%0 Journal Article
%4 sid.inpe.br/plutao/2020/06.16.00.01.31
%2 sid.inpe.br/plutao/2020/06.16.00.01.32
%@doi 10.3390/rs12010040
%@issn 2072-4292
%F lattes: 1596449770636962 2 CairoBLNCMFSC:2020:HyChAl
%T Hybrid chlorophyll-a algorithm for assessing trophic states of a tropical brazilian reservoir based on MSI/Sentinel-2 data
%D 2020
%9 journal article
%A Cairo, Carolline Tressmann,
%A Barbosa, Cláudio Clemente Faria,
%A Lobo, Felipe de Lucia,
%A Novo, Evlyn Márcia Leão de Moraes,
%A Carlos, Felipe Menino,
%A Maciel, Daniel Andrade,
%A Flores Junior, Rogério,
%A Silva, Edson Filisbino Freire da,
%A Curtarelli, Victor Pedroso,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress carolline.cairo@inpe.br
%@electronicmailaddress claudio.barbosa@inpe.br
%@electronicmailaddress felipellobo@gmail.com
%@electronicmailaddress evlyn.novo@inpe.br
%@electronicmailaddress felipe.carlos@fatec.sp.gov.br
%@electronicmailaddress damaciel.maciel@hotmail.com
%@electronicmailaddress rogerio.floresjr@gmail.com
%@electronicmailaddress edson.freirefs@gmail.com
%@electronicmailaddress victor.curtarelli@gmail.com
%B Remote Sensing
%V 12
%N 1
%P e12010040
%K Hybrid Chlorophyll-a Algorithm, monitoramento da qualidade da água, clorofila-a.
%X Using remote sensing for monitoring trophic states of inland waters relies on the calibration of chlorophyll-a (chl-a) bio-optical algorithms. One of the main limiting factors of calibrating those algorithms is that they cannot accurately cope with the wide chl-a concentration ranges in optically complex waters subject to different trophic states. Thus, this study proposes an optical hybrid chl-a algorithm (OHA), which is a combined framework of algorithms for specific chl-a concentration ranges. The study area is Ibitinga Reservoir characterized by high spatiotemporal variability of chl-a concentrations (31000 mg/m3 ). We took the following steps to address this issue: (1) we defined optical classes of specific chl-a concentration ranges using Spectral Angle Mapper (SAM); (2) we calibrated/validated chl-a bio-optical algorithms for each trophic class using simulated Sentinel-2 MSI (Multispectral Instrument) bands; (3) and we applied a decision tree classifier in MSI/Sentinel-2 image to detect the optical classes and to switch to the suitable algorithm for the given class. The results showed that three optical classes represent different ranges of chl-a concentration: class 1 varies 2.8922.83 mg/m3 , class 2 varies 19.5187.63 mg/m3 , and class 3 varies 75.89938.97 mg/m3 . The best algorithms for trophic classes 1, 2, and 3 are the 3-band (R2 = 0.78; MAPE - Mean Absolute Percentage Error = 34.36%), slope (R2 = 0.93; MAPE = 23.35%), and 2-band (R2 = 0.98; MAPE = 20.12%), respectively. The decision tree classifier showed an accuracy of 95% for detecting SAMs optical trophic classes. The overall performance of OHA was satisfactory (R2 = 0.98; MAPE = 26.33%) using in situ data but reduced in the Sentinel-2 image (R2 = 0.42; MAPE = 28.32%) due to the temporal gap between matchups and the variability in reservoir hydrodynamics. In summary, OHA proved to be a viable method for estimating chl-a concentration in Ibitinga Reservoir and the extension of this framework allowed a more precise chl-a estimate in eutrophic inland waters.
%@language en
%3 cairo_remote.pdf