This week, from 16 to 20 September in Louvain-la-Neuve, nearly 100 carefully selected researchers participate in the ‘Advanced Training in Land Remote Sensing’, a training in the exploitation of satellite data acquired by remote sensing. Commissioned by the European Space Agency (ESA), Pierre Defourny, a professor in the Faculty of Bioengineering and head of the Environment and Geomatics Laboratory of the Earth and Life Institute, is ready.
Flashback: In 2014, European Space Agency (ESA) launched a fleet of European satellites as part of the Copernicus programme. Previously named Global Monitoring for Environment and Security (GMES), the programme, which dates back to the 1990s, is an initiative of the European Union (EU) supported by ESA and the European Environment Agency (EEA). It aims to provide Europe with an operational and autonomous Earth observation capacity as a service in the general European interest, with free, universal and total access to its data. In other words, Copernicus must be able to gather all the data obtained from environmental satellites and ground-based measuring instruments in order to generate a public global and comprehensive view of the state of our planet.
Earth observation satellites
Specifically, the satellites launched in 2014 were Sentinel-1A, on Soyuz, and Sentinel-2A and Sentinel-3A, on Rockot. For five years, they have harvested an unprecedented volume of data that has made Europe the world leader in Earth observation for civilian purposes.
Since 2014, the UCLouvain Environment and Geomatics Laboratory has conducted research projects on behalf of ESA to exploit data from this fleet of European satellites. Composed of about 20 researchers working in the field, the lab focuses on satellite monitoring of agricultural production. Leading them is Pierre Defourny, a professor at the Earth and Life Institute, head of the laboratory, and member of the Faculty of Bioengineering. ‘Our laboratory is a pioneer in Sentinel satellite data research’, he says. ‘As leaders of an international consortium, Sen2Agri, we have developed a completely open source satellite image processing system, allowing for the exploitation of images in real time almost automatically at country level.’
Prof. Defourny continued, ‘In view of what Sentinel-2A was doing, the European Commission's Directorate-General for Agriculture wanted a study to be carried out in the framework of the future reform of the Common Agricultural Policy. Our laboratory has been tasked with coordinating the international Sen4CAP consortium to develop methods that make the best use of Sentinel data. These methods, which we are continuing to develop, are being demonstrated in real time in eight European countries: Italy, Romania, Lithuania, the Netherlands, France, Spain, Slovenia and Luxembourg.’
Dual relevance: geomatics and bioengineering
No wonder, then, that the ESA commissioned Prof. Defourny to organise the intensive training course on satellite data exploitation, from 16 to 20 September at UCLouvain. PhD students, postdocs, specialists and experts from international agencies have responded to ESA's call for applications. Applicants were required to submit a poster that presented their work. A poster presentation session will be held on 17 September at UCLouvain, at the SUD 01 Croix du sud auditorium, so that students and visitors can get to know the selected participants, who hail from 34 countries.
Among them are experts from the Food and Agriculture Organization (FAO), the World Food Programme, the Mexico-based International Maize and Wheat Improvement Center, the Mahalanobis National Crop Forecast Centre in New Delhi, and CABI-Oxford in charge of phytosanitary issues – all interested in the operational nature of new big data methods from space. American, Indian, Moroccan and Chinese researchers specialising in monitoring agricultural production or the quality of the environment in their country will work alongside specialists from regional centres such as the Tunis-based Sahara and Sahel Observatory, ICIMOD in Kathmandu, and IGAD in Nairobi.
‘Of the 200 applications we received, 92 were selected to participate in the training’, Prof. Defourny says. Their motivation? ‘Being introduced to new methods of interpreting electromagnetic radiation measured by the satellites. All methods are aimed at making better use of data that’s now available for free online but very complex to analyse.’
Four of the five days feature eight hours of training, from 8:30 am to 5:30 pm. ‘The morning will be devoted to theory and the afternoon to practice in the computer lab’, Prof. Defourny says. ‘If weather permits, we’ll take measurements in a neighbouring field with a drone and see what the satellite tells us about it.’ The principle is to put the morning’s theory into practice in the afternoon. ‘We also invite Dutch, Italian and French professors, at the forefront of their field, to join the team of trainers coordinated by Sophie Bontemps and myself.’ A visit to Louvain-la-Neuve’s Aerospacelab start-up will complete the programme.
One day will be devoted to pre-processing data, which makes it possible to eliminate atmospheric disturbances and to calibrate the recorded signal as a physical quantity. This will allow for comparing data from one satellite to that of another, but also to work over time despite the variability of incident light. Another session will be devoted to how to invert the satellite signal to estimate biophysical variables. ‘The signal recorded in orbit teaches us something about radiation and therefore plant function’, Prof. Defourny explains. ‘From these data, we can translate the radiation into quantities that describe the plant: amount of green matter, water content, leaf area, nitrogen content ... biophysical variables that can be measured in the field, henceforth observable at Earth scale.’
How will these experts use the data?
These future experts in the use of Sentinel data will be able to apply them to a wide range of research and uses: estimate a country’s seasonal agricultural production, determine the quality of nitrogen fertilisation, detect water stress ... these are things that have been talked about for 40 years but that we can now do scientifically, in real time, on the scale of an entire country.
Are we approaching ‘farming 2.0’?
But farming 2.0 isn’t the future, it's the present! We’re already doing a lot of things technologically in our farms. At the last agricultural fair in Libramont, one booth was a great success: the BelCAM project (Belgian Collaborative Agriculture Monitoring), a platform where all Belgian farmers can consult the ‘satellite radiography’ of their fields. The farming world loved it: the project, which we coordinated for more than four years, brought us into dialogue with farmers. This collaboration allows us to respond directly to questions and demand, shortening the link between research and its application. This is what motivates researchers the most: working on concrete cases, being in the real world.
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A glance at Pierre Defourny'bio
Pierre Defourny has been a full professor at UCLouvain since 1993. Head of the Environment and Geomatics Laboratory, he is also the founder of the Earth and Life Institute (ELI), which he chaired from 2010 to 2015 and heads the Environmetrics and Geomatics Laboratory (UCLouvain/ELI-Geomatics), which focuses on local and global-scale remote-sensing terrestrial surface-monitoring, as well as geographic information systems land-use modelling to support agriculture, forestry and land-use planning. Between 1991 and 1993, he conducted his first research at the Asian Institute of Technology (UNEP-GRID), in Thailand. Between 2004 and 2005 he was visiting researcher at the NASA Goddard Space Flight Center in the United States. In 2016, he conducted research in Mexico City at the International Corn and Wheat Improvement Center (CGIAR-CIMMYT). He is the scientific leader of the eBELCAM and Sen2-Agri projects, and of the ‘earth surface’ component of the European Space Agency’s 2010 Climate Change Initiative to improve global climate model simulations. His research is leading to the development of operational methods for extracting statistical information from global time series, including crop monitoring and land-use changes in the context of climate change.