Melt Pond Detection and Surface Type Classification Over Arctic Summer Sea Ice from ICESat-2
Abstract
NASA's Ice, Cloud, and land Elevation Satellite (ICESat-2) launched in September 2018 and during the summer of 2019 acquired profiles of sea ice at various stages of melt across the Arctic Ocean. Differentiating melt ponds at the sea ice surface, from leads/openings between ice floes, will be a key breakthrough as we seek to produce freeboard and thickness estimates through the entire annual cycle. Understanding melt pond properties from ICESat-2 data (e.g. melt pond area/depth) is a further exciting prospect.
Here we present an assessment of the ICESat-2 surface classification algorithm over summer sea ice - an extended use of the surface classification scheme used to differentiate leads/open water from the ice surface used to generate winter ice freeboards. To test the success of the algorithm, we compare the results with coincident (e.g., acquired < 1 hour before/after the ATLAS data) airborne (Operation IceBridge) and satellite (Sentinel-2, WorldView) optical imagery from a suite of platforms at different spatial resolution. The use of a large optical imagery dataset for validation (several tens of images) allows us to statistically assess the success of the algorithm in a wide range of environmental conditions and to identify potential shortcomings. To achieve a systematic and unbiassed assessment, prior to algorithm validation, we classify the optical images using the OSSP (Open Source Sea-ice Processing) algorithm and identify three main classes: ice and snow, open water and leads, and melt ponds. This approach allows a further assessment of the overall surface type classification in ICESat-2 sea ice products.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.C42A..06B
- Keywords:
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- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 0726 Ice sheets;
- CRYOSPHERE;
- 0750 Sea ice;
- CRYOSPHERE;
- 4556 Sea level: variations and mean;
- OCEANOGRAPHY: PHYSICAL