AI is prevalent in all aspects of our lives from the technology behind voice recognition software such as Siri on your iPhone to algorithms that evaluate your credit score or evaluate recidivism amongst convicts prior to parole hearings. I've been doing a lot of thinking lately about geospatial AI and in particular, AI that assists in the creation of geospatial data from imagery, lidar, video, SAR and other modalities. Here are 5 topics on my mind:
1. Geospatial AI is Already Here - And Changing Rapidly
A few years ago, the challenge of identifying a cat or dog in an image was thought to be exceedingly difficult yet within only a few short years, it can now be done using AI with a very high level of success (~98%). As has been often quoted, we are "swimming in sensors and drowning in data" and our industry needs the same ability to extract data from the numerous platforms and sensors at our disposal. A great deal of geospatial AI is developing and we must be aware of it, track its development and use it wisely. Geospatial AI is important for all geospatial professionals whether you are a photogrammetrist, surveyor, engineering, data scientist, CAD technician, database administrator, or GIS Analyst.