Fathom will be returning to the American Geophysical Union’s (AGU) Fall Meeting in New Orleans next week. The annual event takes place across three days and is the largest preeminent Earth and space science meeting in the world.
Fathom’s co-founders have attended the conference regularly over the past 20 years, with Chairman Paul Bates being made an AGU Fellow last year. In fact, it was during a trip to AGU in 2012 that the discussion around forming Fathom first began.
The AGU Fall Meeting brings the world’s Earth and science community together to discuss research and emerging trends. This year, Fathom will be presenting nine talks across the three days, including Dr Andrew Smith’s partnership with Facebook Connectivity Lab, which aims to calculate risk in developing countries by assessing hi-res satellite imagery and AI.
Fathom’s Professor Paul Bates has presented at the meeting on many occasions over the past 20 years, on topics including early flood model algorithms and modelling of the Amazon basin. This year his renowned presentations will include an overview of
Fathom’s up-and-coming US stochastic flood model.
Oliver Wing, author of Fathom’s recent peer-reviewed US model validation paper, will be presenting on Fathom’s ground-breaking large-scale US flood risk analysis, and will also be attending the AGU press conference, whilst Dr Chris Sampson will be talking on
Fathom’s modelling of Hurricane Harvey which provided data to NASA during the disaster.
“We’re very excited
to have such a strong presence at AGU this year. The event itself is always one
of the scientific highlights of the year, bringing together many of the world’s
leading scientists. It’s an opportunity to present our research and methods,
receive feedback from our peers, and plan our collaborations for the coming
Dr Andrew Smith
Read the paper
New estimates of flood exposure in developing countries using high-resolution population data
A Nature Comms publication in which we demonstrate the critical importance of having both high resolution hazard and high resolution population data when assessing at-risk populations.