Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data

Wesley J. Moses, Anatoly A. Gitelson, Richard L. Perk, Daniela Gurlin, Donald C. Rundquist, Bryan C. Leavitt, Tadd M. Barrow, Paul Brakhage

Research output: Contribution to journalArticlepeer-review

110 Scopus citations


Algorithms based on red and near infra-red (NIR) reflectances measured using field spectrometers have been previously shown to yield accurate estimates of chlorophyll-a concentration in turbid productive waters, irrespective of variations in the bio-optical characteristics of water. The objective of this study was to investigate the performance of NIR-red models when applied to multi-temporal airborne reflectance data acquired by the hyperspectral sensor, Airborne Imaging Spectrometer for Applications (AISA), with non-uniform atmospheric effects across the dates of data acquisition. The results demonstrated the capability of the NIR-red models to capture the spatial distribution of chlorophyll-a in surface waters without the need for atmospheric correction. However, the variable atmospheric effects did affect the accuracy of chlorophyll-a retrieval. Two atmospheric correction procedures, namely, Fast Line-of-sight Atmospheric Adjustment of Spectral Hypercubes (FLAASH) and QUick Atmospheric Correction (QUAC), were applied to AISA data and their results were compared. QUAC produced a robust atmospheric correction, which led to NIR-red algorithms that were able to accurately estimate chlorophyll-a concentration, with a root mean square error of 5.54mgm-3 for chlorophyll-a concentrations in the range 2.27-81.17mgm-3.

Original languageEnglish (US)
Pages (from-to)993-1004
Number of pages12
JournalWater Research
Issue number4
StatePublished - Mar 15 2012


  • AISA
  • Atmospheric correction
  • Chlorophyll-a
  • Near infra-red
  • QUAC
  • Remote sensing

ASJC Scopus subject areas

  • Ecological Modeling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution


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