William Lidberg

My research focuses on improving the planning of infrastructure and forest management. Challenges such as undersized road culverts, forestry-related driving damage, and inadequate protection zones can often be prevented if we understand in advance where water is located in the landscape and how it moves through the ground. By combining my interests in geographic information systems (GIS), machine learning, and the unique access I have to nationwide maps of Sweden, I can explore new methods on a large scale. This allows me to be creative, test innovative approaches, and contribute to more sustainable land and water management.

One of the biggest issues with water quality in Sweden is that no one knows where it is. Small streams are missing from our maps which makes it difficult to plan any kind of activities around them. This is especially problematic in forestry where heavy machines operate near wet and sensitive soils. My research uses high resolution digital elevation models to model shallow groundwater flow paths and small streams. The outcome is a detailed wet area map that can be used to plan forestry operations. Buffer zones and driving can be planned in order to minimize damage and rutting to sensitive soils.

I am the course responsible and teacher for the master’s-level course Analysis of Environmental Data 2. In this course, I integrate machine learning, deep learning, and geospatial data (such as LiDAR and satellite imagery) to tackle real-world environmental challenges. The course equips students with the skills to manage and analyze large, complex datasets, and to apply spatial data for evaluating forestland and environmental conditions effectively.

Ph.D., Soil Science, 2019, Swedish University of Agricultural Science, Umeå, Sweden

I am an applied scientist driven to make research impactful and relevant beyond academia. My work bridges science and practice through extensive collaboration with government agencies, forest companies, and other stakeholders. A cornerstone of this engagement is my long-standing partnership with the Swedish Forest Agency, which has co-funded some of my research since 2020. Together, we have translated research into operational tools such as the SLU Soil Moisture Map, SLU Ditch Map, Hunting Pit Map, and AI-based tools for detecting road culverts, now widely used across Sweden to improve forestry, water management, and wetland restoration.

My research has also supported national authorities such as SMHI and the Swedish Transport Administration, shaping new watershed maps and flood risk prediction tools for critical infrastructure. Most recently, I am leading research with several national agencies to develop a new, unified stream network for Sweden, which will strengthen hydrological planning and ecosystem restoration. For this work, I received the Collaboration with Society Award from the Forest Faculty at SLU.