Daehyeon Han

728 total citations
19 papers, 522 citations indexed

About

Daehyeon Han is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Daehyeon Han has authored 19 papers receiving a total of 522 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Atmospheric Science, 10 papers in Global and Planetary Change and 8 papers in Oceanography. Recurrent topics in Daehyeon Han's work include Meteorological Phenomena and Simulations (8 papers), Oceanographic and Atmospheric Processes (7 papers) and Climate variability and models (6 papers). Daehyeon Han is often cited by papers focused on Meteorological Phenomena and Simulations (8 papers), Oceanographic and Atmospheric Processes (7 papers) and Climate variability and models (6 papers). Daehyeon Han collaborates with scholars based in South Korea, United States and United Kingdom. Daehyeon Han's co-authors include Jungho Im, Cheolhee Yoo, Benjamin Bechtel, Sanggyun Lee, Young Jun Kim, Hyun‐Cheol Kim, Su Jeong Lee, Yeonjin Lee, Myoung‐Hwan Ahn and Hyangsun Han and has published in prestigious journals such as Remote Sensing of Environment, Remote Sensing and ISPRS Journal of Photogrammetry and Remote Sensing.

In The Last Decade

Daehyeon Han

17 papers receiving 509 citations

Peers

Countries citing papers authored by Daehyeon Han

Since Specialization

Citations

This map shows the geographic impact of Daehyeon Han's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daehyeon Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daehyeon Han more than expected).

Fields of papers citing papers by Daehyeon Han

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daehyeon Han. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daehyeon Han. The network helps show where Daehyeon Han may publish in the future.

Co-authorship network of co-authors of Daehyeon Han

This figure shows the co-authorship network connecting the top 25 collaborators of Daehyeon Han. A scholar is included among the top collaborators of Daehyeon Han based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daehyeon Han. Daehyeon Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

#	Work	Indexed citations
1	PARAN: A novel physics-assisted reconstruction adversarial network using geostationary satellite data to reconstruct hourly sea surface temperatures 2025 ·Remote Sensing of Environment ·(unknown), Jungho Im, Daehyeon Han	0
2	Expanding high-resolution sea surface salinity estimation from coastal seas to open oceans through the synergistic use of multi-source data with machine learning 2025 ·International Journal of Applied Earth Observation and Geoinformation ·(unknown), (unknown), (unknown), Daehyeon Han, Eunna Jang, Jungho Im	1
3	CARE-SST: context-aware reconstruction diffusion model for sea surface temperature 2025 ·ISPRS Journal of Photogrammetry and Remote Sensing ·(unknown), (unknown), Jungho Im, Daehyeon Han	0
4	Improving Short-Term Prediction of Ocean Fog Using Numerical Weather Forecasts and Geostationary Satellite-Derived Ocean Fog Data Based on AutoML 2024 ·Remote Sensing ·(unknown), Jungho Im, (unknown), Daehyeon Han	3
5	Long-term prediction of Arctic sea ice concentrations using deep learning: Effects of surface temperature, radiation, and wind conditions 2024 ·Remote Sensing of Environment ·Young Jun Kim, Hyun‐Cheol Kim, Daehyeon Han, Julienne Strœve, Jungho Im	5
6	Deep learning-based gap filling for near real-time seamless daily global sea surface salinity using satellite observations 2024 ·International Journal of Applied Earth Observation and Geoinformation ·Eunna Jang, Daehyeon Han, Jungho Im, (unknown), Young Jun Kim	3
7	Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning 2023 ·GIScience & Remote Sensing ·Daehyeon Han, (unknown), Jungho Im, (unknown), (unknown), (unknown)	18
8	Key factors for quantitative precipitation nowcasting using ground weather radar data based on deep learning 2023 ·Geoscientific model development ·Daehyeon Han, Jungho Im, (unknown), (unknown)	6
9	Remote sensing of sea surface salinity: challenges and research directions 2023 ·GIScience & Remote Sensing ·Young Jun Kim, Daehyeon Han, Eunna Jang, Jungho Im, (unknown)	26
10	Pre-trained feature aggregated deep learning-based monitoring of overshooting tops using multi-spectral channels of GeoKompsat-2A advanced meteorological imagery 2021 ·GIScience & Remote Sensing ·(unknown), Miae Kim, Jungho Im, Hyangsun Han, Daehyeon Han	20
11	Short-Term Forecasting of Satellite-Based Drought Indices Using Their Temporal Patterns and Numerical Model Output 2020 ·Remote Sensing ·(unknown), Jungho Im, Daehyeon Han, Jinyoung Rhee	27
12	Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks 2020 ·The cryosphere ·Young Jun Kim, Hyun‐Cheol Kim, Daehyeon Han, Sanggyun Lee, Jungho Im	73
13	Different Spectral Domain Transformation for Land Cover Classification Using Convolutional Neural Networks with Multi-Temporal Satellite Imagery 2020 ·Remote Sensing ·Junghee Lee, Daehyeon Han, Minso Shin, Jungho Im, Junghye Lee, Lindi J. Quackenbush	15
14	Improving Local Climate Zone Classification Using Incomplete Building Data and Sentinel 2 Images Based on Convolutional Neural Networks 2020 ·Remote Sensing ·Cheolhee Yoo, (unknown), Dongjin Cho, Jungho Im, Daehyeon Han	39
15	A Novel Framework of Detecting Convective Initiation Combining Automated Sampling, Machine Learning, and Repeated Model Tuning from Geostationary Satellite Data 2019 ·Remote Sensing ·Daehyeon Han, (unknown), Jungho Im, (unknown), Sanggyun Lee, Hyangsun Han	33
16	Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images 2019 ·ISPRS Journal of Photogrammetry and Remote Sensing ·Cheolhee Yoo, Daehyeon Han, Jungho Im, Benjamin Bechtel	168
17	Retrieval of Total Precipitable Water from Himawari-8 AHI Data: A Comparison of Random Forest, Extreme Gradient Boosting, and Deep Neural Network 2019 ·Remote Sensing ·Yeonjin Lee, Daehyeon Han, Myoung‐Hwan Ahn, Jungho Im, Su Jeong Lee	58
18	The Estimation of Arctic Air Temperature in Summer Based on Machine Learning Approaches Using IABP Buoy and AMSR2 Satellite Data 2018 ·National Remote Sensing Bulletin ·Daehyeon Han, Young Jun Kim, Jungho Im, (unknown), (unknown), Hyun‐Cheol Kim	1
19	Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery 2018 ·IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ·Miae Kim, Jung‐Hee Lee, Daehyeon Han, Minso Shin, Jungho Im, Junghye Lee, Lindi J. Quackenbush, (unknown)	26

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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