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Integration and Validation of Avian Radars (IVAR)
... The applied use of radar has ever increased, through the raised concern about the impact on bird populations of collision mortality with man-made structures such as wind farms and power lines [5,11,14,17,18], as well as to mitigate bird collision risks in aviation, which have increased dramatically during the last few decades [19,20]. A major hurdle for quantitative studies is that often the detection capabilities of bird radars are poorly known [21,22]. Many systems can be considered 'black boxes' of which the detection capabilities and limitations are poorly specified, making interpretation of the output in terms of animal targets difficult and prone to observational biases. ...
... Many systems can be considered 'black boxes' of which the detection capabilities and limitations are poorly specified, making interpretation of the output in terms of animal targets difficult and prone to observational biases. Furthermore, the performance of a radar is dependent on a multitude of factors, such as the type of birds studied, their flight behaviour, the terrain of the study site and meteorological condition2122232425. This underscores the need for practical methods for validating a radar's detection capability in specific field settings, which is the topic of this paper. ...
... Our validation approach consists of determining which fraction of a set of ground-truthed field observations, as a function of bird characteristics like species, distance, flight altitude etc., can be related to radar targets. Links between radar tracks and visual observations have been made manually in many radar studies, either by tracking radars with mounted parallel telescopes, or by radar operators pointing out tracks to nearby visual observers [2,7,21,22,26]. However, as soon as visual observers are positioned at certain distance from the radar and/or bird movements are numerous, it quickly becomes impossible to manually link visual observations to their respective radar targets. ...
Track-while-scan bird radars are widely used in ornithological studies, but often the precise detection capabilities of these systems are unknown. Quantification of radar performance is essential to avoid observational biases, which requires practical methods for validating a radar's detection capability in specific field settings. In this study a method to quantify the detection capability of a bird radar is presented, as well a demonstration of this method in a case study. By time-referencing line-transect surveys, visually identified birds were automatically linked to individual tracks using their transect crossing time. Detection probabilities were determined as the fraction of the total set of visual observations that could be linked to radar tracks. To avoid ambiguities in assigning radar tracks to visual observations, the observer's accuracy in determining a bird's transect crossing time was taken into account. The accuracy was determined by examining the effect of a time lag applied to the visual observations on the number of matches found with radar tracks. Effects of flight altitude, distance, surface substrate and species size on the detection probability by the radar were quantified in a marine intertidal study area. Detection probability varied strongly with all these factors, as well as species-specific flight behaviour. The effective detection range for single birds flying at low altitude for an X-band marine radar based system was estimated at ∼1.5 km. Within this range the fraction of individual flying birds that were detected by the radar was 0.50±0.06 with a detection bias towards higher flight altitudes, larger birds and high tide situations. Besides radar validation, which we consider essential when quantification of bird numbers is important, our method of linking radar tracks to ground-truthed field observations can facilitate species-specific studies using surveillance radars. The methodology may prove equally useful for optimising tracking algorithms.
... The same process can be achieved using trained observers instead of SMR; the SMR makes threat detection more spatially effi cient and more accurate over a greater range of visibility conditions. For a summary of the relative effi cacy of different airborne wildlife detection procedures, see Brand et al. 2011 . The USAF has since deployed and trialled SMR for assessment at several US air force facilities and units have been tested for deployment in combat theatres (Le Boeuf et al. 2008 ). ...
... Similarly, recent international wildlife strike and safety meetings are seeing increasing representations from ICAO and the International Airline Transport Association (IATA) . Most encouraging is the observation that the cultural and fear barriers discussed above are beginning to dissipate as a result of extensive technology validations (Brand et al. 2011 ), good communications and multi-stakeholder discussions (Nohara et al. 2012 ; Hale and Koros 2014 ), and also as a result of strong advocacy from progressive professional associations, particularly the National Business Aviation Association (NBAA) , Embry-Riddle Aeronautical University (ERAU) , and the Australian Airline Pilots Association (AusALPA) . Similarly, signifi cant efforts have been directed at defi ning how wildlife threat information can be standardised, organised, and simply communicated in operational settings (Nohara et al. 2012 ). ...
The conflict between wildlife and aircraft began over David Beard’s cornfield, near Huffman Prairie, Ohio, USA, in 1905. Orville Wright felt confident enough to chase a flock of birds while flying his redesigned Flyer III, hitting one bird and killing it. As separate disciplines aviation safety management and wildlife conflict management have both dramatically evolved over the last 100 years but against the trend for almost all other classes of aviation incidents, wildlife collision rates in civil aviation (wildlife strikes) are still increasing. Wildlife strikes rarely result in serious accidents but nevertheless they cost the aviation Industry in excess of US$1B per year and result in the death of tens of thousands of animals. The current trend in strikes rates is driven by a combination of operational, ecological, commercial and psychosocial factors of which the latter are the most important and most difficult to address. Managing wildlife strike is problematic as flight path conflicts between wildlife and aircraft apparently arise randomly in an open system. There are three generic approaches used to reduce wildlife strike risk in aviation; the engineering approach, the airport bubble approach and the flight path separation approach. The engineering approach is indirect and aimed at making aircraft more structurally robust thus reducing the likelihood of catastrophic consequence to the flight after strike has occurred. The airport bubble approach is also indirect; it is aimed at excluding high-risk wildlife from the airport environs in the hope that this in turn will reduce the probability of wildlife conflicting aircraft flight paths in terminal airspace. The flight path separation approach is the most complex and difficult to implement. It is prefaced on detecting and anticipating the flight vectors of aircraft and wildlife and then in both the planning and execution phases of flight modifying their flight paths to avoid collision. This final approach requires support with detection and communication systems that operate over a range of temporal and spatial scales and is analogous to the systems used in aviation to avoid other dynamic collision hazards such as traffic and bad weather. Here we discuss the strengths and limitations of different management approaches and summarise the main obstacles to achieving effective wildlife management in this industry.
... In the realm of bird radar technology (BRT), the FAA mandates a DRT shorter than 5 seconds for locating Standard Avian Targets (SAT) within scanned areas [16]. We do not endorse the DRT reference in the IVAR project report [22], where "real-time" means the processor can continuously track movements of all confirmed targets within the radar beam's sampling volume, including computing and recording all parametric data for each target, with a typical radar scan taking nominally 2.5 seconds for avian radar systems used in IVAR studies. In the field of DRT, many drone detection radars utilize tracks and/or micro-Doppler spectrograms to identify radar echoes from drones. ...
... There are a few high-performance algorithms suitable for tracking small maneuvering targets, such as birds, in the dense target and clutter environments typically encountered with avian radars. One example is the MHT-IMM algorithm (Blackman 2004), which has been tested extensively with birds (Brand 2011). MHT-IMM is capable of dealing in a consistent manner with converging and diverging birds, algorithms as described above are capable of detecting and tracking hundreds of birds (and other objects) in real-time. ...
Radar provides a useful and powerful tool to wildlife biologists and ornithologists. However, radar also has the potential for errors on a scale not previously possible. In this paper, we focus on the strengths and limitations of avian surveillance radars that use marine radar front-ends integrated with digital radar processors to provide 360° of coverage. Modern digital radar processors automatically extract target information, including such various target attributes as location, speed, heading, intensity, and radar cross-section (size) as functions of time. Such data can be stored indefinitely, providing a rich resource for ornithologists and wildlife managers. Interpreting these attributes in view of the sensor's characteristics from which they are generated is the key to correctly deriving and exploiting application-specific information about birds and bats. We also discuss (1) weather radars and air-traffic control surveillance radars that could be used to monitor birds on larger, coarser spatial scales; (2) other nonsurveillance radar configurations, such as vertically scanning radars used for vertical profiling of birds along a particular corridor; and (3) Doppler, single-target tracking radars used for extracting radial velocity and wing-beat frequency information from individual birds for species identification purposes.
Bird strikes in aviation are an increasing threat to both aircraft and human safety. Management efforts have focused largely on the immediate airport environment. Avian radar systems could potentially be useful in assessing bird strike threats at greater distances from the airport, at higher altitudes, and at night, but few studies have been conducted to assess the capabilities of avian radar systems. Thus, our goal was to assess the detection and tracking abilities of a commercially available avian radar system in an airport environment in Indiana, USA, during October 2011–March 2012. Transits by free-flying birds allowed us to assess radar tracking performance as influenced by flock size, altitude, and distance from the radar unit. Most of the single large-bird targets (raptors) observed within 2 nautical miles (NM) of the radar were tracked ≥1 time, but such targets were generally tracked <30% of the time observed. Flocks of large birds such as geese (Branta canadensis) and cranes (Grus canadensis) were nearly always tracked ≥1 time, and were generally tracked approximately 40–80% of the time observed, even those several NMs away from the radar unit. Our results suggest that avian radar can be a useful tool for monitoring bird flock activity at airports, but less so for monitoring single large-bird targets such as thermalling raptors. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
Digital avian radars can track bird movements continuously in the vicinity of airports without interruption. The result is a wealth of bird-track data that can be used in mitigation efforts to reduce bird strikes on and near airfi elds. To make the sheer volume of bird track data generated by digital avian radars accessible to users, we developed tools to transform these data into analytical and visualization products to improve situational awareness for wildlife and airfi eld personnel. In addition to the parameters traditionally associated with radar tracking (latitude, longitude, altitude, speed, and heading), we have implemented a procedure to estimate the radar cross-section (RCS) of a target, which is related to its size or mass. This additional information can provide wildlife and airfi eld managers with the knowledge they need to prioritize their efforts to deal with the greatest hazards fi rst.
The US government has multiple responsibilities for the protection of endangered species, many of them stemming from its role
as the nation's largest landowner. To explore how endangered and imperiled species are distributed across the federal estate,
we carried out a geographic information system (GIS)-based analysis using natural heritage species occurrence data. In this
10-year update of a previous analysis, we found that the Department of Defense and the USDA Forest Service harbor more species
with formal status under the Endangered Species Act (ESA) than other US agencies. The densities of ESA status species and
imperiled species are at least three times higher on military lands—2.92 and 3.77, respectively, per 100,000 hectares—than
on any other agency's lands. Defense installations in Hawaii are especially significant; more than one-third of all ESA status
species on military lands are Hawaiian. These findings highlight the continued importance of public lands for the survival
of America's plant and animal species.
The National Wildlife Strike Database for Civil Aviation in the United States contained 38,961 reports of aircraft collisions with birds (bird strikes) from 1990–2004 in which the report indicated the height above ground level (AGL). I analyzed these strike reports to determine the distribution of all strikes and those strikes causing substantial damage to aircraft by height. For the 26% of strikes above 500 feet (152 m) AGL (n = 10,143), a simple negative exponential model, with height as the independent variable, explained 99% of the variation in number of bird strikes per 1,000-foot (305-m) interval. Strikes declined consistently by 32% every 1,000 feet from 501–20,500 feet (153–6,248 m). For strikes at ≤500 feet, passerines, gulls and terns, pigeons and doves, and raptors were the identified species groups most frequently struck. For strikes at >500 feet, waterfowl, gulls and terns, passerines, and vultures were the species groups most frequently struck. For strikes that resulted in substantial damage to the aircraft, 66% occurred at ≤500 feet, 29% between 501–3,500 feet (153–1,067 m), and 5% above 3,500 feet. A higher (P < 0.001) proportion of strikes between 501–3,500 feet caused substantial damage to the aircraft (6.0%) than did strikes at ≤500 feet (3.6%) or at >3,500 feet (3.2%). For strikes at ≤500 feet, July–October were the months with the greatest proportion of strikes relative to aircraft movements. For strikes at >500 feet, September–November and April–May had more strikes than expected. About 61% of the reported strikes above 500 feet occurred at night, compared to only 18% of civil aircraft movements. Thus, about 7 times more strikes occurred per aircraft movement at night compared to day above 500 feet. This analysis confirmed that management programs to reduce strikes should focus on the airport environment because 74% of all strikes and 66% of strikes causing substantial damage occur at ≤500 feet. To minimize significant strike events occurring outside the airport (>500 feet), efforts to predict or monitor bird movements using bird avoidance models and bird-detecting radar need to focus on heights between 500 and 3,500 feet AGL, with special emphasis on night movements of birds during April–May and September–November.
Previous studies using thermal imaging cameras (TI) have used target size as an indicator of target altitude when radar was not available, but this approach may lead to errors if birds that differ greatly in size are actually flying at the same altitude. To overcome this potential difficulty and obtain more accurate measures of the flight altitudes and numbers of individual migrants, we have developed a technique that combines a vertically pointed stationary radar beam and a vertically pointed thermal imaging camera (VERTRAD/TI). The TI provides accurate counts of the birds passing through a fixed, circular sampling area in the TI display, and the radar provides accurate data on their flight altitudes. We analyzed samples of VERTRAD/TI video data collected during nocturnal fall migration in 2000 and 2003 and during the arrival of spring trans-Gulf migration during the daytime in 2003. We used a video peak store (VPS) to make time exposures of target tracks in the video record of the TI and developed criteria to distinguish birds, foraging bats, and insects based on characteristics of the tracks in the VPS images and the altitude of the targets. The TI worked equally well during daytime and nighttime observations and best when skies were clear, because thermal radiance from cloud heat often obscured targets. The VERTRAD/TI system, though costly, is a valuable tool for measuring accurate bird migration traffic rates (the number of birds crossing 1609.34 m [1 statute mile] of front per hour) for different altitudinal strata above 25 m. The technique can be used to estimate the potential risk of migrating birds colliding with man-made obstacles of various heights (e.g., communication and broadcast towers and wind turbines)—a subject of increasing importance to conservation biologists.
Affordable avian surveillance radar systems have been developed for natural resource management (NRM) and bird air strike hazard (BASH) applications. The system design described herein demonstrates that affordable, commercial off-the-shelf (COTS) marine radars combined with COTS personal computers (PCs) and sophisticated radar processing software can meet system requirements. Real performance data obtained using the Navy's eBirdRad radar unit installed at Patuxent River Naval Air Station demonstrate a significant advancement in state-of-the-art bird detection and tracking. This provides the impetus for maturing the technology into fully operational systems.