This presentation, "Bringing Innovation to Global Humanitarian Efforts through Human Geography & Predictive Analytics," was presented at Esri UC 2012 by Ben Holland, GeoEye Geospatial Analyst
2. GeoEye Analytics NJ Fusion Center (ROIC) Project
• Geospatial predictive analytics applies advanced
statistical analysis and modeling techniques to Outside
spatial relationships Agencies (e.g.,
FBI, Jersey City
PD)
• To answer questions such as: Sub
j
Ma ect
tte
Exp
ert r ion
– Where is something most likely to occur? ise at
rm g
fo
Tra In arin
dec Sh
raf
– Where is the greatest risk? t
Sof
– How should I best deploy my resources? t wa
re
3. Geospatial Predictive Analytics with Signature Analyst
Jersey City
Area of Interest (AOI)
Geospatial Predictive Analytics
Predictive Assessment
Past Events GIS Factor Data
4. Discovering New Locations of Concern
Identifying geospatially similar areas
Density Map Predictive Assessment
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8. Staten Island, NY Serial Burglary Pattern: January 2012
Past Related Burglary
Likelihood of Future Burglary
Highest
High
More on the software, we see here the initial pieces of geospatial factor data that we use. The first being the area of interest that we are trying to predict in. The shape you see there is Jersey City. The second piece is the event data, the crimes or threats to critical infrastructure that we are trying to predict. And the final and most vital is the geospatial factor data. This consists of layers of data which include demographics, city infrastructure, property value, locations of business and services, pretty much anything you can capture geospatially. We input all this data into the system which uses geospatial predictive modeling to find correlations between the events and the factors within the area of interest. The output is a predictive hotspot map which shows areas and neighbors that are geospatial similar to past events in order to identify to areas of concern.
Here is a better example of a predictive assessment. The density map on the left shows a traditional analysis used to identify hotspots. The predictive map on the right discovers new areas of concern where future events are most likely to occur. The value in this has been for law enforcement deployment planning and as actionable intelligence to decision makers.