Karen Shilo
Assignment Eight
Barbara Parmenter
Project Process Steps
Project: Service area analysis within ½ mile and 1 ½ mile radii showing summary tables
calculating acreage of land use types, population density statistics, and demographic
information surrounding the Massachusetts Bay Transit Authority (MBTA) transit nodes.
Project Goals: My project goal is to further develop my analysis in assignment six by
making a comparison of the land use, population density, and demographics of the ½
mile buffer zones to these same attributes in a 11/2 mile ring around the transit nodes
with the ½ mile buffers removed. The purpose of the project is to form a comparison not
only regarding land use and population density but also of the household income, age of
population, education attainment, and language spoken at home for residents that live
close or farther away from the MBTA. Hoping to better understand how MBTA
integrated communications technologies can better serve its transit riders, this analysis
around the Boston Metro Region transit stops can facilitate the tailoring of operations to
forge a more connected 21st century transit system that meets a wide range of daily needs.
Project Steps Completed:
In assignment 6, I mapped Land Use and Population Density in relationship to the Boston
transit stations utilizing the following tools for the analysis:
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Select by location
Creating a Buffer and
Importing Symbology to the buffer zones to
Find Statistics for selected features
Field Calculator
Summary Table
1. Land Use:
I first created a map of the Boston Metro Region with the MBTA Node, EOTROADS,
MBTA BUS Routes, MBTA Arc, and Annotated Town Name data layers from MassGIS.
Then I added the town boundaries layer and used select by location to highlight the towns
through which the MBTA subway lines run. The next step was to apply a second Select
by Location to define the cities through which both the MBTA bus routes and subway
lines run. I then added the land use data layer and adjusted the coloration to match the
correct colors in the standard classification system. Then I created ½ mile MBTA node
buffer zones over the land use map layer and imported symbology. Finally, I used the
summary table to calculate acreage of particular land use types within the ½ mile buffer
zones.
2. Population Density:
Next, I used select by location to intersect the population density layer with the ½ mile
buffer zones. Using data export, I selected and created a population density information
layer within the ½ mile buffer zones. I then applied the switch tool to select the ½ mile
zones and conversely the area outside the ½ mile zones, which I then exported to create
two separate layers. Next, I used the field calculator to create a new field - population
density per square mile and ran statistics for population density within and outside the ½
mile buffer zones.
Additional Data Processing Steps to Project Completion:
1. Land Use: To take this analysis of land use a step further in the final project, I will use
select by location to analyze land use within 11/2 mile buffer zones, while removing the
land use within the ½ mile buffer zones. Such a comparison will shed light on any
potential similarities and/or differences in land use between the ½ mile buffer and 11/2
mile ring.
2. Population Density: To take this analysis of population desnity a step further in the
final project, I will use select by location to analyze population density within 11/2 mile
buffer zones, while removing the population density within the ½ mile buffer zones.
Such a comparison will shed light on any potential similarities and/or differences in
population density between the ½ mile buffer and 11/2 mile ring.
3. Demographics:
I will map the following layers applying the same methodology:
i. Household_language_spoken.dbf to compare the primary spoken languages of
those living close and farther away from the MBTA.
ii. Education_attainment_by_gender_age.dbf layer to compare the average education
attained of those living close and farther away from the MBTA.
iii. Population_by_age_gender.dbf layer to compare the age similarities and/or
differences of those living close and farther away from the MBTA.
iv. Income_by_household.dbf layer to determine the average income of those living
close and farther away from the MBTA.
Data Layers:
Data Layer
1) Land use
Source
M:\State\MA\MassGIS\Physical_Resources\Land_Poly.sh
p
Minimum
Acceptable
Accuracy
50 ft
2) Population
density
M:\State\MA\MassGIS\Census_2000\Census2000blockgro
ups_poly.shp
500 ft
3)
Population_by_age_
gender.dbf
MassGIS Wesbite:
http://www.mass.gov/mgis/cen2000_blockgroups.htm
500 ft
4)
Household_language
_spoken.dbf
7)
Income_by_househo
ld.dbf
9)
Education_attainmen
t_by_gender_age.dbf
MassGIS Wesbite:
http://www.mass.gov/mgis/cen2000_blockgroups.htm
500 ft
MassGIS Wesbite:
http://www.mass.gov/mgis/cen2000_blockgroups.htm
500 ft
MassGIS Wesbite:
http://www.mass.gov/mgis/cen2000_blockgroups.htm
500 ft
Maps to Produce:
1. In addition to the land use map and summary table for the ½ mile buffer zone below, I
will need to create a second map with a 1 ½ mile radius and ½ mile removed along with a
summary table of land use types and corresponding acreage.
2. In addition to the population density map and statistical analysis for the ½ mile buffer
zone below, I will need to create a second population density map with a 1 ½ mile radius
and ½ mile removed along with population density statistics.
Demographics:
3. I will additionally create maps of ½ mile and 1 1/2 mile buffer zones for each of the
four data layers below along with summary tables and/or statistics:
i.
ii.
iii.
iv.
Language Spoken at home
Household income
Age of Population
Education Attainment