Caitlin Bettisworth
UEP 232: Introduction to GIS
Assignment 6: Detailed Project Proposal
April 14, 2014
1. Project Goals and Spatial Questions
Project Goals
The project proposes to map the indicators of creative communities: density, tax base,
housing rates, vacancy rates, independent businesses, walkability, and transportation
options. The intention of the project is to map all of Massachusetts; however, due to time,
this intention may be scaled down to the greater Boston area. Once mapped, the project
proposes to track the emergence and progression of creative communities over time via
map visualizations. I propose that there are three stages of creative communities: a
primary, intermediate, and advanced stage. The primary stage can be defined by the
emergence of artist squats and high vacancy rates. The intermediate stage can be defined
by decreased vacancy rates, low rental prices, and the emergence of independent
businesses. The advanced stage can be defined by the presence of human capital based
jobs, younger residents, more educated residents, increased rental housing, increased
density, increased walkability, increased transportation, the presence of bike lanes, and
increased tax bases.
To enhance this analysis the ArtsBoston Event Archive dataset will be used in an attempt
to correlate creative communities and the presence of artistic events. This will produce a
mapping of the artistic events provided in the dataset over the past 4 years. The hope
being that as creative communities progress over time the presence of advertised artistic
events increases.
Spatial Questions
Do the artistic event locations help in describing the make up of communities?
Can a progression of creative communities be seen over time?
Is there a correlation between hotspots of artistic events and characteristics of advanced
stage creative communities?
How many artistic events are within walking distance to public transportation?
Is there a correlation between the location of artistic events and T stops?
Which artistic venues are the most popular? Do the presence of these venues help in
describing their communities?
2. Annotated References
The below references are arranged by most to least helpful in terms of the proposed
project. This is due to the lack of current published research on using GIS to help in
tracking and expressing culture.
Gibson, C., Brennan-Horley, C., & Warren, A. (2010). Geographic information
technologies for cultural research: Cultural mapping and the prospects of colliding
epistemologies. Cultural Trends, 19(4), 325-348.
This article attempts to overall explain GIS and how it and other technologies can be used
in the social sciences. They also explore the use of traditional interview techniques that
can be enhanced by GIS and other technologies. They assert that researchers should use a
more holistic approach using technologies like GIS, non-human actors and political
motivations. This idea is interesting in that many projects use GIS in a similar manner
and do not spend the time correlating all of the non-human and political or any other
aspect that may be influencing people that is much harder to map.
Gibson, C., Luckman, S., & Willoughby-Smith, J. (2010). Creativity without
borders? rethinking remoteness and proximity. Australian Geographer, 41(1), 25-38.
This article shows further evidence that creativity and artistry can be analyzed via GIS
mapping. They show throughout the article that people use geography and place as ways
to define themselves, the relationships, and their creativity. They assert that Darwin,
Australia is the perfect example of people who define their creativity based on place in
relation to others.
Feldman M P, 2000, ``Location and innovation: the new economic geography of
innovation, spillovers, and agglomeration'', in The Oxford Handbook of Economic
Geography Eds G Clark, M Gertler, M Feldman (Oxford University Press, Oxford)
pp 373-394.
This article helps in showing the need for geographic analysis among creative
communities. Feldman explains spillovers and the need to have educated people near
each other to progress ideas via spillovers. Other researchers have justified which
industries are creative industries and why as well as how to identify creative communities
by using his ideas on spillovers. Despite it’s connections to creative communities, the
article shows another non-tangible idea that can use geographic mapping to show its
impact.
Brennan-Horley, C., & Gibson, C. (2009). Where is creativity in the city?
integrating qualitative and GIS methods. Environment and Planning A, 41(11), 25952614.
This article looked at using mental mapping as a way to connect how people feel about
places and places they remember. It is an interesting way of attempting to bring the
emotional side of creativity to the very precise side of GIS and analysis. This approach
does; however, take out the ‘meaningful spatial distortion’ of traditional mental mapping.
The articles discusses how the use of a basemap and some streets positively impacted
how well the interviewee’s mental maps were able to be analyzed by GIS. It was also
found; however, that this process of using a basemap tends to take out the spatial
distortion that occurs with traditional mental mapping showing the emotional and
importance of certain places or areas.
3. GIS Data Layers
It should be clarified that to save space not every dataset is listed below. Suffolk County
information is found below; however, it is the intent to analyze parts of Middlesex
County, Norfolk County, and Plymouth County as well. If time permits all counties in
Massachusetts will be looked at (Berkshire, Franklin, Hampshire, Hampden, Worcester,
Middlesex, Norfolk, Bristol, Plymouth, Suffolk, Essex, Barnstable, Dukes, and
Nantucket)
To better track trends, information from the ACS 1 year estimates will be used for all
years available (2002, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, and 2012). Only
the 2012 ACS 1 year estimates are found on the table below.
The below census information is the basic information that will be looked at, if time
permits 1990 census information can also be looked at as well as other possible census
files.
Finally, all datasets below are in the Massachusetts Stateplane projection by feet, if time
permits and the project reaches past the greater Boston area the datasets will be projected
in the Massachusetts Stateplane projection by meters and will result in dataset name
changes.
Dataset
World_Imagery
Basemap_Mass_Stateplane_Feet
USA_States_Mass_Stateplane_Fe
et
2010_Census_Mass_Town_Bound
aries_Mass_Stateplane_Feet
Streets_Mass_Stateplane_Feet
Description
A world imagery basemap
that will be used to confirm
the placement of
unmatched geocoded venue
locations.
Outline of all states in the
US
Outline of all Massachusetts
town boundaries
Line segments of all the
streets in the US. This will
provided a base for
geocoding all the venue
locations both in
Massachusetts and not in
Source
Key Attributes
ESRI
World_Imagery
Tufts GIS
State Polygons
Mass GIS
Town Polygons
Tufts GIS
Geocodable
Street Lines
2010_Census_Tracts_Mass_Mass_
Stateplane_Feet
OceanMask_Poly_Mass_Stateplan
e_Feet
OpenSpace_Poly_Mass_Stateplan
e_Feet
ArtsBoston_Venue_Points_Mass_S
tateplane_Feet
2010_Census_Suffolk_H5_Vacanc
y_Mass_Stateplane_Feet
2000_Census_Suffolk_H5_Vacanc
y_Mass_Stateplane_Feet
2010_Census_Suffolk_H4_Tenure
_Mass_Stateplane_Feet
2000_Census_Suffolk_H4_Tenure
_Mass_Stateplane_Feet
2010_Census_Suffolk_PCT15_Un
married_Mass_Stateplane_Feet
2000_Census_Suffolk_PCT15_Un
married_Mass_Stateplane_Feet
2010_Census_Suffolk_P16_Age_
Mass_Stateplane_Feet
2000_Census_Suffolk_P16_Age_
Mass_Stateplane_Feet
2012_ACS_1YR_Suffolk_S1903_M
ed_Income_Mass_Stateplane_Fee
t
2012_ACS_1YR_Suffolk_S1501_E
ducation_Mass_Stateplane_Feet
2012_ACS_1YR_Suffolk_S2301_E
mployment_Mass_Stateplane_Fee
t
WalkScore_Mass_Stateplane_Feet
Massachusetts.
Outline of all Census tracts
in Massachusetts
Polygon of Atlantic Ocean
surrounding Massachusetts.
This polygon does
completely cut out New
Jersey and spans about
halfway into North Carolina
and halfway into Maine and
only goes out as far as the
most easternly point of
Maine.
Polygons of the open space
is Massachusetts
Based on the information
provided by the ArtsBoston
Event Archive these are
geocoded venue locations
with compiled extra
information for each venue
Polygons of vacancy
percentages throughout
census tracts
Polygons of vacancy
percentages throughout
census tracts
Polygons of rental
percentages by census tract
Polygons of rental
percentages by census tract
Polygons of unmarried
partner percentages by
census tract
Polygons of unmarried
partner percentages by
census tract
Polygons of average age by
census tract
Polygons of average age by
census tract
Mass GIS
Census
Polygons
Mass GIS
Ocean Polygon
Mass GIS
Bettisworth
Open Space
Polygons
Venue
Locations,
Number of
events per
venue, venue
type,
admittance
information, if
applicable type
of events per
venue
Census (2010)
Vacancy
percentages
Census (2000)
Vacancy
percentages
Census (2010)
Census (2000)
Census (2010)
Census (2000)
Rental
percentages
Rental
percentages
Unmarried
partner
percentages
Unmarried
partner
percentages
Census (2010)
Average age
Census (2000)
Average age
Polygons of median income
by census tract
ACS (2012)
Median Income
Polygons of educational
attainment by census
ACS (2012)
Education
Polygons of employment
status by census tract
ACS (2012)
Employment
Assigns a Walkscore
obtained by Walkscore.com
to each town in
Massachusetts
Bettisworth
Walkscores
4. Data Creation, Processing, and Analysis Steps
For the final project two datasets will need to be created using the ArtsBoston Event
Archive as well as information from walkscore.com.
Once this is complete the Kernel Density tool will be used to determine hotspots of
venues.
To better understand the types of venues multiple layers will be created using select by
attribute selecting out each of the venue types separately. The Kernel Density tool will be
used again to determine if there are any hotspots of particular types of venues.
Then the number of events per venue will be looked at in relation to walkscores to
determine if a relationship exists. If one does this will be visually represented using an
overlay tool.
Using the buffer tool venues within 0.25 miles and 0.5 miles of a rapid transit stop will be
determined.
Using the same process venues will be assessed on their closeness to bus stops.
Next the above Census information will be looked at by separating out percentage
quintiles. A relationship between Census information and the venues will then be
determined using overlay tools as well as correlating Kernel Density maps between the
venues and census information
From here any other interesting relationships will be explored.
5. Final Products
The final products will include but will not be limited to a Kernel Density map of venues
and venue usage, interesting census maps, correlation analysis of venues and census
information, and any interesting maps that may be created throughout the exploration
process.