The Big Earth Data Project
A suite of hands-on activities to engage and inspire students to look at current environmental challenges faced today, funded by the UK Space Agency.
Helping introduce young people to the many applications of satellite data
MEI has developed resources to help your students develop skills in exploring large Earth observation datasets while teaching them about the measurements satellites can take.
These resources will help students learn about satellite modelling and forecasting. Focused on engaging contexts such as climate change, the effects of humans on Earth, and emergency disaster response.
Three sets of resources will be released throughout the 2024/25 academic year. Each set will have activities designed for Key Stage 3-4 and A-Level students, using Data Science skills to analyse real satellite data. The best part is that all resources will be free for anyone to access.
Set 1 Atmosphere: The Hole in the Ozone Layer
Overview and Teacher Note
The atmosphere introduction pack will introduce the data set and some Ozone facts.
Download Overview and Teacher Notes PDF
Resource 1: Averages and single variable diagrams
Lesson one will look at seasonal variations in different measurements of the Southern Ozone Hole, using averages, histograms, and box plots.
Resource 2: Time series
Lesson two will examine how the Southern Ozone Hole has varied over time, using time series and averages.
Resource 3: Scatter graphs and correlation
Lesson three will explore the correlation between different measurements related to the Southern Ozone Hole using scatter graphs, measures of outliers and correlation.
Download Lesson Three Worksheet
We value your feedback, if you would like to fill in a feedback form after using the resources it would be much appreciated.
Overview and Teacher Note:
Download Overview and Teacher Notes PDF
Resource 1: Diagrams for single variable data
Lesson one examines seasonal variations in different measurements of Southern Ozone Hole, using averages, histograms, box plots, cumulative frequency curves and frequency polygons.
Resource 2: Exploring outliers
Lesson two uses monthly data to explore how the Southern Ozone Hole has varied over time. Students will explore outliers and how we can use other data to decide if they are valid data points or errors.
Resource 3: Identifying regions in scatter plots
Lesson three will look at bivariate data by comparing the size of the Southern Ozone Hole with other measurements from ground and satellite data. Using scatter graphs, regression lines and correlation coefficients.
Additional resource: Introduction to using Python for data
The additional resource is an introduction to using Python for data. It introduces the data set and some Ozone facts as well as showing how to us Python Notebook to calculate averages and measures of spread.
We value your feedback, if you would like to fill in a feedback form after using the resources it would be much appreciated.
Link to careers
Whilst using these resources in your classroom, you may wish to link the maths students are learning with careers. In the video below Mark, who works for CAMS/ECMWF, explains how a strong foundation in maths has been fundamental to the work he does forecasting atmospheric pollution and discusses the current analysis of the southern ozone hole.
Set 2
Coming Spring 2025
Set 3
Coming Spring 2025
More about the motivations behind this project
Our key motivations for creating these resources are:
- For students to recognise maths as a fundamental tool for tackling environmental issues and its societal benefits.
- To link careers with mathematical skills and learning.
- To create resources that take aspects of the key stage 3-5 curriculum and present them in an interesting and fun way.
More about where the data has come from
All activities in the Big Earth Data Project use data analysis and data science to answer pertinent questions about Earth Observation. All the activities for the Big Earth Data Project will use real data from Copernicus (European Earth Observation space programme), The European Centre for Medium-range Weather Forecasting (CAMS/ECMWF), LandSat (NASA Earth Observation Satellites), and other relevant data sources, including models built from data measured by these satellite programmes.