Monitoring Bedfast Ice and Ice Phenology in Lakes of the Lena River Delta Using TerraSAR-X Backscatter and Coherence Time Series

• Published in: Remote Sensing
• Main Authors: Sofia Antonova, Claude R. Duguay, Andreas Kääb, Birgit Heim, Moritz Langer, Sebastian Westermann, Julia Boike
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2016
• Subjects: lake ice; bedfast ice; ice phenology; SAR; TerraSAR-X; backscatter intensity; interferometric coherence; time series; Lena River Delta; CLIMo; Science; Q; Arctic; Arctic Lake; Ice; lena river; permafrost; Thermokarst; Siberia
• Online Access: https://doi.org/10.3390/rs8110903; https://doaj.org/article/02c6943fb66449bc9a23b3561d6d1020

Thermokarst lakes and ponds are major elements of permafrost landscapes, occupying up to 40% of the land area in some Arctic regions. Shallow lakes freeze to the bed, thus preventing permafrost thaw underneath them and limiting the length of the period with greenhouse gas production in the unfrozen lake sediments. Radar remote sensing permits to distinguish lakes with bedfast ice due to the difference in backscatter intensities from bedfast and floating ice. This study investigates the potential of a unique time series of three-year repeat-pass TerraSAR-X (TSX) imagery with high temporal (11 days) and spatial (10 m) resolution for monitoring bedfast ice as well as ice phenology of lakes in the zone of continuous permafrost in the Lena River Delta, Siberia. TSX backscatter intensity is shown to be an excellent tool for monitoring floating versus bedfast lake ice as well as ice phenology. TSX-derived timing of ice grounding and the ice growth model CLIMo are used to retrieve the ice thicknesses of the bedfast ice at points where in situ ice thickness measurements were available. Comparison shows good agreement in the year of field measurements. Additionally, for the first time, an 11-day sequential interferometric coherence time series is analyzed as a supplementary approach for the bedfast ice monitoring. The coherence time series detects most of the ice grounding as well as spring snow/ice melt onset. Overall, the results show the great value of TSX time series for monitoring Arctic lake ice and provide a basis for various applications: for instance, derivation of shallow lakes bathymetry, evaluation of winter water resources and locating fish winter habitat as well as estimation of taliks extent in permafrost.