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

Author:

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

Abstract

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.

Publisher

Association for the Advancement of Artificial Intelligence (AAAI)

Subject

Artificial Intelligence

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Great Lakes shape nocturnal bird migration in southern Ontario;Avian Conservation and Ecology;2022

2. Flight directions of songbirds are unaffected by the topography of Lake Erie’s southern coastline during fall migration;Journal of Field Ornithology;2021-08-17

3. Novel Feature Extraction Algorithm for Classification of Multiple Occurrence of Flight Calls;Engineer: Journal of the Institution of Engineers, Sri Lanka;2021-08-11

4. Acoustic classification of individual cat vocalizations in evolving environments;2021 44th International Conference on Telecommunications and Signal Processing (TSP);2021-07-26

5. LBP-based bird sound classification using improved feature selection algorithm;International Journal of Speech Technology;2021-07-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3