Tag Archives: Housing

Vancouver-Ottawa Housing Affordability

Lab 4: Comparing Vancouver and Ottawa Housing Affordability according to housing cost and household income

Affordability shows a visual comparison of Vancouver-Ottawa housing affordability using the manual breaks classification method. As opposed to displaying housing cost, which includes price information alone, ‘affordability’ refers to the ability of a single or cumulative income to purchase a house of some cost. This makes it a better indicator of housing affordability than housing cost as it integrates income and cost information. As determined by the 12th Annual Demographia International Housing Affordability Survey 2016 (Wendell Cox Consultancy & Performance Urban Planning: Christchurch, New Zealand), housing affordability rating categories range from a median multiple of under 3.0 being ‘affordable’ to over 5.0 being ‘severely unaffordable.’ This makes ‘affordability’ a potentially good indicator of a city’s ‘livability.’ It is worth noting also, that housing affordability analyses may only give information on single detached housing whereas a city’s livability refers to multiple residential types such as single detached housing, multiplex housing, apartments, condominiums, lane housing, and school housing.

Accomplishment/s:
Analyzed interregional housing affordability according to quantitative survey census tracts

Organized and displayed findings according to differential break classification methods

Quantitative Data Classification for Vancouver Housing Affordability

Lab 4: Spatial Analysis of Vancouver Housing Affordability (using census tracts)

dataclass shows examples of maps utilizing four classification methods in representing housing affordability with Vancouver Census Tracts.

These four classification methods (Natural Break, Standard Deviation, Equal Interval, and Manual Break) help GIS users to display large amounts of complex data simply, as maps. Ultimately, their goal is to relay information in a simple and concise way that caters to the needs and interests of their audience. This could mean withholding information deemed to be unimportant or distracting to the viewers and therefore, GIS users must keep in mind the  different interpretations, complications, and ethical consequences that may arise when organizing data and displaying information in this way. In the case of Vancouver housing affordability, there is a difference between representing the spatial distribution of Vancouver housing affordability as a journalist versus a real estate agent.
A journalist would likely display a map that uses a standard deviation classification method to show average, above-average, and below-average Vancouver housing cost. Since a journalist’s audience would include people other than prospective house buyers, a general idea of average, relatively expensive, and relatively cheap housing would be sufficient and specific prices might not be needed. The ethical implications that arise, however, would be the suggestion of socio-economic exclusion relative to the location of one’s home. A real estate agent, however, would likely opt for a map that uses the natural break classification method so as to be able to relay specific price ranges along with the spatial distribution of similarly priced housing in Vancouver to prospective buyers.