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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.)

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

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Author(s):
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]
Total Authors: 7
Affiliation:
[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
Total Affiliations: 5
Document type: Journal article
Source: REMOTE SENSING; v. 12, n. 7 APR 2020.
Web of Science Citations: 0
Abstract

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)

FAPESP's process: 17/26318-8 - Pantanal da Nhecolândia salt and crystalline lagoons mapping by means of optical and interferometric remote sensing
Grantee:Eder Renato Merino
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 16/14227-5 - Climatic changes and environmental impacts in wetlands of Pantanal region (Brazil): quantification, control factors and long term temporal modeling
Grantee:ADOLPHO JOSÉ MELFI
Support type: Research Program on Global Climate Change - Thematic Grants