The Macroscope Initiative – Building Planetary geoML with OmniSci

On Demand
Presented by:
HEAVY.AI

HEAVY.AI provides advanced analytics that empower businesses and the government to visualize high-value opportunities and risks hidden in their big location and time data, supporting time-sensitive, high-impact decisions.

Featured Guest Speakers:
  • Dr. Mike Flaxman, Spatial Data Science Practice Lead at OmniSci
  • Abhishek Damera, Data Scientist at OmniSci

Microscopes are age-old technology which let us visualize and research phenomena too small to be perceived by the human eye.  Macroscopes, by contrast, are systems designed to reveal spatial and temporal patterns which are so big or slow that they escape normal human perception. We can get some sense of these when we fly, or when we look at time-lapse imagery. But to really make progress requires both the ability to collect planetary-scale information over time, and to harness modern compute technologies to support interactive visualization and interrogation of such data.

The convergence of three technologies is finally allowing the construction of macroscopes, and making them practical for daily use in both scientific and business contexts.  First, there’s the advent of LIDAR, GPS cell phones and ‘cube’ sats. These supply raw observation data from nearly everywhere, capturing both human and natural activities. Then there are machine learning methods which can classify patterns of movement or pixels. As applied to geodata, this is called “geoML.” Last but not least there’s modern computing architectures which move algorithms to data and stream highly-distilled information to client applications. In this presentation, they will explore three applications of the macroscope concept, applying it to the monitoring of individual tree health for hundreds of millions of trees, the exposure of static and moving assets to weather, and the analysis of ship movement patterns.

Agenda:

  • 12:00pm – 12:30pm: Featured Presentation
  • 12:30pm – 1:00pm: Audience Q&A and Interaction

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