Remote Sensing of Arctic Vegetation: Relations between the NDVI, Spatial Resolution and Vegetation Cover on Boothia Peninsula, Nunavut

• Published in: ARCTIC
• Main Authors: Laidler, Gita J., Treitz, Paul M., Atkinson, David M.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: The Arctic Institute of North America 2009
• Subjects: Arctic; Boothia Peninsula; Nunavut; Tundra
• Online Access: http://dx.doi.org/10.14430/arctic2; http://arctic.journalhosting.ucalgary.ca/arctic/index.php/arctic/article/viewFile/2/2

Arctic tundra environments are thought to be particularly sensitive to changes in climate, whereby alterations in ecosystem functioning are likely to be expressed through shifts in vegetation phenology, species composition, and net ecosystem productivity (NEP). Remote sensing has shown potential as a tool to quantify and monitor biophysical variables over space and through time. This study explores the relationship between the normalized difference vegetation index (NDVI) and percent-vegetation cover in a tundra environment, where variations in soil moisture, exposed soil, and gravel till have significant influence on spectral response, and hence, on the characterization of vegetation communities. IKONOS multispectral data (4 m spatial resolution) and Landsat 7 ETM+ data (30 m spatial resolution) were collected for a study area in the Lord Lindsay River watershed on Boothia Peninsula, Nunavut. In conjunction with image acquisition, percent cover data were collected for twelve 100 m × 100 m study plots to determine vegetation community composition. Strong correlations were found for NDVI values calculated with surface and satellite sensors, across the sample plots. In addition, results suggest that percent cover is highly correlated with the NDVI, thereby indicating strong potential for modeling percent cover variations over the region. These percent cover variations are closely related to moisture regime, particularly in areas of high moisture (e.g., water-tracks). These results are important given that improved mapping of Arctic vegetation and associated biophysical variables is needed to monitor environmental change.