gis polygon map overlay intersection operation

Question

There are many algorithms for binary map overlay operation in vector data format which take two layers of map and produce resultant layer i.e overlaid layer as output. I am wondering whether there are any algorithms which take more than two layers say 3 layers simultaneously and produce the overlay result?

Answer 1

There are a variety of geographic computational overlay procedures available for multiple layers. These fall into the group of multiple criteria decision analysis, whereby multiple criteria (map)layers are standardized and combined (overlayed) to produce a resulting (map)layer. However, many of these are for raster data inputs!

If in fact you want to just combine vector data to produce an intersection, a procedural model would work best as @Thomas has commented. This can be done vis a vis python (standalone) or with model builder inside arcgis. Alas, there are other methods that can be used to script the procedural overlay process.

I would like you to think about what exactly you're aiming to do. Let's think about the following scenarios:

You have a vector polygon of some City, and your goal is to overlay all the industrial, residential and commercial land usage. This would leave you to subtract the different land uses from your City polygon, one by one. Or, you can merge your three land uses into one poylgon and subtract from your City polygon.

Given the wide range of multiple criteria decision analysis methodologies (eg. weighted linear combination), a raster methodology might be suitable if you're looking for the "optimal location" For instance, if you were looking for a location in the City that has an optimal combination of industrial, commercial and retail land use, weighted linear combination could be used.

Let us define our land use weights as 20%, 40%, 40% (industrial, commercial, retail). We must also standardize our land use layer values between 0 and 1. The following combination of layer values give the most optimal combination of the three criteria: 0.2, 0.4 and 0.4 = 1.