TY - JOUR
T1 - Reconstructing velocities of migrating birds from weather radar - A case study in computational sustainability
AU - Farnsworth, Andrew
AU - Sheldon, Daniel
AU - Geevarghese, Jeffrey
AU - Irvine, Jed
AU - Van Doren, Benjamin
AU - Webb, Kevin
AU - Dietterich, Thomas G.
AU - Kelling, Steve
PY - 2014
Y1 - 2014
N2 - Bird migration occurs at the largest of global scales, but monitoring such movements can be challenging. In the United States 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 U.S. 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.
AB - Bird migration occurs at the largest of global scales, but monitoring such movements can be challenging. In the United States 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 U.S. 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.
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U2 - 10.1609/aimag.v35i2.2527
DO - 10.1609/aimag.v35i2.2527
M3 - Article
AN - SCOPUS:84904858652
SN - 0738-4602
VL - 35
SP - 31
EP - 48
JO - AI Magazine
JF - AI Magazine
IS - 2
ER -