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Spatial Analysis
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The MCE Analysis

The images below show the fuzzy factor images generated by Decision Wizard.  Note that I assigned different factors different values in the monotonically decreasing linear function based on the attractiveness of the transit service.  The attractiveness, from the most attractive to the less attractive, is in the following order: 

Skytrain stations > Bus Exchange = B-Line Buses > Buses > Peak hour buses. 

A larger “d” values are assigned to more attractive services because people are more likely to walk longer distance for more attractive services.  

busfactorexchangefactorfastbusfactorpeakfactorstationfactor

Fig 1.  Factor images generated by the MCE analysis.  The factors, from left to right, are: conventional buses factor, bus exchange factor, B-line buses factor, peak hour buses factor, and skytrain station factor. 

Result 1 -- Transit usage in the City of Vancouver based on distance and attractiveness of different mode of public transit

Then we continue into the AHP analysis.  The weighting of each factor can be seen in the “methodology” page of this website.  The weighting of each factor is also determined by the attractiveness of each transit service.  Fig 2 on the right shows the resulting MCE map.  High score indicates areas people more likely to use transit while low score indicates areas people less likely to use transit.

Result 2 -- Areas that need better transit services

The third step is to determine areas that need better transit services.  A score from 0.5 to 23.5 (low score) is identified as areas that need better services in order to encourage people to use public transit.  After eliminating park areas, I calculate areas for each group with low score (the grouping is done with the module “group”).  Areas larger than 0.6 km2 are determined to be communities that should have priority for improving transit services.  Fig 3 on the right shows the map of areas that need better transit services in green. 

Result 3 -- Areas suitable for higher population density growth

The last step of this project is to find areas suitable for higher density growth because the livable strategic plan encourages growth within the present urban areas.  Park areas are eliminated because there should not be any development in parks.  High population density communities are also eliminated because the density is already high there.  The other factor being eliminated is the areas with high density residential and mixed use areas because they are already higher density development according to the strategic plan.  Transit usage, however, should be high (a high scores in the AHP map) because we do not want everyone living in a high density neighborhood to be driving.  Combining all these factors we have the following map of suitable areas for higher density development.  Fig 4 shows areas suitable for higher density growth.

The result is obvious.  Large pieces of land along Granville Street are suitable for concentrating growth.

usage
Fig 2.  Result 1 --Transit usage based on distance to transit.  Highest score is shown in red and Lowest score is shown in dark blue.


betterservices
Fig 3.  Result 2 -- Green areas are communities that need improved transit services. 

suitable
Fig 4.  Result 3 -- The light yellow areas are communities that can support higher density growth.