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Open AccessTechnical Note

Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery

by Anne W. Nolin 1,* and Eugene Mar 2,†
Department of Geography, University of Nevada, Reno, NV 89557, USA
College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331-5503, USA
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(1), 50;
Received: 21 October 2018 / Revised: 12 December 2018 / Accepted: 14 December 2018 / Published: 29 December 2018
(This article belongs to the Special Issue MISR)
Sea ice surface roughness affects ice-atmosphere interactions, serves as an indicator of ice age, shows patterns of ice convergence and divergence, affects the spatial extent of summer meltponds, and affects ice albedo. We have developed a method for mapping sea ice surface roughness using angular reflectance data from the Multi-angle Imaging SpectroRadiometer (MISR) and lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). Using an empirical data modeling approach, we derived estimates of Arctic sea ice roughness ranging from centimeters to decimeters within the MISR 275-m pixel size. Using independent ATM data for validation, we find that histograms of lidar and multi-angular roughness values were nearly identical for areas with a roughness < 20 cm, but for rougher regions, the MISR-estimated roughness had a narrower range of values than the ATM data. The algorithm was able to accurately identify areas that transition between smooth and rough ice. Because of its coarser spatial scale, MISR-estimated roughness data have a variance about half that of ATM roughness data. View Full-Text
Keywords: sea ice; surface roughness; remote sensing; MISR sea ice; surface roughness; remote sensing; MISR
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Nolin, A.W.; Mar, E. Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery. Remote Sens. 2019, 11, 50.

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