Shallow Water Mapping Research Articles

Lyzenga Algorithm for Shallow Water Mapping Using Multispectral Sentinel-2 Imageries in Gili Noko Waters

Bathymetric survey is an essential approach for gathering marine geospatial information. The use of an echosounder can provide highly accurate bathymetric data, yet it is expensive and time-consuming. To achieve an accurate chart of shallow water areas is challenging as they are difficult to access by large survey vessels due to their draft limitation. Bathymetric survey can also be carried out by using an Unmanned Surface Vehicles; however, it is restricted to small and calm areas. Thus, a Satellite Derived Bathymetry (SDB) come as a solution to take the place of bathymetric survey using an echosounder, especially in a shallow water with many natural or man-made obstacles. This study utilises Sentinel-2 image data, an optical satellite imagery to determine depth values of shallow water area using SDB approach. Several algorithms have been developed to collect depth values using the SDB. One of the algorithms is Lyzenga algorithm which aims to simplify the process of extracting water depths by comparing water reflectance factors using three bands of panchromatic sensor imagery. This study applied the Lyzenga algorithm to determine water depths using multiple linear regression and it is validated using an in-situ data. The RMSE and MAE values is 1.711m and 1.254m, respectively whilst the correlation coefficient is 0.946.

Modelling of Kuibyshev reservoir shallow water depths by bathymetric surveys and multispectral UAV imagery data: A case study

This study investigates the potential of using multispectral Unmanned Aerial Vehicle (UAV) imagery to model the shallow water depths of the Kuibyshev Reservoir, Russia. Traditional methods like boom soundings and echo sounders, while accurate, are labor-intensive and costly. By leveraging multispectral data from UAVs, we aim to provide a more efficient and detailed approach to bathymetric mapping. Our methodology involved conducting bathymetric surveys with a Garmin GPS Map 178C and a Geoscan 401 Geodesy UAV equipped with a MicaSense RedEdge-MX camera. We performed correlation analysis and modelled depth using various regression techniques, identifying the Decision Tree Regressor as the top-performing model with an R² value of 0.98. Our findings suggest that UAV multispectral bathymetry is a viable alternative for local-scale shallow water mapping, with significant implications for reservoir management and ecological studies.

Coregistration of Hyperspectral Imagery With Photogrammetry for Shallow-Water Mapping

In this paper we present coregistration of hyperspectral imagery with photogrammetry for shallow-water mapping from an Unmanned Aerial Vehicle (UAV). The coregistration is based on a methodology for georeferencing that utilizes outputs from the photogrammetry pipeline through three steps. First, we perform the photogrammetry pipeline. This gives camera poses from Structure-from-Motion (SfM) and a dense point cloud from Multi-View Stereo (MVS). Performing a refraction correction of the dense point cloud yields high-resolution bathymetry. Second, poses from SfM are fused with UAV navigation sensors in a Kalman smoother. Third, the geometric model of the hyperspectral imager is calibrated to align hyperspectral images with photogrammetry. Then, ray tracing is performed to georeference spectral measurements onto the bathymetry from MVS. Using the georeferenced hyperspectral imagery, we present spectral bathymetry estimation. The methods were demonstrated for a coastal site (depth < 6 m) in Norway, using a UAV with a camera and a hyperspectral imager. The georeferencing yielded a horizontal Mean Absolute Error (MAE) of 22 cm between hyperspectral and photogrammetry, equivalent to one hyperspectral pixel. The MVS bathymetry gave a MAE of 14 cm with respect to ground truth acoustic. The spectral bathymetry estimator was calibrated on ground truth acoustics with a MAE of 10 cm. Comparing the bathymetry from MVS with the spectral bathymetry yielded a MAE of 11 cm. The results suggest that coregistration with photogrammetry yields accurate georeferencing of hyperspectral imagery. The results also show that we can map bathymetry accurately using MVS with refraction correction or the spectral estimator.

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.

Introduction to Special Issue “Shallow Water Mapping in Coastal Environments: Recent Research, Current Technologies, and Multi-modal Approaches”

Introduction to Special Issue “Shallow Water Mapping in Coastal Environments: Recent Research, Current Technologies, and Multi-modal Approaches”

Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection.

Airborne LiDAR bathymetry (ALB) has proven to be an effective technology for shallow water mapping. To collect data with a high point density, a lightweight dual-wavelength LiDAR system mounted on unmanned aerial vehicles (UAVs) was developed. This study presents and evaluates the system using the field data acquired from a flight test in Dazhou Island, China. In the precision and accuracy assessment, the local fitted planes extracted from the water surface points and the multibeam echosounder data are used as a reference for water surface and bottom measurements, respectively. For the bathymetric performance comparison, the study area is also measured with an ALB system installed on the manned aerial platform. The object detection capability of the system is examined with placed small cubes. Results show that the fitting precision of the water surface is 0.1227 m, and the absolute accuracy of the water bottom is 0.1268 m, both of which reach a decimeter level. Compared to the manned ALB system, the UAV-borne system provides higher resolution data with an average point density of 42 points/m2 and maximum detectable depth of 1.7–1.9 Secchi depths. In the point cloud of the water bottom, the existence of a 1-m target cube and the rough shape of a 2-m target cube are clearly observed at a depth of 12 m. The system shows great potential for flexible shallow water mapping and underwater object detection with promising results.

Bathymetry and Benthic Habitat Mapping in Shallow Waters From Sentinel-2A Imagery: A Case Study in Xisha Islands, China

Mapping of benthic habitats and bathymetry is crucial for sustainable development and assessment of climate change and human activities. In this study, Hyperspectral Optimization Process Exemplar (HOPE) was modified, renamed as M-HOPE, to simultaneously obtain bathymetry and benthic habitat in shallow waters in Xisha Island, China. A local lookup table (LUT) for benthic reflectance spectra was established. Validation using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> measurements demonstrated good performance of M-HOPE with a R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.76 for bathymetry using the local LUT. Application of M-HOPE to Sentinel-2A imagery further proved good accuracy of M-HOPE derived bathymetry with a R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.86 against <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> observations and a R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.92 against ICESat-2 measurements. M-HOPE-derived benthic classification also agreed well with field observations with probability of detection (POD) > 0.6 and false alarm ratio (FAR) < 0.5. However, uncertainties exist, mainly caused by mixed benthic types, atmospheric correction, and similarity in spectral reflectance of different benthic types.

Vessel-Based, Shallow Water Mapping with a Phase-Measuring Sidescan Sonar

Vessel-Based, Shallow Water Mapping with a Phase-Measuring Sidescan Sonar

A semi-empirical scheme for bathymetric mapping in shallow water by ICESat-2 and Sentinel-2: A case study in the South China Sea

To derive shallow water bathymetry for coastal areas, a common approach is to deploy a scanning airborne bathymetric light detection and ranging (LiDAR) system or a shipborne echosounder for ground surveys. However, recent advancements in satellite remote sensing, including the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) offer new tools for generating satellite derived bathymetry (SDB). The key payload onboard ICESat-2 is the Advanced Topographic Laser Altimeter System (ATLAS), a micro-pulse, photon-counting LiDAR system, simultaneously emitting six separate 532 nm beams at 10 kHz pulse rate. However, despite its high resolution, the major limitation for bathymetry is that ICESat-2 only provides along-track height profiles, leaving observation gaps between the parallel ground tracks. Merging ICESat-2 observations with optical multispectral imagery, as demonstrated herein, provides an effective solution for deriving a full scene of water depth in light of the spectral attenuation behavior.This study aims to combine ICESat-2 and Sentinel-2 optical data to derive shallow water bathymetry (depth <20 m) at six islands and reefs in the South China Sea. ICESat-2 ATL03 point clouds of georeferenced photons are first filtered to determine the seafloor elevation along the ground track. Results indicate a root-mean-square error (RMSE) of 0.26–0.61 m as compared with independent observations from an airborne LiDAR campaign. Next, three semi-empirical functions, namely the Modified Linear/Polynomial/Exponential Ratio Models with its kernel formed by the log ratio between Sentinel-2′s green and blue bands, are used to fit the spectral data with ICESat-2 height profiles. After water depth mapping using the trained model, independent ICESat-2 point clouds are used to validate the Sentinel-2 derived bathymetry. The RMSE values of the three models using the weighted average of multiple images for these six islands are within 0.50–0.90 m in 0–15 m deep. We also demonstrate that a synthesis of satellite laser altimetry and optical remote sensing can produce SDB results that potentially meet the requirement of category C in Zones of Confidence (ZOC) of the Electronic Navigational Chart (ENC) in 0–8 m deep. It is foreseen that ICESat-2 will be a helpful tool for mapping coastal and shallow waters around the world especially where bathymetric data are unavailable.

UAV-Derived Multispectral Bathymetry

Bathymetry is considered an important component in marine applications as several coastal erosion monitoring and engineering projects are carried out in this field. It is traditionally acquired via shipboard echo sounding, but nowadays, multispectral satellite imagery is also commonly applied using different remote sensing-based algorithms. Satellite-Derived Bathymetry (SDB) relates the surface reflectance of shallow coastal waters to the depth of the water column. The present study shows the results of the application of Stumpf and Lyzenga algorithms to derive the bathymetry for a small area using an Unmanned Aerial Vehicle (UAV), also known as a drone, equipped with a multispectral camera acquiring images in the same WorldView-2 satellite sensor spectral bands. A hydrographic Multibeam Echosounder survey was performed in the same period in order to validate the method’s results and accuracy. The study area was approximately 0.5 km2 and located in Tuscany (Italy). Because of the high percentage of water in the images, a new methodology was also implemented for producing a georeferenced orthophoto mosaic. UAV multispectral images were processed to retrieve bathymetric data for testing different band combinations and evaluating the accuracy as a function of the density and quantity of sea bottom control points. Our results indicate that UAV-Derived Bathymetry (UDB) permits an accuracy of about 20 cm to be obtained in bathymetric mapping in shallow waters, minimizing operative expenses and giving the possibility to program a coastal monitoring surveying activity. The full sea bottom coverage obtained using this methodology permits detailed Digital Elevation Models (DEMs) comparable to a Multibeam Echosounder survey, and can also be applied in very shallow waters, where the traditional hydrographic approach requires hard fieldwork and presents operational limits.

Combined geometric-radiometric and neural network approach to shallow bathymetric mapping with UAS imagery

There is a pressing need for shallow bathymetry in regions around the world, including in fragile marine ecosystems, such as coral reefs. Unfortunately, mapping these shallow-water areas using in situ or boat-based methods is expensive, time consuming, and potentially dangerous, due to the need to put personnel and/or boats in high-energy nearshore areas, which may contain rocks, reefs, and other submerged hazards. For this reason, passive remote sensing methods of shallow bathymetric mapping have been rapidly growing in interest and usage. Two general categories of approaches using passive imaging can be distinguished as: (1) those based on geometry (stereo-photogrammetry); (2) those based on radiometry (attenuation of light in the water column). These two broad categories of approaches have been tested on imagery collected using aircraft and satellites in numerous previous studies. Recent work within the geometric category includes processing unmanned aircraft system (UAS) imagery using Structure from Motion and Multi-View Stereo (SfM-MVS) photogrammetry, while radiometric methods encompass the broad range of spectral bathymetry retrieval algorithms. Each broad approach category has advantages and disadvantages. Fortunately, the geometric and radiometric approaches are highly complementary. The geometric approaches tend to work best in areas of high bottom texture, which facilitates feature matching in the SfM-MVS software. Meanwhile, the radiometric approaches work best in relatively homogeneous bottom types. To leverage the strengths of each type of approach and overcome their respective weaknesses, this work develops and tests a combined geometric-radiometric bathymetric mapping approach designed for shallow-water mapping from UAS imagery. Four radiometric models of varying complexity are tested, ranging from a color-based lookup table approach to neural networks. Two UAS flights on Buck Island, off St Croix in the U.S. Virgin Islands (USVI), are used to assess the accuracy of the methodology when compared to aerial bathymetric lidar data. The results show that the combined geometric-radiometric approach provides an increase in spatial coverage of up to 61% and improvement (i.e. decrease) in 95th percentile error of up to 49% when compared to traditional refraction-corrected SfM-MVS bathymetry.

Towards Routine Mapping of Shallow Bathymetry in Environments with Variable Turbidity: Contribution of Sentinel-2A/B Satellites Mission

Satellite-Derived Bathymetry (SDB) has significant potential to enhance our knowledge of Earth’s coastal regions. However, SDB still has limitations when applied to the turbid, but optically shallow, nearshore regions that encompass large areas of the world’s coastal zone. Turbid water produces false shoaling in the imagery, constraining SDB for its routine application. This paper provides a framework that enables us to derive valid SDB over moderately turbid environments by using the high revisit time (5-day) of the Sentinel-2A/B twin mission from the Copernicus programme. The proposed methodology incorporates a robust atmospheric correction, a multi-scene compositing method to reduce the impact of turbidity, and a switching model to improve mapping in shallow water. Two study sites in United States are explored due to their varying water transparency conditions. Our results show that the approach yields accurate SDB, with median errors of under 0.5 m for depths 0–13 m when validated with lidar surveys, errors that favorably compare to uses of SDB in clear water. The approach allows for the semi-automated creation of bathymetric maps at 10 m spatial resolution, with manual intervention potentially limited only to the calibration to the absolute SDB. It also returns turbidity data to indicate areas that may still have residual shoaling bias. Because minimal in-situ information is required, this computationally-efficient technique has the potential for automated implementation, allowing rapid and repeated application in more environments than most existing methods, thereby helping with a range of issues in coastal research, management, and navigation.

Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters

Although aerial image-based bathymetric mapping can provide, unlike acoustic or LiDAR (Light Detection and Ranging) sensors, both water depth and visual information, water refraction poses significant challenges for accurate depth estimation. In order to tackle this challenge, we propose an image correction methodology, which first exploits recent machine learning procedures that recover depth from image-based dense point clouds and then corrects refraction on the original imaging dataset. This way, the structure from motion (SfM) and multi-view stereo (MVS) processing pipelines are executed on a refraction-free set of aerial datasets, resulting in highly accurate bathymetric maps. Performed experiments and validation were based on datasets acquired during optimal sea state conditions and derived from four different test-sites characterized by excellent sea bottom visibility and textured seabed. Results demonstrated the high potential of our approach, both in terms of bathymetric accuracy, as well as texture and orthoimage quality.

Synergistic Use of UAV and USV Data and Petrographic Analyses for the Investigation of Beachrock Formations: A Case Study from Syros Island, Aegean Sea, Greece

Up until the last ten years, remote sensing data and especially high-resolution satellite data and airphotos were mainly used in shallow water mapping. The evolution and low cost of unmanned aerial vehicles (UAVs) provides a new tool for coastal area monitoring. This paper presents the synergistic use of a small commercial UAV and an unmanned surface vehicle (USV) for beachrock mapping in Syros Island, Greece. RGB images collected with a quadcopter were processed using Structure from Motion (SFM) photogrammetry in order to create digital surface models (DSMs) and orthophotos of the coastline. A beachrock lying in shallow waters was detected and mapped using the UAV derived products. At the same time, a USV equipped with a compact side scan sonar (SSS) and bathymetric sonar system, provided the shape of the beachrock by mosaicking the backscatter strength of the SSS. In order to evaluate the results of the UAV and USV data derivatives, the beachrock perimeter and its depth were also mapped using a differential global navigation satellite system (GNSS) receiver. During the fieldwork, samples from the beachrock were collected and analyzed in the laboratory. The mineralogical composition of the bulk samples was determined by powder X-ray diffraction (XRD). Further petrographic study was also performed by petrographic polarizing microscope, macroscope, and scanning electron microscopy (SEM). Beachrock samples are classified as fine to medium grain sandstones and conglomerates. The mineral compositions of their grains and lithoclasts reflect the bedrocks of Syros Island (mainly metamorphic rocks) while a micritic high-Mg calcite constitutes the cement of these rocks.

Shallow Off-Shore Archaeological Prospection with 3-D Electrical Resistivity Tomography: The Case of Olous (Modern Elounda), Greece

It is well known that nowadays as well as in the past the vast majority of human habitation and activities are mainly concentrated in littoral areas. Thus the increased attention to coastal zone management contributed to the development and implementation of shallow-water mapping approaches for capturing current environmental conditions. During the last decade, geophysical imaging techniques like electrical resistivity tomography (ERT) have been used in mapping onshore buried antiquities in a non-destructive manner, contributing to cultural heritage management. Despite its increased implementation in mapping on-shore buried archaeological remains, ERT has minimal to non-existent employment for the understanding of the past dynamics in littoral and shallow off-shore marine environments. This work presents the results of an extensive ERT survey in investigating part of the Hellenistic to Byzantine submerged archaeological site of Olous, located on the north-eastern coast of Crete, Greece. A marine area of 7100 m2 was covered with 178 densely spaced ERT lines having a cumulative length of 8.3 km. A combination of submerged static and moving survey modes were used to document potential buried and submerged structures. The acquired data from the marine environment were processed with two-dimensional and three-dimensional inversion algorithms. A real time kinematic global navigation satellite system was used to map the visible submerged walls and compile the bathymetry model of the bay. The adaptation of ERT in reconstructing the underwater archaeological remains in a shallow marine environment presented specific methodological and processing challenges. The in situ experience from the archaeological site of Olous showed that ERT provided a robust method for mapping the submerged archaeological structures related to the ancient built environment (walls, buildings, roads), signifying at the same time the vertical stratigraphy of the submerged sediments. The inherent limitation of employing ERT in a conductive environment is counterbalanced by the incorporation of precise knowledge for the conductivity and bathymetry of the saline water in the modelling and inversion procedure. Although the methodology definitely needs further refinement, the overall outcomes of this work underline the potential of ERT imaging being integrated into wider shallow marine projects for the mapping of archaeological sites in similar environmental regimes.

Reweighted sparse source-location acoustic mapping in shallow water

Various applications for monitoring and surveillance in littoral waters rely on passive sonar for localizing acoustic sources in shallow-water environments. Although adaptive matched-field processing (MFP) has been successfully used for localization, its performance is degraded when localizing multiple sources at low signal-to-noise ratios (SNRs) and in the presence of model mismatch. Robust MFP using, e.g., the white-noise constraint offers an alternative to cope with the mismatch issue but remains ineffective in the multisource and low SNR setup. This work capitalizes on sparsity for constructing a source location map for shallow water environments. Sparsity naturally arises since only locations corresponding to acoustic sources are expected to appear in the map (nonzero entries), while the remaining map locations are empty (zero entries). A high-resolution map is constructed via a two-step approach that capitalizes on a model for the acoustic propagation environment while being robust to model mismatch. During the first step the robust map is obtained by solving a regularized least-squares (LS) problem. Then, the map coefficients are used to devise a modified criterion with a weighted regularizer yielding a lower-ambiguity map, facilitating detection of quiet sources in the presence of loud interferers.

Intercomparison of shallow water bathymetry, hydro‐optics, and benthos mapping techniques in Australian and Caribbean coastal environments

Science, resource management, and defense need algorithms capable of using airborne or satellite imagery to accurately map bathymetry, water quality, and substrate composition in optically shallow waters. Although a variety of inversion algorithms are available, there has been limited assessment of performance and no work has been published comparing their accuracy and efficiency. This paper compares the absolute and relative accuracies and computational efficiencies of one empirical and five radiative‐transfer‐based published approaches applied to coastal sites at Lee Stocking Island in the Bahamas and Moreton Bay in eastern Australia. These sites have published airborne hyperspectral data and field data. The assessment showed that (1) radiative‐transfer—based methods were more accurate than the empirical approach for bathymetric retrieval, and the accuracies and processing times were inversely related to the complexity of the models used; (2) all inversion methods provided moderately accurate retrievals of bathymetry, water column inherent optical properties, and benthic reflectance in waters less than 13 m deep with homogeneous to heterogeneous benthic/ substrate covers; (3) slightly higher accuracy retrievals were obtained from locally parameterized methods; and (4) no method compared here can be considered optimal for all situations. The results provide a guide to the conditions where each approach may be used (available image and field data and processing capability). A re‐analysis of these same or additional sites with satellite hyperspectral data with lower spatial and radiometric resolution, but higher temporal resolution would be instructive to establish guidelines for repeatable regional to global scale shallow water mapping approaches.

Land-Water Interface Resolved from Airborne LIDAR Bathymetry (ALB) Waveforms

Abstract Airborne light detection and ranging (LIDAR) bathymetry (ALB) is an efficient remote-sensing technique for shallow-water mapping using green-channel waveforms. In addition to the green-channel waveforms, the SHOALS-3000 ALB system collects laser measurements in the red and infrared channels. The goal of this study was to evaluate the capacity of the ALB system to discriminate between land and water using all available channels in the system. This paper provides a review of all currently available ALB-based land-water interface algorithms (green-, red-, and infrared-channel waveforms) and a quantitative evaluation of the algorithms' performance on the basis of both individual laser measurement products and the resulting shoreline vector feature. Data for this study were collected with the use of a SHOALS-3000 system over five study sites along the New Hampshire and Maine coastlines that contain rocks, vegetation, and man-made features. All ALB shoreline algorithms show successful results in discri...

Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths

Sun glint, the specular reflection of light from water surfaces, is a serious confounding factor for remote sensing of water column properties and benthos. This paper reviews current techniques to estimate and remove the glint radiance component from imagery. Methods for processing of ocean color images use statistical sea surface models to predict the glint from the sun and sensor positions and wind data. Methods for higher resolution imaging, used in coastal and shallow water mapping, estimate the glint radiance from the near-infrared signal. The effects of some current methods are demonstrated and possibilities for future techniques are briefly addressed.

SeaWASP: A Small Waterplane Area Twin Hull Autonomous Platform for Shallow Water Mapping

AbstractStudents with Santa Clara University (SCU) and the Monterey Bay Aquarium Research Institute (MBARI) are developing an innovative platform for shallow water bathymetry. Bathymetry data is used to analyze the geography, ecosystem, and health of marine habitats. Current methods for shallow water measurements typically involve large manned vessels that are costly to operate and that may pose a danger to themselves and the environment in shallow, semi-navigable waters. Small vessels, however, are prone to disturbances by shallow water waves, tides, and currents, thereby requiring more instrumentation and computation to accurately process bathymetric data. The SCU/MBARI autonomous surface vessel, SeaWASP, is designed to operate safely and stably in waters as shallow as 1 m without significant manned support in order to produce cost-effective and high-quality bathymetric maps.The SeaWASP design introduces several key design innovations in order to provide high-quality maps with a platform that is safe, stable, and inexpensive. A small waterplane area twin hull (SWATH) design features a submerged dual hull, a small waterplane area, and a high mass-to-damping ratio, thereby making the craft less prone to disturbances. Precision sensing, autonomous control, and platform-level configuration planning and control algorithms are used to navigate the boat along desirable trajectories in support of efficient map generation and to implement low-cost unpiloted operations. Bathymetry is measured with multibeam sonar in concert with Doppler Velocity Logger and GPS sensors.The vessel has been operated successfully in several open water test environments, including Elkhorn Slough, Steven’s Creek Reservoir, and Lake Tahoe, all in California. It is currently in the final stages of integration and test for its first major science mission at Orcas Island, San Juan Islands, WA, in 2009. Final deployment will be at the National Oceanographic and Atmospheric Administration's (NOAA’s) Kasitsna Bay Laboratory in Alaska as one element of a multi-system remote observatory.SeaWASP has been developed in partnership with SCU, MBARI, the University of Alaska‐Fairbanks, and NOAA’s West Coast and Polar Regions Undersea Research Center.