Suitability Modeling -- desired area of interest to have higher weight
Hi all,
I have a Suitability Modeling question for all. I am working with the modeler to visualize hot spot sites for potential healthcare facilities. There was a similar question posted recently, but I have an obstacle in the same vein.
For this healthcare site suitability, I created 5 mile buffer for existing hospitals within our County, to represent the area and people who have and dont have access to a hospital. I would want the model to run a higher weight/preference to the areas outside the buffer (to serve people who aren't within vicinity to an existing hospital). I rasterized the dissolved buffers, and classified it into two different fields (0,1) -- and have applied a 10-weight to areas not in buffer, and 1-weight in areas within said buffer. This should theoretically work, but all my other criteria inputs (proximity to roadway, pop. change, interchanges, land use, etc) also fall within the buffered area -- creating positive suitability within the Hospital Buffer.
I don't want to completely mask out the areas outside of existing hospital vicinity, and this be sole study site area, but I am wanting a higher preference to areas outside the buffer. Should I re-create Euclidean distance and kernel densities for data outside the buffer, and have those be the higher weighted inputs? Essentially splitting up the same data into two geographic areas, and two different rasters - but one being weighted more favorably? Other recommendations?
I know there was similar question posted recently, involving the potential for a negative (-) weight to counter-balance any positive weighted inputs, and I know that is not possible. I imagine I will be having to play around with the sensitivities and weighting scale. But I welcome any feedback or comment, if this post even makes sense haha.
Thanks for your time, and reading this wall of text.
