New equal Earth 2-D map offers better perspective of the world
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The below list of featured spatial datasets will aid in assessing which areas of Vancouver are deemed most accessible: A list, distribution map and point data for all TransLink bus stops in the Metro Vancouver Area; A list and distribution map of all schools, community centres, health care facilities, cultural spaces, and public parks in the Metro Vancouver Area; A digital elevation model DEM for the Metro Vancouver Area; A spatial map of all Metro Vancouver roads; and Census tract data concerning the rental affordability of housing in Metro Vancouver.
The most accessible areas in Vancouver will be determined based on their proximity to each of the amenities and resources listed above, as well as local housing prices.
Thus, the priority for determining the accessibility of an area will be based on distance from public transportation, services, and the slope or gradient of roads or sidewalks in the area.
Combining these data sets, we will identify physically accessible areas, overlaying clustered services and lower cost areas to determine a compromised, broader accessibility.
In order to compile this information, we used a wide variety of spatial tools including clip, intersect, merge, union, raster-to-polygon conversion, dissolve and project. We also performed non-spatial analyses, using the field calculator and the select-by-attribute function. To determine accessibility at the smaller scale of Greater Vancouver, we initially combined elevation data in the form of a Digital Elevation Model DEMhydrology, roads, bus stops, and rapid transit stations, creating buffers around the combined transit stops.
We created 2 buffers, the first of m and the second of m. Areas outside of these two buffers were deemed least accessible. We then used the DEM to create slope information.
New equal Earth 2-D map offers better perspective of the world
Using the guidelines of the British Columbia Building Access Handbook fromthe maximum gradient for accessibility was determined to be 1: We used this grade to remove areas that were too steep for a manual wheelchair user from within the m buffer. However, we argue that accessibility is not merely physical, but must consider the social and economic dimensions of accessibility. To this end, we incorporated housing price data as a loose surrogate for economic accessibility, using median rental prices over census tracts collected by Census Canada.
We normalized rental costs by the average number of rooms for the census tract. To address some of the social wellbeing dimensions of accessibility, we incorporated service information. Using point locations for health and education services, we created a density map across the region to identify sites of service clusters, setting the parameters of the raster layer to the extent of Greater Vancouver and the cell size to 25m, in keeping with the DEM and acknowledging the ground extent of buildings.
Having spatialized the information of these three forms of accessibility physical, economic and socialit was evident that the accessibility criteria yielded often contradictory accessible spaces.Map projections of the Earth
Seeking to explore the compromise between these three components, we classified each layer using natural breaks and three classes. We assigned new values between one and three for each of these classes, one being the most accessible cheapest rental, most services or within the most constrained buffer zone and three being the least accessible most expensive rental, least services or outside of the two transit-accessible buffers.
With these normalized values it was possible to combine the three layers — using the union tool — to derive a single score.
The greatest accessibility was clearly within Vancouver and a greater array of socio-cultural feature information was available for this larger scale, spurring us to develop a map of the City of Vancouver.
The additional features included were community gardens and farms, cultural spaces, homeless shelters, and community centers. Combining these with existing information on education and health, we created a new density map, classifying it once more into three classes using natural breaks.
We clipped the existing physical accessibility information and normalized rental rates to the city of Vancouver extent. We reclassified the rental rates, using natural breaks and assigned normalized values of one to three for each of the classes, repeating this classification between one and three for the physical accessibility and service layers.
Finally, we unioned the physical, economic housing and sociocultural service layers, calculating a common, composite accessibility score and symbolizing accessibility using manual breaks to determine accessibility in the City of Vancouver.
If we consider the Greater Vancouver Area as a whole, commercial centres in Surrey, Delta and New Westminster are also considered to be accessible. Within this m range, we have also defined a smaller range of m that applies to individuals using a manual wheelchair who are not able to travel as quickly in a 5 minute time period. This map also highlights areas that are out of range, usually accounting for regions that are not accessible by transport, but also very steep.
These regions include places like Wreck Beach, Tower Beach, and the south-western corner of Vancouver.
Map projections and distortion
In looking solely at services fig. These services include health care facilities, community centres, community gardens, education facilities, and homeless shelters. Density in the form of a heat map, as well as point data are provided in fig. The map clearly shows that the farther away from the downtown core one moves, the lower the density of services. One important aspect to note is that there are more homeless shelters clustered in the downtown area, specifically the Downtown Eastside.
Not only may this have skewed the data and increased the average and density, but is indicative of larger socioeconomic trends in the city. This area has a higher than average compared to the rest of the city homeless population, which accounts for the presences of homeless shelters.
While geographically this area may be most suitable and accessible for people with mobility issues, there are other qualitative factors that may deter individuals from living or working in a certain area. Another area whose services cater to those with mobility issues is the corridor that runs North-South between Granville Street and Cambie Street.
This is best seen in fig.
Provided that proximity to healthcare was a primary concern, this area would considered very desirable; however, there is a new hospital and variety of healthcare facilities that are being constructed in the region with the highest density of services, making the area perhaps more accessibility with those who require immediate health care to help cope with their mobility issues.
Its scale is 1: Any line you measure on this globe—no matter how long or in which direction—will be one forty -millionth as long as the corresponding line on the earth. In other words, the scale is true everywhere. This is because the globe and the earth have the same shape disregarding the complication of sphere versus spheroid. Now suppose you have a flat map that is 40 million times smaller than the earth.
See the problem coming? Instead of comparing a big orange to a little orange, we're comparing a big orange to a little wafer. This map also has a scale of 1: The stated scale of a map is true for certain lines only.
Which lines these are depends on the projection and even on particular settings within a projection. We'll come back to this subject in Module 4, Understanding and Controlling Distortion.
ArcGIS – ArcGIS Accessibility Mapping Project
Not all of the earth's curves can be represented as straight lines at the same fixed scale. Some lines must be shortened and others lengthened. There are three common ways to express map scale: Linear scales Linear scales are lines or bars drawn on a map with real-world distances marked on them. To determine the real-world size of a map feature, you measure it on the map with a ruler or a piece of string.