Monthly Publications, February 2026
“Monthly Publications” is a monthly summary by the School of Forest Sciences at the University of Eastern Finland, featuring scientific articles published during the month. This summary aims to make the latest research in forest sciences more accessible to practitioners, such as companies, policymakers, and forest owners, to enable more effective practical application of research findings. Researchers from the School of Forest Sciences at the University of Eastern Finland are highlighted in bold
▪ Kangaslampi, R. and Tikkanen, O. P. (2026). Training and utilizing scent detection dogs in the identification of the European spruce bark
beetle Ips typographus. Silva Fennica vol. 60 no. 1 article id 25022. https://doi.org/10.14214/sf.25022
▪ Keya, S.A., Rohinton, E., Haapala, A., Pakarinen T. and Pykäläinen, J. (2025). Urban morphology-energy consumption nexus: A multi-criteria
weather vulnerability analysis model for city planning. Cleaner and Responsible Consumption, Volume 19.
▪ Kuzmin, A., Korhonen, L., Tanhuanpää, T., Kukkonen, M., Maltamo, M and Kumpula, T. 2026. Classification of Tree Species and Standing
Dead Trees in Boreal Forests Using UAV-Based RGB, Multispectral, and LiDAR point clouds. Remote Sensing in Ecology and Conservation.
▪ Laakkonen, A., Heiskanen, A., Näyhä, A., Toppinen, A. & Hurmekoski, E. 2026. Corporate foresight among small and medium-sized
enterprises in forest-based bioeconomy: Conceptual framework and empirical evidence from Finland. Canadian Journal of Forest Research,
22 January 2026, https://doi.org/10.1139/cjfr-2025-0274
▪ Manna, D., Chowdhury, R., Kuittinen, S., Pappinen, A., Vepsäläinen, J. and Hassan, Md. K. ( 2026).Valorization of rice straw through FeCl3
pretreatment: experiments-modelling and optimization. Biomass Conversion and Biorefinery 16:118. https://doi.org/10.1007/s13399-025-
07011-8
▪ Poorazimy, M., Ronoud, G., Yrttimaa, T., Luoma, V., Bianchi, S., Huuskonen, S., Hyyppä, J., Saarinen, N., Kankare, V., & Vastaranta,
M. (2026). Understanding tree growth dependencies using multisensorial point clouds. European Journal of Forest Research, 145(2), 33.
https://doi.org/10.1007/s10342-026-01875-9
▪ Pulgarin Díaz, J. A. , Melin, M., Mehtätalo, L., Polade, S., Aalto, J., Peltola, H., & Tikkanen, O. P. (2026). Stand, landscape and climatic
attributes contributing to the probability of Ips typographus damage in Finland. Forest Ecology and Management, 603, 123436.
https://doi.org/10.1016/j.foreco.2025.123436
▪ Rusanen K., Hujala T. and Pykäläinen J. (2026). “We are already in the frontline” – Sustainable value creation and entrepreneurial orientation
in forest-based small and medium-sized enterprises. Silva Fennica vol. 60 no. 1 article id 25001. https://doi.org/10.14214/sf.25001
▪ Taher, J., Hyyppä, E., Hyyppä, M., Salolahti, K., Yu, X., Matikainen, L., Kukko, A., Lehtomäki, M., Kaartinen, H., Thurachen, S., Litkey, P., Luoma, V.,
Holopainen, M., Kong, G., Fan, H., Rönnholm, P., Vaaja, M., Polvivaara, A., Junttila, S., Vastaranta, M., Puliti, S., Astrup, R., Kostensalo, J.,
Myllymäki, M., Kulicki, M., Stereńczak, K., de Paula Pires, R., Valbuena, R., Carbonell-Rivera, J.P., Torralba, J., Chen, Y.-C., Winiwarter, L., Hollaus,
M., Mandlburger, G., Takhtkeshha, N., Remondino, F., Lisiewicz, M., Kraszewski, B., Liang, X., Chen, J., Ahokas, E., Karila, K., Vezeteu, E.,
Manninen, P., Näsi, R., Hyyti, H., Pyykkönen, S., Hu, P., & Hyyppä, J. (2026). Multispectral airborne laser scanning for tree species classification:
A benchmark of machine learning and deep learning algorithms. ISPRS Journal of Photogrammetry and Remote Sensing, 233, 278–309.
https://doi.org/10.1016/j.isprsjprs.2026.01.031
▪ Kymäläinen, K., Tuupanen, A., Jaakkola, S. & Kärhä, K. 2026. Females as Forest Machine Operators. Canadian Journal of Forest Research. https://doi.org/10.1139/cjfr-2025-0290
▪ Sagar, A., Pohjala, J., Muhojoki, J., Dhital, A., Kaartinen, H., Kärhä, K., Järvelin, K., Ghabcheloo, R., Hyyppä, J. & Kankare, V. 2026. Utilising Mobile Laser Scanning Point Clouds to Assess Harvesting Quality in Thinning Stands. Science of Remote Sensing 13, 100374. https://doi.org/10.1016/j.srs.2026.100374
