RESEARCH
📚 Representative Works
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Prediction of the Arctic Sea Ice Concentrations
The Arctic sea ice refers to the frozen sea water, and the sea ice concentrations (SICs) are the relative amount of area covered by ice. The SICs plays important roles as a factor of measuring of global warming and on-going climate changes. We develop the SIC prediction model using satellite and reanalysis data based on deep learning approaches
•Prediction of the Arctic SICs using satellite and reanalysis data based on deep learning
•Analysis of spatio-temporal patterns of SICs
•Examination of affecting factors to change SICs
In progress
📝 Publications
Last updated : 2021/01/10
Kim, M., Kim, H. C., Im, J., Lee, S., & Han, H. (2020). Object-based landfast sea ice detection over West Antarctica using time series ALOS PALSAR data. Remote Sensing of Environment, 242, 111782.
Kim, Y. J., Kim, H. C., Han, D., Lee, S., & Im, J. (2020). Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks. Cryosphere, 14(3), 1083-1104.
Lee, S., Kim, H. C., & Im, J. (2018). Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data. Cryoshpere, 12(1), 1665-1679.
Han, D., Kim, Y. J., Im, J., Lee, S., Lee, Y., & Kim, H. C. (2018). The estimation of arctic air temperature in summer based on machine learning approaches using IABP buoy and AMSR2 satellite data. Korean Journal of Remote Sensing, 34(6_2), 1261-1272.
Lee, S., Im, J., Kim, J., Kim, M., Shin, M., Kim, H. C., & Quackenbush, L. J. (2016). Arctic sea ice thickness estimation from CryoSat-2 satellite data using machine learning-based lead detection. Remote Sensing, 8(9), 698.
Han, H., Im, J., & Kim, H. C. (2016). Variations in ice velocities of Pine Island Glacier Ice Shelf evaluated using multispectral image matching of Landsat time series data. Remote Sensing of Environment, 186, 358-371.
Han, H., Im, J., Kim, M., Sim, S., Kim, J., Kim, D. J., & Kang, S. H. (2016). Retrieval of melt ponds on arctic multiyear sea ice in summer from terrasar-x dual-polarization data using machine learning approaches: A case study in the chukchi sea with mid-incidence angle data. Remote Sensing, 8(1), 57.
Kim, M., Im, J., Han, H., Kim, J., Lee, S., Shin, M., & Kim, H. C. (2015). Landfast sea ice monitoring using multisensor fusion in the Antarctic. GIScience & Remote Sensing, 52(2), 239-256.