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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Analysis of MERIS Reflectance Algorithms for Estimating Chlorophyll-a Concentration in a Brazilian Reservoir

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Author(s):
Augusto-Silva, Petala B. [1] ; Ogashawara, Igor [1] ; Barbosa, Claudio C. F. [2] ; de Carvalho, Lino A. S. [1] ; Jorge, Daniel S. F. [1] ; Fornari, Celso Israel [3] ; Stech, Jose L. [1]
Total Authors: 7
Affiliation:
[1] Natl Inst Space Res, Remote Sensing Div, BR-12227010 Sao Jose Dos Campos, SP - Brazil
[2] Natl Inst Space Res, Image Proc Div, BR-12227010 Sao Jose Dos Campos, SP - Brazil
[3] Natl Inst Space Res, Associate Lab Sensors & Mat, BR-12227010 Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: REMOTE SENSING; v. 6, n. 12, p. 11689-11707, DEC 2014.
Web of Science Citations: 15
Abstract

Chlorophyll-a (chl-a) is a central water quality parameter that has been estimated through remote sensing bio-optical models. This work evaluated the performance of three well established reflectance based bio-optical algorithms to retrieve chl-a from in situ hyperspectral remote sensing reflectance datasets collected during three field campaigns in the Funil reservoir (Rio de Janeiro, Brazil). A Monte Carlo simulation was applied for all the algorithms to achieve the best calibration. The Normalized Difference Chlorophyll Index (NDCI) got the lowest error (17.85%). The in situ hyperspectral dataset was used to simulate the Ocean Land Color Instrument (OLCI) spectral bands by applying its spectral response function. Therefore, we evaluated its applicability to monitor water quality in tropical turbid inland waters using algorithms developed for MEdium Resolution Imaging Spectrometer (MERIS) data. The application of OLCI simulated spectral bands to the algorithms generated results similar to the in situ hyperspectral: an error of 17.64% was found for NDCI. Thus, OLCI data will be suitable for inland water quality monitoring using MERIS reflectance based bio-optical algorithms. (AU)

FAPESP's process: 08/57719-9 - Program on Climate Change - INCT CLIMA
Grantee:Carlos Afonso Nobre
Support type: Research Program on Global Climate Change - Thematic Grants
FAPESP's process: 11/19523-8 - Developing a semi-analytical model to study the chlorophyll-a concentration and the trophic state of tropical hydroelectric reservoirs
Grantee:José Luiz Stech
Support type: Regular Research Grants