Potential and limitations of RADARSAT SAR data for wet snow monitoring

2000 ◽  
Vol 38 (1) ◽  
pp. 316-320 ◽  
Author(s):  
N. Baghdadi ◽  
Y. Gauthier ◽  
M. Bernier ◽  
J.-P. Fortin
Keyword(s):  
Wet Snow ◽  
Sar Data

scholarly journals Discrimination of glacier facies using multi-temporal SAR data

1998 ◽  
Vol 44 (146) ◽  
pp. 42-53 ◽  
Author(s):  
K. C. Partington
Keyword(s):  
European Space Agency ◽  
Greenland Ice Sheet ◽  
Sensor Calibration ◽  
Lower Altitude ◽  
Mount Pinatubo ◽  
South Central ◽  
Space Agency ◽  
Wet Snow ◽  
Multi Temporal ◽  
Sar Data

AbstractGlacier facies from the Greenland ice sheet and the Wrangell-St Elias Mountains, Alaska, are analyzed using multi-temporal synthetic aperture radar (SAR) data from the European Space Agency ERS-1 satellite. Distinct zones and facies are visible in multi-temporal SAR data, including the dry-snow facies, the combined percolation and wet-snow facies, the ice facies, transient melt areas and moraine. In Greenland and south-central Alaska, very similar multi-temporal signatures are evident for the same facies, although these facies are found at lower altitude in West Greenland where the equilibrium line appears to be found at sea level at 71°30?N during the year analyzed (1992-93), probably because of the cooling effect of the eruption of Mount Pinatubo. In Greenland, both the percolation and dry-snow facies are excellent distributed targets for sensor calibration, with backscatter coefficients stable to within 0.2 dB. However, the percolation facies near the top of Mount Wrangell are more complex and less easily delineated than in Greenland, and at high altitude the glacier facies have a multi-temporal signature which depends sensitively on slope orientation.

scholarly journals Stochastically based wet snow mapping with SAR DATA

2012 ◽  
Author(s):  
N. Besic ◽  
G. Vasile ◽  
J. Chanussot ◽  
S. Stankovic ◽  
J.-P. Ovarlez ◽  
...  
Keyword(s):  
Wet Snow ◽  
Sar Data

scholarly journals Discriminating Wet Snow and Firn for Alpine Glaciers Using Sentinel-1 Data: A Case Study at Rofental, Austria

Geosciences ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 69 ◽  
Author(s):  
Achim Heilig ◽  
Anna Wendleder ◽  
Andreas Schmitt ◽  
Christoph Mayer
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Optical Data ◽  
Optical Remote Sensing ◽  
Mountain Ranges ◽  
Snow Covered Area ◽  
Covered Area ◽  
Wet Snow ◽  
Sar Data ◽  
Sar Analysis

Continuous monitoring of glacier changes supports our understanding of climate related glacier behavior. Remote sensing data offer the unique opportunity to observe individual glaciers as well as entire mountain ranges. In this study, we used synthetic aperture radar (SAR) data to monitor the recession of wet snow area extent per season for three different glacier areas of the Rofental, Austria. For four glaciological years (GYs, 2014/2015–2017/2018), Sentinel-1 (S1) SAR data were acquired and processed. For all four GYs, the seasonal snow retreated above the elevation range of perennial firn. The described processing routine is capable of discriminating wet snow from firn areas for all GYs with sufficient accuracy. For a short in situ transect of the snow—firn boundary, SAR derived wet snow extent agreed within an accuracy of three to four pixels or 30–40 m. For entire glaciers, we used optical remote sensing imagery and field data to assess reliability of derived wet snow covered area extent. Differences in determination of snow covered area between optical data and SAR analysis did not exceed 10% on average. Offsets of SAR data to results of annual field assessments are below 10% as well. The introduced workflow for S1 data will contribute to monitoring accumulation area extent for remote and hazardous glacier areas and thus improve the data basis for such locations.

scholarly journals Wet and Dry Snow Detection Using Sentinel-1 SAR Data for Mountainous Areas with a Machine Learning Technique

2019 ◽  
Vol 11 (8) ◽  
pp. 895 ◽  
Author(s):  
Tsai ◽  
Dietz ◽  
Oppelt ◽  
Kuenzer
Keyword(s):  
Land Cover ◽  
Forest Type ◽  
Global Scale ◽  
Mountainous Areas ◽  
In Situ Data ◽  
Snow Cover Extent ◽  
Wet Snow ◽  
Sar Data ◽  
Agricultural Regions ◽  
F Measure

Traditional studies on mapping wet snow cover extent (SCE) often feature limitations, especially in vegetated and mountainous areas. The aim of this study is to propose a new total and wet SCE mapping strategy based on freely accessible spaceborne synthetic aperture radar (SAR) data. The approach is transferable on a global scale as well as for different land cover types (including densely vegetated forest and agricultural regions), and is based on the use of backscattering coefficient, interferometric SAR coherence, and polarimetric parameters. Furthermore, four topographical factors were included in the simple tuning of random forest-based land cover type-dependent classification strategy. Results showed the classification accuracy was above 0.75, with an F-measure higher than 0.70, in all five selected regions of interest located around globally distributed mountain ranges. Whilst excluding forest-type land cover classes, the accuracy and F-measure increases to 0.80 and 0.75. In cross-location model set, the accuracy can also be maintained at 0.80 with non-forest accuracy up to 0.85. It has been found that the elevation and polarimetric parameters are the most critical factors, and that the quality of land cover information would also affect the subsequent mapping reliability. In conclusion, through comprehensive validation using optical satellite and in-situ data, our land cover-dependent total SCE mapping approach has been confirmed to be robustly applicable, and the holistic SCE map for different months were eventually derived.

scholarly journals Discrimination of glacier facies using multi-temporal SAR data

1998 ◽  
Vol 44 (146) ◽  
pp. 42-53 ◽  
Author(s):  
K. C. Partington
Keyword(s):  
European Space Agency ◽  
Greenland Ice Sheet ◽  
Sensor Calibration ◽  
Lower Altitude ◽  
Mount Pinatubo ◽  
South Central ◽  
Space Agency ◽  
Wet Snow ◽  
Multi Temporal ◽  
Sar Data

AbstractGlacier facies from the Greenland ice sheet and the Wrangell-St Elias Mountains, Alaska, are analyzed using multi-temporal synthetic aperture radar (SAR) data from the European Space Agency ERS-1 satellite. Distinct zones and facies are visible in multi-temporal SAR data, including the dry-snow facies, the combined percolation and wet-snow facies, the ice facies, transient melt areas and moraine. In Greenland and south-central Alaska, very similar multi-temporal signatures are evident for the same facies, although these facies are found at lower altitude in West Greenland where the equilibrium line appears to be found at sea level at 71°30?N during the year analyzed (1992-93), probably because of the cooling effect of the eruption of Mount Pinatubo. In Greenland, both the percolation and dry-snow facies are excellent distributed targets for sensor calibration, with backscatter coefficients stable to within 0.2 dB. However, the percolation facies near the top of Mount Wrangell are more complex and less easily delineated than in Greenland, and at high altitude the glacier facies have a multi-temporal signature which depends sensitively on slope orientation.

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