This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …

Synthetic Aperture Radar (SAR), as a microwave sensor that can sense a target all day or
night under all-weather conditions, is of great significance for detecting water resources …

This study develops a deep learning (DL) model to classify the sea ice and open water from
synthetic aperture radar (SAR) images. We use the U-Net, a well-known fully convolutional …

This study proposes a dual-branch encoder U-Net (DBU-Net) deep learning model to
classify sea ice types based on synthetic aperture radar (SAR) images in the Beaufort Sea …

With the availability of petabytes of oceanographic observations and numerical model
simulations, artificial intelligence (AI) tools are being increasingly leveraged in a variety of …

Abstract Synthetic Aperture Radar (SAR) has emerged as a pivotal technology in
geosciences, offering unparalleled insights into Earth's surface. Indeed, its ability to provide …

Automatically producing Arctic sea ice charts from Sentinel-1 synthetic aperture radar (SAR)
images is challenging for convolutional neural networks (CNNs) due to ambiguous …

Widely used sea ice concentration and sea ice cover in polar regions are derived mainly
from spaceborne microwave radiometer and scatterometer data, and the typical spatial …

Revolutionary advances in artificial intelligence (AI) in the past decade have brought
transformative innovation across science and engineering disciplines. In the field of Arctic …

Sea ice is one of the typical causes of marine disasters. Sea ice image classification is an
important component of sea ice detection. Optical data contain rich spectral information, but …