Abstract's details
Cryo-SEANICE : CryoSat SciEnce-oriented data ANalysis over Sea-ICE areas
CoAuthors
Event: 2016 SAR Altimetry Workshop
Session: Applications, SAR for science
Presentation type: Type Poster
Contribution: not provided
Abstract:
The CryoSat-2 baseline-C data make it possible to detect some leads and polynyas and in some cases to measure freeboard. Nevertheless the processor still faces difficult cases. Indeed sea-ice areas are subject to a high spatial diversity which leads to a broad range of radar signatures. The complexity coming from the spatial diversity is emphasized by the strong temporal variability related to seasonal trends, local surface currents and very frequent extreme events. Some of the CryoSat Ice Processor limitations may be due to a poor understanding of the physics behind the SAR/SARin Level-1A to Level-2 products over the Sea-Ice domain.
Dedicated science oriented tools therefore need to be put in place to make best profit of both in situ data and imagery to thoroughly understand the signatures within the altimeter signals. Such insights could help to improve retrackers and refine the CryoSat Delay Doppler Processor (range zero-padding, burst weighting, echo discrimination, handling of side-lobe effects...).
Our work establishes a conceptual framework that eases and partially automates the analysis of CryoSat-2 measurements through the use of Sentinel-1 SAR imagery and other satellite missions over sea ice areas. The tool addresses several critical aspects: first the selection of closely co-dated satellite data for the area of interest (the results are very sensitive to this critical step which may prevent a full automation of the whole process), second the adequate positioning of the altimeter footprint within the image and third the identification of ice/snow classes that serves to improve the understanding of the physics in the signals and to confirm the detection of leads and polynyas.
The conceptual framework and its early implementation, that will be presented here, exploit SAR images segmentation and classification tools, CryoSat ground projected footprints and visual interfaces to permit a deep inspection of Individual Echoes, Delay Doppler Maps, SAR/SARin waveforms as well as retracker outputs, and help the consolidation of Sentinel-1 radiometry and polarimetry based classes.
Preliminary results are given for specific scenarios. In particular the Range Integrated Power parameters (Kurtosis, Skewness Standard Deviation, Stack Centre and mean waveforms) are analysed in conjunction with the SAR imagery.
Dedicated science oriented tools therefore need to be put in place to make best profit of both in situ data and imagery to thoroughly understand the signatures within the altimeter signals. Such insights could help to improve retrackers and refine the CryoSat Delay Doppler Processor (range zero-padding, burst weighting, echo discrimination, handling of side-lobe effects...).
Our work establishes a conceptual framework that eases and partially automates the analysis of CryoSat-2 measurements through the use of Sentinel-1 SAR imagery and other satellite missions over sea ice areas. The tool addresses several critical aspects: first the selection of closely co-dated satellite data for the area of interest (the results are very sensitive to this critical step which may prevent a full automation of the whole process), second the adequate positioning of the altimeter footprint within the image and third the identification of ice/snow classes that serves to improve the understanding of the physics in the signals and to confirm the detection of leads and polynyas.
The conceptual framework and its early implementation, that will be presented here, exploit SAR images segmentation and classification tools, CryoSat ground projected footprints and visual interfaces to permit a deep inspection of Individual Echoes, Delay Doppler Maps, SAR/SARin waveforms as well as retracker outputs, and help the consolidation of Sentinel-1 radiometry and polarimetry based classes.
Preliminary results are given for specific scenarios. In particular the Range Integrated Power parameters (Kurtosis, Skewness Standard Deviation, Stack Centre and mean waveforms) are analysed in conjunction with the SAR imagery.