Figure 1: Study Site
The study area includes the ten Canadian provinces and the subdivisions within, choosing to ignore the territories because there is not a substantial population within them. Accurately identifying regions of broadband connectivity in the territories would require a different scale to the rest of the data and inclusion would skew the data with extreme outliers. This is supported by the population ecumene data published by Statistics Canada from the 2016 census. The 2016 ecumene data is the latest data considered reliable and, for the purposes of this study constitutes accurate enough data to conduct The resulting study area includes 5128 subdivisions covering 18,488 square kilometres at an average area of 1,137.3 square kilometres per subdivision. The population in this area is nearly 35 million or about 95 percent of Canada’s entire populace.
It should be noted that this limits the scale of the expected results to the subdivision level. However, the data collected provided much-needed insights as well as a replicable model for determining areas that are in need of further broadband development. Time limits data in this study to four-year intervals as the most applicable data source is the Canadian census, conducted every four years.
With increased bandwidth comes better connectivity and greater access to data. Developing speeds in only urban centers leaves Canadians living in rural areas at a great disadvantage when compared to their well-connected counterparts. With certain types of broadband infrastructure, such as fibre optics, the data transfer speeds vastly exceed that of other methods. Speeds are limited by the number of fibres in the wire, the quality of those fibres, and the power of the data receiver at the end of the connection (Grzybowski, L., Hasbi, M., & Liang, J. 2018). Therefore, the study area required large data sources to construct a spatial Multi-Criteria Evaluation.