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RSS FeedsRemote Sensing, Vol. 8, Pages 556: A Semi-Analytic Model for Estimating Total Suspended Sediment Concentration in Turbid Coastal Waters of Northern Western Australia Using MODIS-Aqua 250 m Data (Remote Sensing)

 
 

30 june 2016 11:50:59

 
Remote Sensing, Vol. 8, Pages 556: A Semi-Analytic Model for Estimating Total Suspended Sediment Concentration in Turbid Coastal Waters of Northern Western Australia Using MODIS-Aqua 250 m Data (Remote Sensing)
 


Knowledge of the concentration of total suspended sediment (TSS) in coastal waters is of significance to marine environmental monitoring agencies to determine the turbidity of water that serve as a proxy to estimate the availability of light at depth for benthic habitats. TSS models applicable to data collected by satellite sensors can be used to determine TSS with reasonable accuracy and of adequate spatial and temporal resolution to be of use for coastal water quality monitoring. Thus, a study is presented here where we develop a semi-analytic sediment model (SASM) applicable to any sensor with red and near infrared (NIR) bands. The calibration and validation of the SASM using bootstrap and cross-validation methods showed that the SASM applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua band 1 data retrieved TSS with a root mean square error (RMSE) and mean averaged relative error (MARE) of 5.75 mg/L and 33.33% respectively. The application of the SASM over our study region using MODIS-Aqua band 1 data showed that the SASM can be used to monitor the on-going, post and pre-dredging activities and identify daily TSS anomalies that are caused by natural and anthropogenic processes in coastal waters of northern Western Australia.


 
147 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 8, Pages 554: Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests (Remote Sensing)
Remote Sensing, Vol. 8, Pages 560: Mapping Dynamics of Inundation Patterns of Two Largest River-Connected Lakes in China: A Comparative Study (Remote Sensing)
 
 
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