Geospatial intelligence (GEOINT) is mapping using satellite images, digital elevations, transportation networks, land use classifications, vegetation classifications, weather data, demographics and much more to help the decision making process for any activity a corporation, army, or group wishes to undertake.
Unfortunately much of the best data, the highest resolution and degree of accuracy, is only available to large corporations and nations. This does not mean it is not possible to create your own GEOINT solution.
A small scale solution is constrained by data storage and computing power, in every GIS (Geographic Information System) user’s dream is to be able to have all the data and use it too! To make this possible we are only concerned with the area around a BOL or a route to a BOL, thus keeping the data storage and visualization processing low.
Open source data is available to satisfy most of what a small company or group needs to create their own GEOINT system. As well the software is also free. By accepting a small error in position and quality the job can be accomplished. First we are going to take a look at the hardware needed. Minimum is a laptop of medium quality. Most laptops today come at reasonable prices and have sufficient hard drive space and processing power, but please keep in mind that this setup cannot be used for surfing the web for music and apps or gaming. All the resources of the computer must be dedicated to the GEOINT problem. To make this a bit better we add a second wide screen, 23 inch will do, and a USB 3.0 external hard drive. The computer should have two internal hard drives, preferable a SSD (Solid State Drive) as the primary drive to hold the operating system and the GEOINT programs. The second drive is a normal drive to hold programs that are not used often and the datasets. The external drive is for holding more data if the user wishes to extend the areas of coverage.
Next we need to choose the software, some is free and others come with a small licensing fee. The two most important software packages are QGIS (an open source free fully capable GIS package), and Global Mapper (fee based but cheap and extremely useful) the Swiss Army Knife of GIS software. With these two most tasks can be performed.
Quantum GIS (QGIS) is open source community supported software that rivals ESRI ArcGIS quite expensive GIS solution.
A tutorial on how to use these software packages can run volumes but that is not our goal here today. We are here to see how it is possible to do what the big boys do, and most certainly will use against you.
GEOINT starts with the collection of datasets, overlaying the data in the GIS, and on the very beginning seeing all the information around your locale. The data sets are:
Real colour imagery from Google Maps, Yahoo Maps, Bing Maps, or many other online sources.
SRTM (Shuttle Radar Terrain Mission) digital elevation grayscale imagery
ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer)
OpenStreetMap (Free road network mapping) and transport mapping.
The key point to remember we want to collect the data and have it resident on the laptop because when the data stream ends with the closure of the internet for any reason your system will be able to continue to function. This is where Global Mapper comes in. This software is capable of downloading the online data to softcopy and stored on your hard drive.
Next we begin the process of analysis, for this we use the best ever processor and imaging device, your brain and Mark I Eyeball. As you are downloading the imagery the process of analysis can begin right away. Our brains are superb at spatial recognition and immediate storage of relevant information. We have completed the download of our first full colour image from some online source.
Stare at it for a while, just letting your eyes scan the picture and very soon you begin to see features in the picture that are in some way connected to your location or planned travel route. We do this with or without the GIS programs. There is stuff to see that you had no idea was there and it will have an effect on what you thought was the right thing to do. Keep scanning those images so that you know them and can picture them in your mind’s eye so that when you see from ground level you experience that “Aha!” yes now I know what that is, and the wheels and gears in your head will begin to turn because in some way those previously unknown locations have relevance to your task at hand.
Once we have looked over all the downloaded images we assemble them in the GIS by overlaying. The GIS allows the user to see through one image to the underlying image. The two or more images can now be analysed for relevant information about buildings and road access near your BOL or route. Next step up in analysis is the drape. We want to drape the full colour image on to a 3D surface such as the SRTM data to give the colour image shape of the land. The SRTM data stores elevation and can transfer that to the colour image. We now can see how the landform effects road access, travel to buildings, possible hunting areas, access to water sources and who your potential competitors for that water are.
The United States has the best online sources of free data for CONUS and few other places. Many data types can be integrated into the GIS such as vegetation, biodiversity, population density, agriculture productivity and soil types, mines and mineral occurrences, old mines and ruins, and so much more.
To make it work we need to be realistic about how much data we want to collect because it can get crazy quickly. A reasonable size database can be the extent of your patrol radius. You need a buffer around your locale to cover all possible patrol routes, and twice that to give your some “analysis space” to see what is beyond your area. If possible you can build a dataset to cover routes to and around your closest towns.
I have only teased you today with the ability to build your own GIS and GEOINT system. In the next article I will instruct you on how to design your own patrol routes, how to add visual information such as AAR to the GIS and digital camera snapshots to the GIS.