Geospatial is a term that has only found common usage this millennium. Even the National Geospatial-Intelligence Agency (NGA) with its primary mission of collecting, analyzing, and distributing Geospatial Intelligence (GEOINT) was known as National Imagery and Mapping Agency (NIMA) until 2003. The name change reflected the transition for photographs and paper maps from tools of common use to items of nostalgia.
Now Part of Everyone’s Daily Life
Can anyone remember writing a date and location on the back of a Polaroid? GEOINT is now at our fingertips and can even be summoned by voice. We are guided by GPS to the restaurants of our choice. We all know that roads, rivers, borders, and 3-D buildings now come in layers and can be turned on and off in our phone Apps or Geographic Information Systems (GIS) at will. If we cannot see over our neighbor’s fence, we find imagery from a satellite that can.
The Numbers are Astounding
It is very clear what changed. Cameras became digital, computers to process and serve data became nearly omnipresent, and unmanned vehicles to host the cameras became commonplace. But, the numbers are truly astounding. Billions of cameras are sold each year. Over a billion are in smart phones capable of tagging each image with time, position, and orientation. Some cameras matrix hundreds of individual focal plane arrays, the imaging chips in cameras, to form a single camera capable of imaging tens of square miles in a single frame from an aircraft with many frames captured per second. Millions of drones are sold commercially each year. Hundreds of Predator and Reaper drones have been deployed to militaries across the globe to provide reconnaissance and surveillance information for digestion by commanders and sometimes the viewers of television news. A single commercial satellite can capture roughly a million square miles of imagery with resolution of less than a meter per day and revisit the same area nearly once per day.
With so much data, computers have naturally become essential tools for distilling intelligence information from it. To meet the challenge, computers have gone massively parallel. As silicon chip makers feared the demise of Moore’s law due to anticipated physical limits on minimum transistor size, they worked on coupling multiple processors to divide and conquer problems in parallel.