Winning Posters from the 2011 Crime Mapping Research Conference

At the 2011 Crime Mapping Research Conference, NIJ sponsored a contest to encourage effective and innovative use of cartographic techniques and design principles to present spatial data analysis of crime activity, trends, patterns, or phenomena. Following are the winners:

Neighborhood Stabilization in Oakland, California: Responding to the Foreclosure Crisis in a High Crime Community

ESRI and the Urban Strategies Council, Oakland, Calif.

The following description was submitted by the entrant:

East Oakland has faced multiple crises over the past decades. Specifically, issues such as heavy disinvestment from the mid-century, to spiraling crime, consistently high unemployment and failing public school systems are still present. On top of this, long-term stress for the part of the city referred to in the maps are from the predatory lending of the early 2000's; and this has further resulted in massive foreclosures across an area with historically stable home ownership.

In 2009, the Urban Strategies Council and key allies formed the Oakland Community Land Trust in an effort to stabilize these communities. The model used combines very detailed neighborhood-level data on crime, assets, foreclosures and housing conditions to ensure work is data-driven and proactive.

This map illustrates the growing burden of the foreclosure crisis in Oakland over time. It also shows the changes in stability and serious crimes in this neighborhood that make neighborhood stabilization efforts even more difficult. When considering which foreclosed properties to acquire and rehabilitate (for moderate income affordable housing), it is crucial that there be consideration for the neighborhood context of each property. For example, homes on gang occupied corners or on streets known for shootouts, present serious challenges in attracting new home owners. Likewise, an area with high property crime may result in increased construction costs due to building-site thefts.

Mapping 'In-Transit' Crime Incidents on the Melbourne Railway Network

Timothy Mashford, State Intelligence Division, Victoria Police

The following description was submitted by the entrant:
Victoria Police has made use of GIS technology since the 1990's to map and analyse crime, in support of an 'intelligence-led' approach. With over 300 intelligence analysts making use of desktop mapping applications, Victoria Police relies on GIS to identify problems, locate activity hotspots, and target resources effectively. Victoria Police use GIS to map crime incidences on Melbourne's metropolitan train network — a network of 15 lines, containing 830km of track and 211 train stations. With more than 219 million journeys made each year, crime statistics show that travel on the network is mostly safe. However, like all transport systems around the world, the network does experience crime and anti-social behaviour, and it is therefore important that police resources are efficiently targeted to reduce crime and maintain public confidence.

Incidents which occur on a train cannot easily be geocoded to a single point on the map, as they often occur 'in transit'. For example, an act of vandalism may occur while the train is in motion, effectively covering several kilometres of track. To deal with this, a new methodology was developed which calculates the probability that the offence occurred within any of the between-station sections along the railway network. For example, a crime recorded as having occurred over 4 sections would apply a score of 0.25 (or 25% probability) to each of these sections.

These probabilities are then summed for each section, to calculate a total score per section which can be used to thematically shade the sections with the highest count of offences. Utilising this methodology allows over 95% of the data to be visualised on the map, providing a more complete view of the distribution over the network. Intelligence analysts can then further examine the data using other methods such as temporal analysis, to identify the 'where' and the 'when' for crime reduction patrol targeting.

Vehicle Burglaries — Targeted Enforcement Using Weighted Hotspots

Crime Analysis Unit City of Riverside Police Department, Calif.

The following description was submitted by the entrant:

Given scarce policing resources and a move towards working smarter with innovative tools and analytics, the Crime Analysis Unit at City of Riverside is providing information to support targeted policing strategies. One of the methods developed is the use of weighted hotspots derived from previous year crime data to identify "Hot" specific locations and "Hot" address blocks. Specifically, vehicle burglary crime type is used to illustrate the method.

Densities of vehicle burglaries for the 4th Quarter in the years 2008, 2009, and 2010 are generated using the Kernel Density method with a search radius of a quarter (1/4) mile. The Natural Jenks classification method is used to highlight the "areas of highest density as well as revealing subtle patterns" (Mitchell - ESRI Press) for each year. The object​ive is to highlight the concentration based on the data per year as opposed to using the same classification method for each year.

Using the raster calculator in ArcMap, the hotspot data for the three quarters were assigned weights to derive a "Weighted Average Density." The density for the 4th Quarter 2010 is assigned the highest weight. This is based on the assumption that locations of crime incidence in the most recent quarter play a more significant role in predicting crime for the forecast quarter.

The weighted average density map serves as a good visual for highlighting potential concentrations of vehicle burglaries for 2011. To add a quantitative dimension to the map, the medium to high concentration areas are converted from raster grids to polygons using the reclassify and raster to polygon tools.

Vehicle burglaries within the "hot" areas are then selected using the "hot" polygons and exported to Microsoft Excel for data mining. Summary heat charts are generated in excel showing hours of occurrence in places with high vehicle burglaries. These identified target locations are then overlaid on the hotspot map to make it more meaningful for policing. In addition, the data is summarized by address blocks to widen the scope of the target areas for vehicle burglaries.

Deliverables to Patrol and specialized units are (i) The map showing the weighted density overlaid with the target locations, and (ii) The heat charts for specific places and address blocks. Patrol officers and specialized units are now armed with information to support the targeted policing strategies. In addition, Crime Analysts have access to the data in excel to further analyze and routinely compare it to the current year's crime and advise if patterns remain consistent; if they change; and if new patterns emerge.

Date Created: June 21, 2012