Seokhyeon Kim

Seokhyeon Kim

Assistant Professor at CVEN@Kyung Hee University, Republic of Korea, expert in hydrology, water resources and satellite remote sensing

Improvement of satellite data

Goal

This project aims to improve satellite (not limited to) data. The method that we are currently developing is merging multiple datasets derived from various sources.

Papers

  • Kim, S., Parinussa, R. M., Liu, Y. Y., Johnson, F. M., & Sharma, A. (2015). A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation. Geophysical Research Letters, 42(16), 6662-6670.
  • Kim, S., Parinussa, R. M., Liu, Y. Y., Johnson, F. M., & Sharma, A. (2016). Merging alternate remotely-sensed soil moisture retrievals using a non-static model combination approach. Remote Sensing, 8(6), 518.
  • Hagan, D.F.T., Wang, G., Kim, S., Parinussa, R.M., Liu, Y., Ullah, W., Bhatti, A.S., Ma, X., Jiang, T. and Su, B., 2020. Maximizing temporal correlations in long-term global satellite soil moisture data-merging. Remote Sensing, 12(13), 2164.
  • Kim S., Pham H., Liu Y., Marshall L., Sharma A. (2020). Improving the combination of satellite soil moisture datasets by considering error cross-correlation: A comparison between triple collocation (TC) and extended double instrumental variable (EIVD) alternatives, IEEE Trans. Geosci. Remote Sens., 59(9), 7285-7295.
  • Kim S., Sharma A., Liu Y., Young I. S. (2021). Rethinking Satellite Data Merging: From Averaging to SNR Optimization, IEEE Trans. Geosci. Remote Sens., Early Access, 1-15.