ALSIM is a proposal for a 3 years research project, which will address the problem of largescale mapping of sea ice from synthetic aperture radar (SAR). The project will develop computer-aided algorithms that can reliably, robustly and efficiently extract accurate sea ice information like ice concentration or ice floe size distribution from large SAR scenes. Results will be validated using complementary satellite data and data collected in the field. It is divided into four interrelated work packages. WP1 will use deep learning algorithms to develop automatic sea ice concentration maps. WP2 will use a similar approach to address retrieval of fine scale sea ice features, and WP3 will focus on methods for upscaling information across multiple sensors. WP4 will focus on fieldwork to provide validation information. It will have strong support from CIRFA, and take advantage of field data measured during e.g. MOSAiC and Nansen Legacy field cruises. The project has high relevance to ongoing work at all partner institutions. Results will be disseminated in form of scientific publications, outreach and a seminar.
UiT Norges arktiske universitet
Project manager: Torbjørn Eltoft
Project code: 502018