12 September 2018 Performance of existing QAAs in Secchi disk depth retrieval in phytoplankton and dissolved organic matter dominated inland waters
Thanan Rodrigues, Enner Alcântara, Deepak R. Mishra, Fernanda Watanabe, Nariane Bernardo, Luiz Rotta, Nilton Imai, Ike Astuti
Author Affiliations +
Abstract
A semianalytical model developed to estimate the Secchi disk depth (ZSD) was used in eutrophic-to-hypereutrophic reservoirs (Ibitinga, Ibi, and Barra Bonita, BB) placed in the cascade system of the Tietê River, Brazil. The model was evaluated using the simulated remote sensing reflectance based on the Ocean and Land Color Instrument/Sentinel-3A and the Operational Land Imager/Landsat-8 from both reservoirs. Three quasianalytical algorithm (QAA) versions (QAAv5, QAAM14, and QAAW16) were evaluated to derive the absorption and backscattering coefficients, and then used for ZSD retrieval. For BB, where the chlorophyll-a concentration exceeded 200  mg m  −  3, the model based on QAAv5 showed high uncertainties while the QAAW16, which was originally parameterized for BB showed better performance regarding the ZSD retrieval (mean absolute percentage errors—MAPE of 22%). However, QAAW16 did not perform satisfactorily for Ibi, which is dominated by colored dissolved organic matter (CDOM). For Ibi, QAAv5 provided the best result with MAPE of 34.60%, followed by QAAM14 with 34.65%. QAA-based ZSD models tend to perform poorly in waters with high concentration of chlorophyll-a possibly due to phytoplankton package effect, whereas the same models may require additional parameterization in waters dominated by CDOM. Landsat-8 data showed significant potential for ZSD retrieval in inland waters.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2018/$25.00 © 2018 SPIE
Thanan Rodrigues, Enner Alcântara, Deepak R. Mishra, Fernanda Watanabe, Nariane Bernardo, Luiz Rotta, Nilton Imai, and Ike Astuti "Performance of existing QAAs in Secchi disk depth retrieval in phytoplankton and dissolved organic matter dominated inland waters," Journal of Applied Remote Sensing 12(3), 036017 (12 September 2018). https://doi.org/10.1117/1.JRS.12.036017
Received: 18 April 2018; Accepted: 15 August 2018; Published: 12 September 2018
Lens.org Logo
CITATIONS
Cited by 7 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Scanning probe microscopy

Absorption

Data modeling

Remote sensing

Earth observing sensors

Landsat

Magnesium

Back to Top