Height Calibration - Revision history

Jonare at 05:45, 25 April 2024

2024-04-25T05:45:05Z

Peder at 14:11, 21 November 2014

2014-11-21T14:11:52Z

Peder: /* Weighting */

2014-08-28T15:12:09Z

Weighting

Peder: /* Weighting */

2014-08-28T15:11:31Z

Weighting

Peder: /* Weighting */

2014-08-28T15:09:50Z

Weighting

Peder: /* Weighting */

2014-08-28T15:08:40Z

Weighting

Peder: /* Weighting */

2014-08-28T15:07:48Z

Weighting

Peder: /* Weighting */

2014-08-28T15:07:05Z

Weighting

Peder: /* Weighting */

2014-08-28T15:05:52Z

Weighting

Peder: /* Step 2 - Calibration at stand level */

2014-08-28T15:02:43Z

Step 2 - Calibration at stand level

← Older revision		Revision as of 05:45, 25 April 2024
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−	{{Languages}}	+	{{Languages \| Height Calibration}}

	When importing a stand register to be used as input data the program simulates tree lists with the help of diameter distribution functions. For every tree created the tree height is calculated with height functions (<ref name = "ClaessonEtAl2001">{{:Bibliografi:Söderberg1992}}</ref>). These functions are based on tree sample data from the National Forest Inventory and covers all regions in Sweden. For specific stands, the actual tree heights will of course differ from those projected. Therefore, it is possible to let the system adjust the calculated heights. The purpose of using a height function is to obtain a realistic height distribution, so that not all trees have the same height.		When importing a stand register to be used as input data the program simulates tree lists with the help of diameter distribution functions. For every tree created the tree height is calculated with height functions (<ref name = "ClaessonEtAl2001">{{:Bibliografi:Söderberg1992}}</ref>). These functions are based on tree sample data from the National Forest Inventory and covers all regions in Sweden. For specific stands, the actual tree heights will of course differ from those projected. Therefore, it is possible to let the system adjust the calculated heights. The purpose of using a height function is to obtain a realistic height distribution, so that not all trees have the same height.

← Older revision		Revision as of 14:11, 21 November 2014
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 The formulas above are somewhat simplified, because there is also an adjustment included that lets a user define the relative importance between the data in the import file and the function values. When simulating the tree list, the user can enter a weighting value [between 0 and 1], in dialog Simulate Tree List.
-With weighting, the formula for step 1 is:
+With weighting, the formula for step 1 is:<br>
 <math>
 {q(s,k)} = \frac{w\cdot H_{register}(s,k) + (1-w)\cdot H_{funktion}(s,k)} {H_{function}(s,k)}
 </math>
-and for step 2:
+and for step 2:<br>
 <math>
 {q(k)} = \frac{w\cdot H_{register}(k) + (1-w)\cdot H_{funktion}(k)} {H_{function}(k)}

@@ Line 37: / Line 37: @@
 The formulas above are somewhat simplified, because there is also an adjustment included that lets a user define the relative importance between the data in the import file and the function values. When simulating the tree list, the user can enter a weighting value [between 0 and 1], in dialog Simulate Tree List.
 <math>
-{q(s)} = \frac{w\cdot H_{register}(s) + (1-w)\cdot H_{funktion}(s)} {H_{function}(s)}
+{q(s,k)} = \frac{w\cdot H_{register}(s,k) + (1-w)\cdot H_{funktion}(s,k)} {H_{function}(s,k)}
 </math>

@@ Line 46: / Line 46: @@
 *A weight of zero (''w''=0) means that no calibration should be done, and the function values be used as they are.
 *''w'' = 1 mean that calibration should be done according to step 1 and 2 above, i.e. the import data should be used for calibration to the largest degree allowed, given the restrictions on the q-values described above.
-*''w'' = 0.5 means that import data and function values should have equal weight. If the mean height according to the import data is 12 m and 10 m according the function, the resulting mean height will be 11 m (q = [0.5*12 + (1-0.5)*10]/10 = 11/10 = 1.1). The restriction of the value of q is applied <u>after</u> this weighting, for example: If the mean height according to the import data is 14 m but 10 m according to the function, then ratio q is 1.4 if w = 1. With w = 1 it should be adjusted to 1.3 if it is constrained to the default interval. However, with w = 0.5 the ratio is 1.2 (q = ([0.5*14 + (1-0.5)*10]/10 = 1.2) which is within the allowed range.
+*''w'' = 0.5 means that import data and function values should have equal weight. If the mean height according to the import data is 12 m and 10 m according the function, the resulting mean height will be 11 m (q = [0.5*12 + (1-0.5)*10]/10 = 11/10 = 1.1). The restriction of the value of q is applied <u>after</u> this weighting, for example: If the mean height according to the import data is 14 m but 10 m according to the function, then ratio q is 1.4 if w = 1. With w = 1 it should be adjusted to 1.3 if the default bounds are used. However, with w = 0.5 the ratio is 1.2 (q = ([0.5*14 + (1-0.5)*10]/10 = 1.2) which is within the allowed range.

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 Examples:
 *A weight of zero (''w''=0) means that no calibration should be done, and the function values be used as they are.
-*''w'' = 1 mean that calibration should be done according to step 1 and 2 above, i.e. the import data should be used as the target values, although with the limits described above.
+*''w'' = 1 mean that calibration should be done according to step 1 and 2 above, i.e. the import data should be used for calibration to the largest degree allowed, given the restrictions on the q-values described above.
 *''w'' = 0.5 means that import data and function values should have equal weight. If the mean height according to the import data is 12 m and 10 m according the function, the resulting mean height will be 11 m (q = [0.5*12 + (1-0.5)*10]/10 = 11/10 = 1.1). The restriction of the value of q is applied after this weighting. If the mean height according to the import data is 14 m but 10 m according to the function, then ratio q is 1.4 if w = 1. With w = 1 it should be adjusted to 1.3 if it is constrained to the default interval. However, with w = 0.5 the ratio is 1.2 (q = ([0.5*14 + (1-0.5)*10]/10 = 1.2) which is within the allowed range.

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 <br>''H''<sub>function</sub> (''k'') = Basal are weighted mean height for all created trees (that belong to layer ''k''), adjusted with the factors calculated in step 1.
-The height functions are quite robust, while compartment data often contain poor tree height estimatations. Therefore, there is a built-in restriction for how much the calculated height can be adjusted. By default, the limits are set to max +/- 30 %. This means that the calculated ratios are bounded by the interval [0.7, 1.3]. The limits can be changed by the user in control table Production Model. Example: If the mean height according the import data is 14 m but 10 m according the functions, the ratio is 1.4. Because this is larger than 1.3, the ratio is set to 1.3.
+The height functions are quite robust, while compartment data often contain unreliable tree height estimates. Therefore, there is a built-in restriction for how much the calculated height can be adjusted. By default, the limits are set to max +/- 30 %. This means that the calculated ratios are bounded by the interval [0.7, 1.3]. The limits can be changed by the user in control table Production Model. Example: If the mean height according the import data is 14 m but 10 m according the functions, the ratio is 1.4. Because this is larger than 1.3, the ratio is set to 1.3.
 ====Weighting====