Counting Animals from Space:
Chapter TwoTransitions from Captivity to
Wild Places
Scott Bergen & Eric Sanderson
Why Count Wildlife?
• Fundamental to Conservation
• Foundational to Population Studies
• Federal Programs Spend Millions of Dollars Annual to Count Animals
Nov. 10, 2004
10:52:45 am
35 people involved
21 keepers
15 Volunteers
28 Enclosures mapped for individual animal locations
300 Faux fur targets placed in 4 ‘habitats’Digital Globe Inc ©
Tallying Identification by Species
Logit (identified targets) = -3.666 + 0.019(Color) + 0.970(Size) - 0.230(VegHt) - 0.421(Shade).
Counting Animals• Most reliable estimate use transect with repeat
measures• Population estimates w/ standard deviation • Findings usually extrapolated from small area to
available habitat or other limiting feature• Costly to count animals on ground
• Remote sensing rarely used (aerial imagery)• Time and scale rarely match satellite scale & time• Mismatch in terms of time and location in reference to
identifying- verifying high spatial resolution satellite imagery
Why the National Elk Refuge?
• Reliable elk & bison congregations during winter
• Logistic regression equation shows good fit for size, color, vegetation and shadow
• Annual census of both elk and bison
Animal Count Comparisons
• Refuge level, elk (weekly), bison (annual)
• Ground census estimate @ time of satellite acquisition
• Panoramic photo estimate @ time of satellite acquisition
• Heads up digitizing estimate
• Object oriented estimate
Jackson Wyoming
• Access limited• Freakin’ cold
-20f• Snow
bleaching histogram of sensor
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Ground Census of Elk Group
• High Ground limited
• Limited by distance
• 1360 individuals
• 60/40 female- male ratio
Panaramic Resesults
• Verified over 1,000 elk sex, position, direction position in less than 10 seconds
• Estimated 1070 individuals
• 679 females, 299 males, 89 ?
• Knew there were more but individuals > 1km were not identifiable as well as those totally blocked by other elk
Object Oriented Approach
• Scale based segmentation
• > classification• > revision• >classification• Hierarchical
strutured• Means both
smaller and larger
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Segmentation• Adds new
dimensions to data
• Area, spectra, variability within polygons
• Adjacency• Contextual• Generates
data Important to distinguish animals and differentiate types of animals
Initial Classification
• Good Results
• Identified 1540 individuals
• Misidentification within riparian areas
• Grouped elk in close proximity
Classification• Refined with an area classifier
• 1482 individuals
• Further refinement, standing – sitting, elk vs bison, sexes in bison
Summary of Animal Counts
• Park Estimate: 4,900 elk, 951 bison
• Ground Estimate: 1,360 elk, 60/40 f/m
• Panoramic: 1,071 elk, 69/31 f/m
• Heads up: 1,503 elk
• 1st Object Oriented Class: 1,540
• Ob. Orient w/ Area: 1,480