Peer-review publications 


Noordermeer, L., Økseter, R., Ørka, H.O., Gobakken, T., Næsset, E., Bollandsås, O.M., 2019. Classifications of Forest Change by Using Bitemporal Airborne Laser Scanner Data. Remote Sensing 11, 2145.


Banja, M., Sikkema, R., Jégard, M., Motola, V., Dallemand, J.-F., 2019. Biomass for energy in the EU – The support framework. Energy Policy 131, 215–228.

Blujdea, V., Marin, G., 2018. Obligații asumate și contribuția sectorului forestier la îndeplinirea țintelor de reducerea emisiilor de gaze cu efect de seră ale României (Obligations assumed and contribution of the forestry sector to Romania’s greenhouse gas reduction targets). Bucovina Forestiera 18, 23.

Dutcă, I., 2018. Biomass data for young, planted Norway spruce (Picea abies (L.) Karst.) trees in Eastern Carpathians of Romania. Data Brief 19, 2384–2392.

Dutca, I., Mather, R., Viorel, B., Ioras, F., Abrudan, I.V., 2018. Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.). Biomass and Bioenergy 116, 8–17.

Dutcă, I., Stăncioiu, P.T., Abrudan, I.V., Ioraș, F., 2018. Using clustered data to develop biomass allometric models: The consequences of ignoring the clustered data structure. PLoS One 13, e0200123.

Flinkman, M., Sikkema, R., Spelter, H., Jonsson, R.K.H., 2018. Exploring the drivers of demand for non-industrial wood pellets for heating (European bioenergy markets). Baltic Forestry 24, 86–98.

Jonsson, R., Blujdea, V.N., Fiorese, G., Pilli, R., Rinaldi, F., Baranzelli, C., Camia, A., 2018. Outlook of the European forest-based sector: forest growth, harvest demand, wood-product markets, and forest carbon dynamics implications. iForest 11, 315–328.

Nabuurs, G.-J., Arets, E.J.M.M., Schelhaas, M.-J., 2018. Understanding the implications of the EU-LULUCF regulation for the wood supply from EU forests to the EU. Carbon Balance Manag. 13, 18.

Nguyen, H.H., Erfanifard, Y., Petritan, I.C., 2018a. Nearest Neighborhood Characteristics of a Tropical Mixed Broadleaved Forest Stand. Forest 9, 33.

Nguyen, H.H., Erfanifard, Y., Pham, V.D., Le, X.T., Bui, T. D., Petritan, I.C., 2018b. Spatial Association and Diversity of Dominant Tree Species in Tropical Rainforest, Vietnam. Forest 9, 615.

Nguyen, H.H., Petritan, I.C., Burslem, D.F.R.P., 2018c. High frequency of positive interspecific interactions revealed by individual species–area relationships for tree species in a tropical evergreen forest. Plant Ecol. Divers. 11, 441–450.

Pilli, R., Kull, S.J., Blujdea, V.N.B., Grassi, G., 2018. The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3): customization of the Archive Index Database for European Union countries. Ann. For. Sci. 75, 71.

Saarela, S., Holm, S., Healey, S.P., Andersen, H.-E., Petersson, H., Prentius, W., Patterson, P.L., Næsset, E., Gregoire, T.G., Ståhl, G., 2018. Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data. Remote Sensing 10, 1832.


Dutcă, I., Mather, R., Ioraş, F., 2017. Tree biomass allometry during the early growth of Norway spruce (Picea abies) varies between pure stands and mixtures with European beech (Fagus sylvatica). Can. J. For. Res. 48, 77–84.

Saarela, S., Andersen, H.-E., Grafström, A., Schnell, S., Gobakken, T., Næsset, E., Nelson, R.F., McRoberts, R.E., Gregoire, T.G., Ståhl, G., 2017a. A new prediction-based variance estimator for two-stage model-assisted surveys of forest resources. Remote Sens. Environ. 192, 1–11.

Saarela, S., Breidenbach, J., Raumonen, P., Grafström, A., Ståhl, G., Ducey, M.J., Astrup, R., 2017b. Kriging prediction of stand-level forest information using mobile laser scanning data adjusted for nondetection. Can. J. For. Res. 47, 1257–1265.