Geog 181 Lab 5
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University of Waterloo *
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Course
181
Subject
Geography
Date
Dec 6, 2023
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Pages
5
Uploaded by CaptainBoulderMouse32
GEOG 181 -Lab 5 (48 Marks Total) Due October 26th @ 4 PM
Part 2: Creating Choropleth Maps with QGIS and using the Atlas Function
Tasks:
1.
Create the following choropleth maps. Export them as png files and insert them
into your assignment document. Also for each map, include a short discussion
related to your rationale for choosing the color scheme (i.e. is it qualitative,
sequential, or diverging) and classification method (i.e.: equal interval, quantile,
natural breaks, etc).
a.
Percent of population that is 65 and over for each census subdivision in the
Toronto Census Metropolitan Area (CMA) (10 marks).
I chose a sequential colour scheme for this map. I believe that it shows the data the best
because the larger the number of people in an area, the darker the colour is. It allows you to
visualize the data more easily than the other colour schemes. I used the natural breaks
classification method with 7 different categories. This allows the data to be distributed into more
relevant categories. In other classifications, the category for the largest data points was too
large to be accurately divided. The natural breaks classification creates the categories based on
the patterns in the dataset, so it can accurately break up the categories.
b.
Percent change of population from 2006 to 2016 for Canadian census divisions.
(10 marks)
I used a sequential colour theme to show the increase of change in the population. I used the
colour green because land masses are generally represented with the colour green and the
variation in shades is easily visible. Choosing a Classification method for this map was slightly
harder because of the number of areas, but the natural breaks classification method still
represents the data the most accurately.
c.
Median total income of households of Kitchener - Waterloo - Cambridge CMA
census tracts (10 marks)
I chose a sequential colour theme for this map because it accurately shows the data and shows
the increase in data as an increase in darkness. It makes the map easy to read as most people
know without a legend that if colours are getting darker, something is increasing. I used the
natural breaks classification method again because the way it divided the data shows the
different categories the best. I increased the number of categories to 7 so the data ranges are
not as large and are more accurate.
2.
Create 3 choropleth maps based on a variable from the Canadian census
divisions. Remember that choropleth maps should be map rates or ratios, not
counts or totals. Use the Atlas functionality from the tutorial to automate their
generation and export each image as a png at 300 dpi. For each map briefly
explain the spatial patterns present. (10 marks for Map Design, 6 marks (2
marks/map) for spatial pattern present)
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The spatial patterns in this map show that the majority of people over 85 in Nova Scotia
live away from crowded cities. Halifax has a very low number of people over 85 but is a very
busy city with a lot of action and noise. The division that has the most people that are over 85 is
in the southern part of the province.
In this map, the spatial patterns show that as you move farther south, more people are
over 85. You can also see that this is true for locations closer to lakes. Not a lot of people over
85 live in northern or colder rural areas.
The spatial patterns from this map again show that not many people who are over 85 live
in the northern parts of the province. There are a lot of people over 85 that live in the Sunshine
Coast and Nanaimo divisions, which are side by side. This area most likely has lifestyle
conditions that are favourable to this population.
3.
Automating tasks in GIS is a very valuable tool. Aside from Map Generation, list
two other tasks where automation would be useful in GIS (hint, think about file
management, and some of the tools used in GIS). (2 marks).
Automation would be useful for joining fields. When we were learning how to join the
fields and had to figure out what properties patched the shape files, it would have been helpful
for the proper file to automatically join with the selected shape file. Automation would also be
useful in creating maps with different features but in the same area. It could automatically filter
the maps to only include certain areas.