한국지구과학회지 제40권 제4호 (p.315-328)

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

키워드 :
chlorophyll-a concentration,algorithm,ocean color,remote sensing,oceanic ecosystem

목차

Abstract
Introduction
Ocean Color Satellites
   Near-Polar Orbiting Ocean Color Satellites
   Geostationary Ocean Color Satellites
Chlorophyll-a ConcentrationRetrieval Algorithms
   Empirical Algorithms
   Band-ratio Algorithms: The band-ratio algorithms
   Band-difference Algorithms
   Hybrid Algorithms
   Semi-Analytical Algorithms
   Algorithms Based on Neural Network
   Algorithms for Geostationary Satellites
Accuracy Assessment andValidation
Prospect and Concluding Remarks
References

초록

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.