[HTML][HTML] Sea ice extraction via remote sensing imagery: algorithms, datasets, applications and challenges

W Huang, A Yu, Q Xu, Q Sun, W Guo, S Ji, B Wen… - Remote Sensing, 2024 - mdpi.com
Deep learning, which is a dominating technique in artificial intelligence, has completely
changed image understanding over the past decade. As a consequence, the sea ice …

Sea ice extraction via remote sensed imagery: Algorithms, datasets, applications and challenges

A Yu, W Huang, Q Xu, Q Sun, W Guo, S Ji… - ar** from MODIS TOA reflectance data
Y Wu, CR Duguay, L Xu - Remote Sensing of Environment, 2021 - Elsevier
The topic of satellite remote sensing of lake ice has gained considerable attention in recent
years. Optical satellite data from the Moderate Resolution Imaging Spectroradiometer …

[HTML][HTML] Lake ice-water classification of RADARSAT-2 images by integrating IRGS Segmentation with pixel-based random forest labeling

M Hoekstra, M Jiang, DA Clausi, C Duguay - Remote Sensing, 2020 - mdpi.com
Changes to ice cover on lakes throughout the northern landscape has been established as
an indicator of climate change and variability, expected to have implications for both human …

Estimating sea ice concentration from SAR: Training convolutional neural networks with passive microwave data

CLV Cooke, KA Scott - IEEE Transactions on Geoscience and …, 2019 - ieeexplore.ieee.org
Historically, sea ice concentration (SIC) has been measured through the use of passive
microwave sensors, as well as human interpretation of synthetic aperture radar (SAR) …

Fractal analysis and texture classification of high-frequency multiplicative noise in SAR sea-ice images based on a transform-domain image decomposition method

IH Shahrezaei, HC Kim - IEEE Access, 2020 - ieeexplore.ieee.org
Texture in synthetic aperture radar (SAR) images is a combination of the intrinsic texture of
scene backscattering and the texture due to noncoherent high-frequency multiplicative noise …

[HTML][HTML] The use of C-band and X-band SAR with machine learning for detecting small-scale mining

G Janse van Rensburg, J Kemp - Remote Sensing, 2022 - mdpi.com
Illicit small-scale mining occurs in many tropical regions and is both environmentally and
socially hazardous. The aim of this study was to determine whether the classification of …

[HTML][HTML] River Ice Map** from Landsat-8 OLI Top of Atmosphere Reflectance Data by Addressing Atmospheric Influences with Random Forest: A Case Study on the …

H Han, T Kim, S Kim - Remote Sensing, 2024 - mdpi.com
Accurate river ice map** is crucial for predicting and managing floods caused by ice jams
and for the safe operation of hydropower and water resource facilities. Although satellite …

Evaluation of summer passive microwave sea ice concentrations in the Chukchi Sea based on KOMPSAT-5 SAR and numerical weather prediction data

H Han, H Kim - Remote Sensing of Environment, 2018 - Elsevier
Satellite passive microwave (PM) sensors have observed sea ice in Polar Regions and
provided sea ice concentration (SIC) data since the 1970s. SIC has been used as a primary …

[HTML][HTML] Retrieval of summer sea ice concentration in the Pacific Arctic Ocean from AMSR2 observations and numerical weather data using random forest regression

H Han, S Lee, HC Kim, M Kim - Remote Sensing, 2021 - mdpi.com
The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change
and important information for the development of a more economically valuable Northern …