[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5467/JKESS.2019.40.4.315

Overview of Chlorophyll-a Concentration Retrieval Algorithms from Multi-Satellite Data

Park, Ji-Eun (Department of Science Education, Seoul National University)
Park, Kyung-Ae (Department of Earth Science Education/Research Institute of Oceanography, Seoul National University)
Park, Young-Je (Korea Ocean Satellite Center, Korea Institute of Ocean Science and Technology)
Han, Hee-Jeong (Korea Ocean Satellite Center, Korea Institute of Ocean Science and Technology)

Publication Information

Journal of the Korean earth science society / v.40, no.4, 2019 , pp. 315-328 More about this Journal

Abstract

Since the Coastal Zone Color Scanner (CZCS)/Nimbus-7 was launched in 1978, a variety of studies have been conducted to retrieve ocean color variables from multi-satellites. Several algorithms and formulations have been suggested for estimating ocean color variables based on multi band data at different wavelengths. Chlorophyll-a (chl-a) concentration is one of the most important variables to understand low-level ecosystem in the ocean. To retrieve chl-a concentrations from the satellite observations, an appropriate algorithm depending on water properties is required for each satellite sensor. Most operational empirical algorithms in the global ocean have been developed based on the band-ratio approach, which has the disadvantage of being more adapted to the open ocean than to coastal areas. Alternative algorithms, including the semi-analytical approach, may complement the limits of band-ratio algorithms. As more sensors are planned by various space agencies to monitor the ocean surface, it is expected that continuous monitoring of oceanic ecosystems and environments should be conducted to contribute to the understanding of the oceanic biosphere and the impact of climate change. This study presents an overview of the past and present algorithms for the estimation of chl-a concentration based on multi-satellite data and also presents the prospects for ongoing and upcoming ocean color satellites.

Keywords

chlorophyll-a concentration; algorithm; ocean color; remote sensing; oceanic ecosystem;

Citations & Related Records

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