An analysis of the accessibility of residence halls on the UIUC Campus

1. Analysis of
Accessibility of
Residence Halls to
Campus
By: Walter Stevens

2. Six Steps of GIS Problem
Solving
 Step 0: Topic Selection
 Step 1: Crisp, Clear, Actionable Question or
Problem
 Step 2: Define Project Methodology
 Step 2.5: Choose the Appropriate Software
 Step 3: Data Collection
 Step 4: Execution of Methodology
 Step 5: Review and Revise
 Step 6: Communication of Results

3. Step 0: Topic Selection
Which Residence Halls
are the Most
Connected/Accessible
to Other University
Buildings?

4. Step 1: Crisp, Clear, Actionable
Question or Problem
A Spatial Analysis of the
Accessibility of the
Locations of Different
University-run Housing
Locations With the Main
Campus Area

5. Step 2: Define Project
Methodology
 Assumptions:
 There is a point feature class called
Quad that represents the center
reference point of campus
 There is a point feature class called
Residence Halls that represents the
halls being analyzed
 For this project, these points have only
been assigned to undergraduate residence
halls.

6. Step 2: Define Project
Methodology
Buffer
(i * 200) meters
Quad
(Point)
Init: i = 6
i = i -1
While i > 0
Area
within
200
meters of
Quad
Area
within
400
meters of
Quad
Area
within …
meters of
Quad
Area
within
1200
meters of
Quad
Creates 6 different buffers ranging
from Quad point (200m, 400m, 600m,
800m, 1000m, 1200m)

7. Step 2: Define Project
Methodology
Legend
&3 Quad
!. Residence Halls
Zone_200_Meters_e
Zone_400_Meters
Zone_600_Meters
Zone_800_Meters
Zone_1000_Meters
Zone_1200_Meters
Buildings
Campus_Block
!.
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!.!.
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!.
&3
Legend
&3 Quad
!. Residence Halls
Zone_200_Meters_e
Zone_400_Meters
Zone_600_Meters
Zone_800_Meters
Zone_1000_Meters
Zone_1200_Meters
Buildings
Campus_Block

8. Step 2: Define Project
Methodology
Erase
(Next lowest
overlaying
feature)
Area
within
200
meters of
Quad
Range
between
200 and
400
meters of
Quad
Range
between
(n-200)
and n
meters of
Quad
Range
between
1000 and
1200
meters of
Quad
Iterate through each feature
Iterates through
each feature and
erases it’s next
lower overlapping
feature. Creates 6
different 200 meter
ranges (rings) so that
residence halls can
be classified as
being within these
ranges

9. Step 2: Define Project
Methodology
Legend
&3 Quad
!. Residence Halls
Zone_400_Meters_e
Zone_800_Meters_e
Zone_1200_Meters_e
Buildings
Campus_Block
!.
!.!.
!.!.
!.!.
!.
!.
!.
!.
!.
!.!.
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!.
!.!.
!.
!.
!.
!.
!. !.
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!.
!.
&3
Legend
&3 Quad
!. Residence Halls
Zone_400_Meters_e
Zone_800_Meters_e
Zone_1200_Meters_e
Buildings
Campus_Block

10. Step 2: Define Project
Methodology
Residence
Halls
(Point)
Intersect
Range
between
(n-200)
and n
meters of
Quad
Iterate through each range
Halls
within
200
meters of
Quad
Halls
between
200 and
400
meters of
Quad
Halls
between
(n-200)
and n
meters of
Quad
Halls
between
1000 and
1200
meters of
Quad
Iterates through
each Range and
intersects them with
Residence Halls.
Classifies residence
halls into different
classes based on
their range.

11. Step 2: Define Project
Methodology
&3
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!. !. !.
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!.Legend
!. Residence_Halls_Within_400_Meters
!. Residence_Halls_Within_600_Meters
!. Residence_Halls_Within_800_Meters
!. Residence_Halls_Within_1000_Meters
!. Residence_Halls_Within_1200_Meters
&3 Quad
Buildings
Campus_Block

12. Step 3: Data Collection
 Original Plan:
 Publish service to ArcGIS Online and
collect different points using Collector
app
 Collect points at several different
residence halls of my choosing
 Collect a reference point to represent
the “center of campus”

13. Step 3: Data Collection
 This failed miserably
 The service I thought I had published to ArcGIS Online
had not been successfully published and I was having
extreme issues publishing another
 I then attempted to collect points from another service
I had set up earlier
 This is when my phone decided to explode and I lost all
access to the Collector app
 Murphy’s Law states that “Anything that can go wrong,
will go wrong.” and this was certainly the case for me
during data collection

14. Step 3: Data Collection
 Revised Plan:
 Using James Whitacre’s building feature class from ArcGIS
Online, create point data overlaying residence halls and
supply them with similar attributes
 I downloaded the building feature class into ArcMap for
Desktop and used the “Feature to Point” tool on selected
buildings to create points at the geometric center of each
polygon
 I also used a campus block feature class from USGS to
create a point for the center of the Quad. (The quad is
centric to it’s own block)
 All Residence Hall points have a “Name” and an “Address”
field

15. Step 4: Execution of
Methodology
I performed the
methodology highlighted
in step 2 and came up
with this result

16. Step 4: Execution of
Methodology
&3
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!.Legend
!. Residence_Halls_Within_400_Meters
!. Residence_Halls_Within_600_Meters
!. Residence_Halls_Within_800_Meters
!. Residence_Halls_Within_1000_Meters
!. Residence_Halls_Within_1200_Meters
&3 Quad
Buildings
Campus_Block

17. Step 5: Review and Revise
The analysis worked
correctly with no errors and
the result was expected. No
change to methodology
required

18. Step 6: Communicate Results
 http://courses.atlas.illinois.edu/spring2015/GEOG/GEO
G479/wsteven2/Web%20Map/web_map.html

19. Mistakes Were Made
 Upon reviewing this analysis on the whole, I found some
issues that should have been changed. This analysis
assumes that radial distance equates to higher
connectivity/accessibility. Unfortunately, this is not
always the case. Generally students/vehicles are not
walking directly to campus from their residence halls (in
a straight line). They tend to follow paths or roads.
 In the future, I would perform an in-depth network
analysis of the road systems instead. Perhaps finding the
distance from residence halls to the campus center via
roads or paths. This can lead to very different results.

20. Thank You!
 Any questions?