Phytoplankton blooms in coastal oceans can be beneficial to coastal fisheries production
and ecosystem function, but can also cause major environmental problems,—yet detailed …

A transmission hyperspectral microscopic imager (THMI) that utilizes machine learning
algorithms for hyperspectral detection of microalgae is presented. The THMI system has …

Cyanobacterial blooms are increasingly becoming major threats to global inland aquatic
ecosystems. Phycocyanin (PC), a pigment unique to cyanobacteria, can provide important …

The optical insensitivity of non-optically active water quality parameters (NAWQPs) presents
a significant challenge for remote sensing-based quantitative monitoring, which is an …

Under the influence of intensive human activities and global climate change, the sources
and compositions of dissolved organic matter (DOM) in the eastern plain lake (EPL) region …

A robust and reliable chlorophyll-a (Chla) concentration algorithm is still lacking for optically
complex waters due to the lack of understanding of the bio-optical process. Machine …

Satellite remote sensing allows large-scale global observations of aquatic ecosystems and
matter fluxes from the source through rivers and lakes to coasts, marginal seas into the open …

Classification of water bodies is an effective means of understanding the optical properties
of aquatic environments. However, most existing water classification systems are mainly …

The color of natural waters–oceanic, coastal, and inland–is determined by the spectral
absorption and scattering properties of dissolved and particulate water constituents. Remote …

Water constituents exhibit diverse optical properties across ocean, coastal, and inland
waters, which alter their remote‐sensing reflectance obtained via satellites. Optical water …