Closed teixeirak closed 5 years ago
There are 57 measurements that include the sine method. Based on these two graph comparisons, it seems that including them doesn't help out too much, and you're right, it would require bias corrections like you mentioned. I'm fine leaving them out (and thus not doing the corrections), but I'd use them anecdotally as representation for what the tallest heights should be (like I found today in #25).
Do you agree?
Excluding the sine data gives us
Including the sine data gives us:
After doing a search, I found the following. None of these mentioned actually applying a correction, so I think we're ok to include the measurements as is. Thoughts?
Mention using Nikon ForestryPro, no mention of changing method/applying corrections
Mention using Nikon ForestryPro / Nikon Forestry 550 (same capabilities) and acknowledge errors
Mention using Nikon ForestryPro, used tangent method
Let's go ahead and keep it in.
I'm going to close this issue since we decided to keep the sine measurements as they are.
@mcgregorian1, first, consider if you really want to include the sine method data. Assuming you'll include only one value per tree, do you gain much by including it? If including, we should calculate and apply some correction factor (as mentioned in issue #25).
The best approach is probably this: for each tree... 1- estimate how much each tree you remeasured may have grown since the first measurement based on its change in diameter (requires using an allometry, so there's a bit of circular reasoning. I'd apply the all-species allometry excluding sine data). ∆h would be height estimated based on current dbh - height estimated based on dbh at time of first height measurement 2- add ∆h to the original measurement, h_0 (h' = h_0+∆h)
3- calculate the % difference between sine height measurement and h'. Then, for all trees... 4- average % bias to get a bias correction factor, 5- apply bias correction factor to to all sine measurements.