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

Title
Overview of Chlorophyll-a Concentration Retrieval Algorithms from Multi-Satellite Data
Author(s)
박지은; 박경애; 박영제; 한희정
KIOST Author(s)
Park, Young Je(박영제)
Publication Year
2019-08
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.
ISSN
1225-6692
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/552
Bibliographic Citation
한국지구과학회지, v.40, no.4, pp.315 - 328, 2019
Publisher
한국지구과학회
Keywords
chlorophyll-a concentration; algorithm; ocean color; remote sensing; oceanic ecosystem
Type
Article
Language
English
Publisher
한국지구과학회
Related Researcher
Research Interests

Ocean Color Remote Sensing,Satellite Applications,Ocean color Algorithm,해양원격탐사,위성활용,해색 알고리즘

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