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Counting Animals from Space:. Chapter Two Transitions 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.

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Counting animals from space l.jpg

Counting Animals from Space:

Chapter Two

Transitions from Captivity to

Wild Places

Scott Bergen & Eric Sanderson


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Why Count Wildlife?

  • Fundamental to Conservation

  • Foundational to Population Studies

  • Federal Programs Spend Millions of Dollars Annual to Count Animals


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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 ©


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Ground –vs- Sky

Digital Globe Inc ©


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Information Shadow

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Tallying Identification by Species

Logit (identified targets) = -3.666 + 0.019(Color) + 0.970(Size) - 0.230(VegHt) - 0.421(Shade).


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National Elk Refuge. Jackson , WY


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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


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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


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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


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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


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Thick In Elk

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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


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Heads up

  • 1503 individuals

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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


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Initial Classification

  • Good Results

  • Identified 1540 individuals

  • Misidentification within riparian areas

  • Grouped elk in close proximity


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Classification

  • Refined with an area classifier

  • 1482 individuals

  • Further refinement, standing – sitting, elk vs bison, sexes in bison


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Further refinement


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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


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Future Considerations


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