Inclusion zones and population concepts in forest inventories

Lesson 16: A closer look on the population from which we are sampling. Students are sometimes confused about the underlying population from which we draw sampling elements. These elements are not single trees, but sample plots. The population is therefore a consequence of the stipulated plot design. We can influence this population (and the population- and error variance) by changing the plot design.
#unigöttingen
#forestinventory
#forestmensuration

[@forestinventory]

Thanks to Tyler Morgan-Wall for the amazing rayshader package!

[@starcha4473]

Is it maybe possible to get the R code for the plots, they look amazing!

[@forestinventory]

You find some examples of rayshader here: www.rayshader.com/ The code for this specific simulation is unhandy to share, but I used rayrender for the camera rotation

[@starcha4473]

@@forestinventory Thanks a lot. I'm currently conducting forest inventories in a couple of natural reserves in Austria for my masters thesis and would love to make some graphs as these in the video :)

[@forestappalachia6047]

I thought inclusion zones were areas of the forest that are of an older cohort than the surrounding forest

[@forestinventory]

Might be that the same terminology is used for different purposes?... In the sampling context, it is the area of all (sample-) points that would lead to the inclusion of a tree (or other spatially dispersed objects) in the sample. Based on this we can determine the tree individual inclusion probability (unequal probability sampling) that we need to know for unbiased (design-based) estimation.