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A method for trend-based change analysis in Arctic tundra using the 25-year Landsat archive

Published online by Cambridge University Press:  29 November 2011

Robert Fraser ,
Ian Olthof ,
Mélanie Carrière ,
Alice Deschamps  and
Darren Pouliot
Robert Fraser
Affiliation:
Natural Resources Canada, Earth Sciences Sector, Canada Centre for Remote Sensing, 588 Booth St., Ottawa, ON, K1A0Y7, Canada ([email protected])
Ian Olthof
Affiliation:
Natural Resources Canada, Earth Sciences Sector, Canada Centre for Remote Sensing, 588 Booth St., Ottawa, ON, K1A0Y7, Canada ([email protected])
Mélanie Carrière
Affiliation:
Natural Resources Canada, Earth Sciences Sector, Canada Centre for Remote Sensing, 588 Booth St., Ottawa, ON, K1A0Y7, Canada ([email protected])
Alice Deschamps
Affiliation:
Natural Resources Canada, Earth Sciences Sector, Canada Centre for Remote Sensing, 588 Booth St., Ottawa, ON, K1A0Y7, Canada ([email protected])
Darren Pouliot
Affiliation:
Natural Resources Canada, Earth Sciences Sector, Canada Centre for Remote Sensing, 588 Booth St., Ottawa, ON, K1A0Y7, Canada ([email protected])
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Abstract

Remote sensing has provided evidence of vegetation changes in Arctic tundra that may be attributable to recent climate warming. These changes are evident from local scales as expanding shrub cover observed in aerial photos, to continental scales as greening trends based on satellite vegetation indices. One challenge in applying conventional two date, satellite change detection in tundra environments is the short growing season observation window, combined with high inter-annual variability in vegetation conditions. We present an alternative approach for investigating tundra vegetation and surface cover changes based on trend analysis of long-term (1985-present) Landsat TM/ETM+ image stacks. The Tasseled Cap brightness, greenness, and wetness indices, representing linear transformations of the optical channels, are analysed for per-pixel trends using robust linear regression. The index trends are then related to changes in fractional shrub and other vegetation covers using a regression tree classifier trained with high resolution land cover. Fractional trends can be summarised by vegetation or ecosystem type to reveal any consistent patterns. Example results are shown for a 3 000 km2 study area in northern Yukon, Canada where index and fractional changes are related to growth of vascular plants and coastal erosion.

Type
Research Article
Information
Polar Record , Volume 48 , Special Issue 1: Papers from the 11th Circumpolar Remote Sensing Symposium , January 2012 , pp. 83 - 93
Copyright
Copyright © Cambridge University Press 2011

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