Mapping Surficial Materials in Nunavut Using Radarsat-2 C-Hh and C-Hv, Landsat-8 Oli, Dem and Slope Data
MAPPING SURFICIAL MATERIALS IN NUNAVUT USING RADARSAT-2 C-HH AND C-HV, LANDSAT-8 OLI, DEM AND SLOPE DATA by Justin Thomas Bezanson Byatt BSc Environmental Management, University of New Brunswick, 2014 A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Forestry In the Graduate Academy Unit of Forestry and Environmental Management Supervisors: Brigitte Leblon, PhD, Forestry and Environmental Management Armand LaRocque, PhD, Forestry and Environmental Management Advisory Committee: Jeff Harris, PhD Isabelle McMartin, PhD, Geological Survey of Canada Examining Board: Fan-Rui Meng, PhD, Forestry and Environmental Management Emmanuel Stefenakis, PhD, GGE This thesis is accepted by the Dean of Graduate Studies THE UNIVERSITY OF NEW BRUNSWICK May, 2017 © Justin Thomas Bezanson Byatt, 2017 ABSTRACT The Canadian Arctic is currently the focus of increased mapping activities, which aim to provide better knowledge to assist in making informed decisions for sustainable minerals and energy development, and land-use management. One of the required maps deals with surficial materials. This thesis studies the potential of combining RADARSAT-2 SAR images with Landsat-8 optical data, DEM and slope data to map surficial materials in the region around Wager Bay, Nunavut. Two study areas were selected, one on the northern side of the bay (NTS map areas 046E, K, L, M, 056H, I, J) and another one on the southern side (NTS map sheets 046D, E, 055P, 056A, H). The images were classified using a non-parametric classifier Random Forests. The results show that including RADARSAT-2 images in the classification process increases the overall classification accuracy from 92.8% to 98.1% in the north region and 96.7% to 99.3% in the south region.
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