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Bird Behavior Analysis Around Wind Turbines

At the intersection of biodiversity and wind energy, this project analyzes bird behavior around turbines using camera detections and 3D radar trajectories. It examines flight movements, responses to acoustic deterrence, and links with weather and turbine operation.

  • 2019–2022
  • EDF
Bird Behavior Analysis Around Wind Turbines

Our Approach

4 Project Steps

  1. Step 1 of 4

    Detection & Trajectory Data

    Camera-Based Detections

    Processed bird-detection events recorded by camera-based monitoring systems deployed on several wind farms.

    Detection metadata and video sequences were used to reconstruct approximate trajectories in image space and characterize how birds approached and moved around the rotor area.

    3D Radar Trajectories

    A separate study used full-3D bird-radar data collected around wind turbines.

    The radar provided trajectories with spatial position, altitude and flight speed, enabling bird movements to be analyzed over a much larger area than with individual turbine cameras.

    Environmental Context

    Trajectory data were combined with meteorological information and turbine operating conditions to study how flight behavior varied with the surrounding environment.

    Skills Applied

    Tools & Technologies

  2. Step 2 of 4

    Behavior & Deterrence Analysis

    Acoustic Deterrence

    Camera detections were used to evaluate bird behavior around automated acoustic deterrence events.

    Trajectories before and after warning or dissuasion signals were compared to determine whether a measurable change in flight direction could be observed and whether the bird subsequently moved away from the rotor area.

    Trajectory Comparison

    The analysis considered indicators including changes in heading, relative proximity to the turbine and differences between trajectories exposed and not exposed to deterrence.

    Because the camera systems relied on a single viewpoint, these measurements were treated as image-based trajectory and proximity indicators rather than true 3D positions.

    Flight-Pattern Analysis

    For radar data, KMeans clustering and statistical analysis were used to identify recurring trajectory patterns and characterize bird movements around the wind turbines.

    Skills Applied

    Tools & Technologies

  3. Step 3 of 4

    Visualization & Exploration

    Interactive Analysis

    Developed Streamlit tools for offline exploration of bird-detection and trajectory datasets.

    The interface supported filtering and comparison of detections, trajectories and environmental conditions across different periods and operating conditions.

    Spatial Analysis

    Interactive maps and trajectory plots were used to examine flight paths around turbines, recurring movement patterns and the spatial distribution of bird activity.

    Radar data could additionally be explored in three dimensions using measured position and altitude.

    Behavioral Review

    Visualizations were designed to make individual deterrence events easier to review, including the bird trajectory before and after acoustic signals.

  4. Step 4 of 4

    Performance Assessment

    Deterrence Evaluation

    The objective of the camera-based analysis was to determine whether recorded trajectories provided measurable evidence of a behavioral response to acoustic deterrence.

    Rather than assuming that a triggered warning was effective, the analysis examined how birds actually changed direction and proximity after the intervention.

    Radar-Based Behavior Analysis

    The 3D radar study provided a complementary view of bird activity around wind turbines, allowing flight routes, turbine avoidance patterns and relationships with meteorological conditions to be studied over extended periods.

    Decision Support

    The resulting analyses and visualizations provided technical support for evaluating bird-monitoring and mitigation approaches around wind farms.

    Tools & Technologies