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Bio-optical spatio-temporal characterization and development of analytical algorithms for the systematic monitoring of water masses circulating on the floodplain of medium and lower Amazon

Abstract

The Amazon River floodplain ecosystem is relatively weakly known and studied, when compared to Amazonian terrestrial ecosystems. It is estimated that there are more than 10,000 lakes, with area larger than one hectare (1 ha), of which, less than 1% have been studied. Due to floodplain dimensions, its monitoring is only feasible through orbital remote sensing. Studies conducted by our research group, integrating remote sensing data, spectroradiometric data acquired above water and empirical models, have allowed us to characterize patterns of spatio-temporal dynamics of water masses along the hydrological cycle, without, however, describing and analyzing the spectral composition of underwater light field, essential information, for instance, for estimating the primary productivity in aquatic environments. Recently, our research group, supported by FAPESP, CNPq and ANEEL, has acquired a set of underwater profilers that enabled biotic characterization of the water column and the parameterization of analytical models for mapping water constituents. Biotic analytical models, unlike the empirical ones, have time frame coverage without recalibration, which reduces the need and cost of in situ measurements. It is worth mentioning that the use of those equipment, developed for ocean applications, in highly complex waters such as the Amazon, is an extremely fertile field, since there is a whole line of methods revision and protocols improvement for data correction protocols. This proposal aims at continuing the studies initiated in the context of FAPESP 2011/23594-8 project on biotic characterization and development of a methodology, based on the concepts of forward and inverse modeling for estimation of constituents of water masses that circulate over the Amazon floodplain, using the last generation of orbital sensors (OLI, HICO, Sentinel-2 and 3). (AU)

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Scientific publications (8)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
MACIEL, DANIEL ANDRADE; FARIA BARBOSA, CLAUDIO CLEMENTE; LEAO DE MORAES NOVO, EVLYN MARCIA; CHERUKURU, NAGUR; MARTINS, VITOR SOUZA; FLORES JUNIOR, ROGERIO; JORGE, DANIEL SCHAFFER; SANDER DE CARVALHO, LINO AUGUSTO; CARLOS, FELIPE MENINO. Mapping of diffuse attenuation coefficient in optically complex waters of amazon floodplain lakes. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, v. 170, p. 72-87, . (14/23903-9, 18/12083-1)
FREIRE DA SILVA, EDSON FILISBINO; LEAO DE MORAES NOVO, EVLYN MARCIA; LOBO, FELIPE DE LUCIA; FARIA BARBOSA, CLAUDIO CLEMENTE; CAIRO, CAROLLINE TRESSMANN; NOERNBERG, MAURICIO ALMEIDA; DA SILVA ROTTA, LUIZ HENRIQUE. A machine learning approach for monitoring Brazilian optical water types using Sentinel-2 MSI. REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, v. 23, . (12/19821-1, 13/09045-7, 14/23903-9, 08/56252-0)
MACIEL, DANIEL ANDRADE; FARIA BARBOSA, CLAUDIO CLEMENTE; LEAO DE MORAES NOVO, EVLYN MARCIA; FLORES JUNIOR, ROGERIO; BEGLIOMINI, FELIPE NINCAO. Water clarity in Brazilian water assessed using Sentinel-2 and machine learning methods. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, v. 182, p. 134-152, . (19/15984-2, 11/19523-8, 11/23594-8, 03/06999-8, 08/56252-0, 12/19821-1, 18/12083-1, 13/09045-7, 14/23903-9)
JORGE, DANIEL S. F.; LOISEL, HUBERT; JAMET, CEDRIC; DESSAILLY, DAVID; DEMARIA, JULIEN; BRICAUD, ANNICK; MARITORENA, STEPHANE; ZHANG, XIAODONG; ANTOINE, DAVID; KUTSER, TIIT; et al. A three-step semi analytical algorithm (3SAA) for estimating inherent optical properties over oceanic, coastal, and inland waters from remote sensing reflectance. REMOTE SENSING OF ENVIRONMENT, v. 263, . (14/23903-9)
JORGE, DANIEL S. F.; BARBOSA, CLAUDIO C. F.; DE CARVALHO, LINO A. S.; AFFONSO, ADRIANA G.; LOBO, FELIPE DE L.; NOVO, EVLYN M. L. DE M.. SNR (Signal-To-Noise Ratio) Impact on Water Constituent Retrieval from Simulated Images of Optically Complex Amazon Lakes. REMOTE SENSING, v. 9, n. 7, . (14/23903-9)
MARTINS, VITOR SOUZA; FARIA BARBOSA, CLAUDIO CLEMENTE; SANDER DE CARVALHO, LINO AUGUSTO; FERREIRA JORGE, DANIEL SCHAFFER; LOBO, FELIPE DE LUCIA; LEAO DE MORAES NOVO, EVLYN MARCIA. Assessment of Atmospheric Correction Methods for Sentinel-2 MSI Images Applied to Amazon Floodplain Lakes. REMOTE SENSING, v. 9, n. 4, . (14/23903-9)
PAHLEVAN, NIMA; MANGIN, ANTOINE; BALASUBRAMANIAN, SUNDARABALAN V.; SMITH, BRANDON; ALIKAS, KRISTA; ARAI, KOHEI; BARBOSA, CLAUDIO; BELANGER, SIMON; BINDING, CAREN; BRESCIANI, MARIANO; et al. CIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal water. REMOTE SENSING OF ENVIRONMENT, v. 258, . (14/23903-9)
DA SILVA, EDSON FILISBINO FREIRE; NOVO, EVLYN MARCIA LEAO DE MORAES; LOBO, FELIPE DE LUCIA; BARBOSA, CLAUDIO CLEMENTE FARIA; NOERNBERG, MAURICIO ALMEIDA; ROTTA, LUIZ HENRIQUE DA SILVA; CAIRO, CAROLLINE TRESSMANN; MACIEL, DANIEL ANDRADE; FLORES JUNIOR, ROGERIO. Optical water types found in Brazilian waters. LIMNOLOGY, v. 22, n. 1, . (13/09045-7, 14/23903-9, 12/19821-1, 08/56252-0)

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