Numerous socio-economic disruptions have occurred as a result of the global lockdown since the COVID-19 pandemic started in 2019. Due to the unpredictable nationwide lockdown, it was extremely difficult to physically mobilize survey personnel for field data collection. Submerged vessel-based acoustic gears have traditionally been used to gather hydro-spatial data across the water and contiguous environment including oceans, seas, lakes, rivers, and estuaries. The growing multidisciplinary technological trends in hydrography are revolutionizing the field and shaping its future trajectory. Hydrographic practitioners today must accommodate the “new normal” for staying competitive and effectively addressing the complexities of the hydrographic surveying field. To maximize the reimbursements from the espousal of the multidisciplinary technological swifts, the adoption of high-resolution satellite imagery (multispectral, hyperspectral, etc.), aerial optical sensors (LiDAR, RADAR, SAR, etc.), and different unscrewed surface vehicles (USV) for data acquisition produces valuable hydro-spatial data to serve the hydrographic community. In fact, imagery-derived bathymetry has transformed into a data mining technique that yields actionable hydro-spatial data that can mitigate upcoming economic upheavals. In this study, Stumpf’s model was applied to derive the bathymetric along the Tanjung Kupang Bay using Sentinel-2 multispectral imagery from 2017 to 2022. By contrasting the imagery-derived bathymetric depths on 2018 with the 1367 vessel-based surveyed bathymetric data, the main R-squared accuracy was calculated to be 0.7327; then the computed RMSE was 0.489 m, and the MAE was 0.490 m. Thus, this technique can therefore be a reliable and effective way to determine the seabed topography along lengthy stretches of shoreline. In summary, this contactless approach enables the dependable acquisition of coastal bathymetric depths at a comparatively low cost and less labor-intensive level.