The height difference between the sea ice surface and sea level, known as the freeboard, can be converted to an estimate for the ice thickness. Researcher Jack Landy found that up to 20% improvement in sea ice freeboard indicates that his new method could upgrade current and historic altimetry-derived Arctic sea ice thickness records.
PhD candidate Salman Khaleghian has a new paper published on how deep learning methods help with sea ice classification based on Sentinel-1 synthetic aperture radar data.
PhD fellow Eduard Khachatrian has a new paper on “Automatic Selection of Relevant Attributes for Multi-Sensor Remote Sensing Analysis: A Case Study on Sea Ice Classification”
The thinning and retreating of the Arctic sea ice has led to increased human presence in Arctic seas. Marine traffic is likely to increase in the future, as are activities such as fishing, oil and mineral exploitation. All these activities increase the risk for oil spills in ice-covered waters. Yet, the technology used to monitor…
Muhammad Asims new paper addresses new methodologies for remote sensing of marine Chlorophyll-a (Chl-a) with emphasis on the Barents Sea.
Congratulations to PhD candidate Salman Khalegian`s paper on Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks.
This work presents a combination of machine learning approaches to classify and assess feature relevance in remotely sensed hyperspectral and multispectral data.
A new review article, published by the Journal of Operational Oceanography on March 23, 2020 and funded by CIRFA, presents an overview of dynamics, observation methods and modelling of upper ocean surface currents.
A new paper on incident angle (IA) variation of texture features for sea ice classification has been accepted in the Remote Sensing special issue on Remote Sensing of Sea Ice and Icebergs: “Incident Angle Dependence of Sentinel-1 Texture Features for Sea Ice Classification” by J. Lohse, A. P. Doulgeris and W. Dierking. Remote Sensing 2021.…
Just before Christmas, a new paper is accepted. Knut-Frode Dagestad (MET Norway, left), Oscar Garcia (WaterMapping, LLC, middle), Lars R. Hole (MET Norway, in the back) and Camilla Brekke (UiT, right) collected valuable data during the NORSE2019 campaign and the paper in JGR Oceans and can now be accessed here. The paper is characterizing free…