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

Authors :
Aquino da Silva, André Giskard
Amaro, Venerando E.
Stattegger, Karl
Schwarzer, Klaus
Vital, Helenice
Heise, Björn
Source :
ISPRS Journal of Photogrammetry & Remote Sensing. Jun2015, Vol. 104, p53-62. 10p.
Publication Year :
2015

Abstract

In this study, 11 CBERS 2B and 1 LANDSAT 5-TM satellite images from 2008 were used to estimate the suspended sediment concentration and the total suspended sediment load of the Parnaíba 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 Parnaíba 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 Parnaíba River was approximately 2.54 × 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09242716
Volume :
104
Database :
Academic Search Index
Journal :
ISPRS Journal of Photogrammetry & Remote Sensing
Publication Type :
Academic Journal
Accession number :
102312620
Full Text :
https://doi.org/10.1016/j.isprsjprs.2015.02.011