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Mapping sea-ice types from Sentinel-1 considering the surface-type dependent effect of incidence angle
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-23)
Automated classification of sea-ice types in Synthetic Aperture Radar (SAR) imagery is complicated by the class-dependent decrease of backscatter intensity with Incidence Angle (IA). In the log-domain, this decrease is approximately linear over the typical range of space-borne SAR instruments. A global correction does not consider that different surface types show different rates of decrease in ...
An Optimal Decision-Tree Design Strategy and Its Application to Sea Ice Classification from SAR Imagery
(Journal article; Tidsskriftartikkel; Peer reviewed, 2019-07-03)
We introduce the fully automatic design of a numerically optimized decision-tree algorithm and demonstrate its application to sea ice classification from SAR data. In the decision tree, an initial multi-class classification problem is split up into a sequence of binary problems. Each branch of the tree separates one single class from all other remaining classes, using a class-specific selected feature ...
Cross-platform application of a sea ice classification method considering incident angle dependency of backscatter intensity and its use in separating level and deformed ice
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021)
Wide-swath C-band synthetic aperture radar (SAR) has been used for sea ice classification and estimates of sea ice drift and deformation since it first became widely available in the 1990s. Here, we examine the potential to distinguish surface features created by sea ice deformation using ice type classification of SAR data. To perform this task with extended spatial and temporal coverage, we ...
Incident Angle Dependence of Sentinel-1 Texture Features for Sea Ice Classification
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-04)
Robust and reliable classification of sea ice types in synthetic aperture radar (SAR) images is needed for various operational and environmental applications. Previous studies have investigated the class-dependent decrease in SAR backscatter intensity with incident angle (IA); others have shown the potential of textural information to improve automated image classification. In this work, we investigate ...
Data Augmentation for SAR Sea Ice and Water Classification Based on Per-Class Backscatter Variation With Incidence Angle
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-03)
Monitoring sea ice in polar regions is critical for understanding global climate change and supporting marine navigation. Recently, researchers started to utilize machine/deep learning methodologies to automate the separation of sea ice and open water in synthetic aperture radar imagery. However, this requires a large amount of reliably labeled training data. We here propose an augmentation routine ...