Lee
Zhongping
Lee
Zhongping
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ArticleCapturing coastal water clarity variability with Landsat 8(Elsevier, 2019-05-23) Luis, Kelly M.A. ; Rheuban, Jennie E. ; Kavanaugh, Maria T. ; Glover, David M. ; Wei, Jianwei ; Lee, Zhongping ; Doney, Scott C.Coastal water clarity varies at high temporal and spatial scales due to weather, climate, and human activity along coastlines. Systematic observations are crucial to assessing the impact of water clarity change on aquatic habitats. In this study, Secchi disk depths (ZSD) from Boston Harbor, Buzzards Bay, Cape Cod Bay, and Narragansett Bay water quality monitoring organizations were compiled to validate ZSD derived from Landsat 8 (L8) imagery, and to generate high spatial resolution ZSD maps. From 58 L8 images, acceptable agreement was found between in situ and L8 ZSD in Buzzards Bay (N = 42, RMSE = 0.96 m, MAPD = 28%), Cape Cod Bay (N = 11, RMSE = 0.62 m, MAPD = 10%), and Narragansett Bay (N = 8, RMSE = 0.59 m, MAPD = 26%). This work demonstrates the value of merging in situ ZSD with high spatial resolution remote sensing estimates for improved coastal water quality monitoring.
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ArticleGlobal satellite water classification data products over oceanic, coastal, and inland waters(Elsevier, 2022-09-24) Wei, Jianwei ; Wang, Menghua ; Mikelsons, Karlis ; Jiang, Lide ; Kratzer, Susanne ; Lee, Zhongping ; Moore, Tim ; Sosik, Heidi M. ; Van der Zande, DimitrySatellites have generated extensive data of remote sensing reflectance spectra (Rrs(λ)) covering diverse water classes or types across global waters. Spectral classification of satellite Rrs(λ) data allows for the distinguishing and grouping of waters with characteristic bio-optical/biogeochemical features that may influence the productivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite (VIIRS). We developed and implemented a hyperspectral scheme that accounts for the Rrs(λ) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation result suggests that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data appear to be a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, despite the need for continuous improvement toward perfection.•First mission-long satellite water class products are created from VIIRS satellite.•A reflectance shape-based algorithm was used to resolve the global water classes.•The water classes feature distinct bio-optical and biogeochemical qualities.•Matchup analysis shows the water class products are reliable globally.•Great potentials are shown for aquatic ecology and water quality applications.