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...ity. Importance sampling is applicable to continuous populations where the size attribute is a function from which a probability density function is derive ...selection probabilities proportional to an [[ancillary variable|ancillary size variable]]. With a continuous population we must devise a continuous functi

...right|thumb|300px|'''Figure 1''' Illustration of inclusion proportional to size (basal area) in Bitterlich sampling (Kleinn 2007<ref name="kleinn2007">Klei ...times also referred to point sampling, horizontal point sampling, variable plot sampling, angle count technique, prism cruising, angle gauge sampling, and

...ain unordered set of elements (e.g. a number of trees included by a sample plot) is selected as sample. ... measurements (normally this is not only one tree, but e.g. all trees on a plot). Nevertheless we need to know the inclusion probability of each tree to de

[[File:2.8.4-fig39.png|right|thumb|400px|'''Figure 2''' Residual plot of residual volume (<math>dm^3</math> as Y-axis and ''dbh'' (cm) as X ...to adjust to changing ''dbh''-height relationships as they occur in medium size<br>forest inventories such as [[forest enterprise inventories]] or [[forest

...a defined distance (radius) from the sample point, which constitutes the plot center (Kleinn 2007<ref name="kleinn2007">Kleinn, C. 2007. Lecture Notes fo ...s showing 3 circular plots having different sizes, radii, but sharing same plot center (Kleinn 2007<ref name="kleinn2007">Kleinn, C. 2007. Lecture Notes

...ver bias). A systematic error cannot be compensated by increasing [[sample size]]. ...qual selection probabilities|unequal probability sampling]] approach (or [[plot design]]). Trees are included in a sample, if they appear bigger that a def

...ts]] in which a certain inclusion distance (e.g. the radius of a circular plot up to which trees are included in a sample) is defined, here the number of ...eferred to as plotless methods because there is no need to lay out a fixed plot area.

...<ref name="McRoberts 2003">McRoberts, R.E., 2003. Compensating for missing plot observations in forest inventory estimation. Can.J.For.Res. 33, 1990-1997</ ...e [[:category:plot design|plots]] with missing observations:''' the sample size [[Accuracy and precision|precision]] decrease (because of smaller ''n''): o

...|sampling]], the sampling elements that we select and observe are [[Sample plot|sample plots]]. Consequently, the [[population]] from which we sample is a ...subdivision of the forest area into sample plots of identical shape and size, here: square and hexagonal sample plots. Such a subdivision is also pos

...raditions and conventions and not much is thought about the choice of the plot type. ...ons were exactly known by their grid coordinates, simulation of different plot design could be carried out. There, 4969 trees were mapped on an area of 1

...s obviously not desired but if we wish to make an extrapolation of the per-plot observation to the per hectare observation, then '''all''' related areas mu ...n the slope must be larger such that the target plot area results when the plot is horizontally projected. This is illustrated for circular fixed area plot

... observation from point 1 in time (that is: the observations from the same plot). In that case, change ''c'' is also estimated from <math>c=\bar{y_2}-\bar{ ... repeatedly observed, we can determine the differences (changes) for each plot – and not only for the entire population; we may, therefore, expect that

Area estimation can be based on different plot designs that are discussed in what follows: points, lines and plots. ...mply counted how many points fall into forest; if, out of the total sample size ''n'' there are <math>n_f</math> forest points, then the forest cover propo

...ändler (in review) where forest edge length is estimated from the cluster plot design of the German National Forest Inventory at three different spatial r ...ion of forest edge length differing in the attribute which is observed per plot. They are briefly dealt with in the following sub-chapters.

...ference with respect to statistical analysis: while growing stock and tree size are [[metric variables]] – species richness is a [[nominal variable]]. Th ...tion of the United Nations, Rome. 25p.</ref>). While the area of one field plot is small, the total tallied sample area is large. Thus, such data set shoul

...oted to [[:Category:Sampling design|sampling]] and [[:Category:Plot design|plot design]] techniques and the impression could arise that [[forest inventory] ...est inventory. This is at least as important as the efficient sampling and plot design.

... with respect to statistical precision, accuracy and spatial resolution (size of reporting units). It is important to stress the aspect of data quality i ...se of the inventory. We may group the attributes into those which refer to plot location (e.g. geographical data, ownership data, etc.), to production aspe

...where interviews take place. Planning of a suitable [[sampling design and plot design]] in regard to defined target variables will be done based on sta ... size]] & larger plots) to that of observational studies (larger [[sample size]] & smaller [[fixed area plots| inventory plots]]). The permanent installa

... size (the number of elements (sub-plots) that are combined to one cluster plot). The larger the number of sub-plots, the more close to 0 is the lower, neg ...ror variance is exactly the formula for simple random sampling with sample size <math>nm</math>. In that case (which is very uncommon in applications of fo

...ssessment we need an additional independent reference data set. The sample size should be large enough to divide the reference data into training and test