Approximate Bayesian inference for reconstructing velocities of migrating birds from weather radar

Daniel Sheldon, Andrew Farnsworth, Jed Irvine, Benjamin Van Doren, Kevin Webb, Thomas G. Dietterich, Steve Kelling

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Archived data from the WSR-88D network of weather radars in the US hold detailed information about the continent-scale migratory movements of birds over the last 20 years. However, significant technical challenges must be overcome to understand this information and harness its potential for science and conservation. We present an approximate Bayesian inference algorithm to reconstruct the velocity fields of birds migrating in the vicinity of a radar station. This is part of a larger project to quantify bird migration at large scales using weather radar data.

Original languageEnglish (US)
Title of host publicationProceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013
Pages1334-1340
Number of pages7
StatePublished - 2013
Externally publishedYes
Event27th AAAI Conference on Artificial Intelligence, AAAI 2013 - Bellevue, WA, United States
Duration: Jul 14 2013Jul 18 2013

Publication series

NameProceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013

Other

Other27th AAAI Conference on Artificial Intelligence, AAAI 2013
Country/TerritoryUnited States
CityBellevue, WA
Period7/14/137/18/13

ASJC Scopus subject areas

  • Artificial Intelligence

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