Benthic Habitat Classification Using Sentinel-2a Image With And Without Water Column Correction In Pengudang Village, Bintan Regency

Abstract

Research on the mapping of benthic habitats in the waters of Pengudang Village, Bintan Regency, uses Sentinel-2A imagery. This mapping process has the potential to display the results of classification of benthic habitats in shallow waters. The purpose of this study was to assess the Maximum Likelihood Classification (MLH) algorithm model for mapping benthic habitat cover through Sentinel-2A satellite imagery using the lyzenga water column correction and without water column correction and to calculate the accuracy of the MLH classification results for benthic habitats in waters Pengudang Village. This classification uses a pixel-based image classification which is grouped into a cover class for each pixel. This classification groups into 4 benthic habitat classes, namely dead coral sand (KMP), sea grass (LM), live coral sand (PKH) and sand (PS). The results showed that the application of the lyzenga correction using the MLH algorithm in mapping benthic habitats resulted in a significant accuracy rate (80,00%), while the application without lyzenga correction using the MLH algorithm resulted in an accuracy rate (76,00%). These findings support the use of the lyzenga correction method which can increase the level of accuracy by (4,00%) with the MLH algorithm as a guide in better mapping of benthic habitat cover in Pengudang Village.