The Use of Remote Sensing to Evaluate Shorebird Habitats and Populations on Prince Charles Island, Foxe Basin, Canada

Авторы

  • R.I.G. Morrison

DOI:

https://doi.org/10.14430/arctic1091

Ключевые слова:

shorebirds, Landsat TM, remote sensing, Foxe Basin, habitats

Аннотация

Landsat-5 Thematic Mapper imagery was used to produce a 17-habitat classification of Prince Charles Island, Foxe Basin, Northwest Territories, through a combination of supervised and unsupervised approaches. Breeding shorebirds and habitats were surveyed at 35 study plots in July 1989. Habitat-specific breeding densities calculated from these observations were used to estimate total populations of breeding shorebirds on the island based on areas of habitat derived from the classified image. Breeding densities were further modelled in two ways: first, to adjust for distance from the coast, where regression analyses found a significant relationship between distance and density, and second, to include only those pixels of areas considered suitable for breeding, using results of a proximity analysis to determine habitat associations between known breeding locations (pixels) and other habitats. Six species of shorebirds were found breeding on Prince Charles Island, with a combined population (after modelling) estimated at 294 000 pairs. Comparison of breeding densities and estimated populations of shorebirds with those recorded at other arctic locations indicated that Prince Charles Island supports highly significant numbers of shorebirds, especially white-rumped sandpipers and red phalaropes. Comparison of reference areas of known habitat with those on the classified image indicated classification accuracy averaged over 90%. Remote sensing appears to offer a reliable method for assessing habitats and regional breeding populations of birds in at least some areas, providing that classification methods are carried out in a carefully controlled manner. Use of the method over broad areas of the Arctic would require considerable work to recalibrate imagery for different geographic regions.

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Опубликован

1997-01-01

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Раздел

Articles