Presagis Showcases Rapid Geospatial Production Capabilities

Presagis has been showcasing a range of ground-breaking geospatial solutions designed to leverage the “AAA” approach of Augmentation, Automation, and AI this summer.

In June Presagis demonstrated their VELOCITY and ORB ViewR at GEOINT 2019. These respectively permit the creation of accurate, geo-specific worldwide geospatial data repositories and their integration into gaming engines – such as Epic Games’ UE4 – to deliver open world capabilities.

“Most customers we meet tell us of their challenge when it comes to the creation of large-scale, high-precision geospatial data repositories. New data collection platforms, emerging types of data, greater levels of detail, and sheer volume all increase the challenges faced by agencies and organizations,” explains Jean-Michel Brière, general manager of Presagis. “VELOCITY responds directly to this challenge by combining best-of-breed open source and commercial tools and data with a next-generation automation architecture.”

VELOCITY provides an automation framework that fundamentally changes the way organizations manage the production of large 3D environments by enabling:

  • Fusion of massive amounts of GIS
  • and sensor data including imagery, Lidar, and RADAR
  • Automation and large-scale distributed processing of geospatial data
  • Leveraging of AI and Machine Learning to support feature identification and extraction, multi-sensor data fusion and AI-supported automation

To help users explore their 3D environments and terrains, Presagis developed the ORB ViewR – a free, standalone application powered by the Unreal Engine – that provides users with photo-realistic rendering (including round-earth), streaming and paging with the smooth, seamless performance inherent to game technology.

“From automated data cleanup and 3D reconstruction, to the augmentation delivered by cloud computing and computer vision, Presagis solutions are providing users with new and rapid methods to ingest, transform, visualize, and publish geospatial data sources,” adds Brière. “Furthermore, the combination of computer vision and machine learning algorithms opens one of the most interesting avenues to automate the processing, integration, and analysis of GEOINT data – and the GEOINT Symposium is the best possible venue to showcase this technology.”