An interesting mathy problem I’m encountering:

Suppose I’m interested in finding out the price of certain plots of land. Except, the data I have access to doesn’t match exactly what I want to find out.

For example, suppose there exists 2 land plots, A and B, with shapes I know. They overlap; call this overlapping area C. I know the entire price of A, and I know the entire price of B. I want to come up with an estimate of the price of the overlapping area C, with this information.

One assumption comes to mind- the price of C will certainly be less than the individual prices of A or B. Now, if we scale this up, suppose the shapes I have are something like the following image:

Example Shapes

How can I compute the price estimates for every single uniquely overlapping area? Suppose I have drawn these shapes in python, in shapely. Can I do this algorithmically? This seems like a constraint satisfaction problem or an optimization one.

Something like This, except it’s not the intersections being the addition of all values.