Methodology
Modus Operandi > Introduction
Our conceptual framework was influenced by the fact that the DMTI spatial data contains the unique postal code layer which provides population attribute information. Bracken and Martin (1991) in determining techniques for raster modeling population densities suggests the use of enumeration centroids, unit postal code locations, or user defined data points. For this analysis, enumeration centroids were not considered because the size of each Enumeration Area (EA) is dependent on the number of people that reside in it. In essence, EA’s can be seen as a method of visualizing population density itself because the more people that live in an area, the smaller the EA and the greater the number of EA’s in a specified region, the denser that area is in relation to surrounding regions. The number of centroid points that would be created using EA’s for density mapping would also be far fewer than by using our methodology.
Postal code locations could not be used as we found that after removing the road networks from our land use layer, these points would lie in places such as in the middle of the road and in industrial areas; therefore mapping spatial distribution with points originating from these areas would be a false representation of population density.
For this analysis then, we decided on a user defined set of data points to map our population distribution. When the road network was removed from the residential, agricultural, and mixed use commercial/residential layers, it created resulting layers with many polygons bounded by roads. For the larger municipalities, this was a superior method because these polygons can be converted to centroid points. A roadblock encountered was the question of how to allocate population data from the postal code points to the polygons of our residential layers. Although most postal codes were located within polygons making it simple to sum the population within those polygons, points also existed outside the polygons and in areas where there were no polygons were present. We have proposed a solution to this barrier in section 2.3.6 of the Methodology which provides a detailed description on the steps taken in spatial joining the population attributes from postal code points to the residential, agricultural, and mixed use commercial/residential polygons.
Modus Operandi:
Introduction
Land Use Preparation .
Buffering the Road Network
Removal of the Road Network .
Manual Editing with Aerial Photography
Postal Codes and Spatial Joins .
Centroids & Density
