Study on sea ice albedo based on Sentinel-3 OLCI satellite data

doi:10.13474/j.cnki.11-2246.2022.0173.

Abstract

Abstract: Monitoring sea ice is a global task. The key process is to invert and model the surface albedo. Rather than widely used BRDF method, this paper focuses on a new direct estimation method (encoded in the SNAP tool). In this research, two scenes of OLCI datasets focusing on Utqiagvik with low cloud cover are applied and pre-processed through Rayleigh correction and IdePix cloud classification and produce rBRR bands and cloud layers. The two bands are processed in the snow processor together with OLCI TOA and outputted products, including spectral and broadband albedo. As a result, surface albedo products are compared with other albedo products derived from MISR & MODIS at the coastal sea area. The results suggest that the SNAP tool has overestimated the red-light albedo and underestimated the NIR albedo. Also, in-land ice-albedo is compared with tower-based albedo product at Utqiagvik baseline station. The result shows a very high accuracy of 95%.

Key words: Sentinel-3 satellite, albedo, sea ice, OLCI, SNAP tool

CLC Number:

P237

DUAN Bokai. Study on sea ice albedo based on Sentinel-3 OLCI satellite data[J]. Bulletin of Surveying and Mapping, 2022, 0(6): 66-70.

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