Validation of CryoSat-2 SARIn Data over Austfonna Ice Cap Using Airborne Laser Scanner Measurements

• Published in: Remote Sensing
• Main Authors: Sandberg Sørensen, Louise, Simonsen, Sebastian, Langley, Kirsty, Gray, Laurence, Helm, Veit, Nilsson, Johan, Stenseng, Lars, Skourup, Henriette, Forsberg, René, Davidson, Malcolm
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: MDPI 2018
• Subjects: Austfonna; CryoSat Validation Experiment; Ice cap; Svalbard
• Online Access: https://epic.awi.de/id/eprint/47907/; https://epic.awi.de/id/eprint/47907/1/remotesensing-10-01354-v2.pdf; https://hdl.handle.net/10013/epic.c8e347b9-8135-42bb-83ab-c3a13dd4822f

The study presented here is focused on the assessment of surface elevations derived from CryoSat-2 SARIn level 1b data over the Austfonna ice cap, Svalbard, in 2016. The processing chain that must be applied to the CryoSat-2 waveforms to derive heights is non-trivial, and consists of multiple steps, all requiring subjective choices of methods such as the choice of retracker, geo-relocation, and outlier rejection. Here, we compare six CryoSat-2 level-2 type data sets of surface elevations derived using different SARIn processing chains. These data sets are validated against surface elevation data collected from an airborne laser scanner, during a dedicated CryoSat validation experiment field campaign carried out in April 2016. The flight pattern of the airborne campaign was designed so that elevations were measured in a grid pattern rather than along single lines, as has previously been the standard procedure. The flight grid pattern was chosen to optimize the comparison with the CryoSat-2 SARIn elevation data, the location of which can deviate from nadir by several kilometers due to topography within the satellite footprint. The processing chains behind the six data sets include different outlier/error rejection approaches, and do not produce the same number of data points in our region of interest. To make a consistent analysis, we provide statistics from the validation of both the full data sets from each processing chain, and on only those data that all the six data sets provide a geo-located elevation estimate for. We find that the CryoSat-2 data sets that agree best with the validation data are those derived from dedicated land ice processing schemes. This study may serve as a benchmark for future CryoSat-2 retracker developments, and the evaluation software and data set are made publicly available.