Assessment of Empirical Near-Shore Bathymetry Model Using New Emerged PlanetScope Instrument and Sentinel-2 Data in Coastal Shallow Waters

Shallow water bathymetric information is important for human life because it has a strong influence on phenomena and dynamics in coastal areas. Conventional bathymetric mapping methods are capable of obtaining high-precision accuracy, but require expensive and complex resources. Specifically, in shallow waters, survey instruments have difficulty obtaining adequate depth data due to the many obstacles that must be overcome. Remote sensing-based shallow water bathymetry called as Satellite-Derived Bathymetry (SDB) is a reasonable and efficient choice. Technological developments enable SDB data processing to be much more efficient in terms of time and storage by utilizing cloud-based platforms such as Google Earth Engine (GEE). Spatial and temporal resolution is still a challenge in SDB, so in this condition PlanetScope with daily temporal resolution capabilities is an optimistic choice. However, this image falls into a relatively new image category. In this study we tested the performance of Sentinel-2A imagery and new PlanetScope imagery bands. The existence of the new sensor owned by PlanetScope allows an increased choice of SDB data sources with high spatial and temporal resolution that is better than the general datasets currently available. There are four additional channels are Coastal Blue, Green I, Yellow, and Red Edge. Assessment is needed to test the capabilities of each new channel using empirical methods via the Stumpf algorithm. Based on accuracy assessment observations, the Sentinel-2A channel combination is still better in terms of accuracy and determination, because it is able to represent the depth in the study area up to 70. The potential use of PlanetScope's new channels for SDB applications can still be seen in the combination of the Coastal Blue and Yellow channels. This channel combination is still able to represent 47 of the depth variations in the study area. © 2024, Association for Geoinformation Technology. All rights reserved.