Geospatial Knowledge Discovery (GKD) helps predict relative likelihood locations for future events. It mines text, relation and geospatial data together to pinpoint search locations and it provides predictive geospatial intelligence.

Geospatial Knowledge Discovery extends data mining capabilities to include geospatial data sets. It allows data mining models to handle concurrently numerical data, text data and geospatial data. More importantly, data mining uncovers the underlying trends and patterns that are hidden in data by leveraging one data set upon the other. Concretely, multi-INT data such as IMINT, SIGINT, and MASINT can be mined along with geospatial data and open-source web data.

The ability to handle disparate types of content has tremendous implications on the nature of questions and problems to be solved. Within this new GKD framework, one can finally address the following types of problems: Where are the most likely places to look for activity? Where are likely locations for power lines?