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Artificial Intelligence (AI) for Earth Monitoring

EUMETSAT via FutureLearn

Overview

Learn to use AI and ML to improve the use of big data in Earth Monitoring.

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 AI and ML are transforming the interpretation of EO data.

Understand key AI and ML concepts

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.

Learn Python to fully access the WEkEO platform

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.

Explore EO data with international experts

This course is funded by the Copernicus Programme and has been put together by EUMETSAT, ECMWF, Mercator Ocean International and the EEA.

Their experts in AI, EO, and Earth system monitoring 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 would benefit scientists, policy/decision makers, journalists, educators, business owners, and students. It would also appeal to a curious, general interest audience, or professionals who possess some experience in the subject.

For the hands-on Jupyter Notebook tutorials, you will need to create an account on WEkEO. We recommend you use a computer to access this.

Syllabus

  • Introduction to Copernicus
    • Course Introduction
    • Topic 1a - The Copernicus Programme and the potential of AI
    • Topic 1b - Introduction to the Sentinel Satellites and Contributing Missions
    • Topic 1c - The Role of Copernicus Services and Partners In Managing Big Data
    • Topic 1d - AI and Machine Learning in the Copernicus Programme
    • Topic 1e - Accessing Data and Using The WEkEO Platform
    • Test, Discussion and Feedback
  • AI and Machine Learning with Copernicus Data & Services
    • Week 2 Introduction
    • Topic 2a - Overview of Types of AI
    • Topic 2b - Types of Machine Learning Problem
    • Topic 2c - Understanding Machine Learning Workflows
    • Topic 2d - Common Machine Learning Algorithms
    • Topic 2e - Python Libraries for Machine Learning
    • Topic 2f - Ethical Considerations
    • Topic 2g - Data Fusion with AI
    • Test and Weekly Round-up
  • Monitoring the Land
    • Introduction to Week 3
    • Topic 3a - Introduction To Monitoring The Land
    • Topic 3b - Land Cover Classification
    • Topic 3c - Land Cover Usage Change
    • Topic 3d - AI for Agriculture
    • Topic 3e - Mapping Deforestation In Real Time
    • Topic 3f - Mapping the Extent of Forest Fires
    • Topic 3g - Informal Settlement Mapping
    • Topic 3h - The Ethics of Mapping Poverty
    • Test & Weekly Round-up
  • Monitoring the Oceans
    • Introduction to Week 4
    • Topic 4a - Introduction to Monitoring the Ocean
    • Topic 4b - Tracking Ships
    • Topic 4c - Marine Safety
    • Topic 4d - Monitoring Marine Life
    • Topic 4e - Expanding Our Vision of the Sea Surface
    • Topic 4f - Using ML to Differentiate Between Sediment and Chlorophyll
    • Topic 4g - Using ML To Combine Water Quality Data From Different Satellites
    • Topic 4h – Topic 4h - Marine Analysis for Wider Users
    • Test, Discussion and Feedback
  • Monitoring the Atmosphere
    • Introduction to Week 5
    • Topic 5a - Introduction to Monitoring the Atmosphere
    • Topic 5b - Tracking Air Quality
    • Topic 5c - Methane Retrievals Using Sentinel-5P
    • Topic 5d - Estimating Precipitation
    • Topic 5e - Estimating Emissions During the COVID-19 Pandemic
    • Topic 5f - ML For More Accurate Weather Forecasts.
    • Test & Weekly Round-up
  • Climate Monitoring
    • Introduction to Week 6
    • Topic 6a - Introduction to Climate Monitoring
    • Topic 6b - Mapping Local Climate Zones in Urban Areas
    • Topic 6c - Cloud Classification
    • Topic 6d - Using ML with SAR to monitor changing polar regions & oil spills
    • Topic 6e – Mapping Climate Indicators
    • Topic 6f - How ML Can Speed Up Our Response to Floods & Other Natural Disasters
    • Topic 6g - Neural Networks and In Situ Observations to Improve Weather Forecasting
    • Topic 6h - ML and Ocean Data For Human Health
    • Test, Discussion and Feedback

Taught by

Elena Christodoulou

Reviews

4.5 rating at FutureLearn based on 50 ratings

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