Although I had first selected to apply the Boolean approach for my spatial analysis project, I knew that  my Uncle will appreciate that if I could also present him with regions that were also close in meeting all our set of criteria. To achieve this I had opted to apply the weighted linear combination operation from the Multi-Critera Evaluation module in IDRISI.

                In order to carry out the MCE module, I would reassign a comparable weighted value to each of my factor criteria. The first to be reassigned was the total youth population between the age 15-24.
 
 

             I chose to use the sigmoidal function to reassign weighted value for this factor. The reason behind this decision was that the original percentage values  of youth age 15-24 for all GVRD regions were low to begin with; therefore my Uncle believed that a favourable region for his teahouse business should contain  a youth percentage that are close to 15 % at the least.  As a result, I decided that the percentage of youth population between 12.5% to 15% were a bit too low and therefore should not be considered to have a equal monotonical increased value as compared to percentage of youth population that are over 15%

            The next factor to be examined was the average income of GVRD regions

                   I applied the fuzzy operation from the decision support module of the Analysis manual in IDRISI. Using the 255 palette value of a raster image, I assigned the average income suitability  into 3 categories: those with less than $ 25000 annually, those between $25001 and $30000, and those with more than $ 30000.  Likewise I divided the the 255 palette value into 3 matching categories so that palette 85 represented regions with < $25000 average annual income, palette 170 represented regions with income between $ 25001 to $ 30000, and palette 255 represents regions with >$ 30000.

                 The fuzzy operation for suitability income rating had a linear relationship, meaning that the higher the value, the more suitable of the value.
 
 
 

             Likewise, I applied the same fuzzy linear relationship for the  never married children  at home (age group 18-24), and the part time worker in GVRD factor.
 
 
 
 
 
 
 
 
 

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