My final project is a highly in-depth analysis of crime in Chicago. The study focuses primarily upon the last eleven years of available crime data and emphasizes socioeconomic trends and correlations within the field of “Deceptive Practices.” The project is subdivided as follows:
Part I: “The Residential and Commercial Components of Deceptive Practices.”
Statement of Intent: After the fall of Enron and other multinational corporations in 2001, a major crackdown on corporate and commercial fraud was instituted under the Bush administration and the Security and Exchange Commission [SEC]. Since many corporate and commercial entities reside in Chicago, the first stage of this project maps fraud and other crimes of deception within both the residential and commercial realm. It is hypothesized that since the 2001 ordinance, individuals may be more discouraged from committing fraud within a commercial setting, and – therefore – will be more likely to commit these acts at home. This initial section deconstructs all 150,000 acts of fraudulent crimes and examines each in graph and map form on an annual basis.
Process: Data was imported from the database into Quantum GIS where it was converted into heat maps so as to show which wards engaged in the largest number of deceptive practices per year in both a commercial and residential setting. An additional heat map for each year was produced to show which wards had the greatest ratios of residential to commercial-based fraud by simply dividing the former total by the latter for each ward and re-mapping. After totals for each ward were uncovered using the “points in polygon” query in QGIS (an exhausting process considering the large amount of data), the totals were re-entered into a spreadsheet in order to graph the distributions. Lastly, three graphs showing the overall distribution of deceptive practices for all years were created in order to draw conclusions regarding the distribution.
Results: The final graphs are quite interesting. Though the initial study is somewhat skewed since data from the preceding decade was unavailable for comparison, the final graphs suggest a large decrease in residential and commercial based fraud in wards 1-10 after 2001. Similarly, a close look at the graphs reveals a slight but rather steady rise in deceptive practices committed in a residential setting, as well as a more exponential decrease in those committed in a commercial setting. Similarly, the ratio of commercial to residential-based fraud in almost every ward appears to have increased greatly since 2001, suggesting a reallocation in several wards of where these crimes are committed.
Part II: “The Sociocultural Correlations of Deceptive Practices.”
Statement of Intent: The original intent of the second portion of the project was to investigate various sociocultural components of Chicago and see if there was any correlation between where they occur and where deceptive practices occur. In terms of selecting these components, it was very important that they relate, in some way, to the pathology of why one commits crime. Therefore, this next series of maps investigates the link between a ward’s level of fraud and its median home-value, its adjacency to educational facilities, as well as its rate of population increase/decrease since 2001.
Process: Heat maps of all three components were generated and, once again, each ward’s data was extracted from QGIS’s spatial query functions into spreadsheet format for graphing. The graphs in these sections are especially important since they were used to determine the coefficient of correlation for each query. This was done by creating a graph of the D.P.’s occurring in each ward and superimposing the corresponding graph (whether it was schools per ward or home value per ward) on top of it. By doing so, I was able to get fifty x-points [the DP’s per ward] and fifty y-points [the compared value per ward] from each graph, and input them into a correlation calculator. By doing so, a separate coefficient of correlation for each relationship-query was produced.
Results: While the previous section’s results confirmed their initial hypothesis, the coefficients of correlation were quite low in this section. The highest positive correlation was over .25, suggesting only a moderately affirmative correlation. Despite this, however, the comparison between schools and D.P.’s per ward resulted in a rather strong negative correlation of -.456, suggesting that a lower number of schools in a ward corresponds with a higher number of deceptive crimes within the same boundary.
Part III: “The Urban & Exurban divide in Chicago Crimes”
Statement of Intent: Whereas the previous sections examined deceptive practices in close detail, this last area of crime analysis examined all Chicago-based crimes from 2001-2008 on a formal and graphical level. While, at first glance, the largest appropriation of crime typically occurs in the downtown area, this negates the effects that each ward’s population has on producing the distribution. For example, while it may appear as though there are a large number of crimes occurring in one ward, it may be because the population in that ward is so much higher. I was, therefore, determined to examine whether most crimes actually do occur in greater number in the downtown area or in the suburban/exurban regions of Cook County by re-contextualizing the total crimes per ward.
Process: In order to visualize the distributions of each crime, maps were generated in a very recursive manner showing the point-based assortment of crime across the region in two-year intervals. Spatial queries in QGIS where subsequently executed to determine the number of crimes in each ward for every two-year interval. After that, the total number of urban/downtown-based crimes was divided by the total downtown population, and, conversely, the total number of exurban/suburban crimes divided by the total exurban/suburban population. By undergoing this extremely lengthy process, these ratios were able to tell whether each crime occurred more in an urban or exurban setting with regards to the population density. These ratios were subsequently graphed in order to show the change over time, and a very simple heat map for each crime was generated to show the wards in which the corresponding crime occurred the most throughout the eight year interval.
IIT COA | Urban Information Modeling 