YoonKyung Cha

发表

Deep learning-based retrieval of cyanobacteria pigment in inland water for in-situ and airborne hyperspectral data

Inhyeok Yim, Jihoon Shin, Hyuk Lee, 2020 .

Probabilistic prediction of cyanobacteria abundance in a Korean reservoir using a Bayesian Poisson model

Craig A. Stow, Seok Soon Park, YoonKyung Cha, 2014 .

Long-term and seasonal trend decomposition of Maumee River nutrient inputs to western Lake Erie.

Craig A Stow, Remegio Confesor, YoonKyung Cha, 2015, Environmental science & technology.

A Bayesian hierarchical model to guide development and evaluation of substance objectives under the 2012 Great Lakes Water Quality Agreement

C. Stow, S. Qian, YoonKyung Cha, 2014 .

Effect of Hypoxia on Diet of Atlantic Bumpers in the Northern Gulf of Mexico

Aaron T. Adamack, C. Stow, D. Mason, 2018, Transactions of the American Fisheries Society.

The Effects of Tree Species on Soil Organic Carbon Content in South Korea

N. Oh, YoonKyung Cha, J. Cha, 2019, Journal of Geophysical Research: Biogeosciences.

Load reduction and invasive mussel effects on eutrophication dynamics in Saginaw Bay, Lake Huron

YoonKyung Cha, 2011 .

Evaluation of temperature effects on brake wear particles using clustered heatmaps

Soon-Bark Kwon, Inhyeok Yim, Jihoon Shin, 2019, Environmental Engineering Research.

A Bayesian hierarchical approach to model seasonal algal variability along an upstream to downstream river gradient

C. Stow, YoonKyung Cha, Seok Soon park, 2016 .

New methodology of evaluation of best management practices performances for an agricultural watershed according to the climate change scenarios: A hybrid use of deterministic and decision support models

YoonKyung Cha, S. Ki, Joon Kim, 2018, Ecological Engineering.

Phosphorus targets and eutrophication objectives in Saginaw Bay: A 35 year assessment

Dianna R. Miller, C. Stow, S. Qian, 2014 .

Spatial and temporal patterns of macroscopic benthic primary producers in Saginaw Bay, Lake Huron

Dianna R. Miller, C. Stow, S. Peacor, 2014 .

An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics

Kenneth H. Reckhow, YoonKyung Cha, Ibrahim Alameddine, 2011, Environ. Model. Softw..

Willingness to Pay for Improved Water Supply Services Based on Asset Management: A Contingent Valuation Study in South Korea

Jihoon Shin, YoonKyung Cha, J. Koo, 2021, Water.

Are chlorophyll a-total phosphorus correlations useful for inference and prediction?

Craig A Stow, Yoonkyung Cha, C. Stow, 2013, Environmental science & technology.

Effects of class imbalance on resampling and ensemble learning for improved prediction of cyanobacteria blooms

Jihoon Shin, YoonKyung Cha, Seonghyeon Yoon, 2021, Ecol. Informatics.

Simultaneous feature engineering and interpretation: Forecasting harmful algal blooms using a deep learning approach.

Jihoon Shin, YoonKyung Cha, Youngwook Kim, 2022, Water research.

The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers.

Hyuk Lee, Taegu Kang, K. Cho, 2017, Water research.

Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model

Yakov A. Pachepsky, Hyuk Lee, Kyung Hwa Cho, 2017, Environ. Model. Softw..

Evaluating physico-chemical influences on cyanobacterial blooms using hyperspectral images in inland water, Korea.

Taegu Kang, Kyung Hwa Cho, YoonKyung Cha, 2017, Water research.

A cross‐scale view of N and P limitation using a Bayesian hierarchical model

C. Stow, S. Qian, YoonKyung Cha, 2016 .

Impacts of dreissenid mussel invasions on chlorophyll and total phosphorus in 25 lakes in the USA

Craig A. Stow, YoonKyung Cha, Emily S. Bernhardt, 2013 .

Modeling spatiotemporal bacterial variability with meteorological and watershed land-use characteristics.

K. Cho, YoonKyung Cha, Joon Kim, 2016, Water research.

A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay

Craig A. Stow, YoonKyung Cha, C. Stow, 2014, Environ. Model. Softw..

Implications of Stein's Paradox for Environmental Standard Compliance Assessment.

C. Stow, S. Qian, YoonKyung Cha, 2015, Environmental science & technology.

Validity evaluation of a machine-learning model for chlorophyll a retrieval using Sentinel-2 from inland and coastal waters

Jihoon Shin, YoonKyung Cha, Y. Park, 2022, Ecological Indicators.

Mining web-based data to assess public response to environmental events.

Craig A Stow, YoonKyung Cha, C. Stow, 2015, Environmental pollution.

Prediction of cyanobacteria blooms in the lower Han River (South Korea) using ensemble learning algorithms

Jihoon Shin, YoonKyung Cha, Seonghyeon Yoon, 2017 .

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery

Hyuk Lee, Kyunghyun Kim, Kyung Hwa Cho, 2020, Remote. Sens..

Bayesian modeling approach for characterizing groundwater arsenic contamination in the Mekong River basin.

K. Cho, YoonKyung Cha, S. Sthiannopkao, 2016, Chemosphere.

Forecasting Abrupt Depletion of Dissolved Oxygen in Urban Streams Using Discontinuously Measured Hourly Time‐Series Data

Jihoon Shin, K. Cho, YoonKyung Cha, 2021, Water Resources Research.

Assessing Land-Cover Effects on Stream Water Quality in Metropolitan Areas Using the Water Quality Index

Jihoon Shin, YoonKyung Cha, Youngwook Kim, 2020, Water.

Incorporation of feature engineering and attention mechanisms into deep learning models to develop an early warning system for harmful algal blooms

Jihoon Shin, YoonKyung Cha, Taeho Kim, 2023, Journal of Cleaner Production.

Do invasive mussels restrict offshore phosphorus transport in Lake Huron?

Craig A Stow, Kenneth H Reckhow, Yoonkyung Cha, 2011, Environmental science & technology.

Multilevel regression models describing regional patterns of invertebrate and algal responses to urbanization across the USA

S. Qian, T. Cuffney, J. Coles, 2011, Journal of the North American Benthological Society.

Assessing the impacts of dam/weir operation on streamflow predictions using LSTM across South Korea

YoonKyung Cha, Sangchul Lee, Yeo-Hyun Park, 2023, Scientific reports.

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

Sanghyun Park, Hyuk Lee, Minjeong Kim, 2017, Remote. Sens..

An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebrates.

Jihoon Shin, YoonKyung Cha, Young‐Seuk Park, 2021, Journal of environmental management.

Data-driven models for predicting community changes in freshwater ecosystems: A review

YoonKyung Cha, J. Min, Da-Yeong Lee, 2023, Ecol. Informatics.

Foraging ecology of walleye and brown trout in a Great Lakes tributary

D. Mason, E. Rutherford, YoonKyung Cha, 2016 .

Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

T. Cuffney, YoonKyung Cha, Boknam Lee, 2010 .

The implications of Simpson's paradox for cross-scale inference among lakes.

Craig A Stow, Joseph Stachelek, Song S Qian, 2019, Water research.

Spatial Distribution Modeling of Customer Complaints Using Machine Learning for Indoor Water Leakage Management

Jihoon Shin, YoonKyung Cha, Sanghyun Son, 2022, SSRN Electronic Journal.

Phosphorus load estimation in the Saginaw River, MI using a Bayesian hierarchical/multilevel model.

Craig A Stow, Carlo DeMarchi, Kenneth H Reckhow, 2010, Water research.

Machine learning-based prediction of harmful algal blooms in water supply reservoirs

Jihoon Shin, YoonKyung Cha, Mingu Kim, 2022, Water Quality Research Journal.

Changes in zooplankton community in response to a shift from lentic to lotic conditions in a regulated river

Dong‐Kyun Kim, Jihoon Shin, YoonKyung Cha, 2023, Ecol. Informatics.

The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers.

Hyuk Lee, Taegu Kang, K. Cho, 2017, Water research.

Machine learning-guided prediction of potential engineering targets for microbial production of lycopene.

Y. Choi, Jihoon Shin, YoonKyung Cha, 2022, Bioresource technology.