gis in professional planning practice
TRANSCRIPT
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GIS IN PROFESSIONAL PLANNING PRACTICE
SAMIR GAMBHIRSenior Research AssociateKirwan Institute for the Study of Race and Ethnicity
CRP 608 Winter ‘10Class presentationFebruary 04, 2010
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Overview
Background Kirwan Institute
Our work Using GIS for research and advocacy Opportunity Mapping
Work in progress National Opportunity Model Web-based GIS
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About Kirwan Institute
Multidisciplinary applied research institute Our mission is to expand
opportunity for all, especially for our most marginalized communities
Founded in 2003 by john powell Opportunity Communities Program
(1/3 of staff) Opening pathways to opportunity for
marginalized communities through investments in people, places and supporting linkages
Opportunity mapping
3
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Maps: Powerful Visual Tools
Maps are incredibly efficient
compacting volumes of data
ability to convey information in seconds
tell a story or solve a problem Research has shown that
people can solve problems faster with map based information, than by looking at charts, tables or graphs
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Space and Social Equity Why are maps particularly effective in dealing
with issues of equity? Regional, racial and social inequity often manifest as
spatial inequity Maps are naturally the best tools to display this
spatial phenomena Maps give us the opportunity to look at our
entire regions or states Informing people about an issue at a scale they may not
usually think of linking communities sharing similar problems
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Using Maps for Advocacy
In our work we see mapping as serving these primary advocacy goalsAnalysis
Existing conditions, spatial trends, scenarios, optimization etc.
Storytelling A narrative
Combination
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Analytical Examples
Are minority businesses located in areas of economic opportunity? (Cleveland)
Are hospital investments benefiting communities of color? (Columbus)
Are marginalized communities disproportionately affected by foreclosure crisis? (Connecticut)
Are job growth areas connected to transit? (Baltimore)
What is the impact of stimulus money investment on job creation? (Florida)
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MBE and Projected Job Change 2000-2030
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Hospital Investments and African American nbhds:Columbus
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Race and Foreclosure Crisis
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Spatial Mismatch:Job Growth & PublicTransit in Baltimore
Percent Change in Jobs
30 - 66.6
15 - 30
5 - 15
0 - 5
Job Loss
Recent Job Growth 98-02 and Public Transitin the Baltimore Region
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Stimulus investments
and Job creation in
Orlando MSA, Florida
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Narratives Examples Subsidized housing policy is reinforcing
segregation (Baltimore) Foreclosures in African American
neighborhoods are due to subprime lending patterns (Cleveland)
Vacant property problems are spreading, vacant property challenges are not just an inner city problem (Detroit)
What if Montclair, NJ schools returned to neighborhood school system?
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Conditions in Baltimore
Subsidized housing opportunities in Baltimore are generally clustered in the region’s predominately African American neighborhoods
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Subprime Lending, Race and Foreclosure(Note: Not one of our maps)
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Subprime Lending, Race and Foreclosure(Note: Not one of our maps)
Maps: Produced and adapted from Charles Bromley, SAGES Presidential Fellow, Case Western University
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Looking at Issues Across Time and Space: The Growing Vacant Land Problem in Detroit
8 0 8 16 Miles
N
EW
S
Growth of Vacant Housing in Detroit 1970-2000(% Vacant Housing in 1970 and 2000)
% Vacant 1970
% Vacant 2000
% of Homes Vacant0 - 33 - 1010 - 1515 - 2020 - 57.6
CountiesHighwaysCity of Detroit
Prepared by: Kirwan InstituteSource Data: U.S. Census Bureau
Legend:
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Montclair School District, NJ
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Opportunity Mapping:Combining Analysis with a Strong Narrative
Opportunity mapping is a research tool used to understand the dynamics of “opportunity” within metropolitan areas
The purpose of opportunity mapping is to illustrate where opportunity rich communities exist (and assess who has access to these communities) Also, to understand what needs to be
remedied in opportunity poor communities
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Mapping Opportunity:why and How
Inequality has a geographic footprint
Maps can visually track the history and presence of discriminatory and exclusionary policies that spatially segregate people
Identifying places with gaps in opportunity can help direct future investment and identify structures which impede access to opportunity
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Opportunity Matters: Space, Place, and Life Outcomes
“Opportunity” is a situation or condition that places individuals in a position to be more likely to succeed or excel.
Opportunity structures are critical to opening pathways to success: High-quality education Healthy and safe environment Stable housing Sustainable employment Political empowerment Outlets for wealth-building Positive social networks
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22
Which community would you choose?
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Some people ride the “Up” escalator to reach
opportunity.
Others have to run up the “Down” escalator to get there.
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Opportunity Mapping Model
A refined model to depict spatial pattern of opportunity Identifying indicators as proxy for opportunity Supported by social science literature Data easily available Index based approach compresses multi-factors to an
index
Model is a good communications tool to work with communities
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Opportunity Mapping Booklet
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Methodology
Identifying and selecting indicators of opportunity
Identifying sources of data Compiling list of indicators (data matrix) Calculating Z scores Averaging these scores
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Methodology:Indicator Categories
Education Student/Teacher ratio? Test scores? Student mobility?
Economic/Employment Indicators Unemployment rate? Proximity to employment? Job creation?
Neighborhood Quality Median home values? Crime rate? Housing vacancy rate?
Mobility/Transportation Indicators Mean commute time? Access to public transit?
Health & Environmental Indicators Access to health care? Exposure to toxic waste? Proximity to
parks or open space?
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Methodology:
Sources of Data Federal Organizations
Census Bureau County Business Patterns (ZIP Code Data) Housing and Urban Development (HUD) Environmental Protection Agency (EPA)
State and Local Governmental Organizations Regional planning agencies Education boards/school districts Transportation agencies County Auditor’s Office
Other agencies (non-Profit and Private) Schoolmatters.org DataPlace.org ESRI Business Analyst Claritas
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Methodology:Effect on Opportunity
INDICATORS DATA MATRIX
EDUCATION DESCRIPTIONEffect on opportunity
Educational attainment for total population Percentage of population with college degree Positive
School poverty for neighborhood schools Percentage of economically disadvantaged students Negative
Teacher qualifications for neighborhood schools (or certified teachers) Percentage of Highly Qualified Teachers (HQT) Positive
ENVIRONMENTAL & PUBLIC HEALTH
Proximity to toxic waste release sites Census tracts are ranked based on their distance from these facilities Positive
Proximity to parks/Open spaces Census tracts are ranked based on their distance from open spaces Negative
Medically Underserved Areas Areas designated as MUA Positive
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Methodology:
Calculating Z Scores
Z Score – a statistical measure that quantifies the distance (measured in standard deviations) between data points and the meanZ Score = (Data point – Mean)/ Standard Deviation
Allows data for a geography (e.g. census tract) to be measured based on their relative distance from the average for the entire region
Raw z score performance Mean value is always “zero” – z score indicates distance
from the mean Positive z score is always above the region’s mean,
Negative z score is always below the region’s mean Indicators with negative effect on opportunity should have
all the z scores adjusted to reflect this phenomena
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Methodology:
Calculating Opportunity using Z Scores
Final “opportunity index” for each census tract is the average of z scores (including adjusted scores for direction) for all indicators by category
Census tracts can be ranked Opportunity level is determined by sorting a region’s
census tract z scores into ordered categories (very low, low, moderate, high, very high) Top 20% can be categorized as very high, bottom
20% - very low
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Austin MSA, TX
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Subsidized housing opportunities in Baltimore are generally clustered in the region’s lowest opportunity neighborhoods
Baltimore Opportunity and Subsidized Housing
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African American men are isolated from neighborhoods
of opportunity in Detroit
Detroit Opportunity
and Race
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Low opportunity neighborhoods have higher number of linguistically isolated households
Austin Opportunity and Linguistic Isolation
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Redlining: 1937 to 2009
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Comp Opportunity and Race
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Follow-up
Need more research on methodology The model needs to be made more robust Critical analysis of all indicators e.g. job
mismatch, park access issues
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Work in progress
Customizing data transfer procedures National Opportunity Mapping Web-based Opportunity mapping
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Comparison
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Web-based mapping
Online interactive maps ArcGIS Server
Baltimore Foreclosures (http://kirwan27:8399/BaltimoreForeclosure/mapviewer.jsf?width=261&height=438)
Open source Austin Opportunity Mapping
(http://www.gis.osu.edu/webgis-projects/opportunity/index.html)
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Thank you!For questions, comments or for more information visit our website www.kirwaninstitute.org or e-mail me at [email protected]