GGRC12
Transportation Geography
Professor
Steven Farber
Assignment
1: Describing Transportation and Land Use Patterns
Due
February 25th, 11:00am
In this assignment you are
going to take on the role of a transportation advisor to the City of Toronto.
Specifically, your task is to advise the mayor on the current patterns of land
use, transportation infrastructure, and travel behaviour in Toronto, with the
intention of making basic policy recommendations for transportation development
options. To complete this work, you have been provided a collection of
geospatial datasets representing the current transportation infrastructure in
the area, and counts of different types of trips for each traffic analysis zone
(TAZ) in the region. The assignment is
arranged into the 3 tasks below. Note that underlined terms contain hyperlinks
to additional learning resources.
The data are combined into
the file geodatabase named GGRC12_Lab_One.
In it you will find a Feature Dataset named TransportationFiles.
The dataset includes the following Feature Classes:
·
Highways – A Line feature class containing all the
highways in Toronto.
·
Municipalities – A polygon feature class containing the
boundaries of the former Metro Toronto municipalities.
·
TTC Routes – A line feature class containing all TTC bus,
streetcar, and subway lines.
·
TAZ06_TTS2011_Toronto – A polygon feature class containing the
boundaries of the City’s TAZs as well as a collection of trip data collected
from the Transportation Tomorrow Survey.
·
TransitStops_Access_AM_Peak – a polygon feature class showing the number of
unique transit trips accessible within a 400m walking trip. This can be
considered a transit accessibility indicator for the AM peak period (6am-9am).
You must download and extract
the contents of the assignment zip file to a folder which you have write-access
to. All of your work should be backed up off of the lab computers at the end of
each work session.
In this component your
objective is to create maps and provide a description of seven basic
transportation characteristics in Toronto:
a)
The locations of major
highways
b)
The locations of subway,
streetcar, and bus routes
c)
The bus frequencies in
Toronto
d)
The spatial patterns of where
people live in the city
e)
The spatial patterns of where
AM work trips are destined
f)
The spatial patterns of where
transit trips occur
g)
The spatial patterns of where
driving trips occur
Let’s begin by adding some layers for the first map. We will use the Municipalities layer as a background and
display the Highways layer on top.
You can change the order of the layers to make sure that the highways are on top of
the municipalities.
Next we need to adjust the
symbology of the layers. Right click on Municipalities in the table of contents
and select Properties. Choose the Symbology tab click on the current symbol being used to
enter the Symbol Selector. Choose the
“tan” fill symbol and click OK. Then click the Labels tab on the properties dialogue. Check the box
for “Label features in this layer” and change the Label Field to “Area Name”. You can watch a quick video about
labels here. Click OK to close the dialogue box. Follow
the same steps to change the line symbol used for Highways to the ESRI Style Highway Symbol (solid red, 3.40 width).
Now that we have all of the
layers on our map displayed properly, we can add map elements such as a Legend, North Arrow, Scale Bar, and Title
to our map by working with the layout. You can view a brief video on how to make a
layout here. You will also want to make sure that the
paths are stored as relative paths. To do
so, look under the File menu and
click Map Document Properties. Here
you will see an option to “Store relative pathnames to data sources” make sure
to click this box. When your map is complete, use File, Export Map to save a copy of the image
as a JPG file. You can then paste the JPG into your Word document.
Additionally, you should use File, Save
As to save your work as an MXD file. Choose a name unique to this map, such
as TaskOneHighways so that you can
come back to this exact layout in the future if you ever need to.
Take a look at the map you’ve
made and make some notes on the distribution of highway infrastructure around
the City of Toronto. Where are the highways? Which areas are well served or
underserved?
Task 1b: Public Transit Routes
We are next going to repeat
these steps for the city’s transit infrastructure provided by the TTC. We can
start by saving a copy of the map as TaskOneTTC
so we don’t lose our highway map from before. We can keep the same
background municipalities layer, but you can remove the Highways layer by unchecking it in the table of contents or by
right clicking it in the table of contents and choosing Remove. In its place, add the TTC_Routes
layer. We will need to change the symbology to differentiate between subways,
streetcars and busses. From the Symbology
properties, change the type to Categories,
and select Unique
Values. Change the Value Field to “rt_typ_txt”, which
describes the type of route using text. Click “Add All Values” to populate the
table with the different types of routes. You can now modify the symbols for
each route type with the Color Ramp,
or by right clicking on individual symbols and choosing “Properties for
Selected Symbols”. I recommend using 1 point width for busses, 2 points for
streetcars and 3 points for subway. That way the various modes will be more
visible. With all the lines on display, the outline colour of the municipal
boundaries symbol can be made thicker and brighter to make it more visible.
Follow the steps in Task 1a
to produce and export a layout to jpg and save your MXD file.
Take a look at the map you’ve made and make
some notes on the distribution of TTC public transportation infrastructure
around the City of Toronto. Where are the subways, streetcars and busses? Which
areas are more and less served by the 3 modes of public transit?
Task 1c: Transit Level of Service
Create a new copy of your MXD
file and call it TaskOneTransitAccess.
For this task, we can uncheck the TTC layer and add the TransitStops_Access_AM_Peak layer. This layer contains 400m walking
buffers from each bus, streetcar and subway stop. Additionally, for each
polygon, the number of transit trips that can be reached within the AM peak
period (6-9am) is recorded. If you right click on the Access layer in the table
of contents and select Open
Attribute Table, you will see two fields,
NumTrips and NumTripsPerHr. We will make a map displaying the values of NumTripsPerHr.
Our first step is to bring the municipalities layer to the top of the display
order, and change the tan fill color to “no color” (i.e. transparent). We are
going to make a choropleth map using the NumTripsPerHr variable. Bring up
the symobology properties for the TransitStops_Access_AM_Peak layer and select Graduated Colors under the Quantities heading. Set the value field to NumTripsPerHr. On the
right, we need to set the classification method. For now, let’s use Natural Breaks
(Jenk’s) with 7 classes. Next, change the color
ramp to one of monochromatic options (i.e. only 1 color with different
degrees of brightness) since we are displaying values from low to high. Next,
set the symbol outlines to be transparent. Finally, right click on one of the
symbols, and choose Format Labels.
Select Number of Decimal Places and
use 0 decimal places. This will round the label values to the bus per hour.
Click OK.
Follow the steps in Task 1a
to produce and export a layout to jpg and save your MXD file.
Take a look at the map you’ve made and make
some notes on the transit accessibility. What locations have access to the most
transit trips? Which have the least? Keep in mind that any place outside of a
buffer is more than 400 meters from the nearest transit stop.
Task 1d: City Population
Create a new copy of your MXD
file and call it TaskOnePopulation.
For this task, we can uncheck the TTC layers and add the TAZ06_TTS2011_Toronto. This layer contains the TAZs for the City of
Toronto and a series of transportation variables associated with each zone. Our
first step is to bring the municipalities layer to the top of the display
order, and change the tan fill color to “no color” (i.e. transparent). Next,
right click on the TAZ layer and select Open
Attribute Table. The table contains a
listing of all the TAZ records and
their unique identification numbers in a field
called GTA06. The other fields in the
table are as follows:
Field |
Description |
GTA06 |
TAZ
ID for 2006 TAZ definitions |
num_pers |
TAZ
population |
wrkdestamp |
Total
number of work trips arriving in TAZ during AM peak |
drvpro24h |
Total
number of daily driving trips leaving from TAZ |
psgpro24h |
Total
number of daily car passenger trips leaving from TAZ |
trnpro24h |
Total
number of daily transit trips leaving from TAZ |
othpro24h |
Total
number of daily trips by all other modes leaving from TAZ |
totpro24h |
Total
number of daily trips by all modes leaving from TAZ |
Hectares |
Area
of TAZ measured in Hectares |
In this step, we want to
visualize the pattern of where people live in the city. To do this, we are
going to make a choropleth map using the num_pers variable. Bring up the
symobology properties for the TAZs and select Graduated Colors under the Quantities
heading. Set the value field to
num_pers, and the normalization field
to Hectares. This will produce a map of population per hectare, or in other
words, a population density map. On the right, we need to set the classification method. For now, let’s use Natural Breaks
(Jenk’s) with 7 classes. Next, change the color
ramp to one of monochromatic options (i.e. only 1 color with different
degrees of brightness) since we are displaying values from low to high. Next,
set the symbol outlines to be transparent. Finally, right click on one of the symbols,
and choose Format Labels. Select Number of Decimal Places and use 0
decimal places. This will round the label values to the nearest person. Click
OK.
Follow the steps in Task 1a
to produce and export a layout to jpg and save your MXD file.
Take a look at the map you’ve made and make
some notes on the population density distribution in the City of Toronto. Where
are the densest neighbourhoods? Where are the least dense? What pattern does the density distribution
display? Are any of the theoretical models apparent (ie: perfectly monocentric,
polycentric, flat)? How does the revealed pattern differ from or mimic the
theoretical patterns?
Task 1e: Work Destinations
Create a new copy of your MXD
file and call it TaskOneWorkPlaces.
For this task, we are going to continue working with the TAZ06_TTS2011_Toronto layer. In fact, all we need to do is change
the value field in the symbology
properties from num_pers to wrkdestamp. Make sure you are still normalizing by
Hectares and using 7 classes in a natural breaks classification.
Follow the steps in Task 1a
to produce and export a layout to jpg and save your MXD file.
Take a look at the map you’ve made and make
some notes on the work trip destination density distribution in the City of
Toronto. We can consider this map to be an indication of where jobs are located
throughout the city. Where are the densest employment neighbourhoods? Where are
the least dense? What pattern does the
employment density distribution display? Are any of the theoretical models
apparent (ie: perfectly monocentric, polycentric, flat)? How does the revealed
pattern differ from or mimic the theoretical patterns?
Task 1f: Transit Mode Share
Create a new copy of your MXD
file and call it TaskOneTransitTrips.
For this task, we are going to continue working with the TAZ06_TTS2011_Toronto layer. In fact, all we need to do is change
the value field in the symbology
properties to trnpro24h, and normalize by totpro24h. This produces a map of
transit mode share for each zone. More specifically this is the total number of
transit trips originating from each zone (all day) divided by the total number
of trips originating from each zone (all day). Make sure you are still using 7
classes in a natural breaks classification.
Follow the steps in Task 1a
to produce and export a layout to jpg and save your MXD file.
Take a look at the map you’ve made and make
some notes on the transit mode share pattern across the city. Where is transit
mode share highest? Where is it the lowest? What is the overall shape of the
spatial distribution? Do you see any outliers in the distribution (high areas
surrounded by low, or vice versa)? Where are they? Can you explain why they
exist?
Task 1g: Driving Mode Share
Create a new copy of your MXD
file and call it TaskOneDrivingTrips.
For this task, we are going to continue working with the TAZ06_TTS2011_Toronto layer. In fact, all we need to do is change
the value field in the symbology
properties to drvpro24h, and normalize by totpro24h. This produces a map of
driving mode share for each zone. More specifically this is the total number of
driving trips originating from each zone (all day) divided by the total number
of trips originating from each zone (all day). Make sure you are still using 7
classes in a natural breaks classification.
Follow the steps in Task 1a
to produce and export a layout to jpg and save your MXD file.
Take a look at the map you’ve made and make
some notes on the driving mode share pattern across the city. Where is driving
mode share highest? Where is it the lowest? What is the overall shape of the
spatial distribution? Do you see any outliers in the distribution (high areas
surrounded by low, or vice versa)? Where are they? Can you explain why they
exist?
Task 2a: Calculating and
Mapping Car Mode Share
The goal of this task is to learn
how to conduct basic calculations in the attribute table. First, create a new
copy of your MXD file and call it TaskTwoCarTrips.
We are going to calculate the total number of daily trips by car leaving from each
TAZ. To do this, we have to add a new field in the attribute table of the TAZ06_TTS2011_Toronto layer.
To do this task, open the attribute table of TAZ06_TTS2011_Toronto layer. Click on table options, and select “Add
Field”. Set the name of the field as “carpro24h”. Next, we need to set the type
of the field. Let’s use Double. Click OK.
In your attribute table, right click on the new
field “carpro24h”, then click “Field Calculator”. In the dialogue box, we need to write the formula of
carpro24h. Write “[drvpro24h] + [psgpro24h]” in the bottom box, and click OK.
Now we have the total number of car trips leaving from each TAZ.
Than
we can make a choropleth map using the new variable. All we need to do is change the value field in the symbology properties
to carpro24h, and normalize by totpro24h. This produces a map of car mode share
for each zone. More specifically this is the total number of car trips (driving
plus car passenger) originating from each zone (all day) divided by the total
number of trips originating from each zone (all day). Make sure you are still
using 7 classes in a natural breaks classification.
Follow the steps in Task 1 to
produce and export a layout to jpg and save your MXD file.
Task 2b: Comparison between car trips and
transit trips
The goal of this task is to compare
two variables using the attribute table. To do this task, create a new copy of
your MXD file and call it TaskTwoCarvsTransit.
To do this task, open the attribute table of TAZ06_TTS2011_Toronto layer. Click on table options, and select “Add
Field”. Set the name of the field as “CarVsTransit”. Next, we need to set the
type of the field. Let’s use Double. Click OK.
In your attribute table, right click on the new
field “CarVsTransit”, then click “Field Calculator”. In the dialogue box, we need to write the formula of the
ratio of car trips vs. transit trips. Write “[carpro24h] / [trnpro24h]” in the
bottom box, and click OK. Now we have the ratio of car trips vs. transit trips leaving
from TAZ.
Next, we can make a choropleth map to see in which areas car trips are more
than transit trips, and vice versa. All we need to do is change the value field in the symbology properties
to CarVstTansit. On the right, we need to set the classification method manually. Click “Classify…” to open the
dialogue, and set the method to “Manual”, and choose 4 classes. In the right
box, we can set the break values as “1, 5, 10, 100”. Click OK.
This produces a map of ratio of car vs. transit
trips from TAZ. We can change the color to green if the ratio is less than 1,
which means transit trips are greater than car trips. And we can use gradations
of red to show areas where car trips are more than transit trips.
Follow the steps in Task 2a
to produce and export a layout to jpg and save your MXD file.
Take a look at the maps you’ve made and make
some notes on the car trips share in the City of Toronto. Where are the
neighbourhoods that have highest car mode share? Where are the least car mode
share? In what areas is transit share higher than car share? What’s the transit
supply in these areas? Can you propose any hypothesis that suggests the
relationship between transit supply and travel mode share?
The goal of this task is to
describe the relationship between transport infrastructure supply, land uses,
and travel behaviour. To do this, your job will be to produce combination
variables, overlays of the various maps we’ve created so far, and/or create side-by-side
comparisons of maps when appropriate. In general, the idea is to look at
relationships between transportation supply, population and workplace density,
and mode share characteristics. You should be choosing two of the following comparisons:
-
Highway locations &
driving mode share
-
Transit supply & transit
mode share
-
Transit accessibility &
transit mode share
-
Population density &
driving mode share
-
Population density &
transit mode share
-
workplace density &
driving mode share
-
workplace density & transit
mode share
You may choose to compare
maps side by side simply by inserting JPGs at identical spatial scales into a
word document, but in many cases, it will be better to overlay line features on
top of choropleth maps to discover the spatial relationships. You now have the
skills to explore your different mapping options freely. Based on the readings
and lectures we’ve discussed in class, specifically those pertaining to
transportation/land use relationships, discuss your comparisons in terms of hypothesized
and observed relationships between transportation and land use characteristics.
The goal of this task is to learn
how to compute mode shares for specific areas that are selected using a query. To
do this, your job is to compare the mode share of three parts of the city: TAZs
touching subway lines, downtown Toronto, and Scarborough town center.
First, we need to select the
three parts from the existing polygon.
Task 4a Select TAZs that have subway lines.
Create a new copy of your MXD
file and call it TaskFourTTC.
Click “selection”, and open the “select by
attributes” dialogue. Set layer as “TTC_Routes”. Method: “Create a new
selection”. In the bottom box, write “rt_typ_txt = 'Subway, Metro'”, to select
the subway lines from the TTC_Routes
layer. Click OK.
Next, we are going to select TAZs that have subway
lines. Click “selection”, and open the “select by location” dialogue. Set the
target layer as “TAZ06_TTS2011_Toronto”.
Then set the source layer as “TTC_Routes”.
Check the box for “use selected features”. Set
spatial selection method for target layer feature(s) as “insert the source
layer feature”. Click OK.
Right click on the “TAZ06_TTS2011_Toronto”,
choose “data”à”export
data”. Open the dialogue, and export selected features. Then you can add the
saved features as into a new layer. Let’s call the new layer “TTC_TAZ”.
Task
4b Select Toronto downtown area
Create a new copy of your MXD
file and call it TaskFourDT.
Similarly, we first need to select the TAZs that
located in Toronto downtown. We can do it by clicking on “select features” and
choose “select by polygon”. Then we can draw a polygon in the downtown area of
Toronto, and export it as a new layer “DT_TAZ”.
Task
4c Select Scarborough town center
Create a new copy of your MXD
file and call it TaskFourSC.
Similarly, we first need to select the TAZs that
located in Scarborough
town center. We can follow the steps in task 4b, by clicking on “select
features” and choose “select by polygon”. Then we can draw a polygon in the Scarborough,
and export it as a new layer “SC_TAZ”.
Next, let’s do some summaries.
Finish the following table that contains overall transit and car mode shares
for these areas. To obtain the statistics of the areas, you can open the
attribute table, and right click on “statistics”. For example, to calculate the
transit trips in downtown Toronto, you can open the attribute table of layer
“DT_TAZ”, and right click on “trnpro24h”. Then you can see the summary of this
field. Fill all the blanks in the table, and discuss your results.
Area |
Transit trips |
Car trips |
Total trips |
Transit share |
Car share |
TAZs with subway lines |
|
|
|
|
|
Downtown Toronto |
|
|
|
|
|
Scarborough town center |
|
|
|
|
|
The whole city |
|
|
|
|
|
Discuss the results in the summary table. Where
is transit mode share highest? Where is it the lowest? Do TAZs with subway
lines have higher transit mode share? Where is car mode share highest? Where is
it the lowest? Can you explain why?
For this task, you should
review your discoveries in order to make recommendations for future
transportation initiatives or land-use initiatives that should impact
transportation patterns in the city. Using Metrolinx’s most recent Regional Transportation Plan and/or the Province’s Growth Plan and/or Official Plan Maps of City of Toronto select three transportation or land
use policy or infrastructure initiatives, explain why they are needed, and
provide a statement of their expected impact on transportation patterns. Make
sure that your discussions of the initiatives are justified by the patterns you
see in your maps, and that the expected impacts are justified by theories
covered in the course, especially the land-use/transportation cycle.
Your write-up for this
assignment should be in the format of a report to the Mayor of Toronto. It
should have a brief introduction, followed by separate sections for Tasks 1-5.
For Task 1, your report should describe the transportation and land use
patterns in the city consisting of the 7 maps made for tasks 1a-1g as well as
your descriptions of the patterns of transportation and land uses you observed.
You are expected to write a brief paragraph to describe each map. For Task 2,
you should report two maps and describe the mode share you observed in each
map. Similarly, for Task 3, you should report on the 2 recommended comparisons
with a map (or pair of maps) and a short paragraph for each. For Task 4, your
report is expected to contain the summary table of selected areas, and the
comparison and discussion of the mode shares in these areas. For Task 5, you
should write about 1 paragraph for each of your three 3 hypothesized
initiatives.
Your report must be written
using a word processor, and all maps should be inserted into the appropriate
locations in the document. All figures must have numbered captions and be
referenced in text. PDF’s should be in colour and must include a cover page
with your name, student number, and assignment title. You are responsible for making sure that all
colours and fonts chosen for your maps are easily interpretable on the PDF
versions. Your document should be double-spaced, 12 point font, 1 inch margins.
You should use APA 6th edition for references and in-text citations.
Task 1: 14 points. 1 points for each map and 1 points for each
description.
Task 2: 14 points. 2 points for each calculation, 2 points for
each map, and 3 points for each description.
Task 3: 14 points. 3 points for each comparison and 4 points for
each description.
Task 4: 15 points. 2 points for each map and 2 points for each
description. 3 points for the comparison.
Task 5: 30 points. 10 points for each hypothesized
infrastructure improvement.
Writing and Presentation: 13
points.
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