Behavior Signatures of Birds
An Automated Way to Extract
Wing Beat Frequency and FlapGlide Patterns from Thermal
Imagery
Val Cullinan, Ph.D.
Corey Duberstein, M.Sc.
Shari Matzner, Ph.D.
1
Acknowledgements
Signature Discovery Initiative: PNNL National Security
Directorate
Wind and Water Power Program: DOE Office of
Energy Efficiency & Renewable Energy
2
Presentation Overview
Problem Statement
Wing Beat as a Signature
Data Extraction
Wing Beat Position
Conclusions
3
Problem Statement
How do we assess risk to “flying animals” offshore?
Assess risk
BACI, BA, Impact-Reference Design, Response-Gradient
Design, Resource Selection Function, etc…
Presence, abundance
Behavior: flight height, avoidance
“Flying Animals”
Identification
Bird vs. bat
Common vs. rare spp
Endangered vs. least concern
Offshore
Remote
Inhospitable
Dynamic
4
Wing Beat as a Signature
Pennycuick 1996, 2001 allometric model
F = mass3/8acceleration1/2wingspan-23/24 wing area-1/3 air density-3/8
Bruderer et al. 2010
Measured 155 species, compiled 45 species (Europe)
4 flight types:
Continuous flapping: wading birds, waterfowl, auks, gulls,
terns
Soaring: storks, pelicans, lg raptors
Dynamic soaring: albatrosses, shearwaters
Flap-glide: passerines, gulls, terns
Conclusion: Pennycuick pretty reliable for continuous
flapping flight
5
Data Extraction
Wings
Up
6
Wings
Down
Wings
Up
Wings
Glide
Data Extraction
Pixel intensity values output
Centroid
Centroid of pixel mass output
Calculate “hot
Hot spot”
Spot in pixelated data
7
Wing Position
UP: w = 41, h = 15
Centroid
Hot Spot
NEUTRAL: w = 40, h = 9
DOWN: w = 38, h = 14
8
Wing Position
Discriminant Analysis
Hot spot relative to centroid
Frame height
Hot spot relative to height
and width
1st Root 74% of VAR
91% Correct with crossvalidation
Determine up/down cycle
and wing beat frequency
Root 1 vs. Root 2
5
4
Neutral
3
2
Down
Root 2
1
0
-1
-2
Up
-3
-4
-5
-6
-5
-4
-3
-2
-1
Root 1
9
0
1
2
3
4
Up
Glide
Down
Wing Beat Frequency
(Hz)
Automated vs. Manual
6
5
Gull
Est. WBF (Hz)
Mean (st. dev)
Observer Est. WBF
1 (n = 1)
2.99 Hz
2.5 Hz (n = 1)
2 (n = 3)
3.92 Hz (0.31)
3.34 Hz (0.16)
(n = 2)
4 (n = 3)
4.33 Hz (0.63)
3.70 Hz (n = 1)
3.2 ±1.5 Hz
4
3
2
1
0
Observer
10
3.7 ± 1.7 Hz
Modeled
Conclusions
Automated extraction possible
Advantages = Simplicity
Color agnostic
~Range agnostic
~Wind agnostic
Acoustic agnostic
Disadvantages
Approach or aspect specific?
Allometric data for classification
Frequency overlap and specificity
11
Future Direction
Model N.A. pelagic/coastal species
Robustness: more data (species, aspect, n, etc.)
Shape Analysis
PNNL Signature Discovery Initiative
preliminary work shows promise
Combine all attributes for signature
specificity
12
½W
Range Limitations
Size in Pixels
Camera Specifications
AGD FieldPro 5X
13
Spectral range:
Pixel array:
Pixel pitch:
FOV:
Focal length:
Frame rate:
Distance from Camera (m)
3-5 microns
320 x 256
0.03 mm
6 x 4 deg.
30 mm
30 Hz
W