NDLI: HICO-Based NIR–Red Models for Estimating Chlorophyll- <inline-formula> <tex-math notation=TeX>$a$</tex-math></inline-formula> Concentration in Productive Coastal Waters

Content Provider	IEEE Xplore Digital Library
Author	Moses, W.J. Gitelson, A.A. Berdnikov, S. Bowles, J.H. Povazhnyi, V. Saprygin, V. Wagner, E.J. Patterson, K.W.
Copyright Year	2004
Abstract	We present here results that demonstrate the potential of near-infrared (NIR)-red models to estimate chlorophyll- a (chl- a) concentration in coastal waters using data from the spaceborne Hyperspectral Imager for the Coastal Ocean (HICO). Since the recent demise of the MEdium Resolution Imaging Spectrometer (MERIS), the use of sensors such as HICO has become critical for coastal ocean color research. Algorithms based on two- and three-band NIR-red models, which were previously used very successfully with MERIS data, were applied to HICO images. The two- and three-band NIR-red algorithms yielded accurate estimates of chl- a concentration, with mean absolute errors that were only 10.92% and 9.58%, respectively, of the total range of chl- a concentrations measured over a period of several months in 2012 and 2013 on the Taganrog Bay in Russia. Given the uncertainties in the radiometric calibration of HICO, the results illustrate the robustness of the NIR-red algorithms and validate the radiometric, spectral, and atmospheric corrections applied to HICO data as they relate to estimating chl- a concentration in productive coastal waters. Inherent limitations due to the characteristics of the sensor and its orbit prohibit HICO from providing anywhere near the level of frequent global coverage as provided by standard multispectral ocean color sensors. Nevertheless, the results demonstrate the utility of HICO as a tool for determining water quality in select coastal areas and the cross-sensor applicability of NIR-red models and provide an indication of what could be achieved with future spaceborne hyperspectral sensors in estimating coastal water quality.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	1111
Ending Page	1115
Page Count	5
File Size	399969
File Format	PDF
ISSN	1545598X
Volume Number	11
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sea measurements Hyperspectral sensors Sensors Atmospheric modeling Radiometry Oceans remote sensing Chlorophyll-$a$ International Space Station (ISS) near-infrared (NIR)–red algorithms productive coastal waters Chlorophyll- $a$ near-infrared (NIR)¿red algorithms
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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