Spectral calibration of CBERS 2B multispectral satellite images to assess suspended sediment concentration.

Aquino da Silva, Andre Giskard, Amaro, Venerando E., Stattegger, Karl, Schwarzer, Klaus, Vital, Helenice and Heise, Bjoern (2015) Spectral calibration of CBERS 2B multispectral satellite images to assess suspended sediment concentration. Isprs Journal of Photogrammetry and Remote Sensing, 104 . pp. 53-62.

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Abstract

In this study, 11 CBERS 2B and I LANDSAT 5-TM satellite images from 2008 were used to estimate the suspended sediment concentration and the total suspended sediment load of the Parnaiba River (NE-Brazil). The calculation of the amount of sediment in suspension was performed using Tassan's algorithm, which was originally developed for use on LANDSAT 5-TM images; therefore, the CBERS 2B images were spectrally calibrated using LANDSAT 5-TM at-satellite radiance. The application of atmospheric correction to the images was necessary to account for meteorological influence on the spectral data prior to the calculation of the suspended sediment concentration. Three types of dark object subtraction and the 6S model were tested, and one type of dark object subtraction was chosen as the appropriate atmospheric correction method. Tassan's algorithm requires in situ calibration; therefore, suspended sediment concentrations measured in water samples from the Parnaiba River mouth were used to calibrate the algorithm. The results revealed that the variation of suspended sediment concentration was strongly influenced by seasonal precipitation. In 2008, the suspended sediment released by the Parnaiba River was approximately 2.54 x 10(6) tons. The discharged sediment formed a sediment plume on the inner continental shelf. The extension of the plume depended on the specific hydrodynamic conditions that were forced mainly by the strength of river runoff, longshore currents, tidal currents and amplitudes, and wind and wave climate. (c) 2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

Document Type: Article
Additional Information: Times Cited: 0
Research affiliation: OceanRep > The Future Ocean - Cluster of Excellence > FO-R09
Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
OceanRep > The Future Ocean - Cluster of Excellence > FO-R06
Kiel University
Refereed: Yes
ISSN: 0924-2716
Projects: Future Ocean
Date Deposited: 20 Oct 2016 11:04
Last Modified: 19 Dec 2017 12:44
URI: http://oceanrep.geomar.de/id/eprint/32396

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