7 Must-Haves for Mobile GEOINT Tradecraft

28 May 2014 by Andie Dodd

In today’s world, the potential to collect geospatial data is in the pockets and purses of more people than ever before. Though a lot of existing GEOINT Tradecraft seems to be designed around bringing information to handheld devices in the form of reports and maps, effective tradecraft should be a seamless information exchange to and from the field through mobile capabilities. With the presence of so many mobile devices, there is a lot of potential for this seamless exchange to be applied in the real world.

Patrick, Bryan, and I hosted a workshop at the GEOINT 2013* Symposium aimed at showing the audience how a mobile product for data collection, using Fulcrum as an example, can be effectively deployed for mobile tradecraft. Here are 7 must haves for efficiency in Mobile GEOINT Tradecraft.

EXIF data

  1. Custom, offline layers - the ability to load custom basemaps and layers for use offline is essential for providing context, direction, and information to a field data collector.

  2. Temporary device storage - an essential in an offline environment, the device should temporarily store all collected data for sync upon return to an office or online environment.

  3. Media capture - Photos and videos are extremely important for ground level verification. However, media capture is also useful for collecting derivative information by default, as it is nearly impossible to exclude the surroundings of a subject from the picture or video. This derivative information can greatly add value and depth to analysis.

  4. Geotagged photos - Exif data is great information to have. Not only does it provide additional verification from the field, but it automatically adds another layer of information to data collection without having to take any extra steps.

  5. Standardization - a data collection form should have some level of standardization so that data produced in the field is accurate and consistent. The implementation of choice lists and classification sets in Fulcrum saves the data collector from having to input frequently occurring text values. While this practice saves time on the ground, it also cuts back on typos or spelling mistakes made by the data collector, keeping a high level of data integrity.

  6. Field logic - using field logic helps present the data collector with an easy to use data collection form. For example, with Fulcrum’s visibility and requirement rules, showing specific fields only when relevant or requiring a certain field only under specific circumstances can help to improve data integrity.

  7. Platform independence - platform parity is especially important in a “bring your own device” scenario. When equipment can be made up of multiple operating systems, it can reduce training time since people are using a device they are already familiar with. Plus, teams can collaborate and collect data at the same time, regardless of which device they are using.

Field conditional logic

Andie Dodd

About the author

Andie is a geographer at Spatial Networks. She works with our development team to design the Fulcrum platform. Also a self proclaimed ‘tea snob’ in an office full of coffee drinkers.