Abstract
Detailed information on the spatial and temporal distribution of active layer thickness (ALT) throughout the North Slope of Alaska, were it available, could offer valuable insights into the effects of climate change throughout the region and facilitate the estimation of greenhouse gas emissions resulting from permafrost degradation. We are, therefore, developing extensive high-resolution maps of ALT on the North Slope of Alaska. To do this, we use a machine learning algorithm to extrapolate ALT from high resolution strips of estimated ALT derived from airborne P-band synthetic aperture radar (SAR) acquired over two sets of flights in each of three different years. Our results indicate upscaling root-mean-square error (RMSE) of about 4 cm relative to thousands of randomly-selected SAR-derived ALT validation samples, and RMSE of approximately 10 cm relative to a small number of in-situ ALT measurements.
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