Specifying Transition Rules
The Specify Transition Rules tool is essential to the Advanced Cellular Automata workflow. Currently, there are five general-purpose transition rule types supported to generate or limit cell state transitions in binary or multi-class models. These include:
- Neighbourhood-Based Rules
- Cell-Level Rules
- Stochastic Disturbance Rules
- Allocation and Quantity Rules
- Constraint Rules
1. Neighborhood-Based Rules
Generative Rule
Neighborhood-Based Rules are a characteristic mechanism of cellular automata models. Considering the current cell state and the states of its influential neighbors, we can define the required conditions for some change to occur.
| Required Field Name | Description | Data Type |
|---|---|---|
| Rule Priority | Ranking for rule application. See Rule Priority Settings for more information. | Positive Integer |
| Current State | The cell state that should be affected by this rule. | Positive Integer |
| Neighbor State | The cell state that should be present in the cell’s neighborhood for the rule conditions. | Positive Integer |
| Next State | The cell’s next state should the rule conditions be satisfied. | Positive Integer |
| Lower Bound (#) | The minimum number of cells with the Neighbor State that must be present in the cell’s neighborhood. | Positive Integer |
| Upper Bound (#) | The minimum number of cells with the Neighbor State that must be present in the cell’s neighborhood. | Positive Integer |
| *.nb File | A file path to a Neighborhood Definition file that indicates which relative locations should constitute a cell’s neighborhood. | Neighborhood Definition file |
| Probability | A value indicating the probability or likelihood that the rule propogates a change given that the conditions are satisified. | Positive Integer (values must be in the range of 1 to 100) |
There is a simplified binary Neighborhood-Based Rule built-in to the Basic Cellular Automata tool. Users are limited to specifying one neighborhood function and set of conditions for this rule of this type in the dockpane window.
2. Cell-Level Rules
Generative Rule
Cell-Level Rules can be used to introduce stochastic disturbances without required neighborhood conditions or proximity settings. They can also be used for incrementing some cell’s state at each iteration of the model.
| Required Field Name | Description | Data Type |
|---|---|---|
| Rule Priority | Ranking for rule application. See Rule Priority Settings for more information. | Positive Integer |
| Current State | The cell state that should be affected by this rule. | Positive Integer |
| Next State | The cell’s next state should rule take effect. | Positive Integer |
| Probability | A value indicating the probability or likelihood that the rule propogates a change given that the conditions are satisified. | Positive Integer (values must be in the range of 1 to 100) |
3. Stochastic Disturbance Rules
Generative Rule
Stochastic Disturbance Rules are used to propogate some phenomena based on proximity settings rather than the conditions of a cells neighborhood. This rule type requires users to provide distances as a “number of cells” and is generic to any unit of measurement. Therefore, it is advised to check the spatial resolution of your raster data layer before inputting values.
| Required Field Name | Description | Data Type |
|---|---|---|
| Rule Priority | Ranking for rule application. See Rule Priority Settings for more information. | Positive Integer |
| Affected State | The cell state that should be affected by this rule. | Positive Integer |
| Emitter State | The cell state considered to proliferate changes (i.e., the Next State) | Positive Integer |
| Min. Distance (#) | The minimum distance from an edge of some emitter state that should be affected. | Positive Integer providing the number of cells. |
| Max. Distance (#) | The maximum distance from an edge of some emitter state that should be affected. | Positive Integer providing the number of cells. |
| Probability | A value indicating the probability or likelihood that the rule propogates a change given that the conditions are satisified. | Positive Integer (values must be in the range of 1 to 100) |
4. Allocation and Quantity Rules
Limiting Rule
Allocation and Quantity Rules are used to refine or limit newly changed locations. Users can provide suitability, susceptibility, or probability maps as input to guide the allocations of new changes. Quantity limits can also be imposed. One or both of the optional settings must be specified to create a valid rule.
| Required Field Name | Description | Data Type |
|---|---|---|
| Current State | The cell’s state before generative rules are applied in the current model iteration. | Positive Integer |
| Next State | The cell’s potential new state as determined by the generative rules applied in the current model iteration. | Positive Integer |
| Optional Field Name | Description | Data Type |
|---|---|---|
| Min. Suitability | The minimum value in the Suitability Map provided that would support the from-to transition specified to occur. | Positive decimal value between 0.0 and 1.0 |
| Suitability Map | A suitability, susceptibility, or probability map used to refine from-to transitions given the current and next states provided. | A path to a raster data layer containing values ranging from 0 to 1. See the Data Preparation guidelines for more information. |
| Max. Change (#) | The maximum number of transitions that can occur from the Current State to the Next State provided. | Positive Integer |
There is a simplified binary Allocation and Quantity Rule available in the Basic Cellular Automata tool. Users are limited to specifying a single rule of this type in the dockpane window.
5. Constraint Rules
Limiting Rule
Allocation and Quantity Rules are used to refine or limit newly changed locations. Users can provide suitability, susceptibility, or probability maps as input to guide the allocations of new changes. Quantity limits can also be imposed. One or both of the optional settings must be specified to create a valid rule.
| Required Field Name | Description | Data Type |
|---|---|---|
| Next State | The cell’s potential new state as determined by the generative rules applied in the current model iteration. | Positive Integer |
| Constraint Map | A binary map used to restrict changes to the provided Next State. | A path to a raster data layer containing binary values, where 1 indicates permitted changes and 0 indicates no change to this cell state can occur. See the Data Preparation guidelines for more information. |
There is a simplified binary Constraint Rule built-in to the Basic Cellular Automata tool. Users are limited to specifying a single rule of this type in the dockpane window.
Rule Priority Settings
Rule Priority settings are available for the generative rule types. Rules with lower priority values (i.e., higher values) will be overriden by changes propogated by higher priority rules (i.e., lower values). For example, if you set one rule to have a priority of 1 and another with a rule priority of 2, the rule ranked as 1st priority will supersede changes propogated by the rule assigned as 2nd priority when there are conflicts.
If Rule Priority settings do not matter in your application, sequential rule application order will follow the Default Rule Priority Scheme. To use the default priority scheme, provide all rules a priority value of 1.
Adding, Updating, and Deleting Rules
The Specify Transition Rules tool follows a rule-table structure. You can toggle between the rule type tabs to manage subsets of the rule table.
For each rule type, you Add, Update, or Remove rules as follows:
- Adding a rule: fill in the required fields and click Add.
- Updating an existing rule: click the row shown in the rule table view, modify the values in the fields, and click Update.
- Removing a rule: click the corresponding row to highlight it and then click Delete.
Saving, Modifying, and Loading Transition Rule Files
- To save the Transition Rule file, click “Save As” and provide a descriptive file name in the dialog window. Transition Rule files will be persisted with an “.tr” extension supported by the Advanced Cellular Automata tool.
- To open an existing Transition Rule file to view or edit its contents, click “Load File” and locate the “.tr” file you want to explore.
- If you are editing an existing file and wish to overwrite the file contents, click the “Save” button.
- If you want to save the Transition Rule table as a new file, you can click “Save As” or modify the file name directly in the input field and click “Save.”