Literature DB >> 22707149

An improved algorithm for retrieving chlorophyll-a from the Yellow River Estuary using MODIS imagery.

Jun Chen1, Wenting Quan.   

Abstract

In this study, an improved Moderate-Resolution Imaging Spectroradiometer (MODIS) ocean chlorophyll-a (chla) 3 model (IOC3M) algorithm was developed as a substitute for the MODIS global chla concentration estimation algorithm, OC3M, to estimate chla concentrations in waters with high suspended sediment concentrations, such as the Yellow River Estuary, China. The IOC3M algorithm uses [Formula: see text] to substitute for switching the two-band ratio of max [R (rs) (443 nm), R (rs) (488 nm)]/R (rs) (551 nm) of the OC3M algorithm. In the IOC3M algorithm, the absorption coefficient of chla can be isolated as long as reasonable bands are selected. The performance of IOC3M and OC3M was calibrated and validated using a bio-optical data set composed of spectral upwelling radiance measurements and chla concentrations collected during three independent cruises in the Yellow River Estuary in September of 2009. It was found that the optimal bands of the IOC3M algorithm were λ(1) = 443 nm, λ(2) = 748 nm, λ(3) = 551 nm, and λ(4) = 870 nm. By comparison, the IOC3M algorithm produces superior performance to the OC3M algorithm. Using the IOC3M algorithm in estimating chla concentrations from the Yellow River Estuary decreases 1.03 mg/m(3) uncertainty from the OC3M algorithm. Additionally, the chla concentration estimated from MODIS data reveals that more than 90 % of the water in the Yellow River Estuary has a chla concentration lower than 5.0 mg/m(3). The averaged chla concentration is close to the in situ measurements. Although the case study presented herein is unique, the modeling procedures employed by the IOC3M algorithm can be useful in remote sensing to estimate the chla concentrations of similar aquatic environments.

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Year:  2012        PMID: 22707149     DOI: 10.1007/s10661-012-2705-y

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  3 in total

1.  [Study on quantitative model for suspended sediment concentration in Taihu Lake].

Authors:  Jun Chen; Guan-hua Zhou; Zhen-he Wen; Jin-Feng Ma; Xu Zhang; Dan-qing Peng; Song-lin Yang
Journal:  Guang Pu Xue Yu Guang Pu Fen Xi       Date:  2010-01       Impact factor: 0.589

2.  Model for the interpretation of hyperspectral remote-sensing reflectance.

Authors:  Z Lee; K L Carder; S K Hawes; R G Steward; T G Peacock; C O Davis
Journal:  Appl Opt       Date:  1994-08-20       Impact factor: 1.980

3.  Optical Constants of Water in the 200-nm to 200-microm Wavelength Region.

Authors:  G M Hale; M R Querry
Journal:  Appl Opt       Date:  1973-03-01       Impact factor: 1.980

  3 in total
  3 in total

1.  Noise tolerance of algorithms for estimating chlorophyll a concentration in turbid waters.

Authors:  Jun Chen
Journal:  Environ Monit Assess       Date:  2013-12-18       Impact factor: 2.513

2.  A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.

Authors:  Jun Chen; Yuanli Zhu; Yongsheng Wu; Tingwei Cui; Joji Ishizaka; Yongtao Ju
Journal:  PLoS One       Date:  2015-06-17       Impact factor: 3.240

3.  A database of global coastal conditions.

Authors:  Mariana Castaneda-Guzman; Gabriel Mantilla-Saltos; Kris A Murray; Robert Settlage; Luis E Escobar
Journal:  Sci Data       Date:  2021-11-26       Impact factor: 6.444

  3 in total

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