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In both cases, efficiencies are gained when there is a strong relationship between the forest variable of interest and the derived LiDAR metrics (Maltamo et al. 2011).
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(b) Additionally, our study explored the relationships between the forest variables and NEE, which appeared to be weaker or stronger depending upon the successional stage of the forest.
Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features.
Fine resolution albedo retrievals enable quantifying the relationships between forest variables and albedo also in patchy landscapes, such as in the managed forests in Fennoscandia.
In addition to analysing forest dynamics, our simulation approach also allowed us to explore the relationships between different forest variables and therefore, provided options for exploring ecosystem relationships which have been explored also in other chronosequence forest studies (Denslow and Guzman 2000; Law et al. 2003).
The most important variable, forest coverage ratio, which is the ratio between the forest cover area and the area of the whole grid, was the most important variable in the GLMs, and it was very important in the RFs.
The boundary between the forest and forest-steppe natural zones crosses the republic.
The forest attributes included variables related to stand structure, composition, diversity, regeneration and deadwood.
This finding indicates that a significant relationship exists between the explanatory variables and forest dependency (outcome variable).
For the deforestation decision the amount of removed biomass from the forest is an important variable.
A biplot was created, which allowed for the analysis of the correlation between the different variables and both forest areas.
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