A New Application of Unsupervised Learning to Nighttime Sea Fog Detection
Sign Up to like & getrecommendations! Published in 2018 at "Asia-Pacific Journal of Atmospheric Sciences"
DOI: 10.1007/s13143-018-0050-y
Abstract: This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the 3.7 μm and 10.8 μm channels of the meteorological imager (MI)… read more here.
Keywords: sea; nighttime sea; unsupervised learning; fog detection ... See more keywords
A Probability-Based Daytime Algorithm for Sea Fog Detection Using GOES-16 Imagery
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2020.3036815
Abstract: Fog is a hazardous weather event that can endanger navigation, aviation, and transportation. While human has several limitations in detecting and forecasting offshore fog, satellite remote sensing offers cost-effective images. In this study, a probability-based… read more here.
Keywords: fog; fog detection; sea fog; probability ... See more keywords
MoANet: A Motion Attention Network for Sea Fog Detection in Time Series Meteorological Satellite Imagery
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2023.3340909
Abstract: Sea fog detection is a significant and challenging issue in meteorological satellite imagery. Distinguishing between sea fog and low clouds is challenging due to the similar morphology and brightness characteristics of these two phenomena on… read more here.
Keywords: motion; imagery; sea fog; fog detection ... See more keywords
A Correlation Context-Driven Method for Sea Fog Detection in Meteorological Satellite Imagery
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3095731
Abstract: Sea fog detection is a challenging and essential issue in satellite remote sensing. Although conventional threshold methods and deep learning methods can achieve pixel-level classification, it is difficult to distinguish ambiguous boundaries and thin structures… read more here.
Keywords: fog detection; sea fog; context driven; correlation context ... See more keywords
Dual-Branch Neural Network for Sea Fog Detection in Geostationary Ocean Color Imager
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3196177
Abstract: Sea fog significantly threatens the safety of maritime activities. This article develops a sea fog detection dataset (SFDD) and a dual-branch sea fog detection network (DB-SFNet). We investigate all the observed sea fog events in… read more here.
Keywords: fog detection; sea fog; dual branch; sea ... See more keywords
From Climate to Cloud: Advancing Fog Detection Through Satellite Imagery
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DOI: 10.3390/cli13060110
Abstract: The broad spatiotemporal coverage provided by satellite remote sensing is fundamental for monitoring fog events, a phenomenon that impacts transportation, agriculture, and ecosystem functioning. Despite advances in remote sensing technology, significant knowledge gaps remain regarding… read more here.
Keywords: detection; climate cloud; satellite imagery; fog detection ... See more keywords