During the course you will learn how to design, collect and process data in order to estimate amount of woody biomass biomass in forest stands - as a tool for forest inventory related mainly to carbon sequestration.

The course was originally designed for Forest Information Technology students as a "Special module". It covers the contemporary remote-sensing based forets inventory methods joining airborne lidar data with terrestrial sample plots measurements.
Single tree growth; forest growth, competition and structure; influence of various factors on growth of trees and stands
"Internet Programming" - the elective course designed especially for Forest Information Technology students

The course is the continuation of Statistics I course offered within the frame of Forest Information Technology program. It covers environmental data processing, including regression analysis and analysis of viariance, using SPSS software. In addition to that, basic statistical concepts, sampling, data processing, estimation procedures, significance level, confidence intervals, sample size determination, testing statistical hipotheses, simple and multiple linear regression, nonlinear regression and ANOVA will be discussed with the use R package.

The aim of the course is to give basics for planning forest inventories and the comparison of various equal and unequal probability sampling concepts. The following topics are included: simple statistics, simple random and systematic sampling, horizontal point sampling, stratified sampling, ratio and regression estimators used with various sampling designs, double sampling, multistage sampling, permanent and temporary forest sampling procedures.

The application of statistical procedures and computer technology to problems in forest mensuration and forest management planning. The course covers the following topics:

  • motivation for modeling tree and stand growth,
  • types of growth and yield systems,
  • individual tree volume and taper equations,
  • explicit models (dominant height, site index, stand density, survival functions, yield functions, adjustments for cultural treatments),
  • implicit models (diameter distributions ? pdf?s and distribution free),
  • individual tree models (distance dependent and distance independent),
  • compatibility with whole stand models,
  • growth model derivation and analysis (Generalized Algebraic Difference Method).

For all the above-mentioned topics model derivation, data requirements, parameter estimation methods and model validation procedures will be discussed in detail.