What is Geospatial intelligence?
Geospatial intelligence is, as the name suggests, all about deriving information from geospatial data. In the same way, we use the time to give context to data when analyzing it we can also use location as an extra dimension. If you think about trying to derive meaning from a data set of the number of shoes brought by people living in Canada without any knowledge of the time or date when the shoes were purchased you will quickly understand that creating marketing budget or basing any future decisions on this data would be almost impossible. However, if we know the time and date of the purchases we can start to discover trends in the data because time gives us a way of grouping and relating purchases to each other. Now consider the same scenario with a spatially enabled data set. Now, we can not only ground customer behavior by time but also by location. This might mean that we see patterns like certain geographic areas that brought more or fewer shoes than other areas. These kinds of patterns or trends would be used to inform in other business-related decisions such as where and when should a show company concentrate their marketing efforts.
This, of course, is a very basic example and does not include all the nuances of more complicated problems like where to locate a new playground so it is accessible to the largest number of children or natural disasters in one part of the world might ultimately affect the insurance rate in another part of the word.
The more dimensions we can add to data the more detailed analysis and the more precise our conclusions can be. Tobler's first law of geography states that “all things are related but near things are more related than distant things”. Geospatial intelligence seeks to create value by considering the geography and the relationships between objects based on location.
For a more detailed discussion on geospatial intelligence and how it relates to risk management listen to this podcast episode!