GIS IN PROFESSIONAL PLANNING PRACTICE

SAMIR GAMBHIRSenior Research AssociateKirwan Institute for the Study of Race and Ethnicity

CRP 608 Winter ‘10Class presentationFebruary 04, 2010

Overview

Background Kirwan Institute

Our work Using GIS for research and advocacy Opportunity Mapping

Work in progress National Opportunity Model Web-based GIS

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

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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

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

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

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)

MBE and Projected Job Change 2000-2030

Hospital Investments and African American nbhds:Columbus

Race and Foreclosure Crisis

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

Stimulus investments

and Job creation in

Orlando MSA, Florida

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?

Conditions in Baltimore

Subsidized housing opportunities in Baltimore are generally clustered in the region’s predominately African American neighborhoods

Subprime Lending, Race and Foreclosure(Note: Not one of our maps)

Subprime Lending, Race and Foreclosure(Note: Not one of our maps)

Maps: Produced and adapted from Charles Bromley, SAGES Presidential Fellow, Case Western University

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:

Montclair School District, NJ

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

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

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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Which community would you choose?

Some people ride the “Up” escalator to reach

opportunity.

Others have to run up the “Down” escalator to get there.

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

Opportunity Mapping Booklet

Methodology

Identifying and selecting indicators of opportunity

Identifying sources of data Compiling list of indicators (data matrix) Calculating Z scores Averaging these scores

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?

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

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

     

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

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

Austin MSA, TX

Subsidized housing opportunities in Baltimore are generally clustered in the region’s lowest opportunity neighborhoods

Baltimore Opportunity and Subsidized Housing

African American men are isolated from neighborhoods

of opportunity in Detroit

Detroit Opportunity

and Race

Low opportunity neighborhoods have higher number of linguistically isolated households

Austin Opportunity and Linguistic Isolation

Redlining: 1937 to 2009

Comp Opportunity and Race

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

Work in progress

Customizing data transfer procedures National Opportunity Mapping Web-based Opportunity mapping

Comparison

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)

Thank you!For questions, comments or for more information visit our website www.kirwaninstitute.org or e-mail me at Gambhir.2@osu.edu