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 journalArticle

92 Citations (Scopus)

Abstract

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
Volume46
Issue number4
DOIs
StatePublished - Mar 15 2012

Fingerprint

atmospheric correction
Chlorophyll
chlorophyll a
near infrared
Infrared radiation
Spectrometers
spectrometer
Water
reflectance
water
airborne sensor
Imaging techniques
Surface waters
Mean square error
data acquisition
Spatial distribution
Data acquisition
spatial distribution
surface water
Sensors

Keywords

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

ASJC Scopus subject areas

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

Cite this

Moses, W. J., Gitelson, A. A., Perk, R. L., Gurlin, D., Rundquist, D. C., Leavitt, B. C., ... Brakhage, P. (2012). Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data. Water Research, 46(4), 993-1004. https://doi.org/10.1016/j.watres.2011.11.068

Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data. / Moses, Wesley J.; Gitelson, Anatoly A.; Perk, Richard L.; Gurlin, Daniela; Rundquist, Donald C.; Leavitt, Bryan C.; Barrow, Tadd M.; Brakhage, Paul.

In: Water Research, Vol. 46, No. 4, 15.03.2012, p. 993-1004.

Research output: Contribution to journalArticle

Moses, WJ, Gitelson, AA, Perk, RL, Gurlin, D, Rundquist, DC, Leavitt, BC, Barrow, TM & Brakhage, P 2012, 'Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data', Water Research, vol. 46, no. 4, pp. 993-1004. https://doi.org/10.1016/j.watres.2011.11.068
Moses, Wesley J. ; Gitelson, Anatoly A. ; Perk, Richard L. ; Gurlin, Daniela ; Rundquist, Donald C. ; Leavitt, Bryan C. ; Barrow, Tadd M. ; Brakhage, Paul. / Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data. In: Water Research. 2012 ; Vol. 46, No. 4. pp. 993-1004.
@article{bf85d01771984a4bb44868ec1b772cd1,
title = "Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data",
abstract = "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.",
keywords = "AISA, Atmospheric correction, Chlorophyll-a, FLAASH, Near infra-red, QUAC, Remote sensing",
author = "Moses, {Wesley J.} and Gitelson, {Anatoly A.} and Perk, {Richard L.} and Daniela Gurlin and Rundquist, {Donald C.} and Leavitt, {Bryan C.} and Barrow, {Tadd M.} and Paul Brakhage",
year = "2012",
month = "3",
day = "15",
doi = "10.1016/j.watres.2011.11.068",
language = "English (US)",
volume = "46",
pages = "993--1004",
journal = "Water Research",
issn = "0043-1354",
publisher = "Elsevier Limited",
number = "4",

}

TY - JOUR

T1 - Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data

AU - Moses, Wesley J.

AU - Gitelson, Anatoly A.

AU - Perk, Richard L.

AU - Gurlin, Daniela

AU - Rundquist, Donald C.

AU - Leavitt, Bryan C.

AU - Barrow, Tadd M.

AU - Brakhage, Paul

PY - 2012/3/15

Y1 - 2012/3/15

N2 - 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.

AB - 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.

KW - AISA

KW - Atmospheric correction

KW - Chlorophyll-a

KW - FLAASH

KW - Near infra-red

KW - QUAC

KW - Remote sensing

UR - http://www.scopus.com/inward/record.url?scp=84856087910&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856087910&partnerID=8YFLogxK

U2 - 10.1016/j.watres.2011.11.068

DO - 10.1016/j.watres.2011.11.068

M3 - Article

C2 - 22209281

AN - SCOPUS:84856087910

VL - 46

SP - 993

EP - 1004

JO - Water Research

JF - Water Research

SN - 0043-1354

IS - 4

ER -