25.03.2024
A study published in Ecological Research by the Leibniz Centre for Agricultural Landscape Research (ZALF) in collaboration with the Brandenburg University of Technology Cottbus-Senftenberg sheds light on how artificial intelligence and machine learning could revolutionize ecological research. The study analyzed 1,550 articles.
An outstanding aspect of the study is the comparison of the development and application of artificial intelligence (AI) and machine learning (ML) in environmental research in Asia with countries such as the US, France, Australia, the UK, and Germany. Asia leads the world in the application of AI and ML to environmental research, driven by China and Korea. However, the analysis also reveals a clear difference between the continents in terms of research focus. Asian countries focus more on applied ecology, including environmental engineering and management, underscoring their focus on practical solutions to environmental challenges. In contrast, non-Asian countries, mainly Western industrialized nations, place more emphasis on theoretical understanding and technological development.
The study shows that AI and ML have helped to significantly improve data processing, analysis, and pattern recognition in ecological research overall. "In Asia, the focus of research has shifted in recent years from a predominantly technical perspective to applied issues such as biodiversity conservation, climate change, land use change and societal impacts," explains the study's author, Prof. Masahiro Ryo, head of the Artificial Intelligence Working Group at ZALF. This shift reflects the environmental challenges faced by Asian countries due to rapid economic growth, land development, and the effects of climate change. China takes a leading role in applying AI and ML to ecological research, followed by Korea, Japan, India, and Iran. The study emphasizes that a nationwide strategic approach to promoting computer science education, as seen in China, is crucial for the progress of AI-based environmental research.
The results underscore the need for globally coordinated efforts in ecological research to improve both the theoretical foundations and applied methods for solving pressing global environmental problems.
"By learning from each other and sharing technologies across geographic and disciplinary boundaries, we can develop more effective strategies to protect our global biodiversity and ecosystems," concludes Ryo.
Further information:
