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YoungHyun Koo
YoungHyun Koo
Verifierad e-postadress på lehigh.edu
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Estimation of thermodynamic and dynamic contributions to sea ice growth in the Central Arctic using ICESat-2 and MOSAiC SIMBA buoy data
YH Koo, R Lei, Y Cheng, B Cheng, H Xie, M Hoppmann, NT Kurtz, ...
Remote Sensing of Environment 267, 112730, 2021
192021
Analysis of photovoltaic potential and selection of optimal site near gumdeok mine, North Korea
MC Oh, SM Kim, YH Koo, HD Park
Journal of the Korean Society for New and Renewable Energy 14 (3), 44-53, 2018
112018
Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
YH Koo, H Xie, SF Ackley, AM Mestas-Nuñez, GJ Macdonald, CU Hyun
The Cryosphere 15 (10), 4727-4744, 2021
102021
Estimation and mapping of solar irradiance for korea by using COMS MI satellite images and an artificial neural network model
YH Koo, M Oh, SM Kim, HD Park
Energies 13 (2), 301, 2020
102020
Automated detection and tracking of medium-large icebergs from Sentinel-1 imagery using Google Earth Engine
Y Koo, H Xie, H Mahmoud, JM Iqrah, SF Ackley
Remote Sensing of Environment 296, 113731, 2023
82023
Weekly Mapping of Sea Ice Freeboard in the Ross Sea from ICESat-2
YH Koo, H Xie, NT Kurtz, SF Ackley, AM Mestas-Nuñez
Remote Sensing 13 (16), 3277, 2021
62021
Estimation of solar irradiance at weather stations in Korea using regionally trained artificial neural network models
YH Koo, SM Kim, M Oh, HD Park
Journal of the Korean Society of Mineral and Energy Resources Engineers 56 …, 2019
62019
Landslide risk assessment at the gumdeok mine in North Korea using satellite images and GIS spatial data
K Younghyun, S Kim, M Oh, HD Park
Journal of the Korean Society of Mineral and Energy Resources Engineers 55 …, 2018
52018
Sea ice surface type classification of ICESat-2 ATL07 data by using data-driven machine learning model: Ross Sea, Antarctic as an example
Y Koo, H Xie, NT Kurtz, SF Ackley, W Wang
Remote Sensing of Environment 296, 113726, 2023
42023
Graph Neural Networks as Fast and High-fidelity Emulators for Finite-Element Ice Sheet Modeling
M Rahnemoonfar, Y Koo
arXiv preprint arXiv:2402.05291, 2024
12024
Multi-task Deep Convolutional Network to Predict Sea Ice Concentration and Drift in the Arctic Ocean
Y Koo, M Rahnemoonfar
arXiv preprint arXiv:2311.00167, 2023
12023
Spatiotemporal Analysis of Sea Ice Leads in the Arctic Ocean Retrieved from IceBridge Laxon Line Data 2012–2018
D Sha, Y Koo, X Miao, A Srirenganathan, H Lan, S Biswas, Q Liu, ...
Remote Sensing 13 (20), 4177, 2021
12021
Prediction of sea ice dynamics using physics-informed convolutional neural network
YH Koo, H Xie, M Rahnemoonfar
AGU23, 2023
2023
An efficient digital twin for Ice Sheet System Model (ISSM) based on deep learning
YH Koo, M Rahnemoonfar
AGU23, 2023
2023
The forward cascade of sea ice floes in the Weddell Sea
M Gupta, H Regan, YH Koo, S Chua, X Li, P Heil
2023
Toward Polar Sea-Ice Classification using Color-based Segmentation and Auto-labeling of Sentinel-2 Imagery to Train an Efficient Deep Learning Model
J Masuma Iqrah, Y Koo, W Wang, H Xie, S Prasad
arXiv e-prints, arXiv: 2303.12719, 2023
2023
Using ICESat-2 Satellite Altimeter Data to Improve Understanding of Thermodynamic and Dynamic Sea Ice Characteristics in the Ross Sea
Y Koo
The University of Texas at San Antonio, 2023
2023
Automated detection and tracking of small icebergs in the Amundsen Sea using Google Earth Engine
YH Koo, H Xie, H Mahmoud, JM Iqrah
AGU Fall Meeting Abstracts 2022, C56A-04, 2022
2022
Thermodynamic and dynamic sea ice growth in the Ross Sea from ICESat-2
YH Koo, H Xie, NT Kurtz, SF Ackley
AGU Fall Meeting Abstracts 2022, C22A-47, 2022
2022
Characterizing the shape, size and freeboard of sea-ice floes in the Weddell sea from IceSat-2 and Sentinel-2
M Gupta, YH Koo, H Regan, S Chua, X Li, P Heil
AGU Fall Meeting Abstracts 2022, C25B-06, 2022
2022
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Artiklar 1–20