My first approach to finding the most suitable place to live in Vancouver is to find as much data as possible that fit into the nine determinants (listed below) for assessing the quality of living. I then realized it is too much work and too time consuming to find all the data, therefore, I only used the data that is available in the S drive along with some population data from census 2001.

Vector data/shapefiles

Part of the data manipulation was done in ArcMap, since some shapefiles, such as the bike routes, skytrain stations, and bus stops are in vector-based formats. In order to use them for analysis, I have to first import all the vector data from ArcMap to Idrisi. This can be done by importing ESRI shapefiles (vector data) into IDRISI using the SHAPEIDR function.

As for the population data, more manipulation is needed. I first I had to go through the process of converting all the data from the census to the end product as a database file with a primary key (dauid) so that I can join the data to the da shapefile for further data analysis. Since the attribute table only contains the total population values for the enumeration areas, I had to create new fields to calculate the population density.

Population density simply equals to the total population over the total area.

Once all the data manipulation is done in ArcMap, I can start importing the vectors data from ArcMap to Idrisi and rasterizing all the vector images.

Click here to see the models for the conversion of vector images to raster images.

Here is a sample of the raster images.

Raster data When I use the Polyras module to convert the population density shapefile to a raster image, Idrisi only recognizes the ID numbers and automatically converts the ID numbers instead of the population density values, therefore, I had to create an attribute value file (.avl) to assign all the ID numbers with the population density values in Idrisi. Once this is done, I can then display population density for further analysis.

Rasterized according to the ID numbers	Assigned population density values to each ID numbers.

With the raster image "Landuse", since Landuse contains a lot of useful information which I needed to find the most suitable place, such as residential areas, parks, commercial, institutional, and industrial areas, all I need to do is just perform the edit and assign module to create Boolean images with the targeted areas as 1 (red) and non-targeted areas as 0 (black).

Click here to see the macro modelers.