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

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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 \( {{{\left[ {R_{\text{rs}}^{{ - 1}}\left( {{\lambda_{{1}}}} \right) - {k_1}R_{\text{rs}}^{{ - 1}}\left( {{\lambda_{{2}}}} \right)} \right]}} \left/ {{\left[ {R_{\text{rs}}^{{ - 1}}\left( {{\lambda_{{3}}}} \right) - {k_{{2}}}R_{\text{rs}}^{{ - 1}}\left( {{\lambda_{{4}}}} \right)} \right]}} \right.} \) 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 λ1 = 443 nm, λ2 = 748 nm, λ3 = 551 nm, and λ4 = 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/m3 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/m3. 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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Authors and Affiliations

  1. School of Ocean Sciences, China University of Geosciences, Beijing, 100083, China

    Jun Chen

  2. The Key Laboratory of Marine Hydrocarbon Resources and Environmental Geology, Qingdao Institute of Marine Geology, Qingdao, 266071, China

    Jun Chen

  3. Shanxi Remote Sensing Information Center for Agriculture, Xian, 710000, China

    Wenting Quan

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  1. Jun Chen
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  2. Wenting Quan
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Correspondence to Jun Chen.

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Chen, J., Quan, W. An improved algorithm for retrieving chlorophyll-a from the Yellow River Estuary using MODIS imagery. Environ Monit Assess 185, 2243–2255 (2013). https://doi.org/10.1007/s10661-012-2705-y

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  • DOI: https://doi.org/10.1007/s10661-012-2705-y

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