An initiative of the Computation Institute of the University of Chicago and Argonne National Laboratory
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1 An initiative of the Computation Institute of the University of Chicago and Argonne National Laboratory Charlie Catlett, Senior Computer Scientist, Argonne National Laboratory Senior Fellow, Computation Institute of the University of Chicago and Argonne National Laboratory Director, UrbanCCD Mayors Innovation Project Oak Park, Illinois August 16, 2013
2 Chicago Delhi Shanghai Land Area Increase Building Height Increase Cities in India and Southeast Asia are Growing at Unprecedented Rates Frolking S, T Milliman, KC Seto, MA Friedl A global fingerprint of macro-scale change in urban 2-D and 3-D structure from 1999 to 2009, Environ. Res. Lett.
3 1980 The Pearl River Delta in 1980 and today, illustrating the impact of urbanization on the planet By 2020, China will invest $300B in new infrastructure to transform the delta into a single 40M person city.
4 Motivation: Rapid Global Urbanization IN 2025: 70% of Chinese will live in cities with 1M or more people. And by Chinese cities will have 1M or more people. Source: Foreign Policy Magazine, Sep/Oct 2010, Megacities, Richard Dobbs (McKinsey Global Institute) More than the entire population of the US... China will add 400 million city dwellers...requiring the construction of one New York City every year for several decades......enough floorspace to cover the country of Switzerland. Sources: CEIC; UN Population Division; The Economist
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6 UrbanCCD Programs Environment Infrastructure Society Modeling Data Analytics Sensing Dissemination and Training (CI Fellows)
7 City-Scale Development in Chicago: Lakeside 1930 Opportunity: partnership with developer and architect of 600acre city expansion Chicago Lakeside Development, LLC
8 Today s urban growth is driving city-scale development projects. Experience Demand Chicago Lakeside
9 Residential Retail Commercial Parking Zoning and Use Physical Attributes Decisions: Energy, Water, Civil Engineering, Transportation... Goal to close the gap between design and impact, allowing interactive "what if" exploration.
10 Design Existing Computational Simulations Analyze Plan Decide Energy demand Energy Supply Water Demand / Waste Water/Sewage Infrastructure Geometry Financial, Economic Model Storm water Storm water treatment/mgmt Transportation Streets, Public Transport Independent consultant studies
11 Opportunity: City of Chicago open data and unique City/ University partnerships. Social Service Data Census Bob Goerge, Kathleen Cagney Interviews
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13 Stanford University University of California-Irvine Arizona State University University of Texas-Austin University of Wisconsin-Madison University of Texas-Austin Instituto Technológico Autónomo de México University of Chicago University of Illinois-Chicago University of Michigan University of Alabama Georgia Institute of Technology Carnegie Mellon University Cornell University Israel Institute of Technology University of Maryland City University of New York Columbia University Yale University Harvard University Massachusetts Institute of Technology University of Cambridge 2013 Eric and Wendy Schmidt Data Science for Social Good 36 Summer Fellows from 22 Universities
14 2013 Eric and Wendy Schmidt Data Science for Social Good A diverse interdisciplinary community. PhD/Postdoc/Professional Masters Undergraduate Computer Science Social Sciences & Public Policy Mathematics, Statistics, Physical Sciences
15 2013 Eric and Wendy Schmidt Data Science for Social Good Real-world projects with public and private sector partners.
16 Chicago census tracts clustered by relative crime prevalence from 2001 to mid Reported incidents of violent crimes versus daily high temperature at O Hare International Airport, Varoon Bashyakarla, Edward McFowland III, Paul Meinshausen, and Tom Plagge
17 What can we learn from 311? Varoon Bashyakarla, Edward McFowland III, Paul Meinshausen, Zach Seeskin, Alessandro Panella, Matt Gee, Tom Plagge
18 Redshift Data Base (copy of CTA s DB) Model Simulation Webapp Jordan Bates, Andrés Akle Carranza, Walter Dempsey, David Sekora, Brandon Willard
19 Example: City of Chicago Proactive Intervention Create "Neighborhood Health Index" - identify early indicators to neighborhood decline and corresponding preventative interventions, e.g.: Predict locations of abandoned buildings/vacant lots. Predict restaurant failures based on food service reports, social media, and other data. Estimate economic health ("micro-gnp") of neighborhoods and sub-neighborhoods. Research Capabilities Analytics, machine learning, and other algorithms, guided by social, economic, education, health, and related research areas, to examine urban data as a means to define and measure neighborhoods and related functions. Impacts on City Challenges Early detection of at-risk neighborhoods w.r.t. crime, education, economics, employment, leading to preventative vs reactive intervention. Articulated need common to multiple city departments and functions Requires computer scientists, mathematicians, economists, and social scientists. With specific and measurable outcomes for city government and/or city dwellers.
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21 Vacant properties in a particularly distressed portion of Cook County, which has over 100,000 vacant residential properties. (CMAP Green Healthy Neighborhoods plan). Sophia Alice, Evan Misshula, Skyler Whorton, and Tom Plagge
22 Scoring Census Tracts Stability score Affordability score Green is more stable. Green is more affordable. Stability score (S) is based on Walker & Winston (2010), and depends on: property values (V), transaction volume (V1,V2) mortgages to owner occupants (M), and the prevalence of high-cost lending (H). Affordability score (A) is based on: income (I) and median property sale price (P) in each census tract Sophia Alice, Evan Misshula, Skyler Whorton, and Tom Plagge
23 Scoring Individual Properties Nuisance Value 311 and crime reports Economic Impact Hedonic pricing model (property and neighborhood characteristics). Use historical data to estimate impact of foreclosure, vacancy, or demolition (in % property values) Our preliminary model indicates that, controlling for the basic demographic and economic characteristics of its community, each foreclosure that occurs within 1/8 mile of a property has approximately a -2% effect on its price. Sophia Alice, Evan Misshula, Skyler Whorton, and Tom Plagge
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