First post ever and I'm hoping you can help.
We collected perception data by having people compare photos side by side. Then we ranked them using an algorithm that scores images that "won" these comparisons more as 1 and images that lose all the time as 0.
We plot these images on the map, with their associated scores and I get the map attached. For each color cell, there were 2 images, facing opposite directions, each with their own score. The cell color is the mean of those two colors.
Any interpolation model I fit gives me an RMS value of around .12 so I know the model is terrible.
Is there any other analysis I can do on this spatially if I can't fit a model? I was planning on referencing that model to crime data and see if perception of safety and actual crimes align in anyway. I was also going to look at housing pricing, etc. But since I can't make a good model, am I hosed?