Geographic Information Systems (GIS) Field Upended by Neural Networks

On today's episode of "The Interview" with The Next Platform, we focus on how geographic information systems (GIS) is, as a field, being revolutionized by deep learning. This stands to reason given the large volumes of satellite image data and robust deep learning frameworks that excel at image classification and analysis–a volume issue that has been compounded by more satellites with ever-higher resolution output. Unlike other areas of large-scale scientific data analysis that have traditionally relied on massive supercomputers, our audio interview (player below) reveals that a great deal of GIS analysis can be done on smaller systems. However, with the addition of deep learning, the field could be investing in more GPU systems for training and still others for inference at scale. Using lower end TitanX GPUs from Nvidia, the team, which includes Sudeep Sarkar and Mauricio Pamplona Segunda that created a CNN approach to GIS land classification described here, it was shown that deep learning can be a successful tool in the box of GIS analysts.