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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Estimating Water pH Using Cloud-Based Landsat Images for a New Classification of the Nhecolandia Lakes (Brazilian Pantanal)

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Autor(es):
Pereira, Osvaldo J. R. [1] ; Merino, Eder R. [1] ; Montes, Celia R. [2] ; Barbiero, Laurent [3] ; Rezende-Filho, Ary T. [4] ; Lucas, Yves [5] ; Melfi, Adolpho J. [1]
Número total de Autores: 7
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, NUPEGEL, IEE, BR-05508010 Sao Paulo - Brazil
[2] Univ Sao Paulo, NUPEGEL, CENA, BR-13400970 Piracicaba - Brazil
[3] UPS, OMP Toulouse, CNRS, GET, IRD, F-31400 Toulouse - France
[4] Univ Fed Mato Grosso do Sul, FAENG, BR-79079900 Campo Grande, MS - Brazil
[5] Aix Marseille Univ, Univ Toulon, CNRS, IM2NP, F-83041 Toulon 9 - France
Número total de Afiliações: 5
Tipo de documento: Artigo Científico
Fonte: REMOTE SENSING; v. 12, n. 7 APR 2020.
Citações Web of Science: 0
Resumo

The Nhecolandia region, located in the southern portion of the Pantanal wetland area, is a unique lacustrine system where tens of thousands of saline-alkaline and freshwater lakes and ponds coexist in close proximity. These lakes are suspected to be a strong source of greenhouse gases (GHGs) to the atmosphere, the water pH being one of the key factors in controlling the biogeochemical functioning and, consequently, production and emission of GHGs in these lakes. Here, we present a new field-validated classification of the Nhecolandia lakes using water pH values estimated based on a cloud-based Landsat (5 TM, 7 ETM+, and 8 OLI) 2002-2017 time-series in the Google Earth Engine platform. Calibrated top-of-atmosphere (TOA) reflectance collections with the Fmask method were used to ensure the usage of only cloud-free pixels, resulting in a dataset of 2081 scenes. The pH values were predicted by applying linear multiple regression and symbolic regression based on genetic programming (GP). The regression model presented an R-2 value of 0.81 and pH values ranging from 4.69 to 11.64. A lake mask was used to extract the predicted pH band that was then classified into three lake classes according to their pH values: Freshwater (pH < 8), oligosaline (pH 8-8.9), and saline (<greater than or equal to>9). Nearly 12,150 lakes were mapped with those with saline waters accounting for 7.25%. Finally, a trend surface map was created using the ALOS PRISM Digital Surface Model (DSM) to analyze the correlation between landscape features (topography, connection with the regional drainage system, size, and shape of lakes) and types of lakes. The analysis was in consonance with previous studies that pointed out that saline lakes tend to occur in lower positions compared to freshwater lakes. The results open a relevant perspective for the transfer of locally acquired experimental data to the regional balances of the Nhecolandia lakes. (AU)

Processo FAPESP: 17/26318-8 - Mapeamento das lagoas salinas e cristalinas do Pantanal de Nhecolândia por meio de sensoriamento remoto ótico e interferométrico
Beneficiário:Eder Renato Merino
Linha de fomento: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 16/14227-5 - Mudanças climáticas e impactos ambientais em áreas alagadas (wetlands) do Pantanal (Brasil): quantificação, fatores de controle e previsão em longo prazo
Beneficiário:Adolpho José Melfi
Linha de fomento: Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - Temático