An approach to determine depth and ice thickness of shallow lakes and ponds using Landsat Thematic Mapper (TM) and European Remote Sensing (ERS)-1 Synthetic Aperture Radar (SAR) data is presented. A summertime Landsat TM image is used to map lake bathymetry and multi-date ERS-1 images acquired during winter are utilized to determine when and which lakes freeze to the bottom during winter. The two remotely sensed derived products are then combined to estimate ice thickness from lakes and ponds on a monthly basis. The approach has been developed and tested successfully in a sub-Arctic tundra-forest landscape in the Hudson Bay Lowland near Churchill, Manitoba, Canada. Lake depth estimates derived from Landsat TM band 2 generally compared well with measurements obtained in the field, especially in the tundra zone [rms error (RMSE) = 15 cm]. Maximum ice thickness estimates were also within the range of those typically measured during winter in this study area (tundra and forest-tundra zones ≅ 1.6 m; open forest zone ≅ 1.2 m). Results indicate that the approach is particularly well suited for estimating depth and ice thickness of shallow oligotrophic and ultra-oligotrophic lakes that are widespread in many regions above treeline. However, the results also suggest that the Landsat-based approach will require further testing and improvement if one wishes to map bathymetry for shallow lakes in which large nutrient concentrations or amounts of suspended sediments are found.
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Document Type: Research Article
Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska 99775-7320, USA; e-mail: email@example.com
Department of Geography, Trent University, Peterborough, Ontario, Canada K9J 7B8
Publication date: 2003-02-01
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