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 reconstructing velocity


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

AI Magazine

Each volume scan consists radial velocity data. For any given pulse volume, radial of a sequence of sweeps during which the antenna velocity tells us the component of target velocity in rotates 360 degrees around a vertical axis while the direction of the radar beam, and we have no additional keeping its elevation angle fixed (figure 2). The result information about the component orthogonal of each sweep is a set of raster data products summarizing to the radar beam. However, the overall pattern of the the radar signal returned from targets within sweep often provides clear evidence about the true discrete pulse volumes, which are the portions of the target velocities. In this example, targets to the northeast atmosphere sensed at a particular antenna position (NE) of the radar station have negative radial and range from the radar. The coordinates of each velocities (dark colors), which means they are pulse volume (r, ϕ, ρ) are measured in a three-dimensional approaching the radar, and targets to the southwest polar coordinate system: r is the distance in (SW) of the radar station have positive radial velocities meters from the antenna, ϕ is the azimuth, which is (light colors), which means they are departing the angle in the horizontal plane between the antenna direction and a fixed reference direction (typically the radar station. We can infer that the targets (in this degrees clockwise from due north), and ρ is the elevation case, predominantly migrating birds) are moving uniformly angle, which is the angle between the antenna in a SW direction, as shown in panel (c). The direction and its projection onto the horizontal spiral pattern in the velocity image is due to changes plane.


Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar

AAAI Conferences

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.