30 March 2011

Suitability Analysis revisited

A little while ago I posted the old handwritten Suitability Analysis notes from when Steve Strom used these techniques in his studio. This four page set of Suitability Analysis notes is online now as a PDF (broken link fixed).  His description of weighted analysis lacks a graphic, so I created a digital version of both some of his graphics and a new Weight and Rate graphic that should help you work through it all as you look ahead to Monday's exam:To be clear, each grid shows the very same piece of land but being rated for a different issue (soils, slope, vegetation).  Presumably that is fairly objective.  But each individual criterion is then weighted based on relative importance.  In this case, Slope has rather subjectively been weighted as 5 times more important that Vegetation.  If you click on my graphic it will enlarge and be more readable.


Gauri Joshi said...

So, in general is weight more objective than rate, or is it the other way around?

David Tulloch said...

The weighting is often openly subjective, because it is an opinion about what is more important. The rating is more objective, since it often is performed based on measurements about known locations of features in the landscape.

Stephanie said...

I am not able to bring up the posted PDF with the Strom notes, was it taken down already? I wanted to read it over again before the exam

David Tulloch said...

Sorry about that. I fixed the link.

Charlotte said...

If we were asked where the best location for suitability would be, it would be the cell(s) where the value produced is the lowest?

So in the graphic produced, it would be either the cells where the value is 4 in the additive overlay or where the value of the cell is 10 in the weight and rate?

Now with that being said (and if it is correct), would that make it so the weight and rate method of find suitability is more accurate because only one cell is produced with the lowest value and therefore it would represent the best location for suitability?

David Tulloch said...

The best values can be either lowest or highest as long as you are consistent.

Unlike the Steiner and Strom additive examples, which use the lowest values as better, I use higher values as better because of the weighting.

But consistency is the key. If bigger is better in rating, then it must be true in the weighting too.