Pre-trained feature aggregated deep learning-based monitoring of overshooting tops using multi-spectral channels of GeoKompsat-2A advanced meteorological imagery-Reference-Cited by-同舟云学术

Pre-trained feature aggregated deep learning-based monitoring of overshooting tops using multi-spectral channels of GeoKompsat-2A advanced meteorological imagery

Published:2021-08-10 Issue:7 Volume:58 Page:1052-1071
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Lee Juhyun¹^ORCID,Kim Miae¹^ORCID,Im Jungho¹^ORCID,Han Hyangsun²^ORCID,Han Deahyeon¹^ORCID

Affiliation:

1. Department of Urban & Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

2. Department of Geophysics, Kangwon National University, Chuncheon, Republic of Korea

Funder

National Research Foundation of Korea

Ministry of Interior and Safety

Ministry of Science and ICT

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2021.1960075

Reference56 articles.

1. Classification of polarimetric SAR images using compact convolutional neural networks

2. Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements

3. Needles in a Haystack: Tracking City-Scale Moving Vehicles From Continuously Moving Satellite

4. Objective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness Temperature Gradients

5. Overshooting cloud top detections using MSG SEVIRI Infrared brightness temperatures and their relationship to severe weather over Europe

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep learning-based gap filling for near real-time seamless daily global sea surface salinity using satellite observations;International Journal of Applied Earth Observation and Geoinformation;2024-08

2. Enhancing tropical cyclone intensity forecasting with explainable deep learning integrating satellite observations and numerical model outputs;iScience;2024-06

3. Bridging satellite missions: deep transfer learning for enhanced tropical cyclone intensity estimation;GIScience & Remote Sensing;2024-03-11

4. Convective Cloud Detection From Himawari-8 Advanced Himawari Imager Data Using a Dual-Branch Deformable Convolutional Network;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

5. Key factors for quantitative precipitation nowcasting using ground weather radar data based on deep learning;Geoscientific Model Development;2023-10-20