Hi Steve, following up on the thread from late last week. I have ran through my model quickly, in the same workflow as I would normally, in order to take screenshots. You can see here, I can add in my criteria metrics, which are a combination of unique categorical data (land use, zoning, brownfield sites) and continuous data (Distance from Highways, POIs, Fiber lines, etc.)
Below are screenshots of my categorical data (transformation pane), as well as an example of one of my continuous datasets for reference.
You can see the zoning and parcels are features that, before rasterizing, I queried to only have the criteria I want (and then rasterized before adding into the model). Which is why they are scattered, individual pieces. Please let me know if it is better to have the entire dataset in and rasterized, instead of scattered pieces. Below is the resulting output of my model - it is just one small polygon.
When running the model with only the Euclidean distance rasters, the model outputs a beautiful, suitability model (results that one would expect - though I did not attach any here).
Are there any obvious faults I have with my inputs? Or weighting issues you see, etc.? I value any feedback, comments, or ideas you have. Thanks for your time!