Ocean color remote sensing

Ocean color remote sensing measures the spectrum of sunlight reflected back from the ocean surface, captured by satellite radiometers, and uses subtle shifts in that color to estimate what is in the water: chlorophyll concentration from phytoplankton, suspended sediment, and dissolved organic matter. Greener water generally signals more phytoplankton; browner water signals more sediment.

Retrieving these estimates requires atmospheric correction, since most of the light a satellite sensor receives comes from the atmosphere rather than the water itself, followed by an algorithm that converts corrected reflectance ratios into a chlorophyll or turbidity value. This differs from sea surface temperature retrieval, which is typically done with infrared or microwave sensors on the same satellite platforms but measures heat rather than visible light, and the two are frequently combined in ocean and climate analysis as part of broader remote sensing.

Ocean color data feeds fisheries management, harmful algal bloom detection, and coastal water quality index monitoring, since chlorophyll concentration is a proxy for primary productivity and nutrient pollution. The main pitfalls are that clouds and sun glint make many scenes unusable, and that coastal and inland waters, with their complex mix of sediment, algae and dissolved matter, need different retrieval algorithms than open ocean; applying an open-ocean algorithm nearshore produces unreliable results.