The Coverage Processing toolbox includes the Process Signal Strength geoprocessing model which is used to create the voice coverage layer. Within the model, a number of additional geoprocessing models are used to produce the final results. To learn more about how the resulting voice coverage layer is created, learn more about the models outlined below.
| Model Name | Overview |
| Process Signal Strength | This geoprocessing model creates the voice coverage layer. To do this, the input raster goes through a series of iterative processes before being vectorized. As a vector, the data is simplified and further cleaned, which produces a generalized series of features. The output is then joined with the user-defined power level descriptions and saved to disk as the final voice coverage layer. |
| 1 Process Raster | This geoprocessing model composites the input raster into a single band. The submodel 1.1 Segment Raster then processes the single band image. The intermediate outputs are then mosaicked together, where only the maximum cell values of overlapping areas are kept. |
| 1.1 Segment Raster | This geoprocessing model reclassifies the input raster at remap values ranging from each individual power level to the raster cell value maximum. For each image reclassified this way, the submodel 1.1.1 Filter and Clean iteratively performs a filter and cleaning process. The intermediate output is then resampled and filtered to further generalize the cell values. |
| 1.1.1 Filter and Clean | This geoprocessing model performs a Majority Filter and Boundary Clean process five times, with the output from Boundary Clean becoming the next input to Majority Filter after each iteration. |
| 2 Process Vector | This geoprocessing model utilizes the submodel 2.1 Eliminate Selection to eliminate features under a certain area. The intermediate output is processed with Delete, Eliminate Polygon Part, and the submodel, 2.2 Eliminate Gap to further remove small areas, holes, and gaps. The intermediate output is then processed with Generalize and Integrate at a user-defined distance, which removes jagged edges and simplifies the polygons |
| 2.1 Eliminate Selection | This geoprocessing model determines if there are any features under a certain area to Eliminate. The model is run twice so that multiple features with shared boundaries will be eliminated. |
| 2.2 Eliminate Gap | This geoprocessing model determines if there are any gaps under a certain area to Eliminate, where a gap is an area with no data that is completely enclosed by multiple features (that is, it differs from a hole which is completely enclosed by a single feature). |