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lesson_16 [2020/02/14 19:39] argemiro |
lesson_16 [2020/02/20 17:45] argemiro |
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| - | Load the model ''calc_mean_patch_sizes_and_standard_deviations.ego'' from ''examples\landscape_metrics\calc_mean_patch_sizes_and_standard_deviations'' | + | Load the model ''calc_mean_patch_sizes_and_standard_deviations.ego'' from ''\Guidebook_Dinamica_5\Models\Landscaspe_metrics\calc_mean_patch_sizes_and_standard_deviations'' |
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| - | Now, load the model ''calc_mean_patch_edges_and_standard_deviations.ego'' from ''Examples\landscape_metrics\ calc_mean_patch_edges_and_standard_deviations''. | + | Now, load the model ''calc_mean_patch_edges_and_standard_deviations.ego'' from ''\Guidebook_Dinamica_5\Models\Landscaspe_metrics\calc_mean_patch_edges_and_standard_deviations''. |
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| This model calculates the edge length of each patch of a landscape class and for each class the mean patch edge length and patch edge length standard deviation. | This model calculates the edge length of each patch of a landscape class and for each class the mean patch edge length and patch edge length standard deviation. | ||
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| - | These two set of metrics are input for more complex metrics, such as fractal dimension and largest patch index. For example, fractal dimension for a landscape class can be estimated using the perimeter-area relationship, if sufficient data are available, the slope of the line obtained by regressing log(P), patch edge lengths, on log(A), patch areas, is equal to 2/D (Burrough, 1986). Check other landscape metrics models, such as mean patch distance, largest patch index, in ''examples\landscape_metrics''. | + | These two set of metrics are input for more complex metrics, such as fractal dimension and largest patch index. For example, fractal dimension for a landscape class can be estimated using the perimeter-area relationship, if sufficient data are available, the slope of the line obtained by regressing log(P), patch edge lengths, on log(A), patch areas, is equal to 2/D (Burrough, 1986). Check other landscape metrics models, such as mean patch distance, largest patch index, in ''Guidebook_Dinamica_5\Models\Landscaspe_metrics''. |
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| - | Recently, a new submodel was built to calculate various landscape metrics quickly and easily in Dinamica EGO. This model is called **Landscape Metrics** and you can find it at the following directory: ''Guidebook_Dinamica_5\Models\Landscape_metrics'' | + | Recently, a new submodel was built to calculate various landscape metrics quickly and easily in Dinamica EGO. This model is called **Landscape_Metrics.egoml** and you can find it at the following directory: ''Guidebook_Dinamica_5\Models\Landscape_metrics'' |
| </note> | </note> | ||
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| - | To use this submodel, load and double click the submodel, and, in the new window, load the map you want to calculate the andscape metrics, and choose a destination and a name to save the results table: | + | To use this submodel, load and double click the submodel, and, in the new window, load the map you want to calculate the landscape metrics, and choose a destination and a name to save the results table: |
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| - | Below are described the landscape metrics that are calculated by this sub-model: | + | ☞[[lesson_17|Next Lesson]] |
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| - | \\ | + | ☞[[:guidebook_start| Back to Guidebook Start]] |
| - | Congratulations, you have successfully completed this lesson! Now let’s move to the **next lesson:** [[lesson_17|LESSON 17: Calculating accumulated cost surface and least-cost pathway]] | + | |