CONFIRM – Copernicus Data for Novel High-Resolution Wildfire Danger Services in Mountain Regions

Wildfires are becoming an increasing threat to human health, infrastructure, forestry, agriculture and biodiversity. In Alpine regions, fires are often at the start of cascading risks including avalanches, mudslides or rock fall due to the loss of forest and vegetation layers. Additionally, wildfires are expected to occur more frequently in the future as a result of a warming climate, which is estimated to affect alpine regions in particular.

Fire danger forecasts, such as the commonly used Fire Weather indices, indicate the danger of forest fires based on numerical weather forecasts. Such indices are typically available at coarse spatial resolutions and, hence, have limited use in mountainous regions with their highly variable weather and other environmental conditions. Stakeholders, such as fire departments and forest managers, require more detailed forecasts in order to make robust decisions and efficiently plan their resources. The CONFIRM project, which started in December 2019 with funding from the Austrian Research Promotion Agency (FFG) under the Austrian Space Applications Programme (ASAP), addresses this gap by using high-resolution earth observation data provided by the European Copernicus programme to develop a pre-operational fire danger forecast system.

Data from both optical and microwave sensors aboard satellites are known to be sensitive to changes in soil and vegetation water content. Exploiting this sensitivity, satellite data with high temporal and spatial resolutions from the Copernicus Sentinel-1 and Sentinel-2 missions will be used to estimate fuel moisture state. The estimates will be integrated with airborne Laser-scanning (LiDAR) data, high-resolution weather forecasts, socioeconomic and topographic data to develop a novel, high-resolution integrated forest fire danger system (IFDS) for Austria. The project team will apply its expertise in forest management, remote sensing, fire science and machine learning to estimate fire danger using the Austrian fire database, an extensive record of historic fire events, as a training dataset. Key stakeholders from national weather services (ZAMG, DWD), fire brigades, state forest administrations and infrastructure providers (Austrian Railways ÖBB) are continuously involved in the project to develop the IFDS according to their requirements. They will evaluate the prototype of the system during the fire season of 2021.