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University of Bayreuth, Presse release No. 025/2023 - 14 March 2023

Fighting forest fires with artificial intelligence: New research project with the University of Bayreuth

Artificial intelligence should soon make it possible to detect forest fire hazards earlier than before and to fight forest fires more effectively. This is the goal of the joint project "AI-based Forest Monitoring - Artificial Intelligence for Early Detection of Forest Fire Events (KIWA)", in which the University of Bayreuth is participating with its research competencies in biogeography and disturbance ecology. The German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) is funding the project for the next two years with a volume of around 1.8 million euros.

The KIWA joint project aims to use the latest technologies such as artificial intelligence, drones and decision support systems in combination so that potential forest fire risks can be identified and preventive measures can be taken at an early stage. Up-to-date situation assessments and forecasts will enable fire departments and civil protection to plan operations more quickly and effectively in the event of a fire. In this way, the project results will help to relieve society of the high costs incurred each year by forest fires. At the same time, KIWA pursues a climate-political goal: The prevention or rapid suppression of forest fires helps to preserve the function of the forest as a CO₂ reservoir and to reduce the emission of fire-related CO₂ emissions.

Pine forests on the Canary Island of La Palma have been severely damaged by forest fires in recent years and have partially regenerated.

In pine forests on La Palma, the Corazoncillo de La Palma (Lotus hillebrandii), a shrub plant with yellow flowers, is widespread.

On the part of the University of Bayreuth, Prof. Dr. Carl Beierkuhnlein and Prof. Dr. Anke Jentsch will contribute their expertise in the fields of biogeography and disturbance ecology to the project. This ensures that the application-related work is based on the latest knowledge of the relevant ecological, climatic and agroforestry contexts. In the process, proven scientific measurement and evaluation methods must be optimally adapted to the specific tasks in the field of forest fire prevention and control. "Central to our work will be the acquisition and analysis of image data so that areas at risk from forest and wildland fires can be identified and monitored. Drones – we refer to them in research as Unmanned Aerial Systems – and satellites will collect remote sensing data and support the mapping efforts," says Beierkuhnlein, adding: "It is already clear that the patterns of forest and wildland fires that have been common to date will change significantly under the influence of climate change, making conventional risk assessment methods less effective in the future. This makes it all the more important to make an increased use of the latest digital technologies in this area as well."

Artificial intelligence will play an important role in analyzing the data transmitted by drones and satellites: It will identify patterns and trends that indicate a fire risk or a possible fire event. The data, which is analyzed in real time, will be forwarded directly to all institutions responsible for preventing or fighting fires, such as local fire departments and disaster task forces. They are also linked to current weather and climate data so that the respective situation can be correctly assessed and counteraction can be taken. Modern decision support systems are to be used here, which can accelerate the necessary risk assessments and the identification of effective measures.

Together with the University of Bayreuth, the following institutions are involved in the KIWA project: [ui!] Urban Mobility Innovations in cooperation with Quantum-Systems GmbH, the Technical University of Deggendorf and the State Fire Brigade School Würzburg as an associated partner. The consortium leader is Urban Mobility Innovations (B2M Software GmbH). "This unusual alliance combines all the competencies that must work together in an ambitious project like KIWA: Expertise in data analysis, artificial intelligence and data platforms, technical and economic expertise in the development of unmanned high-tech aerial systems, practical experience in preventing and fighting forest and wildfires, and scientific expertise regarding the relevant findings from basic or applied research in each case," says Beierkuhnlein.

Background:
Recent studies estimate that forest fires are responsible for about five to ten percent of global CO₂ emissions and accelerate climate change. The World Meteorological Organization (WMO) reported at the World Economic Forum 2023 in Davos that the average annual global cost of forest fires has risen sharply in recent years and exceeds $50 billion by now. It also noted that more than 6,400 megatons of CO₂ were released into the atmosphere from wildfires in 2021 alone, and that a huge increase in extreme fires worldwide is expected by 2050.

Prof. Dr. Carl Beierkuhnlein

Prof. Dr. Carl Beierkuhnlein

Chair of Biogeography
University of Bayreuth

Phone: +49 (0)921 / 55-2270
E-mail: carl.beierkuhnlein@uni-bayreuth.de

Prof. Dr. Anke Jentsch.

Prof. Dr. Anke Jentsch

Disturbance Ecology and Vegetation Dynamics
University of Bayreuth

Phone: +49 (0)921 / 55-2290
E-mail: anke.jentsch@uni-bayreuth.de

Christian Wißler, Wissenschaftskommunikation

Christian Wißler

Deputy Press & PR Manager, Research Communication
University of Bayreuth

Phone: +49 (0)921 / 55-5356
E-mail: christian.wissler@uni-bayreuth.de