Detection of the river sediment deposition area at Kuala Perlis river mouth using Landsat 8 OLI within the years 2019, 2020 and 2021 / Nur Zakira Ain Zamrun

Sedimentation at the mouth of the river always occurs in Kuala Perlis disrupting the ferries and boats’ travel, especially during the low tide. Therefore, this study aimed to compare the best method for foreseeing river sediment deposition between K-Means unsupervised image classification machine learning and water spectral indices (MNDWI) to analyze the areas most influenced by deposited river sediments from the clustered images. Quantification of Landsat 8 OLI satellite images was applied using ENVI software on the study area for detecting sedimentation in the study area that used image data band correlation in deposited river sediment through unsupervised classifier algorithm and selection of spectral bands for MNDWI. The determination of determinant bands from analysis of correlation coefficient resulted in NIR bands for their lowest R² coefficient that ranged R² 0.5 to R² 0.7. The selected K-Means classification method has been taken for further clustered image analysis compared to the MNDWI method. From the analysis through stage’s statistic, visual observation and previous studies review, the river sediment deposition at the river mouth was significantly increased from the year 2019 to the year 2021. These results were supported with the percentage of increase (14%) for riverbed regions subjected to sediment deposition. The location of Kuala Perlis itself exacerbated the problem of dumping sediment returned to the river mouth in a brief period, which is also reliant on the wave flow. This study was beneficial for the future development of Kuala Perlis and local communities nearby.