| Offshore and nearshore chlorophyll increases induced by typhoon winds and subsequent terrestrial rainwater runoff GM Zheng, DL Tang Marine ecology progress series 333, 61-74, 2007 | 289 | 2007 |
| Correction of pathlength amplification in the filter-pad technique for measurements of particulate absorption coefficient in the visible spectral region D Stramski, RA Reynolds, S Kaczmarek, J Uitz, G Zheng Applied Optics 54 (22), 6763-6782, 2015 | 132 | 2015 |
| Uncertainties and applications of satellite-derived coastal water quality products G Zheng, PM DiGiacomo Progress in oceanography 159, 45-72, 2017 | 120 | 2017 |
| Remote sensing of chlorophyll-a in coastal waters based on the light absorption coefficient of phytoplankton G Zheng, PM DiGiacomo Remote Sensing of Environment 201, 331-341, 2017 | 74 | 2017 |
| Evaluation of the Quasi-Analytical Algorithm for estimating the inherent optical properties of seawater from ocean color: Comparison of Arctic and lower-latitude waters G Zheng, D Stramski, RA Reynolds Remote sensing of environment 155, 194-209, 2014 | 59 | 2014 |
| A model based on stacked‐constraints approach for partitioning the light absorption coefficient of seawater into phytoplankton and non‐phytoplankton components G Zheng, D Stramski Journal of Geophysical Research: Oceans 118 (4), 2155-2174, 2013 | 43 | 2013 |
| A model for partitioning the light absorption coefficient of natural waters into phytoplankton, nonalgal particulate, and colored dissolved organic components: A case study for … G Zheng, D Stramski, PM DiGiacomo Journal of Geophysical Research: Oceans 120 (4), 2601-2621, 2015 | 38 | 2015 |
| A model for partitioning the light absorption coefficient of suspended marine particles into phytoplankton and nonalgal components G Zheng, D Stramski Journal of Geophysical Research: Oceans 118 (6), 2977-2991, 2013 | 23 | 2013 |
| Linkages between phytoplankton and bottom oxygen in the Chesapeake Bay G Zheng, PM DiGiacomo Journal of Geophysical Research: Oceans 125 (2), e2019JC015650, 2020 | 22 | 2020 |
| Requirements for Different Applications of Ocean Colour Data IOCC Group Uncertainties in Ocean Colour Remote Sensing 18, 113, 2019 | 22* | 2019 |
| Evolution of sediment plumes in the Chesapeake Bay and implications of climate variability G Zheng, PM DiGiacomo, SS Kaushal, MA Yuen-Murphy, S Duan Environmental Science & Technology 49 (11), 6494-6503, 2015 | 20 | 2015 |
| Detecting phytoplankton diatom fraction based on the spectral shape of satellite‐derived algal light absorption coefficient G Zheng, PM DiGiacomo Limnology and Oceanography 63 (S1), S85-S98, 2018 | 18 | 2018 |
| Chlorophyll-a in Chesapeake Bay based on VIIRS satellite data: Spatiotemporal variability and prediction with machine learning X Yu, J Shen, G Zheng, J Du Ocean Modelling 180, 102119, 2022 | 9 | 2022 |
| Retrieval of oceanic chlorophyll concentration from GOES-R advanced baseline imager using deep learning G Zheng, CW Brown, PM DiGiacomo Remote Sensing of Environment 295, 113660, 2023 | 5 | 2023 |
| A simple water clarity-turbidity index for the Great Lakes G Zheng, PM DiGiacomo Journal of Great Lakes Research 48 (3), 686-694, 2022 | 5 | 2022 |
| Report on ioccg workshop: phytoplankton composition from space: towards a validation strategy for satellite algorithms A Bracher, N Hardman-Mountford, T Hirata, S Bernard, E Boss, R Brewin, ... (The International Ocean-Colour Coordinating Group (IOCCG) 25-26 October …, 2015 | 5 | 2015 |
| Satellite observations estimating the effects of river discharge and wind‐driven upwelling on phytoplankton dynamics in the Chesapeake Bay NP Nezlin, JM Testa, G Zheng, PM DiGiacomo Integrated Environmental Assessment and Management 18 (4), 921-938, 2022 | 3 | 2022 |
| Hypoxia forecasting for Chesapeake Bay using artificial intelligence G Zheng, S Schollaert Uz, P St-Laurent, MAM Friedrichs, A Mehta, ... Artificial Intelligence for the Earth Systems 3 (3), 230054, 2024 | | 2024 |
