Publications

Exploring the potential of machine learning post-processing to generate ERA5-consistent atmospheric profiles from geostationary satellite retrievals

D. Han, M. Choo, S. Jung, J. Lee, H. Choi, J. Im

Remote Sensing 18(14), 2310, 2026

Robust daily satellite sea surface salinity reconstruction using deep learning in low-salinity coastal regions

S. Jung, S.H. Kim, E. Jang, J. Lee, D. Han, J. Im

Marine Pollution Bulletin 221, 118462, 2025

A novel sea ice floe fragmentation index using Sentinel-2 and AMSR2 satellite data based on machine learning

W. Kim, S. Sim, S. Lee, J. Stroeve, D. Han, J. Im

Int. J. Applied Earth Observation and Geoinformation 144, 2025

Improving timeliness and accuracy of daily gap-free satellite sea surface salinity using a self-supervised deep neural network

S. Kim, S. Jung, E. Jang, J. Lee, D. Han, J. Im

Proc. SPIE 13666, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVII, 2025

Exploring the potential of latent embeddings for sea ice characterization using ICESat-2 data

D. Han, M. Karimzadeh

IGARSS 2025, 2025

PARAN: A novel physics-assisted reconstruction adversarial network using geostationary satellite data to reconstruct hourly sea surface temperatures

S. Jung, J. Im, D. Han

Remote Sensing of Environment 323, 114749, 2025

Expanding high-resolution sea surface salinity estimation from coastal seas to open oceans through the synergistic use of multi-source data with machine learning

T. Sung, S.H. Kim, S. Sim, D. Han, E. Jang, J. Im

Int. J. Applied Earth Observation and Geoinformation 137, 2025

Long-term prediction of Arctic sea ice concentrations using deep learning: Effects of surface temperature, radiation, and wind conditions

Y.J. Kim, H. Kim, D. Han, J. Stroeve, J. Im

Remote Sensing of Environment 318, 114568, 2025

CARE-SST: Context-aware reconstruction diffusion model for sea surface temperature

M. Choo, S. Jung, J. Im, D. Han

ISPRS Journal of Photogrammetry and Remote Sensing 220, 454–472, 2025

Deep learning-based gap filling for near real-time seamless daily global sea surface salinity using satellite observations

E. Jang, D. Han, J. Im, T. Sung, Y.J. Kim

Int. J. Applied Earth Observation and Geoinformation 132, 2024

Improving short-term prediction of ocean fog using numerical weather forecasts and geostationary satellite-derived ocean fog data based on AutoML

S. Sim, J. Im, S. Jung, D. Han

Remote Sensing 16(13), 2348, 2024

Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning

D. Han, M. Choo, J. Im, Y. Shin, J. Lee, S. Jung

GIScience & Remote Sensing 60(1), 2203363, 2023

Remote sensing of sea surface salinity: Challenges and research directions

Y.J. Kim, D. Han, E. Jang, J. Im, T. Sung

GIScience & Remote Sensing 60(1), 2166377, 2023

Classification of carbon-based global marine eco-provinces using remote sensing data and K-means clustering

Y.J. Kim, D. Bae, J. Im, S. Jung, M. Choo, D. Han

Korean Journal of Remote Sensing 39(5), 1043–1060, 2023

Key factors for quantitative precipitation nowcasting using ground weather radar data based on deep learning

D. Han, J. Im, Y. Shin, J. Lee

Geoscientific Model Development 16, 5895–5914, 2023

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

J. Lee, M. Kim, J. Im, H. Han, D. Han

GIScience & Remote Sensing 58(7), 1052–1071, 2021

Sensitivity analysis for CAS500-4 atmospheric correction using simulated images and suggestion of the use of geostationary satellite-based atmospheric parameters

Y. Kang, D. Cho, D. Han, J. Im, J. Lim, K. Oh, E. Kwon

Korean Journal of Remote Sensing, 2021

Detection of Arctic summer melt ponds using ICESat-2 altimetry data

D. Han, Y.J. Kim, S. Jung, S. Sim, W. Kim, E. Jang, J. Im, H.C. Kim

Korean Journal of Remote Sensing, 2021

Rainfall intensity estimation using geostationary satellite data based on machine learning: A case study in the Korean Peninsula in summer

Y. Shin, D. Han, J. Im

Korean Journal of Remote Sensing, 2021

Improving local climate zone classification using incomplete building data and Sentinel-2 images based on convolutional neural networks

C. Yoo, Y. Lee, D. Cho, J. Im, D. Han

Remote Sensing 12(21), 3552, 2020

Short-term forecasting of satellite-based drought indices using their temporal patterns and numerical model output

S. Park, J. Im, D. Han, J. Rhee

Remote Sensing 12(21), 3499, 2020

Different spectral domain transformation for land cover classification using convolutional neural networks with multi-temporal satellite imagery

J. Lee, D. Han, M. Shin, J. Im, J. Lee, L.J. Quackenbush

Remote Sensing 12(7), 1097, 2020

Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks

Y.J. Kim, H.C. Kim, D. Han, S. Lee, J. Im

The Cryosphere 14(3), 1083–1104, 2020

Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images

C. Yoo, D. Han, J. Im, B. Bechtel

ISPRS Journal of Photogrammetry and Remote Sensing 157, 155–170, 2019

Retrieval of total precipitable water from Himawari-8 AHI data: A comparison of random forest, extreme gradient boosting, and deep neural network

Y. Lee, D. Han, M.H. Ahn, J. Im, S.J. Lee

Remote Sensing 11(15), 1741, 2019

A novel framework of detecting convective initiation combining automated sampling, machine learning, and repeated model tuning from geostationary satellite data

D. Han, J. Lee, J. Im, S. Sim, S. Lee, H. Han

Remote Sensing 11(12), 1454, 2019

Convolutional neural network-based land cover classification using 2-D spectral reflectance curve graphs with multitemporal satellite imagery

M. Kim, J. Lee, D. Han, M. Shin, J. Im, J. Lee, L.J. Quackenbush, Z. Gu

IEEE JSTARS, 2018