Publications

Pour, HK; Duguay, CR; Scott, KA; Kang, KK (2017). Improvement of Lake Ice Thickness Retrieval From MODIS Satellite Data Using a Thermodynamic Model. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 55(10), 5956-5965.

Abstract
Observations of ice thickness are limited in high latitude regions, at a time when they are increasingly being requested by operational ice centers. This study aims to improve the retrieval of lake ice thickness using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Aqua (P.M.) and Terra (A.M.) satellites. The accuracy of ice thickness retrievals based on MODIS lake ice surface temperature (LIST) is investigated using a commonly used heat balance equation and the retrieved ice thicknesses are compared to in situ measurements from the Canadian Ice Service. The accuracy of ice thickness estimates is improved when using snow depth from the 1-D thermodynamic lake ice model Canadian Lake Ice Model (CLIMo) rather than an empirical relationship between snow depth and ice thickness utilized in the recent investigations. Taking into account all data over the study period (2002-2014), the mean bias error and the root-mean-square error are reduced from -0.42 to 0.07 m and 0.58 to 0.17 m, respectively, with the novel approach proposed herein. However, this approach is limited to ice thickness estimations of less than ca. 1.7 m.

DOI:
10.1109/TGRS.2017.2718533

ISSN:
0196-2892