| Abstract: | The spatial variability and co-variability of two different types of remote sensing derivatives that portray vegetation and geomorphic patterns are analyzed in the context of estimating regional-scale CO2 flux from land surfaces in the arctic tundra. For a study area encompassing the Kuparuk River watershed of the North Slope of Alaska, we compare satellite-derived maps of the normalized difference vegetation index (NDVI) generated at two different spatial resolutions to a map of vegetation types derived by image classification of data from the Landsat multispectral scanner (MSS). Mean values of NDVI for each cover type stratum are unique (with the exception of moist acidic tundra and shrubland types). Based on analysis of semi-variograms generated for SPOT-NDVI data, most of the vegetation cover and landform features of this arctic tundra landscape have spatial dimensions of less than 1 km. Thaw lakes on the coastal plain and glacial depositional landforms, such as moraines in the foothills, seem to be the largest features, with vegetation units having dimensions no larger than 700 m. Frequency distributions of NDVI and vegetation types extracted for sampling transects flown by an aircraft sensing CO2 flux, relative to distributions for the entire Kuparuk River watershed, suggest a slight sampling bias towards greater cover of mesic wet sedge tundra and thaw lakes and associated lower NDVI values. The regional pattern of NDVI for the North Slope of Alaska corresponds primarily to differences between the two major physiographic provinces of this region. |
