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

• Grant number: 14/23903-9
• Support type: Regular Research Grants
• Duration: June 01, 2015 - November 30, 2017
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Cláudio Clemente Faria Barbosa
• Grantee: Cláudio Clemente Faria Barbosa
• Home Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). São José dos Campos , SP, Brazil

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)

Scientific publications

(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)

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 JUL 2017. Web of Science Citations: 4.

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 APR 2017. Web of Science Citations: 35.