Our consortium’s work continues!
With 3.5 years of work now behind us, our contribution to Europe’s forest monitoring agenda is a measurable reality. We look back with pride at the 2025 year where ambition met action across every corner of our consortium.
Nine times last year, PathFinder research partners contributed new knowledge to the scientific record. Across all of them, researchers tackled some of the most pressing methodological and applied challenges in European forest science. Several contributions advanced the way we map and validate forest attributes at scale, including the development of high-resolution pan-European forest structure maps integrating Earth observation and National Forest Inventory data. Others pushed the boundaries of statistical rigour, exploring uncertainty quantification and small area estimation techniques that make forest monitoring more reliable and reproducible.
The question of biodiversity was central to two publications, which examined how forest biodiversity indicators can be better harmonized and assessed across different inventory plot designs. Meanwhile, the human dimension of forest management was not overlooked, with research dedicated to mapping management regimes across Europe and identifying the megatrends that will shape European forests in the decades to come. Finally, innovation in field monitoring took centre stage witha deep learning approach for estimating species coverage from ground-level imagery, a glimpse of what the next generation of forest observation tools may look like.
Together, these papers reflect the breadth and ambition of what PathFinder set out to do: produce science that is not only rigorous, but genuinely useful for the future of European forest monitoring.
Click the doi links below to explore their latest publications:
Kangas, A., Myllymäki, M., & Packalen, P. (2025). Small area estimators in a simulation test. Canadian Journal of Forest Research, 55, 1–17. https://doi.org/10.1139/cjfr-2024-0070
Koma, Z., & Breidenbach, J. (2025). Large-scale validation of forest attribute maps across different spatial resolutions. Zenodo. https://doi.org/10.5281/zenodo.14626363
Kuronen, M., Räty, J., Packalen, P., & Myllymäki, M. (2025). Uncertainty quantification for forest attribute maps with conformal prediction and k-nearest neighbor method. Remote Sensing of Environment, 325, 114758. ISSN 0034-4257. https://doi.org/10.1016/j.rse.2025.114758
Langenbacher, J., Levering, A., & Verburg, P. H. (2025). Mapping megatrends shaping European forests. Sustainability Science, 21, 21–38. https://doi.org/10.1007/s11625-025-01747-y
Miettinen, J., Breidenbach, J., Adame, P., Adolt, R., Alberdi, I., Antropov, O., Astrup, R., Berger, A., Chirici, G., Corona, P., D’Amico, G., Fejfar, J., Fischer, C., Gohon, F., Gschwantner, T., Hertzler, J., Koma, Z., Korhonen, K. T., Krajnc, L., … Wurpillot, S. (2025). PathFinder’s High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data. Zenodo. https://doi.org/10.5281/zenodo.17107267
Moreno-Fernández, D., Breidenbach, J., Cañellas, I., Chirici, G., D’Amico, G., Ferretti, M., Giannetti, F., Puliti, S., Schnell, S., Shackleton, R., Skudnik, M., & Alberdi, I. (2025). Enhancing forest biodiversity indicators in inventories through harmonized protocols. iForest, 18, 109–120. https://doi.org/10.3832/ifor4778-018
Moreno-Fernández, D., Oliveira, N., Myllymäki, M., Cañellas, I., Kuronen, M., & Alberdi, I. (2025). Evaluation of the performance of forest structural indices under different National Forest Inventory plot designs. Ecological Indicators, 181, 114434. ISSN 1470-160X. https://doi.org/10.1016/j.ecolind.2025.114434
Müller, P., Puliti, S., & Breidenbach, J. (2025). Towards enhancing field-based vegetation monitoring: A deep learning approach for species coverage estimation from ground-level imagery. Methods in Ecology and Evolution, 16, 949–957. https://doi.org/10.1111/2041-210X.70024
Scherpenhuijzen, N., West, T. A. P., Debonne, N., Oostdijk, S., Adame, P., Astrup, R., & Verburg, P. H. (2025). Mapping forest management regimes in Europe. Forest Ecology and Management, 594, 122940. ISSN 0378-1127. https://doi.org/10.1016/j.foreco.2025.122940