Projects archive

Improvement of the growth models
Leader: Jānis Donis
Start date: 1.2.2016
End date: 1.12.2020

Contracting entity – JSC "Latvia's State Forests".

Project tasks:

  1. Preparation of NFI 2019 data for growth and yield model improvement.
  2. Calculation of coefficients of growth equations based on 5 years measurement data of 3rd NFI cycle, including a thinning effect in the models.
  3. Model for modal values of basal area growth for un-managed stands.
  4. Preparing description of detailed formula interaction according to the approach in the formula testing excel file (without the young stand formulae).
  5. Development of the forecasting model of growth, mortality and net change based on NFI 3rd cycle 3 years’ data.
  6. Development of individual tree growth model. Validation and verification of individual tree growth developed models. Statistics analysis of the results obtained.
  7. Calculation of the average height of the first floor using LIDAR data. To Create a stand`s 1st floor average height calculation model for ArcGIS using CHM raster layer based on LGIA LiDAR data.
  8. Average height increment calculation model. Create an ArcGIS model which based on the LiDAR scanning date in combination with the dominant tree species and the age of trees, predicts the height increase average height of trees of the 1st floor according to equations elaborated in Task 2.
  9. Re-measurement of previously installed sample plots in uneven-aged stands (50 objects).
  10. Development of multilevel stand growth models using data collected in 2019 and previous years.
  11. Development of a system of equations for assessing the effects of anthropogenic forest regeneration (breeding effect) on the growth rate of pines, spruce and birch stands, analysis of data and drawing up sound conclusions.
  12. Establishment and Renovation of the sites of the established thinning experiment plots. Tree measurements in local coordinate system in the established permanent sample plots.
  13. Development of the thinning felling impact models.


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