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MAO Zhihua,ZHU Qiankun,GONG Fang,PAN Delu.The algorithms of chlorophyll-a concentration for CMODIS[J].Acta Oceanologica Sinica,2007,(5):25-33
The algorithms of chlorophyll-a concentration for CMODIS
The algorithms of chlorophyll-a concentration for CMODIS
投稿时间:2005-04-15  修订日期:2007-02-08
DOI:
中文关键词:  CMODIS  chlorophyll-a concentration  suspended sediment concentration
英文关键词:CMODIS  chlorophyll-a concentration  suspended sediment concentration
基金项目:
作者单位E-mail
MAO Zhihua Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou 310012, China 
maozh@hzcnc.com 
ZHU Qiankun Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou 310012, China 
 
GONG Fang Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China  
PAN Delu Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou 310012, China 
 
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中文摘要:
      The algorithms of extracting chlorophyll-a (Chl-a) concentration have been established for Chinese moderate resolution imaging spectrometer (CMODIS) mounted on Shenzhou-3 spaceship launched on 25 March 2002.The CMODIS is an ocean color sensor with 30 visible channels and 4 infrared channels, much different from other ocean color satellites and needs new algorithms to process data.Three models of Chl-a concentration were established based on Chl-a data retrieved from sea-viewing wide field-of-view sensor (SeaWiFS), with the average relative errors of 26.6%, 24%.0% and 33.5%, respectively.This practical and economic approach can be used for developing the algorithms of Chinese ocean color and temperature sensor (COCTS) on the satellite Haiyang-1 to derive the Chl-a concentration concentration distribution.The applicability of the algorithms was analyzed using some in situ measurements.Suspended sediment is the main factor influencing the accuracy of the spectral ratio algorithms of Chl-a concentration.The algorithms are suitable to using in the regions where suspended sediment concentrations (SSC) are less than 5 g/m3 under the condition of relative error of Chl-a concentration retrieval within 35%.High concentration of suspended sediment leads to the overestimate remote sensing retrieval of concentration of Chl-a, while low-middle SSCs lead to the low Chl-a concentration values using the spectral ratio algorithms.Since the accuracy of Chl-a concentration by the spectral ratio algorithms is limited to waters of Case 2, it is necessary to develop semi-analytical models to improve the performance of satellite ocean color remote sensing in turbid coastal waters.
英文摘要:
      The algorithms of extracting chlorophyll-a (Chl-a) concentration have been established for Chinese moderate resolution imaging spectrometer (CMODIS) mounted on Shenzhou-3 spaceship launched on 25 March 2002.The CMODIS is an ocean color sensor with 30 visible channels and 4 infrared channels, much different from other ocean color satellites and needs new algorithms to process data.Three models of Chl-a concentration were established based on Chl-a data retrieved from sea-viewing wide field-of-view sensor (SeaWiFS), with the average relative errors of 26.6%, 24%.0% and 33.5%, respectively.This practical and economic approach can be used for developing the algorithms of Chinese ocean color and temperature sensor (COCTS) on the satellite Haiyang-1 to derive the Chl-a concentration concentration distribution.The applicability of the algorithms was analyzed using some in situ measurements.Suspended sediment is the main factor influencing the accuracy of the spectral ratio algorithms of Chl-a concentration.The algorithms are suitable to using in the regions where suspended sediment concentrations (SSC) are less than 5 g/m3 under the condition of relative error of Chl-a concentration retrieval within 35%.High concentration of suspended sediment leads to the overestimate remote sensing retrieval of concentration of Chl-a, while low-middle SSCs lead to the low Chl-a concentration values using the spectral ratio algorithms.Since the accuracy of Chl-a concentration by the spectral ratio algorithms is limited to waters of Case 2, it is necessary to develop semi-analytical models to improve the performance of satellite ocean color remote sensing in turbid coastal waters.
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