Remote estimation of chl-a concentration in turbid productive waters - Return to a simple two-band NIR-red model?

Daniela Gurlin, Anatoly A. Gitelson, Wesley J. Moses

Research output: Contribution to journalArticle

118 Scopus citations


Today the water quality of many inland and coastal waters is compromised by cultural eutrophication in consequence of increased human agricultural and industrial activities. Remote sensing is widely applied to monitor the trophic state of these waters. This study investigates the performance of near infrared-red models for the remote estimation of chlorophyll-a concentrations in turbid productive waters and evaluates several near infrared-red models developed within the last 34years. Three models were calibrated for a dataset with chlorophyll-a concentrations from 0 to 100mgm-3 and validated for independent and statistically different datasets with chlorophyll-a concentrations from 0 to 100mgm-3 and 0 to 25mgm-3 for the spectral bands of the MEdium Resolution Imaging Spectrometer (MERIS) and MODerate resolution Imaging Spectroradiometer (MODIS). The MERIS two-band model estimated chlorophyll-a concentrations slightly more accurately than the more complex models, with mean absolute errors of 2.3mgm-3 for chlorophyll-a concentrations from 0 to 100mgm-3 and 1.2mgm-3 for chlorophyll-a concentrations from 0 to 25mgm-3. Comparable results from several near infrared-red models with different levels of complexity, calibrated for inland and coastal waters around the world, indicate a high potential for the development of a simple universally applicable near infrared-red algorithm.

Original languageEnglish (US)
Pages (from-to)3479-3490
Number of pages12
JournalRemote Sensing of Environment
Issue number12
StatePublished - Dec 15 2011



  • Chl-a
  • Estimation
  • Remote
  • Water

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

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