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Updated: Nov 1, 2025

Visually Sexing Loggerhead Shrike Lanius Ludovicianus Using Plumage Coloration and Pattern
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Eastern Canada Flocks: images and manually annotated bird positions.

Marcos Cruz1, Javier González-Villa2, Josée Lefebvre3

  • 1Department of Mathematics, Statistics and Computer Science, University of Cantabria, Av. Los Castros 48, Santander, ES-39005, Spain.

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Summary

The Eastern Canada Flocks dataset provides manually annotated bird images for testing flock size estimation methods. This resource aids in developing precise animal abundance estimation techniques using aerial imagery.

Keywords:
Eastern Canadacommon eidercomputer visionecologyflock sizegreater snow gooseimage analysispopulation sizesegmentationstereologywildlife management

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Area of Science:

  • Ornithology and Wildlife Ecology
  • Computer Vision and Machine Learning
  • Data Science and Geospatial Analysis

Background:

  • Accurate wildlife population counts are crucial for conservation and management.
  • Manual annotation of aerial imagery for bird surveys is labor-intensive and prone to error.
  • Developing automated methods for bird detection and counting is essential for large-scale ecological studies.

Purpose of the Study:

  • To introduce and describe the Eastern Canada (ECA) Flocks dataset, a manually annotated collection of Common Eider (COEI) and Greater Snow Geese (GSGO) images.
  • To provide a benchmark dataset for evaluating the precision of automated flock size estimation algorithms, specifically the CountEm method.
  • To facilitate research in automated animal abundance estimation from aerial imagery.

Main Methods:

  • Acquisition of aerial images from Common Eider Winter Survey and Greater Snow Geese Spring Survey in Eastern Canada.
  • Manual annotation of bird positions and species/sex identification using ImageJ's Cell Counter plugin.
  • Creation of a dataset including original and cropped images, with detailed .csv files of annotated bird data.

Main Results:

  • The ECA Flocks dataset contains 179 COEI and 99 GSGO images, with 637,555 annotated bird positions (124,309 COEI, 514,235 GSGO).
  • Annotated data includes species and sex identification for COEI, with detailed counts for males, females, and other species.
  • The dataset exhibits high variability in lighting, backgrounds, and bird distribution, making it suitable for rigorous method testing.

Conclusions:

  • The ECA Flocks dataset is a valuable public resource for advancing automated methods in wildlife population monitoring.
  • The dataset's comprehensive annotations and diverse image conditions will enable robust validation of bird detection and counting algorithms.
  • Researchers are encouraged to cite the dataset and contact the core team for potential updates and ongoing analyses.