Title :

Mapping of diffuse attenuation coefficient in optically complex waters of amazon floodplain lakes

Author(s) :

Maciel, Daniel Andrade [Auteur]
Barbosa, Claudio Clemente Faria [Auteur]
Novo, Evlyn Márcia Leão de Moraes [Auteur]
Cherukuru, Nagur [Auteur]
Martins, Vitor Souza [Auteur]
Flores Júnior, Rogério [Auteur]
Jorge, Daniel Schaffer [Auteur]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Sander de Carvalho, Lino Augusto [Auteur]
Carlos, Felipe Menino [Auteur]

Journal title :

ISPRS Journal of Photogrammetry and Remote Sensing

Pages :

72-87

Publication date :

2020

English keyword(s) :

K<SUB>d</SUB>
Turbid waters
Diffuse attenuation coefficient
Sentinel-2
Complex waters
Atmospheric correction

HAL domain(s) :

Planète et Univers [physics]

English abstract : [en]

The modeling of underwater light field is essential for the understanding of biogeochemical processes, such as photosynthesis, carbon fluxes, and sediment transports in inland waters. Water-column light attenuation can be ...
Show more >The modeling of underwater light field is essential for the understanding of biogeochemical processes, such as photosynthesis, carbon fluxes, and sediment transports in inland waters. Water-column light attenuation can be quantified by the diffuse attenuation coefficient of the downwelling irradiance (K<SUB>d</SUB>) using semi-analytical algorithms (SAA). However, the accuracy of these algorithms is currently limited in highly turbid environments, such as Amazon Floodplains, due to the SAA parametrization steps. In this study, we assessed an SAA approach for K<SUB>d</SUB> retrieval using a sizeable (n = 239) and diverse dataset (e.g., K<SUB>d</SUB> (490) ranging from almost 0 to up to 30 m<SUP>-1</SUP> with mean values of 5.75 ± 3.94 m<SUP>-1</SUP>) in Amazon freshwater ecosystem. The main framework of this study consists of i) re-parametrization of a quasi-analytical algorithm using regional in-situ inherent optical properties (IOPs) and ii) application and validation of SAA for K<SUB>d</SUB> retrieval using in-situ and Sentinel-2/MSI (n = 49) derived from Remote Sensing Reflectance (R<SUB>rs</SUB>). Overall, the performance of the calibrated SAA was satisfactory for both in-situ and satellite R<SUB>rs.</SUB> The validation results with in-situ data achieved a Mean Absolute Percentage Error (MAPE) lower than 22%, Correlation Coefficient (R) > 0.80, Root Mean Square Error (RMSE) lower than 1.7 m<SUP>-1,</SUP> and bias between 0.73 and 1.34 for simulated visible bands of Sentinel-2/MSI (490, 560 and 660 nm) (VIS). The results using MSI imagery were similar to those of in-situ, with R > 0.9, MAPE < 20%, RMSE < 1.25 m<SUP>-1</SUP>, and bias between 0.98 and 1.10 for VIS bands, which illustrate the viability of this methodology for K<SUB>d</SUB> mapping in Amazon Floodplain Lakes. Therefore, this study demonstrates a successful application of satellite remote sensing data for the spatialization of the K<SUB>d</SUB> in the optically complex waters of Amazon Basin, which is essential for the ecological management of the Amazon Floodplain Lakes.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Laboratoire d'Océanologie et de Géosciences (LOG) - UMR 8187

Source :

Harvested from HAL