Case Study
Seal Counting and Population Surveys
Rapid and accurate assessments of seal colonies
Rapid Data Collection
High Resolution Imagery
Minimal Wildlife Disturbance
Case Study Overview
Utilising High-resolution Aerial Photography for Seal Population Surveys
This case study explores the innovative use of aerial photography and deep learning to accurately count seal numbers and classify adults and pups at Blakeney Point in Norfolk.
The outcomes demonstrate accurate automated surveying techniques from a snapshot of the colony captured from a fixed-wing aircraft during the breeding season.
Collect Time
< 10 Minutes
Number of Seals
5,500
Accuracy
77 – 91%*
Population
35% Pups
*classification of pups and adults across a range of different habitats
Key Advantages of Aerial Photography
Efficient, High-Resolution Data
Rapid Data Collection
Rapid data capture avoids problems with double-counting and ensures consistent lighting conditions for automated counting methods.
High-Resolution Imagery
Centimeter resolution to ensure the differences between age classes can be observed.
Non-Intrusive Observation
No disturbance reported to the population during the survey.
Colony Scale Surveys
Entire colonies can be captured in a single survey, which is repeatable across the season.
key steps
Automated Seal Surveying Workflow
Our pipeline for acquiring, processing, analysing and validating aerial photography for studying seal populations.
Fast Data Capture
The fixed-wing aircraft conducted the data capture in 10 minutes reducing the likelihood of double counting
Data Processing
Post-collect the data is automatically ingested and processed.
10GB of RGB data
Seal Counting and Classification
A deep learning model is applied to identify the 5,500 seal ‘objects’ and classify the age, across sandy and vegetated backgrounds.
5,500 seals
Accuracy Assessment
Accuracy of 77-91% was achieved and verified by manual validation of the output from the automated approach, ensuring product quality for the customer.
77 – 91%
Results and Insights
Key Outcomes of the Seal Population Survey
The use of a fixed-wing aircraft facilitated rapid and non-intrusive data capture, which addressed some of the challenges of double counting, variable illumination conditions, and disturbance that occur when using a UAV-based platform.
The use of deep learning techniques provided accurate seal counts and population age classification across a range of background environments present at Blakeney Point. The method creates a repeatable approach to seal population studies at the colony scale.
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