The constraints and factors chosen for the Multi Criteria Analysis are based on my research, as well as my knowledge and understanding of the topic. It is crucial to note that these features are subjective, and do not fully encompass all the characteristics that affect the decision process. In retrospect, I feel that some important factors were left out of my analysis. Data of current hospital admission numbers, or emergency room data could have made the analysis more robust. The cost of land in various regions of Vancouver would have likely been of great interest to the potential developers, as well as taxpayers.

The relative weights assigned to the various factors are also subjective. They represent my ideas of their relative importance. Depending on the emphasis placed on each of the factors, the final results of the analysis can vary radically. This project embodies my perception of the importance, and may not be representative of what the city of Vancouver is the deciding factor in locating a new hospital. Additionally, the project does not take into account the likely distribution of the population in the future and does not deal with actual numbers of expected population growth or expected population distribution.

The Decision Wizard offers choices for the shape and type of function that best represents a given phenomenon. It also allows the user to set control points to anchor the data. All these choices, however, are capable of only approximating reality. The output of MCE attempts to model the world, but is never truly successful, because the extent of the interactions between the various factors is never fully understood. To quote Dr. Nadine Schuurman, I’d like to stress that “all model are wrong, [although] some are useful”. My model of the most suitable locations for a new hospital development attempts to combine important characteristics of Vancouver’s demographics, as well as regional geography to create the best representation of the problem and the solution.

Many of the dificulties I experienced during this project were related to my limited previous interactions with Idrisi Kilimanjaro, and GIS. Although many of the tools necessary for this project were presented in our labs, the creation of this project was a very difficult learning experience. One aspect I found particularly frustrating were the general error messages in the Decision Wizard. They offered little help with determining what part of the input was causing the errors, and stalled the MCE process for over 10 hours. In the end, starting the MCE from scratch seemed to fix the problem. I feel that this project gave me the confidence and the opportunity to utilize the skills I learned in my labs.