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Abstract. Studies on suspended sediment concentrations at aseasonal scale play a vital role in understanding coastal hydrodynamicprocesses in an area. Assessment of spatio-temporal changes in suspendedsediments in nearshore areas has gained complexity due to the utilization ofconventional methods; this issue can be successfullysolved nowadays using multi-temporal remotely sensed images with the help ofadvanced image processing techniques. The present study is an attempt todemonstrate the model algorithm used to extract suspended sedimentconcentrations using Landsat 8 OLI (Operational Land Imager) sensor images.The study was executed in a near-offshore area of the Thiruvananthapuramcoast, southern India, and focused on the extraction of suspended sedimentconcentrations and their seasonal variability during pre-monsoon andpost-monsoon periods. The OLI images were pre-processed to obtain the actualreflectance using the FLASSH module of the ENVI v5.5 software. The genericmodel developed herein is designed to compute the spectral reflectancevariability between coastal water and suspended sediments and todifferentiate the spatial accumulation of the suspended sedimentconcentrations from the coastal water at the pixel scale. Maximum (0.8 % innear-infrared bands) and minimum (0.6 % in blue bands) spectral reflectanceindicates the occurrence of suspended sediments in the coastal water. Themodel-derived results revealed that the suspended sediment concentrationgradually decreased with increasing depth and distance from the shoreline.Higher sediment concentrations accumulated at lower depths in coastal waterdue to wave and current action that seasonally circulated the sediments. Thishigher concentration of the suspended sediment load was estimated to be0.92 mg L −1 at the shallow depths (  m) of the coastal waters and0.30 mg L −1 at a depth of 30 m. Seasonal variability of suspendedsediments was observed in a north–south direction during the pre-monsoon;the reverse was noted during the post-monsoon period. The spatial variabilityof suspended sediments was indirectly proportional to the depth and distancefrom the shoreline, and directly proportional to offshore wave and littoralcurrent activity. This study proves that the developed model coupled with theprovided computational algorithm can be used as an effective tool for theestimation of suspended sediment concentrations using multi-temporal OLIimages; furthermore, the output may be helpful for coastal zone managementand conservation planning and development.

ocean science

Monitoring of seasonal variability and movement of suspended sediment concentrations along the Thiruvananthapuram coast, southern India, using the Landsat OLI sensor