Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island

Abstract

Turbidity is a parameter of the marine environment that greatly affects the condition of seagrass whose habitat is an intertidal zone in shallow sea waters. Seagrass is an important type of ecosystem that can be found in several coastal areas of Ternate Island. This study aims to analyze the turbidity conditions of seagrass habitat waters and apply a remote sensing algorithm using Sentinel 2B images. The turbidity research method was carried out by field measurements. The turbidity algorithm model used refers to references with mathematical equations (Rrs665-0.014)/0.013, and the development of a new algorithm as a comparison algorithm. Both algorithms were validated with field data to determine the level of accuracy using the Normalized Mean Absolute Error (NMAE) and determination coefficient (R2). The results were obtained from turbidity data with values ranging from 0.3 NTU to 1.5 NTU with an average value of 0.87 0.45 NTU. The Sentinel 2B image in this study was restored with geometric corrections, atmosphere, radiometric digital values, land masking, and sun glint. The turbidity algorithm model used obtained good accuracy in mapping and monitoring the turbidity of seagrass habitat waters on Ternate Island. The application of the turbidity algorithm used as a reference in this study has an NMAE value of 50.44 and R2 of 0.8822, while the newly discovered turbidity algorithm has an NMAE value of 29.38 and R2 of 0.8827.Keywords:remote sensingecosystemscoastalsedimentationNorth Maluku