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

Authors

Alexander A. Gilerson, The City College of the City University of New YorkFollow
Anatoly Gitelson, University of Nebraska-LincolnFollow
Jing Zhou, The City College of the City University of New York
Daniela Gurlin, University of Nebraska-LincolnFollow
Wesley Moses, University of Nebraska-Lincoln
Ioannis Ioannou, The City College of the City University of New York
Samir A. Ahmed, The City College of the City University of New York

ORCID IDs

Anatoly Gitelson

Date of this Version

2010

Comments

©2010 Optical Society of America

Abstract

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)/R_rs(665) and R_rs(753)/R_rs(665). The three-band algorithm with MERIS bands was in the form R3 = [R_rs⁻¹(665) − R_rs⁻¹(708)] × R_rs(753). It is shown that the relationships of both R_rs(708)/R_rs(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.