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Applied Statistics in Forestry and Environmental Sciences

Homepage of Lauri Mehtätalo





Curriculum vitae




My research interests


Mixed-effects models

MIxed-effects models are a natural way to model such grouped data sets where the goups are a sample from a larger sample of groups. The modeling framework provides a convenient framework both for inference and prediction using such data. About 50% of my publications apply mixed-effects models in various fields, including forest mensuration, ecology, remote sensing, and game research. The models include linear mixed-effects models with various kind of grouping structures, nonlinear mixed-effects models, generalized linear mixed-effects models and systems of mixed-effects models.

Remote sensing

My earlier research and PhD was about modelling forest stand structure, and especially tree size (=diameter distribution) and basic allometric relationships among trees of a stand (H-D curve). Together with some additional models (that for spatial pattern of tree locations and allometric relationships between tree size and crown properties), they essentially define probabilistic properties of a three-dimensional object called forest stand. In remote sensing, we are taking either two or three-dimensional observations from this object. Remote sensing takes observations from a realization of such model, and aerial forest inventory tries to infer forest parameters from such data.

Forest biometrics

The traditional topics in forest biometrics are models for site and stocking, modelling of tree and stand growth, modelling ingrowth and mortality, allometric relationships of trees, taper curves and volume models, and diameter distributions. I have conducted and I am currently conducting some research on these topics. My special interest is utilizing of sample measurements to improve the predictions from these models, by using the best linear (unbiased) predictor (BLP or BLUP). This terminology is closely related to mixed-effects models, but can be generalized also to other models.

Diameter distributions

With diameter distributions, my main interests are (i) how to take into account the mathematical relationships of stand variables and the diameter distribution into account in modelling, (ii) how to improve the prediction by using sample information, and (iii) modelling of percentile-based diameter distribution.

Forest planning

My research on forest palnning is related to cost-efficient use of the forest data in planning. In addition, I supervise theses on the effects of different sources of inaccuracy to the quality of a forest plan.

Current collaborators


  • University of Jyväskylä (Department of statistics),
  • University of Helsinki (Department of forest sciences),
  • University of Eastern Finland (All faculties)
  • University of Oulu (Department of biology)
  • Natural Resources Institute Finland (e.g. groups in NFI, statistics, game research, ...)


  • Yale University (CT, USA)
  • Virginia Tech (VA, USA)
  • University of Natural Resources and Life Sciences, Vienna, Austria
  • Brazil (Federal Technological University of Paraná and University of Sao Paulo)
  • I also have some more or less active collaboration with several other national and international organizations.

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"Thinking is the hardest work there is, which is the probable reason why so few engage in it."
  --  Henry Ford


Last Updated: September 16, 2018