How to combine socio-economic indicators into one impact metric across European regions?

 

The COVID19 pandemic strongly affected economy and society across Europe, with an impact varying over time and by country, depending on structure of the economy and regional characteristics.

This challenge looks at the socio-economic sector, with a particular focus on production, trade and transport. The goal is to develop an integrated indicator (also known as composite indicator) to unravel territorial differences in the impact of the pandemic across Europe.

 

 

The RACE dashboard currently already provides a range of economic indicators on how the pandemic impacted economic sectors, such as transport, commodity imports/exports or inventory levels at production sites.

Here are some relevant examples based on Sentinel-1 and Sentinel-2 that you can explore on race.esa.int:

• and driving trucks indicators that characterises the logistic sector;
• parked airplanes and flying airplanes indicators that characterise the aviation sector.

Additional indicators (or “proxies”) may be derived directly from the available EO and additional data, but you may bring your own data as well.

Some interesting additional data to consider (and some hints):

• You may want to build a new indicator that refers to a specific economic sector. The Open Street Map API or the Copernicus Land Monitoring Service Corine Land Cover+ dataset may be used to select representative areas-of-interest (AOIs) for an economic sector in a country, for example, the 25 largest commercial retail parking lots in Poland.
• Mobility data from Google and the GSA are available on race.esa.int and can be integrated to provide a complementary perspective on social mobility.
• Many other datasets exist that could be integrated into your analysis (e.g. population density).
• You may want to combine your proxies in a meaningful way, to define an integrated indicator. A simple way to do this is by using a weighted average of different indicators/proxies. Have a look at the Example below.
• Your final aim is to demonstrate how the socio-economic system is/has been affected over the course of the pandemic (and potentially prior to that).
• You may also reuse and integrate the existing indicators (see tutorial notebooks available in the Euro Data Cube, showing you how to access and use these datasets).

 

Challenge objectives

Everyone is invited to propose and develop an integrated socio-economic indicator (based on several sub-indicators/proxies) that characterises the pandemic’s impact on socio-economic activity in a region/country at a point in time by use of EO-based and interdisciplinary data available in the RACE dashboard and the Euro Data Cube.

The indicator shall be developed for each country/region, using a representative set of AOIs for the different economic components.

 

Keep in mind that within the RACE initiative, we primarily focus on Europe and the relevant impacts of the pandemic on the European environment, economy and society.

 

Example

A participant develops:

• Three proxies/sub-indicators: (1) S1 SAR backscatter over commercial retail parking lots, (2) Thermal infrared monthly averages based on Landsat-8 over heavy industry sites and (3) Nightlights monthly averages over healthcare facilities.
• Creates AOI sets for France (using the OSM overpass API*): (1) 20 largest commercial retail parking lots, (2) 20 largest heavy industry production sites, (3) 20 largest healthcare facilities.
• Calculates the proxies for the 18 administrative regions in France from June 2019 to March 2021.
• Creates a weighted average of the sub-indicator/proxies, resulting in a (fused) time series of the integrated socio-economic indicator for the regions in France.

Your idea may be of lower or higher complexity than this example. That’s fine too!

[* Note that the Corine Land Cover dataset also allows delineating e.g. industrial estates]

 

Available input datasets

Here follows a list of key datasets available in the RACE dashboard and the Euro Data Cube environment:

1. Sentinel-1/2/3/5P and all data available from the Euro Data Cube

e.g. Sentinel-1 SAR backscatter variations might be used as a proxy for the volume of cars in parking lots; Sentinel-2 smoke plumes or thermal infrared heat signatures over industrial assets could be a proxy for industrial production activities.)

2. Existing economic indicators in RACE (accessible via EDC GeoDB)

• • Shipping vessels in harbours
  • Driving trucks
  • Flying and parked airplanes
  • Finished and intermediate goods inventory levels.

3. GSA border crossing mobility and Google mobility data
4. Copernicus Land Monitoring Service Corine Land Cover + (CLC+) 2018
5. Population density data
6. Your own data is welcome! (as long as you have the rights to use it)

We encourage you to think of good ways to make use of the interdisciplinary data in the RACE dashboard and the Euro Data Cube environment: be innovative and creative, of course always keeping scientific integrity in mind!

 

Sample questions that might be addressed

Questions relevant in this context that your analysis could address:

• • 1. Which additional proxies for economic activity proxies could be calculated from EO data, consistently over different EU member states?
    2. How can I define and prepare, for each country/region, a representative set of areas-of-interest (AOIs) for different segments of the socio-economic system starting from available datasets?
    3. What’s the most effective approach to combine all component indicators into a single integrated one? What justifies using such approach?

 

How to participate

You may find a detailed overview of the RACE dashboard challenges 2021 and instructions on how to participate in the announcement.

This explains also the evaluation criteria that we will follow during the review of your contribution.

For this first stage of the challenge, the Euro Data Cube provides you kindly with a tailored trial account, this will allow you to:

• • 1. Host and preconfigure Juypter notebooks for interactive development of your contribution to this challenge
    2. Access the relevant EO and non EO datasets currently in the RACE dashboard
    3. Access existing indicators in the RACE dashboard via the Euro Data Cube GeoDB
    4. Access tutorial notebooks and help articles of how to best make use of the Euro Data Cube technologies in an effective way

Sign-up for the challenge on this page. After signing-up you will receive an email from Euro Data Cube with tailored instructions.

For any query, please refer to the following e-mail addresses:

• • • all technical issues – racecontest@eurodatacube.com
    • more general questions – eodash@esa.int

 

Don’t forget that

This second challenge will stay open for six weeks and close on 14/05/2021 at midnight CET.

By then you are expected to submit within the Euro Data Cube environment your results which should include:

• • 1. Juypter notebook with your prototype analysis, executable within Euro Data Cube. This should contain the analysis workflow and required functionality but should also provide some visualisation of derived results and some description and explanations of what you are doing in the overall workflow;
    2. Presentation with a summary of your results, addressing the following sections: Background, Objective, Approach, Methods, Implementation and Results;
    3. One page proposal for your upscaling plans: explain to us how would upscale your analysis for Stage 2 of this challenge to a European coverage and expanded time frame, to allow for continent scale impact assessment.

Please also send an email with links to the result documentation to: racecontest@eurodatacube.com