Plot design examples
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| + | These are some self-stuy test questions that might be relevant in context of planning a suitable plot design in national forest inventories or for the test in forest inventory: | ||
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| − | + | * Explain why a major statistical planning criterium for the choice of a [[plot design]] is to capture as much of the given variability of the target variable as possible! | |
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| − | + | * List some target variables that could be estimated based on one dimensional [[line sampling|lines]] as observation units! | |
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| − | # A decision maker is arguing on your report: „you observed only 0.05 % of the forest area of our country in the field, i can‘t believe that these results are reliable!“ How can you defend your results? (describe how [[Sampling intensity vs. sample size|sampling intensity and sample size]] are affecting [[accuracy and precision|precision]]) | + | |
| + | * Explain the rational of a [[Fixed_area_plots#Nested_sub-plots|nested plot design]], in which trees of different diameter classes are included in sub-plots of different area size (smaller trees in small plots, large trees in large plots)! | ||
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| + | * What sources of information might be a suitable basis for the decision on plot design options if you carry out a NFI for the first time? | ||
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| + | * Planning for field protocols and plot designs is very much a compromise between statistical considerations and feasability in practical field implementation. Explain why compact circular (sub-) plots are common, even if elongated rectagular plots might be more suitable from a pure statistical point of view! | ||
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| + | * You are responsible to allocate a limited budget for the implementation of a national forest inventory. Would you rather opt for a small number of large plots or a large number of rel. small plots? Explain! | ||
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| + | * A decision maker is arguing on your report: „you observed only 0.05 % of the forest area of our country in the field, i can‘t believe that these results are reliable!“ How can you defend your results? (describe how [[Sampling intensity vs. sample size|sampling intensity and sample size]] are affecting [[accuracy and precision|precision]]) | ||
[[Category:Forest Inventory Examples]] | [[Category:Forest Inventory Examples]] | ||
| + | [[Category:plot design]] | ||
Latest revision as of 13:04, 26 October 2013
These are some self-stuy test questions that might be relevant in context of planning a suitable plot design in national forest inventories or for the test in forest inventory:
- Explain why a major statistical planning criterium for the choice of a plot design is to capture as much of the given variability of the target variable as possible!
- List some target variables that could be estimated based on one dimensional lines as observation units!
- Explain the rational of a nested plot design, in which trees of different diameter classes are included in sub-plots of different area size (smaller trees in small plots, large trees in large plots)!
- What sources of information might be a suitable basis for the decision on plot design options if you carry out a NFI for the first time?
- Planning for field protocols and plot designs is very much a compromise between statistical considerations and feasability in practical field implementation. Explain why compact circular (sub-) plots are common, even if elongated rectagular plots might be more suitable from a pure statistical point of view!
- You are responsible to allocate a limited budget for the implementation of a national forest inventory. Would you rather opt for a small number of large plots or a large number of rel. small plots? Explain!
- A decision maker is arguing on your report: „you observed only 0.05 % of the forest area of our country in the field, i can‘t believe that these results are reliable!“ How can you defend your results? (describe how sampling intensity and sample size are affecting precision)
