and critical time for Earth Observation (EO), especially for those involved in its use for climate and meteorology. On this course, you’ll get a comprehensive overview of the Copernicus Programme and the wealth of EO data it provides, as well as how Artificial Intelligence (AI) and Machine Learning (ML) are transforming the interpretation of EO data.

You’ll learn about the Copernicus data and services and the massive amounts of Earth observation data that are collected every day from space, covering the oceans, land, atmosphere and, over longer periods, the climate.

You’ll then learn basic AI and ML concepts and types, exploring how they have transformed many aspects of the EO ‘value chain’.

This includes automatic feature extraction, new ways of processing very large data sets, and the development of new products and services.

The WEkEO platform is a ‘one-stop shop’ for Copernicus and Sentinel satellite data and services.

You’ll learn how to access Earth Observation data through it, using the Python programming language and Jupyter Notebooks to process and analyse EO data with AI.

This course is funded by the Copernicus programme and produced by Imperative Space with support from EUMETSAT, ECMWF, Mercator Ocean International and the EEA.

Their experts in AI, EO, and Earth system monitoring, along with others from ESA and leading environmental data organisations across Europe, will take you through four themed weeks – land, ocean, atmosphere, and climate – leaving you well-versed in the intricacies of EO and satellite data, as well as how AI and ML can unlock its full potential.

This course is presented by Dallas Campbell.

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