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Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data
Department of Geography, Ryerson University, Toronto, ON M5B 2K3, Canada
Department of Geography, Queen's University, Kingston, ON K7L 3N6, Canada
* Author to whom correspondence should be addressed.
Received: 4 October 2012; in revised form: 26 November 2012 / Accepted: 4 December 2012 / Published: 10 December 2012
Abstract: As a result of the warming observed at high latitudes, there is significant potential for the balance of ecosystem processes to change, i.e., the balance between carbon sequestration and respiration may be altered, giving rise to the release of soil carbon through elevated ecosystem respiration. Gross ecosystem productivity and ecosystem respiration vary in relation to the pattern of vegetation community type and associated biophysical traits (e.g., percent cover, biomass, chlorophyll concentration, etc.). In an arctic environment where vegetation is highly variable across the landscape, the use of high spatial resolution imagery can assist in discerning complex patterns of vegetation and biophysical variables. The research presented here examines the relationship between ecological and spectral variables in order to generate an ecologically meaningful vegetation classification from high spatial resolution remote sensing data. Our methodology integrates ordination and image classifications techniques for two non-overlapping Arctic sites across a 5° latitudinal gradient (approximately 70° to 75°N). Ordination techniques were applied to determine the arrangement of sample sites, in relation to environmental variables, followed by cluster analysis to create ecological classes. The derived classes were then used to classify high spatial resolution IKONOS multispectral data. The results demonstrate moderate levels of success. Classifications had overall accuracies between 69%–79% and Kappa values of 0.54–0.69. Vegetation classes were generally distinct at each site with the exception of sedge wetlands. Based on the results presented here, the combination of ecological and remote sensing techniques can produce classifications that have ecological meaning and are spectrally separable in an arctic environment. These classification schemes are critical for modeling ecosystem processes.
Keywords: arctic; tundra vegetation; vegetation mapping; correspondence analysis; cluster analysis; remote sensing; IKONOS
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MDPI and ACS Style
Atkinson, D.M.; Treitz, P. Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data. Remote Sens. 2012, 4, 3948-3971.
Atkinson DM, Treitz P. Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data. Remote Sensing. 2012; 4(12):3948-3971.
Atkinson, David M.; Treitz, Paul. 2012. "Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data." Remote Sens. 4, no. 12: 3948-3971.