Seokhyeon Kim

Seokhyeon Kim

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

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

portfolio

Improvement of satellite data

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

publications

Evaluation of the reliability improvement of a water distribution system by changing pipe

Published in Journal of Korea Water Resources Association, 2009

How the reliability of WDS is improved by chnaging pipes?

Recommended citation: Jun, H. D., Kim, S. H., Yoo, D. G., & Kim, J. H. (2009). Evaluation of the reliability improvement of a water distribution system by changing pipe. Journal of Korea Water Resources Association, 42(6), 505-511. https://www.koreascience.or.kr/article/JAKO200918839962063.page

Use of single layer concrete armour units as toe reinforcement

Published in Proceeding of International Conference on Coastal Engineering, 2012

2D flume test for an alternative desing of a breakwater in the Colombo Port Expansion Project

Recommended citation: Young, M., Hayman-Joyce, J., & Kim, S. H. (2012). Use of single layer concrete armour units as toe reinforcement. In Proceeding of International Conference on Coastal Engineering (pp. 48-59). https://www.researchgate.net/profile/Seokhyeon_Kim/publication/273144005_USE_OF_SINGLE_LAYER_CONCRETE_ARMOUR_UNITS_AS_TOE_REINFORCEMENT/links/54fa2f220cf2040df21b1d2b.pdf

A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation

Published in Geophysical Research Letters, 2015

Dara merging framework to improve temporal correlation of satellite data.

Recommended citation: 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. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2015GL064981

Assessment of Design Alternation via 2D Physical Modelling in the Main Breakwater of Colombo Port Expansion Project

Published in Journal of Japan Society of Civil Engineers, 2016

2D flume model for an alternate design of breakwater toe.

Recommended citation: Silva, A., Subasinghe, K., Rajapaksha, C., Raveenthiran, K., Kim, S. H., Young, M., ... & Araki, S. (2016). Assessment of Design Alternation via 2D Physical Modelling in the Main Breakwater of Colombo Port Expansion Project. Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering), 72(2), I_1129-I_1134. https://www.jstage.jst.go.jp/article/kaigan/72/2/72_I_1129/_article/-char/ja/

Spatial disaggregation of coarse soil moisture data by using high-resolution remotely sensed vegetation products

Published in IEEE Geoscience and Remote Sensing Letters, 2017

Development of a method to disaggregate coarse satellite soil moisture data by only using a vegetation index.

Recommended citation: Kim, S., Balakrishnan, K., Liu, Y., Johnson, F., & Sharma, A. (2017). Spatial disaggregation of coarse soil moisture data by using high-resolution remotely sensed vegetation products. IEEE Geoscience and Remote Sensing Letters, 14(9), 1604-1608. https://ieeexplore.ieee.org/abstract/document/7999216/

Building a flood-warning framework for ungauged locations using low resolution, open-access remotely sensed surface soil moisture, precipitation, soil, and topographic information

Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018

Development of a physical model to estimate floods using various open access datasets.

Recommended citation: Kim, S., Paik, K., Johnson, F. M., & Sharma, A. (2018). Building a flood-warning framework for ungauged locations using low resolution, open-access remotely sensed surface soil moisture, precipitation, soil, and topographic information. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(2), 375-387. https://ieeexplore.ieee.org/abstract/document/8276238/

Catchment scale simulations of soil moisture dynamics using an equivalent cross-section based hydrological modelling approach

Published in Journal of Hydrology, 2018

Computationally efficient modelling of soil moisture at catchment scales and validation using satellite soil moisture data.

Recommended citation: Khan, U., Ajami, H., Tuteja, N. K., Sharma, A., & Kim, S. (2018). Catchment scale simulations of soil moisture dynamics using an equivalent cross-section based hydrological modelling approach. Journal of Hydrology, 564, 944-966. https://www.sciencedirect.com/science/article/pii/S0022169418305808

A comprehensive validation of the SMAP Enhanced Level-3 Soil Moisture product using ground measurements over varied climates and landscapes

Published in Remote Sensing of Environment, 2019

A comprehensive validation of a SMAP soil moisture dataset.

Recommended citation: Zhang, R., Kim, S., & Sharma, A. (2019). A comprehensive validation of the SMAP Enhanced Level-3 Soil Moisture product using ground measurements over varied climates and landscapes. Remote Sensing of Environment, 223, 82-94. https://www.sciencedirect.com/science/article/pii/S003442571930015X

A framework for improving reliability of water distribution systems based on a segment-based minimum cut-set approach

Published in Water, 2019

Development of a method to improve the reliability of a water distribution system using the genetic algorithm.

Recommended citation: Kim, S., Jun, H. D., Yoo, D. G., & Kim, J. H. (2019). A framework for improving reliability of water distribution systems based on a segment-based minimum cut-set approach. Water, 11(7), 1524. https://www.mdpi.com/2073-4441/11/7/1524

Using 3D robust smoothing to fill land surface temperature gaps at the continental scale

Published in International Journal of Applied Earth Observation and Geoinformation, 2019

Application and validation of a gap-filling algorithm using continental scale LST data.

Recommended citation: Pham, H. T., Kim, S., Marshall, L., & Johnson, F. (2019). Using 3D robust smoothing to fill land surface temperature gaps at the continental scale. International Journal of Applied Earth Observation and Geoinformation, 82, 101879. https://www.sciencedirect.com/science/article/pii/S0303243419300339

A Review of Satellite-Derived Soil Moisture and Its Usage for Flood Estimation

Published in Remote Sensing in Earth Systems Sciences, 2019

A comprehensive review on satellite soil moisture data and its applications for flood estimation.

Recommended citation: Kim, S., Zhang, R., Pham, H., & Sharma, A. (2019). A Review of Satellite-Derived Soil Moisture and Its Usage for Flood Estimation. Remote Sensing in Earth Systems Sciences, 2(4), 225-246. https://link.springer.com/article/10.1007/s41976-019-00025-7

Using particle composition of fly ash to predict concrete strength and electrical resistivity

Published in Cement and Concrete Composites, 2020

Development of a model to estimate the concrete strength and electrical resistivity based on a PCA analysis on fly ash components.

Recommended citation: Kim, T., Ley, M. T., Kang, S., Davis, J. M., Kim, S., & Amrollahi, P. (2020). Using particle composition of fly ash to predict concrete strength and electrical resistivity. Cement and Concrete Composites, 107, 103493. https://www.sciencedirect.com/science/article/pii/S0958946519313368

Maximizing Temporal Correlations in Long-Term Global Satellite Soil Moisture Data Merging

Published in Remote Sensing, 2020

Improving temporal correlation of soil moisture data through data merging.

Recommended citation: 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. https://www.mdpi.com/2072-4292/12/13/2164

Quantifying natural organic matter concentration in water from climatological parameters using different machine learning algorithms

Published in H2Open Journal, 2020

Development of a machine-learning based model to estimate water quality of a reservoir using various emvironmental data.

Recommended citation: Moradi, S., Agostino, A., Gandomkar, Z., Kim, S., Hamilton, L., Sharma, A., Henderson, R. and Leslie, G., 2020. Quantifying natural organic matter concentration in water from climatological parameters using different machine learning algorithms. h2oj, 3(1), 328-342. https://iwaponline.com/h2open/article/3/1/328/76304

Impact of atmospheric circulation on the rainfall-temperature relationship in Australia

Published in Environmental Research Letters, 2020

Temperature-rainfall sensitivity conditioned by weather types.

Recommended citation: Magan, B., Kim, S., Wasko, C., Barbero, R., Moron, V., Nathan, R., & Sharma, A. (2020). Impact of atmospheric circulation on the rainfall-temperature relationship in Australia. Environmental Research Letters, 15(9), 094098. https://iopscience.iop.org/article/10.1088/1748-9326/abab35/meta

Using remotely sensed information to improve vegetation parameterization in a semi-distributed hydrological model (SMART) for upland catchments in Australia

Published in Remote Sensing, 2020

Development of vegetation parameterization method to imporve model simulation performances.

Recommended citation: Kim, S., Ajami, H., & Sharma, A. (2020). Using Remotely Sensed Information to Improve Vegetation Parameterization in a Semi-Distributed Hydrological Model (SMART) for Upland Catchments in Australia. Remote Sensing, 12(18), 3051. https://www.mdpi.com/2072-4292/12/18/3051

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

Published in IEEE Transactions on Geoscience and Remote Sensing, 2020

Data merging considering the error cross-correlation in the datasets to be merged.

Recommended citation: 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 Transactions on Geoscience and Remote Sensing, 59(9), 7285-7295 https://ieeexplore.ieee.org/document/9246707

Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability using a model combination approach

Published in Remote Sensing of Environment, 2021

Identification of relative strengths of three satellite soil moisture data for capturing the temporal variability of the ground truth.

Recommended citation: Zhang, R., Kim, S., Sharma, A., & Lakshmi, V. (2021). Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability. Remote Sensing of Environment, 252, 112126. https://www.sciencedirect.com/science/article/pii/S0034425720304995

Probabilistic forecasting of Cyanobacterial concentration in riverine systems using environmental drivers

Published in Journal of Hydrology, 2021

Development of a probabilistic model to forecast cyanobacterial concentration in a river.

Recommended citation: Kim, S., Mehrotra, R., Kim, S., & Sharma, A. (2021). Probabilistic forecasting of cyanobacterial concentration in riverine systems using environmental drivers. Journal of Hydrology, 593, 125626. https://www.sciencedirect.com/science/article/pii/S0022169420310878

Assessing countermeasure effectiveness in controlling cyanobacterial exceedance in riverine systems using probabilistic forecasting alternatives

Published in Journal of Water Resources Planning and Management, 2021

Countermeasure effectiveness in controlling cyanobacterial exceedance in riverine systems.

Recommended citation: Kim S., Mehrotra R., Kim S., Sharma A. (2021). Assessing countermeasure effectiveness in controlling cyanobacterial exceedance in riverine systems using probabilistic forecasting alternatives, Journal of Water Resources Planning and Management, 147(10), 04021062 https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29WR.1943-5452.0001449

A triple collocation-based comparison of three L-band soil moisture datasets, SMAP, SMOS-IC, and SMOS, over varied climates and land covers

Published in Frontiers in Water, 2021

A triple collocation-based comparison of three L-band soil moisture datasets, SMAP, SMOS-IC, and SMOS, over varied climates and land covers.

Recommended citation: Kim S., Dong J., Sharma A. (2021). A triple collocation-based comparison of three L-band soil moisture datasets, SMAP, SMOS-IC, and SMOS, over varied climates and land covers, Frontiers in Water, 3, 64 https://www.frontiersin.org/articles/10.3389/frwa.2021.693172/full

Development of Car-free Street Mapping (CfSM) Model using an Integrated System with Unmanned Aerial Vehicle, Aerial Mapping Camera and Deep Learning Algorithm

Published in Journal of Computing in Civil Engineering, 2022

Development of car-free street map.

Recommended citation: Lee, S., Kim, S., Moonb, S. (2022). Lee, S., Kim S., and Moon S., Development of Car-free Street Mapping (CfSM) Model using an Integrated System with Unmanned Aerial Vehicle, Aerial Mapping Camera and Deep Learning Algorithm, Journal of Computing in Civil Engineering, 36(3), 04022003 https://ascelibrary.org/doi/10.1061/%28ASCE%29CP.1943-5487.0001013

software

SNR-opt

MATLAB codes for SNR-opt for merging datasets (Kim et al.,2022)

talks

teaching

Catchment & Water Resources Modelling

Masters course (CVEN9612), School of Civil and Environmental Engineering, UNSW Sydney, 2020

  • Teaching period: 2020 (T3), 2019(T3), 2018(S2), 2017(S2)
  • Position: Post-Doctoral Teaching Assistant
  • Role: Teaching, coordinating and consulting
  • Number of students: 21~45
  • Course Profile (T3, 2020)

Water Resources Engineering

Undergraduate course (CVEN3501), School of Civil and Environmental Engineering, UNSW Sydney, 2020

  • Teaching period: 2020(T1), 2019(T1)
  • Position: Post-Doctoral Teaching Assistant
  • Role: Teaching, coordinating and consulting
  • Number of students: 452~610
  • Course Profile (T1, 2020)