Remote Sensing in the Canadian
Arctic: Wildlife Management
Taylor Fragomeni
GPHY 426
Remote sensing provides a unique tool for habitat mapping and
wildlife management in the Canadian Arctic. The relative
inaccessibility of the arctic landscape makes it difficult to gather
data on the wildlife present. Remote sensing provides an
innovative platform for ecological management in a region where
small changes in climate and land use can have drastic impacts on
the wildlife.
There are a number of studies which were conducted in the
Canadian Arctic utilizing satellite imagery.
1. Polar Bears from Space: Assessing Satellite
Imagery as a Tool to Track Arctic Wildlife
Study Area: Rowley Island, Nunavut
Goal: Determine whether remote sensing using high-resolution satellite imagery is an
accurate method of determining and tracking polar bear populations.
Imagery: Worldview-1, Worldview-2, and QuickBird
Application: Images were corrected to account for terrain, sensor settings, sun
irradiance, sun elevation angle, Earth-sun distance, and top-of–atmosphere
reflectance. Then, a histogram stretch was applied to brighten the ice-free areas in
order to make it easier for the human analysts to observe the polar bears (2-meter
white spots). The researchers then compared their target images, in which they were
searching for the bears, to a previously taken reference image to rule out any
landscape features which may have been mistaken for bears.
Assessment: An aerial survey was conducted by helicopter to verify the results of the
data collected from the imagery. The team flew 7-km transects perpendicular to the
major axis of the island with 2 observers marking observations of polar bears.
Results: They determined that remote sensing was a viable option for the tracking of
polar bears. They estimated 102 bears from the aerial survey and found 92 in the
satellite imagery.
http://www.polarbearworld.com/polar_bear_in_the_canadian_ar
ctic/
Polar bear detection: Aerial vs. remotely sensed results.
(Stapleton, S., LaRue, M., Lecomte, M., Atkinson, S., Garshelis, D
Porter, C., and Atwood, T., 2014)
2. Modeling Probability of Waterfowl Encounters
from Satellite Imagery of Habitat in the Central
Canadian Arctic
Study Area: Rasmussen Lowlands and Queen Maud Migratory Bird Sanctuary,
Nunavut
Goal: Determine whether landcover determined from Landsat imagery could
provide a useful proxy for the modeling of landscape-level habitat interactions and
breeding-ground distributions of five waterfowl species: greater white-fronted geese,
Canada & cackling geese, tundra swans, king eiders, and long-tailed ducks.
Imagery: Landsat TM & Landsat ETM
Application: A mosaic of three Landsat images was processed through a supervised
classification. At least 30 training sites were specified for each of 10 terrestrial and 3
water classes (based on turbidity). The analysts employed a maximum likelihood
algorithm for the classification. True accuracy of the mosaicked image following
landcover classification was 87.6%. A logistic regression model was applied to
determine the probability of encountering a species based on landcover,
latitude/longitude, elevation, and distance to coast.
Assessment: The researchers employed the area-under curve and receiver operating
characteristic statistical methods to determine the predictive power of their models
developed using the remotely sensed imagery. Ground visits were paid in order to
assess the accuracy of the landcover classification. Aerial surveys were performed at
400-meter transects in order to gain knowledge of baseline waterfowl populations.
Two observers would record the number of each species they observed along each
transect.
Results: Several models were created for each species to account for uncertainties.
Tundra Swan
http://www.valcomnews.com/?p=1920
King Eider
http://ibc.lynxeds.com/photo/kingeider-somateria-spectabilis/two-malesresting-ice-one-them-antena-otherfishing-net-aroun
Landcover classification of the Rasmusse
3. Variation in the Seasonal Selection of Resources by
Woodland Caribou in Northern British Columbia
Study Area: Greater Besa-Prophet Region of Northern British Columbia
Goal: Use remote sensing and GPS to identify and accurately model variability in
resource selection by season for woodland caribou in order to better plan for land
use changes. Caribou are a protected species, so areas specified as ideal to meet
standards for wintering, breeding, and calving will be legally protected.
Imagery: Landsat ETM
Application: Landsat ETM imagery was used to classify vegetation into 9 classes:
burned-disturbed, alpine, spruce, shrubs, riparian spruce, non-vegetated, pine, Carex
spp., and sub-alpine.
Assessment: The vegetation classification derived from the satellite imagery was
combined with topographic variables from a DEM and GPS data from collared
female caribou. Ultimately, variables considered in the analysis were vegetation type,
an index of vegetative fragmentation, aspect, slope, elevation, and a year classification
based on when winter occurred (late-winter or winter).
Results: The researchers were able to determine the subtle changes in caribou forage
selection throughout the year. They especially noted the caribou’s tendency to avoid
burned or otherwise disturbed areas in every season except summer.
A female woodland caribou and her calf in BC.
http://www.naturallysuperior.com/blog/2011/08/albino-caribou-on-michipicoten-island/
4. Can Landsat Data Detect Variations in Snow
Cover within Habitats of Arctic Ungulates?
Study Area: Bathurst Island Complex, Nunavut
Goal: Use Landsat imagery to calculate a Normalized Difference Snow Index
(NSDI), calculate snow covered area, and apply these indices to the foraging habits
of muskoxen and the endangered Peary caribou. The authors also aimed to
determine the feasibility of using Landsat imagery for arctic ungulate research.
Selec
Imagery: Landsat TM and Landsat ETM
Application: Snow and ice have relatively high reflectance rates in the green portion
of the visible spectrum and low reflectance in the mid-infrared. So, bands 2 & 5 of
the Landsat TM imagery were used to calculate NDSI.
Assessment: Ground data was collected in areas which were recognized as preferred
caribou habitat in the past in order to specify the nature of the snow present (i.e.
hardened, fresh, or easily-brushed-away crystals) and compare it to the estimates
gathered from the Landsat imagery.
Results: The researchers were able to determine variation in snow cover in areas
with light snow, but had difficulty applying their methods to more northern areas due
to sun angles. Therefore, they recommend higher resolution imagery and suggest
greater applicability of their methods in southern arctic regions.
Muskoxen
http://www.visitorstocanada.com/article16-vacation-in-nunavut.html
Conclusion
Remote sensing provides a useful tool for ecological understanding,
whether used for direct species tracking, or as a means of better
understanding continuous environmental data which affects the
distribution of species in hard-to-reach places. Knowledge of these species
allows for better land and resource management in a region where the
slightest changes in climate or land use could have drastic impacts on
highly adapted wildlife.
Or
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So, whether you are counting polar bears, examining landcover as it
relates to migratory birds, tracking woodland caribou throughout the year,
or examining snow cover to understand the difficulties that ungulates may
face in forage, satellite imagery provides an efficient and cost-effective
means to an end.
Sources
Conkin, J.A. and Alisauskas, R.T., 2013, Modeling Probability of Waterfowl Encounters from
Satellite Imagery of Habitat in the Central Canadian Arctic: The Journal of Wildlife Management,
v. 77, p. 931-946
Gustine, D.D. and Parker, K.L., 2008, Variation in the seasonal selection of resources by
woodland caribou in northern British Columbia: Canadian Journal of Zoology, v. 86, p. 812-825
Maher, A.I., Treitz, P.M., and Ferguson, M.A.D., 2012, Can Landsat data detect variations in
snow cover within habitats of arctic ungulates?: Wildlife Biology, v. 18, p. 75-87
Stapleton, S., LaRue, M., Lecomte, M., Atkinson, S., Garshelis, D., Porter, C., and Atwood, T.,
2014, Polar Bears from Space: Assessing Satellite Imagery as a Tool to Track Arctic Wildlife:
PLoS ONE, v. 9