Coastal Bathymetry Research Articles

Coastal bathymetry determined from water waves observed by airborne lidars: A case study near Ganquan Island, South China Sea

Coastal bathymetry determined from water waves observed by airborne lidars: A case study near Ganquan Island, South China Sea

Floquet stability analyses of stratified oscillating boundary layers on adiabatic slopes

The presence of a no-slip, impermeable, adiabatic, sloped boundary in an otherwise quiescent, stably stratified, Boussinesq flow generates baroclinic vorticity within a diffusive boundary layer. Such conditions are typical of the oscillating boundary layers on adiabatic abyssal slopes, sloped lake bathymetry and sloped coastal bathymetry in the absence of high-wavenumber internal waves, mean flows, far-field turbulence on larger scales, and resonant tidal–bathymetric interaction. We investigate the linear stability of the oscillating flow within non-dimensional parameter space typical of the $M_2$ tide and hydraulically smooth, middle-latitude abyssal slopes through Floquet linear stability analysis. The flow dynamics depends on three non-dimensional variables: the Reynolds number for Stokes’ second problem, the Prandtl number, and a frequency ratio that accounts for the resonance conditions ( $C$ , criticality) of the buoyant restoring force and the tidal forcing. The Floquet analysis results suggest that oscillating laminar boundary layers on adiabatic abyssal slopes are increasingly unstable as Reynolds number, criticality parameter and/or spanwise disturbance wavenumber are increased. We also show that the two-dimensional Floquet linear instability necessarily generates three-dimensional baroclinic vorticity, which suggests that the evolution of the gravitational instabilities may be nonlinear as $t\rightarrow \infty$ .

Assessment of Atmospheric Correction Processors and Spectral Bands for Satellite-Derived Bathymetry Using Sentinel-2 Data in the Middle Adriatic

Satellite-derived bathymetry (SDB) based on multispectral satellite images (MSI) from the satellite’s optical sensors is a recent technique for surveying shallow waters. Sentinel-2 satellite mission with an open access policy and high spatial, radiometric, and temporal resolution of MSI-s started a new era in the mapping of coastal bathymetry. More than 90 percent of the electromagnetic (EM) signal received by satellites is due to the atmospheric path of the EM signal. While Sentinel-2 MSI Level 1C provides top-of-atmosphere reflectance, Level 2A provides bottom-of-atmosphere reflectance. The European Space Agency applies the Sen2Cor algorithm for atmospheric correction (AC) to model the atmospheric path of the signal and reduce the MSI reflectance from L1C to L2A over the land area. This research evaluated the performance of different image-based AC processors, namely: Sen2Cor, Acolite, C2RCC, and iCOR for SDB modelling. The empirical log band ratio algorithm was applied to a time series of Sentinel-2 MSI in the middle Adriatic. All AC processors outperformed Sentinel-L2A MSI for SDB. Acolite and iCOR demonstrated accurate performance with a correlation coefficient higher than 90 percent and the RMSE under 2 m for depths up to 20 m. C2RCC produced more robust bathymetry models and was able to retrieve the depth information from more scenes than any other correction. Furthermore, a switch model combining different spectral bands improved mapping in shallow waters, demonstrating the potential of SDB technology for the effective mapping of shallow waters.

Coastal bathymetry inversion using SAR-based altimetric gravity data: A case study over the South Sandwich Island

The global bathymetry models are usually of low accuracy over the coastline of polar areas due to the harsh climatic environment and the complex topography. Satellite altimetric gravity data can be a supplement and plays a key role in bathymetry modeling over these regions. The Synthetic Aperture Radar (SAR) altimeters in the missions like CryoSat-2 and Sentinel-3A/3B can relieve waveform contamination that existed in conventional altimeters and provide data with improved accuracy and spatial resolution. In this study, we investigate the potential application of SAR altimetric gravity data in enhancing coastal bathymetry, where the effects on local bathymetry modeling introduced from SAR altimetry data are quantified and evaluated. Furthermore, we study the effects on bathymetry modeling by using different scale factor calculation approaches, where a partition-wise scheme is implemented. The numerical experiment over the South Sandwich Islands near Antarctica suggests that using SAR-based altimetric gravity data improves local coastal bathymetry modeling, compared with the model calculated without SAR altimetry data by a magnitude of 3.55 m within 10 km of offshore areas. Moreover, by using the partition-wise scheme for scale factor calculation, the quality of the coastal bathymetry model is improved by 7.34 m compared with the result derived from the traditional method. These results indicate the superiority of using SAR altimetry data in coastal bathymetry inversion.

MANAJEMEN PENGELOLAAN WILAYAH PESISIR DALAM MENUNJANG KEPARIWISATAAN DI PANTAI MATTIROTASI KOTA PAREPARE

Based on the results of research in the management of coastal areas in increasing tourists visiting Mattirotasi Beach, it is known that the results of the analysis of the coastal tourism environment are known to have a coastal height of 0-3 meters above sea level with a slope of 0-8%, coastal bathymetry in the city of Parepare, wind speeds ranging from 173.4 m. /min to 117.6 n/min can generate sea waves with a height of 0.5-1.2 meters. Meanwhile, in the East monsoon, which has a range of wind speeds between 133.2-45 m/s, it is able to generate waves that reach a height of 0.4 – 1.4 meters. up to 0.1852 m/s. With wave intervals ranging from +1.1 meters to 1.5, and seeing the potential for attraction, there is the Nusantara Port which functions as one of the main gates as access to Tanjungpinang City. This area stretches for ± 5 Km and is directly adjacent to the waters, so it has the potential to be developed as a recreational area with the potential to present a sunset view by the beach and Suppa Bay. This condition is also supported by the strategic position of the City of Parepare as a Madya City which is a connecting node in the central part of South Sulawesi Province towards West Sulawesi and the northern part of South Sulawesi Province. Therefore, the Mattirotasi coastal area is a coastal tourist attraction that has quite a variety of attractions. This beach tourism activity is included in the recreational category, which is the type of activity that is most dominantly carried out by tourists.

Gradient Boosting and Linear Regression for Estimating Coastal Bathymetry Based on Sentinel-2 Images

Thousands of vessels travel around the world every day, making the safety, efficiency, and optimization of marine transportation essential. Therefore, the knowledge of bathymetry is crucial for a variety of maritime applications, such as shipping and navigation. Maritime applications have benefited from recent advancements in satellite navigation technology, which can utilize multi-spectral bands for retrieving information on water depth. As part of these efforts, this study combined deep learning techniques with satellite observations in order to improve the estimation of satellite-based bathymetry. The objective of this study is to develop a new method for estimating coastal bathymetry using Sentinel-2 images. Sentinel-2 was used here due to its high spatial resolution, which is desirable for bathymetry maps, as well as its visible bands, which are useful for estimating bathymetry. The conventional linear model approach using the satellite-derived bathymetry (SDB) ratio (green to blue) was applied, and a new four-band ratio using the four visible bands of Sentienl-2 was proposed. In addition, three atmospheric correction models, Sen2Cor, ALOCITE, and C2RCC, were evaluated, and Sen2Cor was found to be the most effective model. Gradient boosting was also applied in this study to both the conventional band ratio and the proposed FVBR ratio. Compared to the green to blue ratio, the proposed ratio FVBR performed better, with R2 exceeding 0.8 when applied to 12 snapshots between January and December. The gradient boosting method was also found to provide better estimates of bathymetry than linear regression. According to findings of this study, the chlorophyll-a (Chl-a) concentration, sediments, and atmospheric dust do not affect the estimated bathymetry. However, tidal oscillations were found to be a significant factor affecting satellite estimates of bathymetry.

Analysis of univariate linear, robust-linear, and non-linear machine learning algorithms for satellite-derived bathymetry in complex coastal terrain

The blue economic, maritime, and exploration activities rely on precise knowledge of coastal bathymetry. The recent trends in Satellite-Derived Bathymetry (SDB) research have focused on various methods of estimation using very high-resolution satellite imagery and in-situ data, but mostly in clear and transparent water. The Indian coastal region mostly has murky water, which is further constrained to employ SDB techniques in areas of river mouth and delta due to the presence of numerous underwater rocks and rich sediment carried by rivers. This study is focused on analyzing SDB in two study areas characterized as turbid, sediment-laden, and complex due presence of numerous underwater rocks. The objective of the research is to analyze and compare the performance of a few univariate Machine Learning (ML) regression algorithms in SDB estimation using ASTER, LANDSAT-8, and Sentinel-2A spectral bands with high resolution in-situ bathymetric data. This study evaluates linear, three robust linear Huber, RANSAC & ThielSen, and a non-linear Gaussian Process Regression ML algorithm, to analyze the efficacy in SDB estimation using a univariate spectral bandwidth of satellite imagery. The applied non-linear regression model has estimated SDB with the accuracy of R2 0.87, RMSE 1.77 m, and MAE 1.27 m for depth of 30 m in site A; and site B, R2 0.91, RMSE 1.51 m & MAE 1.17 m for depth of 22 m. The advantage offered by this approach includes; minimum required parameters, less processing time, and the potential to be an alternative to hydrographic surveys.

Impact of coastal development on coastal morphology of Taiwan: Case studies and proposed countermeasures

When economic expansion started in the late 1970s, Taiwan was in desperate need of better infrastructure. In response, the government began construction along the coasts around the island. Many of these structures were constructed under time constraints, and their possible effects on the environment were not considered. Years later, some of the structures were found to have disrupted littoral sediment transport, resulting in the retreat of shorelines downstream. The Integrated Coastal Zone Management Plan demands the implementation of remedial measures for erosion by the responsible party in the near future. However, as morphological changes are complicated processes involving both natural and human-induced drivers, the liabilities of the parties involved are typically difficult to determine. In this study, bathymetric analysis and numerical simulation were used to assess the effects of coastal structures on coastal erosion. With the former, the rate of change of the bathymetric volume along the shore was used to identify the extent of the structural effect. The latter one is then used to clarify the respective effect of adjacent structures on coastal bathymetry. Three cases with different surroundings were considered to verify the scheme. It is suggested that range of influence of the structure should be determined in terms of coastal cells. In the case of multiple structures existing within a cell, the cost of remedial measures should be proportional to the length of the structure vertical to the coastline. Remedies to restore the continuity of longshore drift are then proposed. These results can be used to promote effective coastal zone management and prevent further deterioration.

The new era of regional coastal bathymetry from space: A showcase for West Africa using optical Sentinel-2 imagery

Large-scale coastal bathymetry is paramount to understand natural and human-induced coastal behaviour and plays a vital role in coastal research and governance. Here, we use a recently developed algorithm, S2Shores (Satellite to Shores), to invert coastal bathymetry from wave kinematics, based on the linear dispersion relation. Wave numbers and celerity are extracted from optical Sentinel-2 imagery, by exploiting the small temporal offset between the image bands of its Multi-Spectral Instrument. Inverted depths are output at 200 m resolution, and individual depth points are merged to create a composite bathymetry using a weighted average of images from 10 different dates. The resulting bathymetry mosaic spans 4000 km along the West African coast. S2Shores is able to detect depths up to 35 m, depending on mean incident wave conditions and cloud cover, which varies by location. Underwater features are well reproduced by S2Shores, such as flow channels in Guinea, the St. Ann's Shoal in Sierra Leone, and ebb delta lobes at several outlets along the Niger River Delta. S2Shores results match well (r2 = 0.76, RMSE = 4.9 m) with a bathymetry survey along the Senegalese coast. As a difference with traditional satellite-derived bathymetry methods based on water colour, a wave-based approach allows estimations in turbid areas and relatively deep waters, which suggest that the two approaches are complementary and should be used in combination to cover coastal environments in their diversity. The new possibility offered by this regional coastal atlas opens the door to increased research and planning capabilities and sets an example that can be applied to the rest of the world.

Propagation of barotropic Kelvin waves around Antarctica

Barotropic (i.e., depth-uniform) coastal oceanic Kelvin waves can provide rapid teleconnections from climate and weather events in one location to remote regions of the globe. Studies suggest that barotropic Kelvin waves observed around Antarctica may provide a mechanism for rapidly propagating circulation anomalies around the continent, with implications for continental shelf temperatures along the West Antarctic Peninsula and thus Antarctic ice mass loss rates. However, how the propagation of Kelvin waves around Antarctica is influenced by features such as coastal geometry and variations in bathymetry remains poorly understood. Here we study the propagation of barotropic Antarctic Kelvin waves using a range of idealized model simulations. Using a single-layer linear shallow water model with 1∘ horizontal resolution, we gradually add complexity of continental configuration, realistic bathymetry, variable planetary rotation, and forcing scenarios, to isolate sources and sinks of wave energy and the mechanisms responsible. We find that approximately 75% of sub-inertial barotropic Kelvin wave energy is scattered away from Antarctica as other waves in one circumnavigation of the continent, due mostly to interactions with bathymetry. Super-inertial barotropic Kelvin waves lose nearly 95% of their energy in one circumpolar loop, due to interactions with both coastal geometry and bathymetry. These results help to explain why only sustained signals of low-frequency resonant barotropic Kelvin waves have been observed around Antarctica, and contribute to our understanding of the role of rapid, oceanic teleconnections in climate.

Depth Inversion from Wave Frequencies in Temporally Augmented Satellite Video

Optical satellite images of the nearshore water surface offer the possibility to invert water depths and thereby constitute the underlying bathymetry. Depth inversion techniques based on surface wave patterns can handle clear and turbid waters in a variety of global coastal environments. Common depth inversion algorithms require video from shore-based camera stations, UAVs or Xband-radars with a typical duration of minutes and at framerates of 1–2 fps to find relevant wave frequencies. These requirements are often not met by satellite imagery. In this paper, satellite imagery is augmented from a sequence of 12 images of Capbreton, France, collected over a period of ∼1.5 min at a framerate of 1/8 fps by the Pleiades satellite, to a pseudo-video with a framerate of 1 fps. For this purpose, a recently developed method is used, which considers spatial pathways of propagating waves for temporal video reconstruction. The augmented video is subsequently processed with a frequency-based depth inversion algorithm that works largely unsupervised and is openly available. The resulting depth estimates approximate ground truth with an overall depth bias of −0.9 m and an interquartile range of depth errors of 5.1 m. The acquired accuracy is sufficiently high to correctly predict wave heights over the shoreface with a numerical wave model and to find hotspots where wave refraction leads to focusing of wave energy that has potential implications for coastal hazard assessments. A more detailed depth inversion analysis of the nearshore region furthermore demonstrates the possibility to detect sandbars. The combination of image augmentation with a frequency-based depth inversion method shows potential for broad application to temporally sparse satellite imagery and thereby aids in the effort towards globally available coastal bathymetry data.

Numerical Simulation of Time-Optimal Path Planning for Autonomous Underwater Vehicles Using a Markov Decision Process Method

Many path planning algorithms developed for land or air based autonomous vehicles no longer apply under the water. A time-optimal path planning method for autonomous underwater vehicles (AUVs), based on a Markov decision process (MDP) algorithm, is proposed for the marine environment. Its performance is examined for different oceanic conditions, including complex coastal bathymetry and time-varying ocean currents, revealing advantages compared to the A* algorithm, a traditional path planning method. The ocean current is predicted using a regional ocean model and then provided to the MDP algorithm as a priori. A computation-efficient and feature-resolved spatial resolution are determined through a series of sensitivity experiments. The simulations demonstrate the importance to incorporate ocean currents in the path planning of AUVs in the real ocean. The MDP algorithm remains robust even if the ocean current is complex.

Assessing the Ability to Quantify Bathymetric Change over Time Using Solely Satellite-Based Measurements

Coastal regions are undergoing rapid change, due to natural and anthropogenic forcings. A current constraint in understanding and modeling these changes is the lack of multi-temporal bathymetric data, or recursive observations. Often, it is difficult to obtain the repeat observations needed to quantify bathymetric change over time or events. However, the recent availability of ICESat-2 bathymetric lidar creates the option to map coastal bathymetry from solely space-based measurements via satellite-derived bathymetry with multispectral imagery (IS-2/SDB). This compositional space-based bathymetric mapping technique can assess temporal change along the coasts without other remote sensing or in situ data. However, questions exist as to the accuracy of the technique relative to both quantitative uncertainties and the ability to resolve the spatial patterns of erosion and deposition in the nearshore environment, indicative of geomorphologic change. This paper addresses the concept using data from the Florida panhandle (Northern Gulf of Mexico) collected by Sentinel-2 and ICESat-2 at two epochs to assess the feasibility of using IS-2/SDB for bathymetric change detection at scientifically relevant scales, spatial resolutions and accuracies. The comparison of the satellite-only result is compared to airborne data collected at similar epochs to reveal both quantitatively and qualitatively the utility of this technique.

Automated high-resolution satellite-derived coastal bathymetry mapping

Accurate and up-to-date maps of coastal bathymetry are fundamental for coastal resource management, commercial and military navigation, and aquaculture, among many applications. Existing methods for bathymetry mapping require intensive and costly field surveys or targeted aerial captures, neither of which are easily or affordably replicated for repeat mapping and change monitoring. Satellite-derived bathymetry (SDB), however, offers the potential to map shallow water bodies repeatedly and efficiently with high spatial and temporal resolution (i.e., daily-weekly at 5 m or better). One challenge to large-scale implementation of SDB lies in the automated derivation of inherent water column properties such that they may be accurately compensated for across a variety of depth and substrate conditions. Here we present an algorithm that leverages WorldView (Maxar/Digital GlobeTM) satellite imagery to map the entire 3700 km2 Florida Keys (USA) island chain at 2-meter resolution without the need for any in-situ data collections. Preprocessing included radiometric calibration, atmospheric correction, automated deglinting, and automated detection of optically deep water, which was then used to estimate chlorophyll-a concentration assuming that the study area is primarily comprised of Case-I water (i.e., those where the optical signal is dominated by water, Chlorophyll-a in phytoplankton, and properties that vary in proportion to Chlorophyll-a concentration). Estimating Chlorophyll-a concentration allowed us to calculate the appropriate tuning coefficients used in a spectral band ratio equation for estimating bathymetry. The entire process was fully automated from ingestion of Level-1B image to bathymetry raster output. Mapping the Florida Keys from Key Largo to Key West required 34 WorldView images and was completed in approximately 27 min for an average processing time of 47 s per image using a single GPU core (i.e., supercomputing resources were not needed). After combining the products (mosaicking) in ArcMap, the wall-to-wall bathymetry map was validated against a LiDAR-derived bathymetry model with over 600,000 points; results show an RMSE of 1.95 m over depths from 0 to 15 m.

A Self-Adaptive Method for Mapping Coastal Bathymetry On-The-Fly from Wave Field Video

Mapping coastal bathymetry from remote sensing becomes increasingly more attractive for the coastal community. It is facilitated by a rising availability of drone and satellite data, advances in data science, and an open-source mindset. Coastal bathymetry, but also wave directions, celerity and near-surface currents can simultaneously be derived from aerial video of a wave field. However, the required video processing is usually extensive, requires skilled supervision, and is tailored to a fieldsite. This study proposes a video-processing algorithm that resolves these issues. It automatically adapts to the video data and continuously returns mapping updates and thereby aims to make wave-based remote sensing more inclusive to the coastal community. The code architecture for the first time includes the dynamic mode decomposition (DMD) to reduce the data complexity of wavefield video. The DMD is paired with loss-functions to handle spectral noise and a novel spectral storage system and Kalman filter to achieve fast converging measurements. The algorithm is showcased for fieldsites in the USA, the UK, the Netherlands, and Australia. The performance with respect to mapping bathymetry was validated using ground truth data. It was demonstrated that merely 32 s of video footage is needed for a first mapping update with average depth errors of 0.9–2.6 m. These further reduced to 0.5–1.4 m as the videos continued and more mapping updates were returned. Simultaneously, coherent maps for wave direction and celerity were achieved as well as maps of local near-surface currents. The algorithm is capable of mapping the coastal parameters on-the-fly and thereby offers analysis of video feeds, such as from drones or operational camera installations. Hence, the innovative application of analysis techniques like the DMD enables both accurate and unprecedentedly fast coastal reconnaissance. The source code and data of this article are openly available.

Predicting coastal impacts by wave farms: A comparison of wave-averaged and wave-resolving models

Wave energy converters (WECs) will have to be arranged into arrays of many devices to extract commercially viable amounts of energy. To understand the potential coastal impacts of WEC arrays, most research to date has relied on wave-averaged models given their computational efficiency. However, it is unknown how accurate wave-averaged model predictions are given a lack of validation data and their inherent simplifications of various hydrodynamic processes (e.g., diffraction). This paper compares the predictions of coastal wave farm impacts from a coupled wave-averaged and flow model (Delft3D-SNL-SWAN), to a wave-resolving wave-flow model (SWASH) that intrinsically accounts for more of the relevant physics. Model predictions were compared using an idealized coastal bathymetry over a range of wave conditions and wave farm geometries. Both models predicted the largest impacts (changes to the nearshore hydrodynamics) for large and dense wave farms located close to the shore (1 km) and the smallest impacts for the small and widely spaced farm at a greater offshore distance (3 km). However, the wave-resolving model generally predicted somewhat larger impacts (i.e., changes to the nearshore wave heights, mean velocities and mean water levels). We also found that coupling the wave-averaged model to a flow model resulted in more realistic downstream predictions than the stand-alone wave-averaged model.

Global Satellite-Based Coastal Bathymetry from Waves

The seafloor—or bathymetry—of the world’s coastal waters remains largely unknown despite its primary importance to human activities and ecosystems. Here we present S2Shores (Satellite to Shores), the first sub-kilometer global atlas of coastal bathymetry based on depth inversion from wave kinematics captured by the Sentinel-2 constellation. The methodology reveals coastal seafloors up to a hundred meters in depth which allows covering most continental shelves and represents 4.9 million km2 along the world coastline. Although the vertical accuracy (RMSE 6–9 m) is currently coarser than that of traditional surveying techniques, S2Shores is of particular interest to countries that do not have the means to carry out in situ surveys and to unexplored regions such as polar areas. S2Shores is a major step forward in mitigating the effects of global changes on coastal communities and ecosystems by providing scientists, engineers, and policy makers with new science-based decision tools.

Internal wave intensity and angle of propagation modulate small-scale settlement patterns of intertidal barnacles during peak recruitment

The settlement of intertidal barnacles Chthamalus spp. was measured for an entire recruitment season at 3 sites separated by 100 m in Baja California, Mexico. During a 10 d pulse that accounted for nearly 30% of yearly settlement, coastal wind speed and direction, nearshore water column temperature, and current velocities were also measured. During this period, strong internal tidal forcing was observed, with short episodes (1-1.5 h) of rapid fluctuations in water column temperature, stratification, and currents. Chthamalus spp. settlement was significantly and positively correlated with cumulative high-frequency fluctuations in temperature, thermal stratification, and surface current flows, but not with onshore winds. Furthermore, the spatial pattern in the number of settlers was correlated with the angle of propagation estimated for onshore-moving internal waves, potentially modulated by nearshore bathymetry. This relationship between Chthamalus spp. settlement and high-frequency changes in water column temperature was also shown for a site in La Jolla, California, USA, but not for a similar barnacle, Balanus glandula, suggesting that interspecific differences in larval behavior and nearshore depth distribution may translate into differences in transport. Our results suggest that both the number of settlers at shore and their spatial pattern can be modulated by the intensity and direction of internal wave events, at least during peak settlement periods. Future research should consider both the intensity and geometry of internal-wave-induced variability in the nearshore, as well the small-scale features of coastal geomorphology and bathymetry.

Pan-European Satellite-Derived Coastal Bathymetry—Review, User Needs and Future Services

Low-lying coastal zones are home to around 10% of the world’s population and to many megacities. Coastal zones are largely vulnerable to the dynamics of natural and human-induced changes. Accurate large-scale measurements of key parameters, such as bathymetry, are needed to understand and predict coastal changes. However, nearly 50% of the world’s coastal waters remain unsurveyed and for a large number of coastal areas of interest, bathymetric information is unavailable or is often decades old. This lack of information is due to the high costs in time, money and safety involved in collecting these data using conventional echo sounder on ships or LiDAR on aircrafts. Europe is no exception, as European seas are not adequately surveyed according to the International Hydrographic Organisation. Bathymetry influences ocean waves and currents, thereby shaping sediment transport which may alter coastal morphology over time. This paper discusses state-of-the-art coastal bathymetry retrieval methods and data, user requirements and key drivers for many maritime sectors in Europe, including advances in Satellite-Derived Bathymetry (SDB). By leveraging satellite constellations, cloud services and by combining complementary methods, SDB appears as an effective emerging tool with the best compromise in time, coverage and investment to map coastal bathymetry and its temporal evolution.

A Generic Method to Derive Coastal Bathymetry From Satellite Photogrammetry for Tsunami Hazard Assessment

AbstractIn this study, we use Pleiades satellite stereo imagery to map shallow‐water bathymetry specifically for the purpose of assessing tsunami hazard in coastal regions. In order to calculate the refraction correction factor, we independently measure the refractive indices of seawater mixed with a variety of phytoplankton, which was previously unquantified. We find that the refractive index of seawater increases with cell density of phytoplankton, ranging from 1.3410 to 1.3425. Through rigorous error analysis, we demonstrate that the change in refraction due to heterogeneous distribution of phytoplankton is negligible, suggesting that the technique is applicable to the global ocean. Using the Penghu Islands as a case example, we show that photogrammetric bathymetry is able to reveal tsunami impacts more accurately and reasonably than the commonly used General Bathymetric Chart of the Oceans data, highlighting the importance of high‐resolution and high‐accuracy bathymetry for tsunami hazard assessment.