Abstract
Roosting birds of certain species can be agricultural pests, hazards to aircraft on takeoff and landing, and a purported health hazard. Locating roosts of pest bird species and estimating the numbers of birds using them is time-consuming field work, especially when use of different roosts changes seasonally. Since the middle of the previous century, radar has been used to observe early morning bird echoes, then called “ring angels”. Today, large Doppler radars designed for meteorological work can routinely observe bird roosts, even when birds fly at treetop height. Radar images can often locate all roosts within a certain distance from the radar and can provide an indication of the number of birds using each roost and the general location of their food sources. Single images from the lowest tilt angle (lowest elevation) of different radars show roosts in several areas of the country, and successive scans of a research radar across an area becomes an animated picture of the detailed spatial behavior of birds leaving the roost. Applying a computer image recognition technique, the Hough Transform, to single radar-derived images of bird roosts results in objective numerical estimates of roost location and other data. Data are shown comparing ground-truth visual counts of European starling and brown-headed cowbird departures with such quantitative radar-derived data. The radar correctly estimated the central tendency of flight speed of the birds (20 m/sec), time of morning flight (mean 13.2 min past civil sunrise), and roost location (modal error about 2 km). Sometimes (5.1% of identifications) the algorithm found a “roost” that could not be located by field observers; occasionally there were other sources of confusing echo such as vehicles or migrating birds.
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