Rob Emanuele
Rob Emanuele is a Geospatial Architect at Microsoft with the AI for Earth team working on the Planetary Computer.
Sessions
At Microsoft AI for Earth we're taking petabytes of openly licensed, cloud optimized Earth science data and making it searchable and analysis-ready in what we're calling a Planetary Computer. We've built pipelines that process data into cloud optimized formats, derive metadata in the SpatioTemporal Asset Catalog (STAC) format, and index the data such that it is queryable through the OGC API - Features and STAC API standards. We're also supporting the integration of our data within the Pangeo open source ecosystem to enable open architecture approaches to Earth science analytics and applications.
In this talk I'll present the architecture of the Planetary Computer, how it is built on the amazing ecosystem of open source tools that work with these datasets, and how we build in a way that enables contribution to and support that ecosystem.
The Paris climate agreement targets limiting our global heating to 1.5°C above pre-industrial averages. However, there are reports stating that this goal is now "virtually impossible"[1] to achieve, and recent research claims that the planet is already committed to over 2°C[1] of global heating. The effects of this level of warming will be widespread and hard to predict, but one thing is clear - our ability to process and analyze geospatial data in order to monitor, model and manage Earth's natural systems will be key to responding effectively and intelligently to the challenges humanity will face over the next century.
We in the open source geospatial community have the opportunity to build the technologies that will be critical to mitigating and adapting to the rising effects of climate change. In this talk I will challenge our amazing community to use its vast talents and capabilities to work towards supplying the future with the data and tools it needs in the fight to protect our Earth.
[1] The risks to Australia of a 3°C warmer world | Australian Academy of Science
[2] Greater committed warming after accounting for the pattern effect | Nature Climate Change