Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands

Alexander A. Gilerson, Anatoly A. Gitelson, Jing Zhou, Daniela Gurlin, Wesley Moses, Ioannis Ioannou, Samir A. Ahmed

Research output: Contribution to journalArticlepeer-review

295 Scopus citations


Remote sensing algorithms that use red and NIR bands for the estimation of chlorophyll-a concentration [Chl] can be more effective in inland and coastal waters than algorithms that use blue and green bands. We tested such two-band and three-band red-NIR algorithms using comprehensive synthetic data sets of reflectance spectra and inherent optical properties related to various water parameters and a very consistent in situ data set from several lakes in Nebraska, USA. The two-band algorithms tested with MERIS bands were R rs(708)/Rrs(665) and Rrs(753)/R rs(665). The three-band algorithm with MERIS bands was in the form R3 = [Rrs-1(665) - Rrs-1(708)] × Rrs(753). It is shown that the relationships of both R rs(708)/Rrs(665) and R3 with [Chl] do not depend much on the absorption by CDOM and non-algal particles, or the backscattering properties of water constituents, and can be defined in terms of water absorption coefficients at the respective bands as well as the phytoplankton specific absorption coefficient at 665 nm. The relationship of the latter with [Chl] was established for [Chl] > 1 mg/m3 and then further used to develop algorithms which showed a very good match with field data and should not require regional tuning.

Original languageEnglish (US)
Pages (from-to)24109-24125
Number of pages17
JournalOptics Express
Issue number23
StatePublished - Nov 8 2010
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics


Dive into the research topics of 'Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands'. Together they form a unique fingerprint.

Cite this