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DISCUSSION

Although the project is likely to be accurate on some level, there is always an element of error in every GIS project. No matter how perfectly an analysis is conducted, data is not always reliable or available. Also, the human interaction that goes into these projects shapes the outcome as decisions are made along the way. In retrospect, this project would likely turn out quite differently had the opportunity to try it again after completion been an option.

DATA:
This is where the majority of problems arose.
The census data used was from 2001, which places this project's accuracy behind by at least seven years. The more current census data was available, but did not open properly. Also, the census data should have preferably been considered a factor rather than a constraint. Origionally, the project was supposed to be valued as 0 in areas where were were no people of an ideal age, and 255 were there were the most. The census data was origionally put into the fuzzy module as factors and the result was blank rasters with no data. This led to starting again and adjusting the census data accordingly
The most regrettable issue with this project is that everything was a boolean image before it was put into the MCE module. At the time of the analysis, assigning values between 0 and 255 to areas of varying importance and suitability seemed daunting, so boolean images were used instead. Now that the project is completed, weighting values between 0 and 255 seems easy, and if it was not for time constraints, likely would have been redone. Both the Landuse and Age data layers were not used to their full potential as a result of this.
Some of the data (Libraries, Hospitals and Current Retirement homes) were created specifically for this project. As the data collection was not done by a professional, it is likely that there are elements of inaccuracy.

FACTORS AND CONSTRAINTS:
It is absolutely impossible to list every potential factor and constraint that could constribute to the ideal location of a new retirement home. The ones selected were based on personal preference, data availability and time. For example, not every GIS analyst may consider proximity to libraries to be an important factor in finding a suitable location for a new retirement home.

WEIGHTS:
The weights were based on personal opinion and preference. It is very likely that had another GIS analyst addressed the problem, the output would have changed in some way. It all depends on personal preference and the intent behind the analysis.

RESULT:
Overall the resulting output from the analysis was pleasing. Many projects encounter results that are inconsistent with practical knowledge. It is reassuring to compare the results with what areas such as Port Moody have to offer and realise that there is consistency.