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tutorial:calculating_accumulated_cost_surface_and_least-cost_pathway [2013/08/14 15:05] admin |
tutorial:calculating_accumulated_cost_surface_and_least-cost_pathway [2016/11/23 19:27] isabella |
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- | The **Source** port will receive the Map ''railroad.tif'' and the friction map output by the third //[[:Calculate Map]]//. Turn on **Diagonals Cost More**. This will penalize the movement across diagonal cells. Set **Maximum Number of Passes** to “2”. Leave all other options untouched.{{ :tutorial:cost7.2.jpg |}} | + | The **Source** port will receive the Map ''railroad.tif'' and the friction map output by the third //[[:Calculate Map]]//. Turn on **Diagonals Cost More**. This will penalize the movement across diagonal cells. Set **Maximum Number of Passes** to “2”. Leave all other options untouched. |
- | Open //[[:Calc Pathway Map]]// now with the Edit Functor Ports. Link Map ''town1.tif'' to the **Source** port <note tip>**TIP**: **Source**, in this case, also represents the destiny since the cost map was built from the existing railroad. Thus, this algorithm will search for the least-cost pathway from the source to the existing feature, i.e. the railroad.</note> | + | Open //[[:Calc Pathway Map]]// now with the Edit Functor Ports. |
- | Link the map output from //[[:Calc Cost Map]]// to the port **Cost** and Map ''railroad.tif'' to **Network** (because it represents a linear feature network) and the output **Network** port to //Save Map//. {{ :tutorial:cost8.2.jpg |}} | + | Link Map ''town1.tif'' to the **Source** port <note tip>**TIP**: **Source**, in this case, also represents the destiny since the cost map was built from the existing railroad. Thus, this algorithm will search for the least-cost pathway from the source to the existing feature, i.e. the railroad.</note> |
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+ | Link the map output from //[[:Calc Cost Map]]// to the port **Cost** and Map ''railroad.tif'' to **Network** (because it represents a linear feature network) and the output **Network** port to //[[:Save Map]]//. {{ :tutorial:cost8.2.jpg |}} | ||
Activate the option **Use Lottery** (this is an artifact that permits the model to solve the path when two or more local minima are found).\\ | Activate the option **Use Lottery** (this is an artifact that permits the model to solve the path when two or more local minima are found).\\ | ||
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- | {{ :tutorial:cost9.jpg?300|}}//[[:Calc Pathway Map]]// ignores cells with values equal or lesser than 0 or null cells. In turn //[[:Calc Cost Map]]// needs a network map with null cells representing non-features. Go to //[[:Load Categorical Map]] and open it with the Edit Functor. Press the flag **Null Value** and make sure **Use specific value** is set to “0”.\\ | + | {{ :tutorial:cost9.jpg?300|}}//[[:Calc Pathway Map]]// ignores cells with values equal or lesser than 0 or null cells. In turn //[[:Calc Cost Map]]// needs a network map with null cells representing non-features. Go to //[[:Load Categorical Map]]// and open it with the Edit Functor. Press the flag **Null Value** and make sure **Use specific value** is set to “0”.\\ |
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- | You may try to maximize the solution for the Calc Cost Map algorithm by setting the **Maximum Number of Passes** to “0”. Compare the time spent by this run and its resulting path with that of previous model? Did it make a big difference?\\ | + | You may try to maximize the solution for the //[[:Calc Cost Map]]// algorithm by setting the **Maximum Number of Passes** to “0”. Compare the time spent by this run and its resulting path with that of previous model? Did it make a big difference?\\ |
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This type of model can also be modified to develop simultaneously multiple paths. Open the model ''join_towns.egoml'' in lesson 4 folder.{{ :tutorial:cost12.jpg |}} | This type of model can also be modified to develop simultaneously multiple paths. Open the model ''join_towns.egoml'' in lesson 4 folder.{{ :tutorial:cost12.jpg |}} |