Cryosphere > Permafrost

Permafrost

Spatio-temporal variability of X-band radar backscatter and coherence over the Lena River Delta

Satellite-based monitoring strategies for permafrost remain under development and are not yet operational. Remote sensing allows indirect observation of permafrost, a subsurface phenomenon, by mapping surface features or measuring physical parameters that can be used for permafrost modeling. We have explored high temporal resolution time series of TerraSAR-X backscatter intensity and interferometric coherence for the period between August 2012 and September 2013 to assess their potential for detecting major seasonal changes to the land surface in a variety of tundra environments within the Lena River Delta, Siberia.

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The TerraSAR-X signal is believed to be strongly affected by the vegetation layer, and its viability for the retrieval of soil moisture, for example, is therefore limited. In our study individual events, such as rain and snow showers, that occurred at the time of TerraSAR-X acquisition, or a refrozen crust on the snowpack during the spring melt were detected based on backscatter intensity signatures. The interferometric coherence showed marked variability; the snow cover onset and snow melt periods were identified by significant reduction in coherence. Principal component analysis provided a good spatial overview of the essential information contained in backscatter and coherence time series and revealed latent relationships between both time series and the surface temperature.

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Datasets listed in this Collection

Antonova, Sofia; Kääb, Andreas; Heim, Birgit; Langer, Moritz; Boike, Julia (2017): One-year (2012-2013) TerraSAR-X backscatter and coherence stacks for different landscape types in the Lena River Delta, Siberia. PANGAEA, doi:10.1594/PANGAEA.873554

Related Journal Article

Antonova, S et al. (2016): Spatio-temporal variability of X-band radar backscatter and coherence over the Lena River Delta, Siberia. Remote Sensing of Environment, 182, 169-191, doi:10.1016/j.rse.2016.05.003.


Monitoring bedfast ice and ice phenology in lakes of the Lena River

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.

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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.

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Datasets listed in this Collection

Antonova, Sofia; Duguay, Claude R; Kääb, Andreas; Heim, Birgit; Langer, Moritz; Westermann, Sebastian; Boike, Julia (2016): Monitoring bedfast ice and ice phenology in lakes of the Lena River Delta using TerraSAR-X backscatter and coherence time series. PANGAEA, doi:10.1594/PANGAEA.873586

Related Journal Article

Antonova, S et al. (2016): Monitoring bedfast ice and ice phenology in lakes of the Lena River Delta using TerraSAR-X backscatter and coherence time series. Remote Sensing, 8(11), 903, doi:10.3390/rs8110903


Disturbance: Top-cliff erosion (WP C8)

Permafrost landscapes are fragile environments. Disturbances and geohazards express themselves as landslides, active layer detachments, and thermo-erosion that can be monitored by satellite remote sensing. Thawing-induced cliff top retreat in permafrost landscapes is mainly due to thermo-erosion. Ground-ice-rich permafrost landscapes are specifically vulnerable to thermo-erosion and may show high degradation rates. High-temporal resolution time series of TerraSAR-X satellite data allow the inter-annual and intra-annual monitoring of the upper cliff-line retreat also under bad weather conditions and continuous cloud coverage. This data product contains the retreating upper cliff lines of a 1.5 km long part of eroding ice-rich coast of Kurungnakh Island in the central Lena Delta based on TerraSAR-X data from 2013-2014.

Data Publication:

Stettner, Samuel; Bartsch, Annett; Widhalm, Barbara; Heim, Birgit; Günther, Frank; Morgenstern, Anne; Roth, Achim; Chetverova, Antonina; Fedorova, Irina (2015): Retreat of top cliff of Kurungnakh Island, Lena Delta, Siberia, Russia, 2010-2014, with links to shapefiles. Alfred Wegener Institute - Research Unit Potsdam, http://doi.org/10.1594/PANGAEA.846164

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