Reconstructing Velocities of Migrating Birds from Weather Radar – A Case Study in Computational Sustainability Public Deposited

http://ir.library.oregonstate.edu/concern/articles/j38608487

This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by the Association for the Advancement of Artificial Intelligence (AAAI) and can be found at:  http://www.aaai.org/Magazine/magazine.php.

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • Bird migration occurs at the largest of global scales, but monitoring such movements can be challenging. In the US there is an operational network of weather radars providing freely accessible data for monitoring meteorological phenomena in the atmosphere. Individual radars are sensitive enough to detect birds, and can provide insight into migratory behaviors of birds at scales that are not possible using other sensors. Archived data from the WSR-88D network of US weather radars hold valuable and 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 describe recent work on an AI system to quantify bird migration using radar data, which is part of the larger BirdCast project to model and forecast bird migration at large scales using radar, weather, and citizen science data.
Resource Type
DOI
Date Available
Date Issued
Citation
  • Farnsworth, A., Sheldon, D., Geevarghese, J., Irvine, J., Van Doren, B., Webb, K., . . . Kelling, S. (2014). Reconstructing velocities of migrating birds from weather radar - A case study in computational sustainability. AI Magazine, 35(2), 31-48. doi:10.1609/aimag.v35i2.2527
Series
Rights Statement
Funding Statement (additional comments about funding)
Publisher
Peer Reviewed
Language
Replaces
Additional Information
  • description.provenance : Approved for entry into archive by Deanne Bruner(deanne.bruner@oregonstate.edu) on 2014-09-25T19:08:19Z (GMT) No. of bitstreams: 1 DietterichThomasElectricalEngineeringComputerScienceReconstructingVelocitiesMigrating.pdf: 2478084 bytes, checksum: 15f0e57eea9630ef703014996c51a6fc (MD5)
  • description.provenance : Made available in DSpace on 2014-09-25T19:08:19Z (GMT). No. of bitstreams: 1 DietterichThomasElectricalEngineeringComputerScienceReconstructingVelocitiesMigrating.pdf: 2478084 bytes, checksum: 15f0e57eea9630ef703014996c51a6fc (MD5) Previous issue date: 2014
  • description.provenance : Submitted by Deanne Bruner (deanne.bruner@oregonstate.edu) on 2014-09-25T19:07:24Z No. of bitstreams: 1 DietterichThomasElectricalEngineeringComputerScienceReconstructingVelocitiesMigrating.pdf: 2478084 bytes, checksum: 15f0e57eea9630ef703014996c51a6fc (MD5)

Relationships

In Administrative Set:
Last modified: 07/26/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items