Saarela, S., Holm, S., Healey, S.P., Patterson, P.L., Yang, Z., Andersen, H.E., Dubayah, R.O., Qi, W., Duncanson, L.I., Armston, J.D., Gobakken, T., Næsset, E., Ekström, M. & Ståhl, G. (2022). Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation. Remote Sensing of Environment 278, 113074. DOI

Saarela, S. , Wästlund, A., Holmström, E., Mensah, AA, Holm, S., Nilsson, M., Fridman, J. & Ståhl, G. (2020). Mapping aboveground biomass and its uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors. Forest Ecosystems , 7(43), 1-17. DOI

Saarela, S. , Holm, S., Healey, SP, Andersen, H.-E., Petersson, H., Prentius, W., Patterson, PL, Næsset, E., Gregoire, TG & Ståhl, G. ( 2018). Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data. Remote Sensing , 10(11), 1832.  DOI

Saarela, S. , Breidenbach, J., Raumonen, P., Grafström, A., Ståhl, G., Ducey, MJ & Astrup, R. (2017). Kriging prediction of stand level forest information using mobile laser scanning data adjusted for non-detection. Canadian Journal of Forest Research 47,  1257-1265. DOI

Saarela, S. , Andersen, H.-E., Grafström, A., Schnell, S., Gobakken, T., Næsset, E., Nelson, RF, McRoberts, RE, Gregoire, TG & Ståhl, G. ( 2017). A new prediction-based variance estimator for two-stage model-assisted surveys of forest resources. Remote Sensing of Environment 192,  1-11. DOI

Saarela, S. , Holm, S., Grafström, A., Schnell, S., Næsset, E., Gregoire, TG, Nelson, RF & Ståhl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73(4),  895-910. DOI

Saarela, S. , Schnell, S., Tuominen, S., Balazs, A., Hyyppä, J., Grafström, A. & Ståhl, G. (2016). Effects of positional errors in model-assisted and model-based estimation of growing stock volume. Remote Sensing of Environment, 172,  101-108. DOI

Saarela, S. , Schnell, S., Grafström, A., Tuominen, S., Nordkvist, K., Hyyppä, J., Kangas, A. & Ståhl, G. (2015). Effects of sample size and model form on the accuracy of model-based estimators of growing stock volume in Kuortane, Finland. Canadian Journal of Forest Research, 45,  1524–1534. DOI 

Saarela, S. , Grafström, A., Ståhl, G., Kangas, A., Holopainen, M., Tuominen, S., Nordkvist, K. & Hyyppä, J. (2015). Model-assisted estimation of growing stock volume using different combinations of LiDAR and Landsat data as auxiliary information. Remote Sensing of Environment, 158,  431-440. DOI