Year of Award


Document Type


Degree Type

Master of Science (MS)

Degree Name


Department or School/College

Department of Geography

Committee Chair

Anna E. Klene

Commitee Members

Carl Seielstad, Kevin McManigal


climate change, DEM, high resolution data, LIDAR, permafrost, subsidence


University of Montana


Arctic regions underlain by permafrost are among the most vulnerable to impacts from climate change. This study examined changes in the active layer of permafrost near Barrow, Alaska at very fine scale to capture subtle changes related to microtopography and landcover. In 2010, terrestrial LIDAR was used to collect high-resolution elevation data for four 10 m × 10 m plots where maximum active-layer thickness (ALT) and elevation have been monitored on an annual basis since the mid-1990s and had been monitored in the 1960s as well. The raw LIDAR point cloud was analyzed and processed into four 10 cm resolution digital elevation models (DEMs). Elevation data, collected using differential global positioning system (DGPS) to assess heave and subsidence, has been gathered annually since 2004 and was used to assess the accuracy of the DEMs generated for August 2010. Higher-resolution DEMs did not have higher accuracy compared to the DGPS control points due to artifacts inherent in the LIDAR data. The four DEMs were used to classify each plot based on microtopographical variations derived from terrain attributes including elevation, slope, and Melton’s Ruggedness Number (MRN). Landcover at each plot was classified using the Visible Vegetation Index (VVI), calculated from a series of high-resolution (~10 cm) kite photographs obtained in August 2012 by researchers from the University of Texas – El Paso. The microtopography and land-cover classifications were then used to analyze ALT and elevation data from a range of years. Analysis revealed little difference in either dataset based upon microtopography and landcover. The high amount of interclass and interannual variation made it difficult to draw any conclusions about temporal trends. The results suggest that while microtopography and vegetation are important factors within the complex interaction which determines ALT, the scale of analysis made possible by the high-resolution data utilized in this study did not significantly enhance understanding of the main controlling mechanisms. While terrestrial LIDAR is excellent for many applications, particularly those with substantial vertical variability, for future research at this scale on relatively flat topography, airborne LIDAR may be more suitable.



© Copyright 2013 Julia Smith