Project description
Saving forests to protect people and planet
Our survival depends on the health of our forests. They play a significant role in fighting climate change (absorbing and storing CO2 from the atmosphere). However, the survival of our forests hinges on how we tackle threats like insect outbreaks, fires, windthrow and droughts. And climate change is behind it all – causing insects to breed more and providing more dry fuel for wildfires. In this context, the EU-funded SWIFTT project will provide a scientifically sound and technically feasible way to help monitor and manage forest risks. It will enable forest managers to adapt to climate change with affordable, simple and effective remote sensing tools backed up by machine learning models. This solution will be tested in real conditions.
Objective
Forests are essential to life on Earth. They proForests are essential to life on Earth. They provide habitats for thousands of creatures and combat climate change through carbon sequestration. However, our forests are threatened by insect outbreaks, fires, windthrow and droughts. Notably, insect outbreaks are one of the leading causes of forest loss globally, destroying 85M ha of forest worth €15B annually. At the same time, wildfires destroy 400M ha annually on a global scale, according to the European Space Agency. The wind is also a significant forest disturbance agent in the temperate forests of France, Germany, and most of Europe.
Climate change affects forests, causing insects to breed more frequently. It also provides more dry fuel for global wildfires. The dry conditions increase the length of the fire season and the size of areas affected by the fire. In addition, both the frequency and the severity of large storms causing windthrow can be attributed to climate change. As a result, countless habitats are lost, and CO2 sequestered yearly decreases by over 4850M tons.
Our solution, SWIFTT, will provide a scientifically sound and technically feasible way to help monitor and manage forest risks: windthrow, insect outbreaks, and forest fires. SWIFTT will enable forest managers to adapt to climate change with affordable, simple and effective remote sensing tools backed up by powerful machine learning models. Our solution will offer a monthly health monitoring service using Copernicus satellite imagery to detect and map the various risks to which forests and their managers are exposed. Early threat detection aids timely intervention. SWIFTT will be tested in real conditions by several end-users from the forest industry, which include Fürstliches Forstamt, Groupe Coopération Forestière and the Rigas Mezia. We anticipate monitoring and protecting up to 40M ha of global forests by 2030, saving foresters over €468M in monitoring costs and creating over 50 direct jobs.
Fields of science
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- agricultural sciencesagriculture, forestry, and fisheriesforestrysilviculture
- natural sciencesbiological scienceszoologyentomology
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
Topic(s)
Funding Scheme
IA - Innovation actionCoordinator
75015 Paris
France
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.