Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument ...

• Main Authors: Kokhanovsky, Alexander, Lamare, Maxim, Danne, Olaf, Brockmann, Carsten, Korkin, Sergey, Et Al
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: MDPI 2019
• Subjects: Greenland; Steen; The Sentinel; Antarc*; Antarctica; Ice Sheet
• Online Access: https://dx.doi.org/10.13016/m2pzwf-qalu; https://mdsoar.org/handle/11603/28815

Authors: - Alexander Kokhanovsky , Maxim Lamare , Olaf Danne , Carsten Brockmann , Marie Dumont , Ghislain Picard , Laurent Arnaud , Vincent Favier , Bruno Jourdain , Emmanuel Le Meur , Biagio Di Mauro , Teruo Aoki , Masashi Niwano , Vladimir Rozanov , Sergey Korkin , Sepp Kipfstuhl , Johannes Freitag , Maria Hoerhold , Alexandra Zuhr , Diana Vladimirova , Anne-Katrine Faber , Hans Christian Steen-Larsen , Sonja Wahl , Jonas K. Andersen , Baptiste Vandecrux , Dirk van As , Kenneth D. Mankoff , Michael Kern , Eleonora Zege and Jason E. Box ... : The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400–1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is ...