types of combinations

Summary of Overlay Types when simplifying continuous data in layers

1. 1. Binary Layers
      1. overlay by multiplying two binary risk layers (“quality A” and “quality B”)

      	Quality B low hazard 0	Quality B high hazard 1
      Quality A low hazard 0	low risk	low risk
      Quality A high hazard 1	low risk	high risk

      or adding them

      	Quality B low hazard 0	Quality B high hazard 1
      Quality A low hazard 0	low risk	moderate risk
      Quality A high hazard 1	moderate risk	high risk

      open the overlay project to try these in a model
      use the geoprocessing model in the toolbox in the overlay folder to find the binary plus and times models

   2. Multiple Category Layers
      1. multiple boolean operators become very complex but can be done with a script
      2. overlay by adding or multiplying;

      	High Hazard	Mod Hazard	Low  Hazard
      High Hazard	high risk	moderate risk	low risk
      Mod Hazard	high risk	low risk	no risk
      Low Hazard	moderate risk	low risk	no risk

But how would you “hand pick” various levels of risk as shown above, when the weighting is not symmetrical as shown? (look at the “combine” tool)

3. 3. Index Layers
      1. use reclassify or map algebra to create indices
      2. overlay by adding or by multiplying has a different effect on the distribution of high and low results.
         From the file overlay project,
         use the overlay_examples tool in the overlay toolbox to run an index overlay.
   4. Layer Weighting (can be combined with Overlay Types #1-3)
      1. one layer (or more) is more important or has more influence on the outcome than others
      2. use raster calculator or the “weighted sum” tool
      3. can use weighted overlay tool
         (Note that the input is complicated, because this tool does both the simplification/reclass step and the overlay with weighting step in a single toolbox).