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.

CO2 Emission

Carbon dioxide (CO2) emissions are both natural and man-made. Natural sources include oceans, soil, plants, animals and volcanoes while human-related CO2 is emitted through deforestation, burning of fossil fuels such as coal, natural gases and oil for transportation, and energy for commercial, industrial and residential use. Although human-related emissions account for only 5% of the total, they have increased enormously overtime. According to the U.S. EPA, since 1970, global CO2 emissions have increased 90%, the major contributors (78%) being fossil fuel combustion and industrial processes, followed by deforestation, land-use change and agriculture.

While there are many ways to reduce carbon emission, the most effective is to reduce the consumption of fossil fuel. I pride myself for being environmentally conscious – reducing wastes by using energy-efficient products (furnace, light bulbs, etc.), taking public transportation, recycling and reusing things. Yet, using the “carbon footprint,” a calculator provided by the U.S. EPA, my annual footprint for home energy, transportation and household waste totaled 18,131 lbs., compared to the U.S. average of 24,550 lbs. for a single householder. However, this doesn’t include the CO2 emissions related to producing and delivering my daily consumption of certain goods (food, beverages, clothing, etc.) and services (restaurants, local grocer, etc.) including the amount of energy I use both at work (technology equipment, etc.) and commuting there (based on my 12-15 hours spent outside my home each day). This tool also revealed that just switching my washing machine from warm to cold water would cut carbon emission 150 lbs. per year and save me about $12. If you’d like to see your carbon footprint and/or identify ways to reduce consumption and save money, click on the EPA’s calculator here.

The following infographic shows the extent and distribution of CO2 emissions in the world, the U.S. and Illinois, including the carbon footprints of certain products.

Click through to see the enlarged image.


CarbonEmission_Infograph

Techniques Used
The above visualization includes 3 types of techniques:

Quantitative Analysis: A bar and pie chart were used to visualize quantitative data to show carbon emissions by various sectors over time and in 2013.

Statistical Analysis (GIS): Spatial analysis included two major techniques. The choropleth maps and classification methods were used to show the distribution of the emission levels globally and for the U.S.

Graphics: Images were obtained from Google and modified using Photoshop graphic design software

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.

Hate Nation

Although we take pride in being a developed nation, we still have a long way to go towards reducing organized hatred, hostility and violence against people who differ from “us” in race, color, ethnicity, nationality, religion, gender, sexual orientation or are designated as marginal within our society.

According to the Southern Poverty Law Center’s 2015 Intelligence Report, the number of hate groups active in the U.S rose from 784 in 2014 to 892 in 2015. The U.S. is home to the world’s most notorious hate group, the Ku Klux Klan, which had the largest share of U.S. hate groups that year (21.3 %). It was followed by the Black Separatists (20.2%), the Racist Skinheads (10.7%), the White Nationalists (10.7%) and the Neo-Nazis (10.5%). These 5 groups comprise 73% of the known hate groups in the U.S. Among the states, Texas reported the largest number, 84, 55 of which were KKK. California came second with 68 groups, mainly Black Separatists and Racist Skinheads. Florida ranked third, with 59, 22 of which were Black Separatist groups.

The following infographic shows the extent and distribution of known hate groups in the U.S.

Click through to see the enlarged image.

HateGroups_Infograph

Techniques Used
The above visualization includes 3 types of techniques:

Quantitative Analysis: A bar chart was used to visualize quantitative data on the number of known hate groups.

Statistical Analysis (GIS): Spatial analysis included 3 major techniques. The geocoding technique converted hate group locations to a point on the map, choropleth maps and classification methods were used to show the distribution of hate groups by state and to identify the correlation among race and the density of hate groups in each state.

Graphics: Graphics and images used in the infographics were edited using Photoshop graphic design software.

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.

Putting Art History on the Map

Joanna Gardner-Huggett, associate professor and chair of the Department of the History of Art and Architecture (HAA), has taken the plunge into the digital environment, setting her compass on mapping and spatial analysis to guide her current art historical research.

ARCHer subject is two Chicago feminist arts collectives that began in 1973: Artemisia, which lasted until 2003, and the still-operating ARC.  Her goal is to
tell the collective history of the two galleries by measuring their impact on the careers of the individual artists they touched as well as on the practice of art in and beyond Chicago at a significant point in the history of feminism and of separatist organizations.

Using ArcGIS data visualization software, she has been creating geographical maps based on the social, educational and professional demographics of the 129 member and guest artists who had solo shows at the two galleries from 1980–1985, “just to see if there were any patterns,” Joanna said.

What she’s discovered is that it’s “really a local story.  The mapping helped distill that beautifully,” she added.  To her surprise, she found that it “mostly had little to do w/ feminism,” she added.  “That was eye-opening, but really useful.”  She considers the role of the two collectives as essential in the development of a whole new generation of women artists.  “That’s the challenge,” Joanna said.  “There are so many people.  How do you write about a big group?”

The ARC and Artemisia archives held at the Ryerson and Burnham Libraries are her primary research source.  Through mapping and an analysis of spatial evidence she hopes to discover when the two groups were at their highest and lowest points of influence and what intersections were occurring at those points in time.

“I think art historians can make broad generalizations when discussing archival data, and the mapping makes us more accountable for our conclusions,” she explained.  “For me, the mapping is just a really wonderful tool.”

Joanna credits her HAA colleague Professor Paul Jaskot for igniting her digital exploration.  At his suggestion, she applied for and was selected as one of 15 Fellows to take part in the first-ever Summer Institute on Digital Mapping and Art History held in August 2014 at Middlebury College.  Paul and Middlebury Associate Professor of Geography Anne Kelley Knowles organized and co-direct the annual, hands-on, two-week symposium funded by the Samuel H. Kress Foundation.  Joanna thanks DPU Department of Geography Chair Euan Hague for referring her to the SSRC where Nandhini Gulasingam is guiding her use of Geographic Information Systems (GIS) and data visualization tools and techniques.  Joanna in turn has referred fellow HAA Associate Professor Delia Cosentino to the SSRC for help creating maps locating metal replicas of Mayan calendar stones for a project in Pilsen.

“It’s so great having that as a resource,” Joanna said of the SSRC.  “A lot of my colleagues don’t have that kind of support at other institutions.”  The students in Nandhini’s WQ Community GIS II class in the Department of Geography will incorporate Joanna’s database into their community-based group projects.  Joanna’s next steps will be to increase her own GIS proficiency and to develop more narrative-driven maps, possibly using Tableau or other visual analytics applications, with the help of the SSRC.

Some of Joanna’s maps may become available to future researchers on a website database that former members of Artemisia are building.  She’s also grateful to the Women and Leadership Archives at Loyola University Chicago which is collecting and preserving the papers of ARC and Artemisia members.

Which Commuters of the Largest U.S. Cities Use the Greenest Mode of Transportation to Work?

According to the 2010 U.S. Census, New York City (population 8.2 million), with one of the best subway systems in the world, ranked greenest mode of work transportation among the four biggest cities in the U.S mainly for its extensive subway system. Almost three-quarters of NYC’s commuters (72.7%) took public transportation, biked or walked to work, or worked from home. Less than one-quarter (22.4%) drove alone to work.

Only one-third of the commuters in third-biggest Chicago (2.7 million) chose public transportation to get to work. A half drove alone, mainly due to lack of or inconvenient mass transit in the outlying areas of the city.

With its underdeveloped and inadequate mass transit system, roughly 77% of Los Angeles commuters either drove alone or carpooled to work, while only 20% used public transportation.

Houston, the country’s forth largest city (2.1 million), was the flipside of NYC and ranked lowest of the four in green-friendly mode of transportation to work. Three-fourths of Houston’s commuters drove alone, and less than one-tenth (9.7%) used public transportation, biked, walked, or worked from home. Historically, Houston residents and elected officials have opposed the development of a mass transit system. It was the last major city to finally implement a 7.5-mile, 16-station light rail system, in 2004 that served only the densest areas.

Click through to see the enlarged image.

Green_Transportation
 

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. Some 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 Sociology Asst. Prof. Fernando DeMaio’s Center for Community Health Equity (CCHE) project. This research project used a multi-pronged approach in which maps were first created by SSRC to spatially visualize the areas served by hospitals in Chicago by various sub-geographies. Later, the SSRC trained Fernando’s research assistants how to clean and convert health, demographic and socio-economic data into mappable formats. They were also trained to create maps comparing health and demographic disparities in Chicago and Toronto, similar to the four-city transportation visualization depicted here.
 

Ask us how to visualize your research
If you want help with 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.