| Drone-based imaging to assess the microbial water quality in an irrigation pond: A pilot study BJ Morgan, MD Stocker, J Valdes-Abellan, MS Kim, Y Pachepsky Science of the total environment 716, 135757, 2020 | 34 | 2020 |
| Persistent Patterns of E. coli Concentrations in Two Irrigation Ponds from 3 Years of Monitoring MD Stocker, YA Pachepsky, J Smith, B Morgan, RL Hill, MS Kim Water, Air, & Soil Pollution 232, 1-15, 2021 | 13 | 2021 |
| Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data SM Hong, BJ Morgan, MD Stocker, JE Smith, MS Kim, KH Cho, ... Water research 260, 121861, 2024 | 11 | 2024 |
| Effect of shallow subsurface flow pathway networks on corn yield spatial variation under different weather and nutrient management BJ Morgan, CST Daughtry, AL Russ, WP Dulaney, TJ Gish, YA Pachepsky International Agrophysics 33 (2), 2019 | 7 | 2019 |
| Accuracy and reliability of predictions of E. coli concentrations in water of irrigation ponds from drone-based imagery as affected by parameters of the random forest algorithm BJ Morgan, MD Stocker, YA Pachepsky, MS Kim Sensing for Agriculture and Food Quality and Safety XIII 11754, 44-54, 2021 | 2 | 2021 |
| Spatial patterns of water quality and remote sensing indices from UAV-based multispectral imagery across an irrigation pond S Hong, BJ Morgan, MD Stocker, J Smith, YA Pachepsky Heliyon, 2025 | | 2025 |
| Stable spatial patterns of concentrations of antibiotic resistant bacteria in irrigation water MD Stocker, JE Smith, BJ Morgan, MJ Prinn, Y Pachepsky Environmental Systems Research 13 (1), 56, 2024 | | 2024 |
| Estimating Escherichia coli levels using drone-based RGB imagery and machine learning techniques S Hong, B Morgan, M Stocker, J Smith, M Kim, KH Cho, Y Pachepsky EGU General Assembly Conference Abstracts, 6648, 2024 | | 2024 |
| Evaluation of Machine Learning Algorithms for Predicting E. coli Concentrations using Drone-based RGB Images and Water Quality Data with Imbalanced Dataset S Hong, YA Pachepsky, B Morgan, M Stocker, MS Kim AGU Fall Meeting Abstracts 2023 (1371), H51T-1371, 2023 | | 2023 |
| Long-term Research of Microbial Quality of Irrigation Waters in Maryland and Pennsylvania Y Pachepsky, M Stocker, J Smith, B Morgan, R Hill, K Staver, M Harriger, ... AGU Fall Meeting Abstracts 2021, GH15E-0630, 2021 | | 2021 |
| Comparison of Machine Learning Algorithms for the Prediction of E. coli concentrations in Agricultural Pond Waters M Stocker, RL Hill, J Smith, B Griffith, YA Pachepsky ASA, CSSA, SSSA International Annual Meeting, 2021 | | 2021 |
| Estimating phytoplankton species populations in irrigation ponds from drone-based imagery and in situ water quality sensing and sampling JE Smith, BJ Griffith, MD Stocker, MS Kim, YA Pachepsky EGU General Assembly Conference Abstracts, EGU21-6395, 2021 | | 2021 |
| UAV-based imagery analysis with machine learning to facilitate microbial water quality monitoring of irrigation ponds Y Pachepsky, B Morgan, M Stocker, M Kim EGU General Assembly Conference Abstracts, 22365, 2020 | | 2020 |
| Estimating E. coli concentrations in water using sensor and drone-based imagery data M Stocker, B Morgan, J Valdes-Abellan, YA Pachepsky AGU Fall Meeting 2019, 2019 | | 2019 |
| Estimating E. coli concentrations in water using sensor and drone-based imagery data YA Pachepsky, M Stocker, B Morgan, J Valdes-Abellan AGU Fall Meeting Abstracts 2019, GH41C-1214, 2019 | | 2019 |
| Machine Learning to Determine Lead Water Quality Parameters Influencing E. coli Concentrations in Irrigation Ponds Using Multi-Year Data M Stocker, YA Pachepsky, RL Hill, J Smith, B Morgan, K Sellner ASA, CSSA and SSSA International Annual Meetings (2019), 2019 | | 2019 |
| Drone-based imaging to assess microbial water quality in irrigation ponds: a pilot study (Conference Presentation) B Griffith, Y Pachepsky, M Stocker, J Valdes-Abellan Sensing for Agriculture and Food Quality and Safety XI 11016, 110160D, 2019 | | 2019 |
