Astronomy of Crime

Mapping homicide statistics as constellations


As a data artist and a San Francisco resident, I’m driven to understand my city and somehow make meaning out of the chaos of this urban environment. I’m drawn to dark data, and there’s nothing darker than when someone takes another person’s life.

This is a map of murders throughout the Bay Area. Constellations are formed by connecting homicides from 2013 that are in close geographic proximity to each other. Homicides from 2014 are also layered on to provide a bit more context, although not used to form the constellations. The patterns emerge organically through the visualization of these geographic connections.

The symbology of representing deaths as stars in the night sky is a common cultural thread. We often like to think our loved ones are shining down above us.

Below is the detailed view of San Francisco, Oakland and Hayward, which have some of the most interesting constellations. Oakland certainly stands out, although 2013 actually saw one of the lowest homicide rates in the city’s recent history.

As with clouds in the sky, different people will see different things. San Francisco jumps out as a dog to me. In Oakland I can see a whale or shark (facing south toward Hayward) or a caterpillar (facing north toward Berkeley).

The surrounding cities of the Bay Area that have notable densities of homicides are Richmond, Antioch, East Palo Alto, and San Jose. The data covers the counties of San Francisco, San Mateo, Santa Clara, Alameda and Contra Costa.

Just north of Berkeley we have a cluster in Richmond, forming what to me resembles a child swinging in a hammock. Even though Richmond still stands out, its homicide rate for 2013 was actually at a 33-year low.

A bit to the east is Antioch and Pittsburgh. Antioch is the main cluster in the middle and Pittsburgh is the smaller cluster to the west. 2013 seemed to be a particularly brutal year for Antioch when it came to murders, even though the rate of other crimes significantly dropped.

East Palo Alto is a notable cluster that stands out due to its concentration and isolation. The data has eight 2013 murders in East Palo Alto, contrasted with almost nothing in the richer surrounding cities of Palo Alto, Atherton, and Menlo Park.

The sprawling city of San Jose also produces a sprawling map — connecting the dots of the 2013 killings produces a disarming image that looks an awful lot like a human face.

The Data

San Francisco publishes a decent amount of crime data on its data portal, DataSF, however homicide data is not included. The data used in these maps was collected and published by the San Jose Mercury News.

2013 map and kml file.

2014 map and kml file.

Method

Both the 2013 points and the 2014 points were used in the map. To form the constellations, however, only the full set of 2013 data was used. Constellations were formed by connecting the 2013 points using Delaunay triangulation and then filtering down the resulting lines to only include lines shorter than a certain distance. That left clusters of points that are all close together.

Here’s the map of only 2013 points connected using Delaunay triangulation, before filtering the lines by distance.

There is no connection between any of these locations besides their proximity to each other. A line connecting two points is not meant to signify any relationship, other than their geographic proximity.

Tools

The data was processed using QGIS for the initial exploration work and to create the Delaunay triangulation lines. I then brought the data into MapBox Studio, which was used to style the points and lines and to export a high resolution image. The rest of the processing was done in Photoshop.