Toward a Collaborative Framework: Integrating Remote Sensing Research with Forestry Practice

Abstract. There is an increasing demand for current and comprehensive forest information due to climate change, economic pressures, and sustainable forest management. Current remote sensing technologies and methodological advances in deep learning provide valuable information for forest assessments, but their integration into forestry practices is slow and user expectations are often unmet due to knowledge gaps and misunderstandings. Challenges include technical language and skill barriers, misunderstanding the information content of remote sensing-based forest products, and adapting existing user processes and systems. Thus, efforts, such as expert groups of researchers and practitioners, aiming to bridge this gap by fostering collaboration, are highly needed. These initiatives should focus on a regular knowledge exchange and active participation of practitioners, needs-orientated practical workshops, and iterative development of remote sensing-based forest products incorporating user feedback. Here, using an example of a first initiative on integrating remote sensing research with practice in Switzerland, we show that collaborative efforts improve remote sensing-based forest products and further stimulate the development of user-orientated methods in the forestry sector.