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about-me

Hello world!

This is Daehyeon Han’s reserach blog.

Daehyeon Han received the B.S. degree in Earth science and engineering from Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea, in 2016. He is currently studying for a Ph.D. at UNIST. His research interests include the development of remote sensing and GIS-based​ models for the understanding of the Earth system.

  • 2016: B.S. Environmental Science and Engineering, UNIST
  • 2016-current: combined M.S. and Ph.D. course in IRIS lab, UNIST (adviser: Dr. Jungho Im)

Publications

  • Lee, J.+, Han, D.+, Shin, M., Im, J.*, Lee, J., & Quackenbush, L. J. (2020). Different Spectral Domain Transformation for Land Cover Classification Using Convolutional Neural Networks with Multi-Temporal Satellite Imagery. Remote Sensing, 12(7), 1097. ISO 690

  • 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. The Cryosphere, 14, 1083–1104

  • Yoo, C., Han, D., Im, J.*, & Bechtel, B. (2019). Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images. ISPRS Journal of Photogrammetry and Remote Sensing, 157, 155-170. ISO 690

  • Lee, Y., Han, D., Ahn, M. H.*, Im, J., & Lee, S. J. (2019). Retrieval of total precipitable water from Himawari-8 AHI data: a comparison of random forest, extreme gradient boosting, and deep neural network. Remote Sensing, 11(15), 1741.

  • Han, D., Lee, J., Im, J.*, Sim, S., Lee, S., & Han, H. (2019). A novel framework of detecting convective initiation combining automated sampling, machine learning, and repeated model tuning from geostationary satellite data. Remote Sensing, 11(12), 1454.

  • 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.

  • Kim, M., Lee, J., Han, D., Shin, M., Im, J.*, Lee, J., … & Gu, Z. (2018). Convolutional neural network-based land cover classification using 2-D spectral reflectance curve graphs with multitemporal satellite imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(12), 4604-4617.

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