Are Chicago’s Safe Passage Routes Located in the Highest Risk Areas?

Safe passage routes to school provide not only a sense of safety for Chicago students from pre-K through high school, but they reduce crime involving students and help increase school attendance. Chicago’s Safe Passage program was introduced in 2009 after the beating death by gangs of 16-year-old Fenger High School honors student Derrion Albert, which was captured on cell phone video. His death and the circumstances received national attention along with a series of other incidents involving CPS students caught in gang violence. Since then, the program has expanded to include schools, parents, residents, law enforcement officials and even local businesses in efforts to provide students with a safe environment. The various types of safe passage programs among the 51 safe route programs currently available include: safe haven programs in which students who fear for their safety can find refuge at the local police station, fire house, library and even convenience stores, barbershops and restaurants; patrols along school routes by veterans, parents and local residents; and walking to school programs in which parents and local residents create a presence to help deter unlawful incidents.

The map below shows the number of all crimes committed in the city of Chicago during the current school year, and the locations of schools and safe routes among those communities that have safe routes. Currently, there are 517 Chicago public schools, of which, only 136 Chicago public schools (26.3% of all schools) fall within the 51 safe routes. Although the safe routes are located in 37 of the high crime communities in general (south, west and northeast sides of Chicago), they do not exist in the pockets of the highest crime incidents (1,500+ highlighted in burgundy) where children are the most vulnerable. Of the 47 schools that fall within the extreme crime areas (1,500+ incidents a year), only 6 have safe routes; the others offer no safe passage options. A list of the schools appears at the end of this blog.

Click through to see the enlarged image.


SafePassage_Routs

Schools located in extremely high-crime areas of Chicago (Schools highlighted in green have safe passage routes):
Bennett, Bowen HS, Bradwell, Camelot Safe – Garfield Park, Camelot Safe Academy, Clark HS, Coles, Community, Ericson, Frazier Charter, Frazier Prospective, Galapagos Charter, Great Lakes Charter, Gregory, Harlan HS, Hefferan, Heroes, Herzl, Hirsch HS, Hubbard HS, Learn Charter – Butler, Leland, Mann, Mireles, Noble Charter – Academy, Noble Charter – Baker College Prep, Noble Charter – DRW, Noble Charter – Muchin, Noble Charter – Rowe Clark, Oglesby, Plato, Polaris Charter, Powell, Schmid, Shabazz Charter – Shabazz, Smith, South Shore Intl HS, Webster, Westcott, Winnie Mandela HS, YCCS Charter – Association House, YCCS Charter – CCA Academy, YCCS Charter – Community Service, YCCS Charter – Innovations, YCCS Charter – Olive Harvey, YCCS Charter – Sullivan, YCCS Charter – Youth Development

 

Implementing visualization techniques in faculty research
The image of the map reflects the different visualization techniques that might be used to effectively convey data or research conclusions to different types of audiences in various disciplines or industries. Visualizations can help identify existing or emerging trends, spot irregularities or obscure patterns, and even address or solve issues.

Ask us how to visualize your research
For help visualizing your own research findings or seeing if your research lends itself to similar techniques including data acquisition and pre-processing of both quantitative and qualitative data, contact Nandhini Gulasingam at mgulasin@depaul.edu.

Vehicle Theft in Chicago

Even though vehicle thefts accounted for only 3.9% (10,099) of all crimes in Chicago last year, 62% of the stolen vehicles were recovered with severe damage says the Chicago Police department. Most often the vehicles are stolen by organized rings to be sold on black-markets or shipped overseas, and stripped for parts and resold to various body-shops, or are even resold to unsuspecting customers. In Chicago, 78.9% of the vehicles are stolen from streets, alleys and alongside sidewalks, 8.6% from buildings other than residences, 6.7% from parking lots, 5.5% from residences, and 0.3% from the airports.

The map below shows a hot-spot analysis of the communities that are most and least affected by vehicle theft. The visualization shows statistically significant (statistically significant is the likelihood that a theft is caused by something other than mere random chance) hot-spots in red where a high number of thefts occur and statistically significant cold-spots in blue where few or no thefts occur.

Communities most-prone to vehicle theft (not safe): Uptown (3) in the north, or Austin (25), Avondale (21), Logan Square (22), Hermosa (20), Humboldt Park (23), West Town (24), East/West Garfield Parks (26, 27), Near West Side (28), North Lawndale (29) in the west , or any south central parts of Chicago, namely Chicago Lawn (66), East/West Englewoods (67, 68), Greater Grand Crossing (69), South Shore (43), Auburn Gresham (71) are prone to vehicle thefts.

Communities least-prone to vehicle theft (safe): Edison Park (9), Norwood Park (10), Jefferson Park (11), Forest Glen (12), North Park (13), Dunning (17), Portage Park (15), Lincoln Square (4), North Center (5), Lincoln Park (7) in the north and Bridgeport (60), New City (61), Garfield Ridge (56), Clearing (64), Ashburn (70), West Pullman (53), Morgan Park (75), Beverly (72), Washington Heights (73), East Side (52) and Calumet Heights (48) in the south are least prone to vehicle thefts.
Click through to see the enlarged image.

VehicleTheft_StatSig_2015

 

Techniques Used
The above visualization includes 2 major types of spatial analysis techniques. The vehicle theft locations were geocoded using the addresses and then, Getis-Ord Gi* statistic was used to generate a hot-spot analysis to identify statistically significant clusters.

Implementing visualization techniques in faculty research
The image of the map reflects the different visualization techniques that might be used to effectively convey data or research conclusions to different types of audiences in various disciplines or industries. Visualizations can help identify existing or emerging trends, spot irregularities or obscure patterns, and even address or solve issues.

Ask us how to visualize your research
For help visualizing your own research findings or seeing if your research lends itself to similar techniques including data acquisition and pre-processing of both quantitative and qualitative data, contact Nandhini Gulasingam at mgulasin@depaul.edu.

Crime in Chicago

Among the 11,363 crimes reported in Chicago during the first 9 months of 2015, theft, battery, criminal damage, narcotics and assault ranked highest, totaling 68% of all reported crime. The infographic below shows a snapshot of crime in Chicago during this period.

Click through to see the enlarged image.
ChicagoCrime_Final

Techniques Used
The above visualization includes 4 main types of visualization techniques:

Text Analysis: The first image is a visual a representation of text data, specifically the word count of the type of crimes (i.e. frequency) displayed as a word cloud.

Spatial Analysis (GIS): The map uses an Inverse Distance Weighted (IDW) interpolation method to identify crime hotspots (in red). It also allows one to predict the frequency of crime at an unknown location based on the known values.

Quantitative Analysis: Two chart types were used to visualize quantitative data – a bar chart showing the crime counts of the major crime types for the most affected ward/community, and a bubble chart showing the number of crime by ward and community.

Implementing visualization techniques in faculty research
The image above shows different visualization techniques that might be used to effectively convey data or research conclusions to different types of audiences in various disciplines or industries.  Visualizations can help identify existing or emerging trends, spot irregularities or obscure patterns, and even address or solve issues.

A good example of one such implementation is John Conroy’s Legal Clinic project in the College of Law. This research project used a multi-pronged approach in which first, various visualizations were created to compare exonerations and false convictions in major U.S. cities. Later, the SSRC trained Conroy’s research assistants how to create an exoneration database and clean and convert data into mappable formats using various techniques.

Ask us how to visualize your research
If you want help visualizing your own research findings or wonder if your research lends itself to similar techniques including data acquisition and preprocessing of both quantitative and qualitative data, contact Nandhini Gulasingam at mgulasin@depaul.edu.

Primary Data Sources for Geospatial and Non-Geospatial Data

datasources

I am often asked, ‘where can I find good data for my research?’ which prompted me to put together a list of good data sources for both geospatial and non-geospatial data.

Geography: Chicago

Description: The City of Chicago Data Portal includes more than 250 datasets, both spatial and non-spatial, organized into 16 different categories ranging from transportation and sanitation to education and economic development. Users can visualize the data as maps, graphs and charts, by specifying filtering criteria. Experienced users can download the information as datasets in various formats for further analysis.

URL: https://data.cityofchicago.org/


Geography: Cook County

Description: Similar to the Chicago’s data portal, the Cook County Open Portal also has an extensive collection of geospatial and non-geospatial datasets. The data is organized into 8 main categories such as courts, economic development, finance and administration, forest preserves, health care, public safety, property tax and GIS/Maps. Users can download the data into various formats or visualize it within the portal, even embedding the visuals into their own sites.

URL: https://datacatalog.cookcountyil.gov/


Geography: Illinois

Description: The University of Illinois Springfield has compiled a list of data sources related to Illinois and the United States, grouped by 5 different topics, and including both spatial and non-spatial data.

URL: http://www.uis.edu/gis/projects/data/


Geography: USA

Description:

(1) U.S. Census is the first place to go for data related to population or housing. It provides new census data every 10 years and annual data from the American Community Survey in between its decennial censuses. Two decades of both spatial and non-spatial data are available concerning demographic, socio-economic and housing characteristics for various geographic extents and units of analysis. The information can be downloaded as raw data files or as summary tables, and sometimes as maps.

URL: http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml (Raw Data)
http://www.census.gov/geo/maps-data/ (All other)

(2) Data.gov is the U.S. Government’s open data portal for federal, state and local data including tools and resources to conduct research and design data visualizations. The data is grouped into 14 main industries ranging from agriculture, manufacturing and energy to education, consumer and government. The data comes from hundreds of organizations, including federal and non-federal government agencies.

URL: https://www.data.gov/

(3) The Pew Research Center’s data site consists of a multitude of key national, political, economic and demographic trends gathered over time on issues, attitudes and trends for the U.S. and also world polling/survey data.

URL: http://www.pewresearch.org/data/download-datasets/
http://www.pewresearch.org/data/ (Indicators)


Geography: World

Description:

(1) The World Bank’s open data site consists of datasets, databases, pre-formatted tables, reports and other resources aggregated by countries, regions or sub-regions over multiple decades. Similar to other data portals, this site also lets users download data, filter it by criteria and/or visualize it.

URL: http://databank.worldbank.org/data/databases.aspx
http://datacatalog.worldbank.org/ (Catalog)
http://data.worldbank.org/ (Reports)

(2) The UN has more than 60 million datasets spanning decades and covering a wide range of topics including agriculture, crime, education, employment, energy, environment, health, HIV/AIDS, human development, industry, population, refugees, tourism and trade, to name just some. The site not only allows downloading data based on filtering criteria, but also provides easy access to country profiles.

URL: http://data.un.org/Explorer.aspx

(3) GISGeography.com put together a list of 10 free, downloadable, geospatial data sources for global data from various reputable sources. The link shows a list of sites, their advantages and categories by data types.

URL: http://gisgeography.com/best-free-gis-data-sources-raster-vector/


Where else can you find good data?

On Chicago Potholes+Big Data

One thing I was not prepared for when I moved from Florida last year was the sheer state of roads here in Chicago.  The potholes are insane.  AmIrite? In fact, I have taken to naming them.  With help of friends on the Facebook, some names I have come up with: The Kraken, The Terminator, The Abyss, The Violator, Destructor, Earthquake, The Tea Party (for the trolls out there), the Door to China, the Door to Narnia, and The Gorge (affectionately, this should be pronounced like “Jorge”).

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Oh, you think I am being melodramatic?  I offer you this evidence from Old Town:

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I have worked through several different theories as to why potholes are so prominent in Chicago, thinking it was about the cold and the snow.  I am no scientist, but I suspected that it was a combination of the two that caused potholes.  If this theory holds water, one would find other large northern cities like Boston, New York, Buffalo, Minneapolis, Madison, Detroit, Columbus, and St. Louis rounding out the top 10 cities with the worst potholes, even if there was such a list.  Oh wait, there is.

A national transportation research group called TRIP, issued a report in October 2013 that listed the cities with the worst road conditions in the United States.  Rubbing my hands together like a gleeful child, I opened the document, looking for evidence that would support my theory.  And there was none.

The report categorized cities among several different indicators that influence road conditions in a metropolitan area.  According to TRIP, annual VOC (vehicle operating costs) and the % of poor in a metro area are important.  One could argue about the validity of a measure like VOC as an indicator of the damage that cars incur from poor road conditions.  It is possible that this might not be accurate in cities without extensive and well-developed public transportation systems, requiring more people to own cars in order to transport themselves around.  This would increase the number of poor people who own cars, but cannot afford to maintain them (they might report lower VOC).  Also, people living in cities with strong public transportation networks might decide to forego costly car repairs because they can.  If an encounter with a rough pothole leaves them needing costly car repairs, they might be able to use alternative methods of transportation until they can afford the repairs, lowering the risk of near-future damages, because they abstain from driving for weeks or months at a time.  Of course there is likely some merit to the inclusion of “percent of poor people” there are in a metro area means there is less taxable income and thus, fewer resources for public works like road repair.

Below are tables for the 20 urban areas with greater than 500,000 residents, the first is for annual VOC and the second is for % poor in the city.  Of the twenty cities listed in each table, 16 overlap.  This means that 16 of the cities with the highest VOC are also in the top 20 for % poor in large urban areas.

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What is intriguing (and unfortunate for my Cold Hard Winter theory) is the presence of so many warm/temperate weather cities on the VOC list (assuming that VOC is a valid indicator of poor road conditions).  If you are curious about how Chicago compares: Index A details the state of Chicago’s roads as 33% poor, 39% mediocre, 14% fair, and 14% good and #29 on the percent poor list with 33% of residents considered poor.  In terms of VOC, Index C shows that Chicago falls just outside the top 20 with an annual cost of $567 a year.

My takeaway- roads in Chicago are bad, but not as bad as some places.

Some are suggesting putting Big Data to use by crowd-sourcing locations of bad potholes.  Boston’s Mayoral office New Urban Mechanics launched a project in July 2012 called Street Bump has attempted to do this, allowing users to report potholes with their smart phones.  This is an interesting concept, particularly if you consider what is possible with real-time reporting and navigation, with other apps, like Waze.  Could you imagine driving and your phone giving a ping or some other notification that you’re about to drive into Destructor?

Because, that would be amazing.

Math Errors and Schools Closings

As a newcomer to Chicago (with a young child), I have been fascinated by the whole public school closing dust-up.  I have been fascinated by the decision to close so many schools.  And then there is the sheer amount of money that is involved.  Now throw that whole situation against the backdrop of a city that is influx following the structural changes in housing that have occurred recently.

If you are interested in tuning into see what has been happening, check out WBEZ’s coverage:

http://www.wbez.org/news/education/zero-trust-after-cps-admits-it-overstated-savings-closing-schools-107044