Methods of quantitative and qualitative analysis of bird migration with a tracking radar

Methods of analyzing bird migration by using tracking radar are discussed. The procedure for assessing the rate of bird passage is described. Three topics are presented concerning the grouping of nocturnal migrants, the velocity of migratory flight, and identification of species by radar echoes. The height and volume of migration under different weather conditions are examined. The methods for studying the directions of migration and the correlation between winds and the height and direction of migrating birds are presented

Sensitivity Analysis for Optimal Parameters for Marine Radar Data Processing

A bird and bat monitoring system has been developed that uses marine radar, IR camera and acoustic recorders for wind farm applications. IR video recording is used to monitor birds and bats activity which will be useful for wildlife biologists in developing mit igation techniques to minimize impact of wind turbines on birds and bats. The goal is to quantify birds and bats activity near wind turbines. Radar will provide z-coordinate (alt itude) and IR camera will provide (x, y) coordinates of birds/bats. Acous tic monitoring is used to identify birds and bats at their species level. This paper deals with the use of marine radar for determining altitudes, direction and quantity (passage rates) of birds/bats. Data from the marine radar is digitized and processed with open source radR software. Since the data is unknown tracking and quantification can be very challenging. This paper deals with the sensitivity analysis and effects of various parameters used in the tracking algorithm so resulting data can be meaningful

Perception and steering control in paired bat flight

Animals within groups need to coordinate their reactions to perceived environmental features and to each other in order to safely move from one point to another. This paper extends our previously published work on the flight patterns of Myotis velifer that have been observed in a habitat near Johnson City, Texas. Each evening, these bats emerge from a cave in sequences of small groups that typically contain no more than three or four individuals, and they thus provide ideal subjects for studying leader-follower behaviors. By analyzing the flight paths of a group of M. velifer, the data show that the flight behavior of a follower bat is influenced by the flight behavior of a leader bat in a way that is not well explained by existing pursuit laws, such as classical pursuit, constant bearing and motion camouflage. Thus we propose an alternative steering law based on virtual loom, a concept we introduce to capture the geometrical configuration of the leader-follower pair. It is shown that this law may be integrated with our previously proposed vision-enabled steering laws to synthesize trajectories, the statistics of which fit with those of the bats in our data set. The results suggest that bats use perceived information of both the environment and their neighbors for navigation.2018-08-0

Beware the Boojum: Caveats and Strengths of Avian Radar

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

Improving the efficiency and accuracy of nocturnal bird Surveys through equipment selection and partial automation

This thesis was submitted for the degree of Engineering Doctorate and awarded by Brunel University.Birds are a key environmental asset and this is recognised through comprehensive legislation and policy ensuring their protection and conservation. Many species are active at night and surveys are required to understand the implications of proposed developments such as towers and reduce possible conflicts with these structures. Night vision devices are commonly used in nocturnal surveys, either to scope an area for bird numbers and activity, or in remotely sensing an area to determine potential risk. This thesis explores some practical and theoretical approaches that can improve the accuracy, confidence and efficiency of nocturnal bird surveillance. As image intensifiers and thermal imagers have operational differences, each device has associated strengths and limitations. Empirical work established that image intensifiers are best used for species identification of birds against the ground or vegetation. Thermal imagers perform best in detection tasks and monitoring bird airspace usage. The typically used approach of viewing bird survey video from remote sensing in its entirety is a slow, inaccurate and inefficient approach. Accuracy can be significantly improved by viewing the survey video at half the playback speed. Motion detection efficiency and accuracy can be greatly improved through the use of adaptive background subtraction and cumulative image differencing. An experienced ornithologist uses bird flight style and wing oscillations to identify bird species. Changes in wing oscillations can be represented in a single inter-frame similarity matrix through area-based differencing. Bird species classification can then be automated using singular value decomposition to reduce the matrices to one-dimensional vectors for training a feed-forward neural network