Resource assessment exercises: introduction to response designs
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| + | : ''This article is part of the '''Resource assessment exercises'''. See the [[:category:Resource assessment exercises 2014|category page]] for a (chronological) table of contents. | ||
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In the introduction we mentioned that in forest inventories we usually do not sample individual trees. In this section we will have a look at different response designs. These include fixed area, nested fixed area plots, and plots of variable size. For other types of observation units see, e.g. Gregoire & Valentine (2008)<ref name=Gregoire08>Gregoire, T.G., Valentine, H.T., 2008. ''Sampling Strategies for Natural Resources And The Environment, Applied Environmental Statistics.'' Chapman & Hall/CRC.</ref>, and Kleinn (2013) <ref name=Kleinn13>Kleinn, C., 2013. ''Lecture Notes for the Teaching Module Forest Inventory.''</ref>. | In the introduction we mentioned that in forest inventories we usually do not sample individual trees. In this section we will have a look at different response designs. These include fixed area, nested fixed area plots, and plots of variable size. For other types of observation units see, e.g. Gregoire & Valentine (2008)<ref name=Gregoire08>Gregoire, T.G., Valentine, H.T., 2008. ''Sampling Strategies for Natural Resources And The Environment, Applied Environmental Statistics.'' Chapman & Hall/CRC.</ref>, and Kleinn (2013) <ref name=Kleinn13>Kleinn, C., 2013. ''Lecture Notes for the Teaching Module Forest Inventory.''</ref>. | ||
Latest revision as of 09:23, 23 July 2014
- This article is part of the Resource assessment exercises. See the category page for a (chronological) table of contents.
In the introduction we mentioned that in forest inventories we usually do not sample individual trees. In this section we will have a look at different response designs. These include fixed area, nested fixed area plots, and plots of variable size. For other types of observation units see, e.g. Gregoire & Valentine (2008)[1], and Kleinn (2013) [2].
Our target parameter will be the basal area (BA) ha\(^{-1}\). The BA in square meters (m\(^{2}\)) of a single tree, i.e., the cross-section of a tree trunk, is defined as,
| $\text{BA}=\frac{\pi\times(\text{DBH}/2)^2}{10000}$ | 1 |
Here, the DBH is given in centimeters, and we, therefore, have to divide by 10,000. The BA ha\(^{-1}\) for the simulated forest is
trees$ba <- (pi * (trees$dbh/2)^2)/10000 sum(trees$ba)/50 # the area of the forest is 50 hectares ## [1] 28.66 tapply(trees$ba, trees$stratum, function(x) sum(x)/25) # per stratum ## 1 2 ## 13.95 43.36
What the function sum()does- the function
sum(x)simply takes the sum ofx. To get the sums of columns and rows usecolSums()androwSums(), respectively.
- What the function
tapply()does - The function
tapply(x, group, function)applies afunctionto values in a group. In the last code example we looked at the variablebaoftrees. The grouping variable isstratum. For all valuesbain each group (i.e., stratum) we apply a function. The argumentxinfunction(x)stands for the values in group $i$. The sum is taken for all the values in the group and then divided by 25.tapply(trees$dbh,trees$stratum, mean)
[edit] Related pages
- Previous page: Basic statistics additional exercises
- Next page: Fixed area plots
