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Cruise Design Measurement Computations. Determined by 1.Value of product(s) 2.Variability within the stand 3.Budget limitations Sampling Intensity.

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Presentation on theme: "Cruise Design Measurement Computations. Determined by 1.Value of product(s) 2.Variability within the stand 3.Budget limitations Sampling Intensity."— Presentation transcript:

1 Cruise Design Measurement Computations

2 Determined by 1.Value of product(s) 2.Variability within the stand 3.Budget limitations Sampling Intensity

3 Trees in the population are selected with equal probability Normally plot locations are allocated on an unbiased grid pattern Works best for large areas with relatively uniform density and species distribution Application

4 If highly variable stand, large plots and/or large numbers of plots may be needed to get accurate estimates. Potential Problems

5 USFS Way Sampling Intensity

6 1.Determine the sampling error for the sale as a whole. (set to 10%) 2.Subdivide (or stratify) the sale population into sampling components as needed to reduce the variability within the sampling strata. 3.Calculate the coefficient of variation (CV) by stratum and a weighted CV over all strata. (this will be covered more later in the statistics lectures) 4.Calculate number of plots for the sale as a whole and then distribute by stratum. Sample Selection – from Precruise data

7 Number of Plots Value of t is assumed to be 2 Error is set at 10%

8 For each stratum, the calculation would look like this: n 1 = (17.6 * 185) / 67.9 = 48 plots n 2 = (7.7 * 185) / 67.9 = 21 plots n 3 = (7.2 * 185) / 67.9 = 20 plots n 4 = (35.4 * 185) / 67.9 = 96 plots Which totals to the 185 plots for the sale. Distribute Plots by Stratum

9 Tree Expansion Factor 1 divided by the fixed plot size times the number of plots

10 Sample Error - step 1 (Calculate Standard Error)

11 Sample Error – Step 2 36.2% is a bit larger than the level we set to begin with (10%) – Implications?

12 Sampling Intensity Without Precruise data (cheaper) Assumes fairly uniform distribution of species, sizes and grades Can work for even-aged or uneven-aged stands if assumptions are met

13 Plot cruise planning: 160 acre tract 10% cruise (sample) 1/5 acre plots Plot Cruising Fixed Area Plot Sampling 1. Area to be sampled: Given

14 Plot cruise planning: 160 acre tract 10% cruise (sample) 1/5 acre plots (0.2 ac.plots) area sampled = 16.0 ac. Plot Cruising Fixed Area Plot Sampling 2. No. of plots needed:.

15 Plot cruise planning: 160 acre tract 10% cruise (sample) 1/5 acre plots area sampled = 16.0 ac. 80 plots needed Plot Cruising Fixed Area Plot Sampling 3. Samples represent how much area?

16 Plot cruise planning: 160 acre tracteach represents 2 acres (20 sq. chains) 10% cruise (sample) 1/5 acre plots area sampled = 16.0 ac. 80 plots needed Plot Cruising Fixed Area Plot Sampling 4. Plot spacing? Distance between plots

17 Plot cruise planning: 160 acre tracteach represents 2 acres (20 sq. chains) 10% cruise (sample)5 chain spacing between lines 1/5 acre plots area sampled = 16.0 ac. 80 plots needed Plot Cruising Fixed Area Plot Sampling 5. Plot spacing? Distance between lines

18 Office Procedures

19 Tract size times percentage sampling intensity gives you total sample area needed Example: 23 acre tract X 10 percent sample = 2.3 acres Area needed times plot area gives plots needed. Goal: Select plot size that yields around 4 to 8 trees per plot Example 1: 2.3 acres X 5 (fifth acre plots per acre) = 11.5 plots (make it 12) each represents 2 acres Example 2: 2.3 acres X 10 (tenth acre plots per acre) = 23 plots each represents 1 acre Number of Plots

20 Plot center is marked Circular plot radius measured Often 10 percent sampled Unless huge forest with limited budget Or highly variable forest Or high valued forest Operational Features

21 Fixed Plot – 1/10 th acre

22 Plot Allocation Can be unbiased yet systematic by randomizing location of start point and bearing of sample lines.

23 Example of Systematic Layout

24 Fixed Plot Cruising

25 Mark plot center Start checking trees for tally clockwise from the North for consistency Mark each finished tree to prevent tallying the same tree twice Procedure

26 Slope Correction

27 If entire plot doesn’t fall within the survey area, don’t simply shift the plot center so it fits into the tract. This results in fewer edge trees sampled. Boundary Plots

28 If entire plot doesn’t fall within the survey area, double count the half that does. Boundary Plots – Half plot

29 can be used in corners where all tally trees are counted 4 times. Boundary Plots – Quarter plots

30 Boundary Plots - Mirage Plots (preferred) Imagine folding the plot back on itself

31 Boundary Plots - Walkthrough plots If a line the same distance from the plot center to the tree, when projected through the tree crosses the boundary, count it twice.

32 Date = 8/19/2013Size = 1/10 th acreForest Cover Type = Stand Size and Condition = Stand Age = Stocking or Density Class = Site Index =Slope = Soil Classification = Understory Vegetation =Treatments needed = Plot = 1 TreeSpeciesDBHForm ClassHeightGradeCrown ClassNotes 1RO14781.52 2SP168022 3YP18822.51 Plot = 2 Etc. Tally Sheet

33 Can be preformed by hand, in Excel or in Two Dog Trees per acre – by species and/or by size Basal Area per acre – by species and/or by grade Expansion Factor equals percent area sampled Computations

34 No. of treesCubic-foot volumes --------------------------------------------------------------------- DBHPer acrePer acre (in.)Tract totalaverageTract totalaverage ------------------------------------------------------------------------------------------- 51195.511.2 1730.4 16.1 61432.613.4 3767.6 35.1 71455.113.6 5667.8 52.9 81150.610.7 6294.4 58.7 91128.010.5 8379.0 78.2 101082.910.110622.4 99.1 11 823.4 7.711142.7103.9 ------------------------------ Total8268.177.247604.3444.0 Combined Stand and Stock Table Stand table gives estimated number of stems by size (in this case) and per acre Stock table gives total volume and per acre volume (could be board foot or cubic foot) 107.2 acre tract of small mixed hardwoods

35 Cruise Summary (by species not sizes)


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