Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision | ||
|
tutorial:using_local_saturation [2013/08/14 19:55] admin |
tutorial:using_local_saturation [2020/02/18 23:12] (current) argemiro |
||
|---|---|---|---|
| Line 2: | Line 2: | ||
| - | Load the model ''simulate_deforestation_using_local_saturation.egoml'' from ''\Examples\advanced\local_saturation''. Local saturation prevents a change from occurring within a specific region, in which a class area is greater than an established threshold (Fig.1). This feature is useful to simulate diffusion process as well as to establish a minimum forest remaining area (as established by the Brazilian forest code for private properties). Local saturation can be implemented by reducing the probability of a transition using an asymptotic function as follows: | + | Load the model ''simulate_deforestation_using_local_saturation.egoml'' from ''\Guidebook_Dinamica_5\Models\additional_resources_lucc\local_saturation''. Local saturation prevents a change from occurring within a specific region, in which a class area is greater than an established threshold (Fig.1). This feature is useful to simulate diffusion process as well as to establish a minimum forest remaining area (as established by the Brazilian forest code for private properties). Local saturation can be implemented by reducing the probability of a transition using an asymptotic function as follows: |
| - | **P2 = P1 * (Li – Oc) / (Li + Oc), case Li >= Oc\\ | + | **P<sub>2</sub> = P<sub>1</sub> * (Li – Oc) / (Li + Oc), case Li >= Oc\\ |
| - | P2 = 0, case Li < Oc | + | P<sub>2</sub> = 0, case Li < Oc |
| ** | ** | ||
| Line 12: | Line 12: | ||
| For each model step, the amount of deforested cells is calculated in every 3x3 window of the landscape map. In this case, the threshold consists of five cells as follows: | For each model step, the amount of deforested cells is calculated in every 3x3 window of the landscape map. In this case, the threshold consists of five cells as follows: | ||
| - | **P2 = P1 * (5 - Oc) / (5 + Oc), case Li >= Oc\\ | + | **P<sub>2</sub> = P<sub>1</sub> * (5 - Oc) / (5 + Oc), case Li >= Oc\\ |
| - | P2 = 0, case 5 < Oc** | + | P<sub>2</sub> = 0, case 5 < Oc** |
| Line 22: | Line 22: | ||
| **nbCount(i1, 3, 3)** | **nbCount(i1, 3, 3)** | ||
| - | where nbCount is the neighborhood counting operator, i1 is map # 1, and 3,3 is the window size in cells. You could easily increase the neighborhood size, changing these values. Then, a third //[[:Calculate Map]]// is added to apply the local saturation rule on the probability map as follows: | + | where nbCount is the neighborhood counting operator, i1 is map #1, and 3,3 is the window size in cells. You could easily increase the neighborhood size, changing these values. Then, a third //[[:Calculate Map]]// is added to apply the local saturation rule on the probability map as follows: |
| **if v1 - i1 >= 0 then i2 * (v1 - i1) / (v1 + i1) else 0** | **if v1 - i1 >= 0 then i2 * (v1 - i1) / (v1 + i1) else 0** | ||