Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar
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.
Cite
Text
Sheldon et al. "Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar." AAAI Conference on Artificial Intelligence, 2013. doi:10.1609/AAAI.V27I1.8486Markdown
[Sheldon et al. "Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar." AAAI Conference on Artificial Intelligence, 2013.](https://mlanthology.org/aaai/2013/sheldon2013aaai-approximate/) doi:10.1609/AAAI.V27I1.8486BibTeX
@inproceedings{sheldon2013aaai-approximate,
title = {{Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar}},
author = {Sheldon, Daniel and Farnsworth, Andrew and Irvine, Jed and Van Doren, Benjamin and Webb, Kevin F. and Dietterich, Thomas G. and Kelling, Steve},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2013},
pages = {1334-1340},
doi = {10.1609/AAAI.V27I1.8486},
url = {https://mlanthology.org/aaai/2013/sheldon2013aaai-approximate/}
}