Search Results (11)

Synthetic aperture radar (SAR) imagers are active microwave sensors that could overcome many challenges of passive optical bathymetry inversion, yet their capacity to yield accurate high-resolution bathymetric mapping is not studied sufficiently. In this study, we evaluate the feasibility of applying fast Fourier transform (FFT) to SAR data in coastal nearshore bathymetry derivation in Florida’s coastal waters. The study aims to develop a robust SAR bathymetry inversion framework across extensive spatial scales to address the dearth of bathymetric data in deeper nearshore coastal regions. By leveraging the Sentinel-1 datasets as a rich source of training data, our method yields high-resolution and accurate depth extraction up to 80 m. A comprehensive workflow to determine both the wavelength and peak wave period is associated with the proposed automated model compilation. A novel contour geometry-based spectral analysis technique for wavelength retrieval is presented that enables an efficient and scalable SAR bathymetry model. Multi-date SAR images were used to assess the robustness of the proposed depth-retrieval model. An accuracy assessment against the GMRT data demonstrated the high efficacy of the proposed approach, achieving a coefficient of determination ($R^2$) above 0.95, a root-mean-square error (RMSE) of 1.56–10.20 m, and relative errors of 3.56–11.08% in automatically extracting the underwater terrain at every 50 m interval. A sensitivity analysis was conducted to estimate the uncertainty associated with our method. Overall, this study highlights the potential of SAR technology to produce updated, cost-effective, and accurate bathymetry maps of high resolution and to fill bathymetric data gaps worldwide. The code and datasets are made publicly available. Full article

Deep-sea environments face increasing pressure from anthropogenic exploitation and climate change, but remain poorly studied. Hence, there is an urgent need to compile quantitative baseline data on faunal assemblages, and improve our understanding of the processes that drive faunal assemblage composition in deep-sea environments. The Southwest Atlantic deep sea is an undersampled region that hosts unique and globally important faunal assemblages. To date, our knowledge of these assemblages has been predominantly based on ex situ analysis of scientific trawl and fisheries bycatch specimens, limiting our ability to characterise faunal assemblages. Incidental sampling and fisheries bycatch data indicate that the Falkland Islands deep sea hosts a diversity of fauna, including vulnerable marine ecosystem (VME) indicator taxa. To increase our knowledge of Southwest Atlantic deep-sea epibenthic megafauna assemblages, benthic imagery, comprising 696 images collected along the upper slope (1070–1880 m) of the Falkland Islands conservation zones (FCZs) in 2014, was annotated, with epibenthic megafauna and substrata recorded. A suite of terrain derivatives were also calculated from GEBCO bathymetry and oceanographic variables extracted from global models. The environmental conditions coincident with annotated image locations were calculated, and multivariate analysis was undertaken using 288 ‘sample’ images to characterize faunal assemblages and discern their environmental drivers. Three main faunal assemblages representing two different sea pen and cup coral assemblages, and an assemblage characterised by sponges and Stylasteridae, were identified. Subvariants driven by varying dominance of sponges, Stylasteridae, and the stony coral, Bathelia candida, were also observed. The fauna observed are consistent with that recorded for the wider southern Patagonian Slope. Several faunal assemblages had attributes of VMEs. Faunal assemblages appear to be influenced by the interaction between topography and the Falkland Current, which, in turn, likely influences substrata and food availability. Our quantitative analyses provide a baseline for the southern Patagonian shelf/slope environment of the FCZs, against which to compare other assemblages and assess environmental drivers and anthropogenic impacts. Full article

Identifying the locations of hydrothermal chimneys across mapped areas of seafloor spreading ridges unlocks the ability to research questions about their correlations to geology, the cooling of the lithosphere, and deep-sea biogeography. We developed a Chimney Identification Tool (CIT) that utilizes a Convolutional Neural Network (CNN) to classify 1 m gridded AUV bathymetry and identify the locations of hydrothermal vent chimneys. A CNN is a type of Machine-Learning model that is able to classify raster data based on the shapes and textures in the input, making it ideal for this task. The criteria that have been used in previous manual classifications of chimneys have focused on the round base and spire shape of the features, and are not easily quantifiable. Machine-Learning techniques have previously been implemented with sonar data to classify seafloor geology, but this is the first application of these methods to hydrothermal systems. In developing the CIT, we compiled the bathymetry data from two rasters from the Endeavor Ridge—each gridded at a 1 m resolution—containing 34 locations of known hydrothermal chimneys, and from the 92° W segment of the Galapagos Spreading Center (GSC) containing 14. The CIT produced a primary group of outputs with 96% agreement with the manual classification; moreover, it correctly caught 29 of the 34 known chimneys from Endeavor and 10 of the 14 from the GSC. The CIT is trained to identify features with the characteristic shape of a hydrothermal vent chimney; therefore, it is susceptible to the misclassification of unusually shaped cases, given the limited training data. As a result, to provide the option of having a more inclusive application, the CIT also produced a secondary group of output locations with 61% agreement with the manual classification; moreover, it caught three of the four additional known chimneys from the GSC and four of the five from Endeavor. The CIT will be used in future investigations where an inventory of individual chimneys is important, such as the cataloguing of off-axis hydrothermal venting and the investigation of chimney distribution in connection to seafloor eruptions. Full article

Digital Elevation Models (DEMs) are widely used as a proxy for bathymetric data and several studies have attempted to improve DEM accuracy for hydrodynamic (HD) modeling. Most of these studies attempted to quantitatively improve estimates of channel conveyance (assuming a non-braided morphology) rather than accounting for the actual channel planform. Accurate representation of river conveyance and planform in a DEM is critical to HD modeling and can be achieved with a combination of remote sensing (e.g., satellite image) and field data, such as water surface elevation (WSE). Therefore, the objectives of this study are (i) to develop an algorithm for predicting channel conveyance and characterizing planform via satellite images and in situ WSE and (ii) to estimate discharge using the predicted conveyance via an HD model. The algorithm is named River Bathymetry via Satellite Image Compilation (RiBaSIC) and uses Landsat satellite imagery, Shuttle Radar Topography Mission (SRTM) DEM, Multi-Error-Removed Improved-Terrain (MERIT) DEM, and observed WSE. The algorithm is tested on four study areas along the Willamette River, Kushiyara River, Jamuna River, and Solimoes River. Channel slope and predicted hydraulic radius are subsequently estimated for approximating Manning’s roughness factor. Two-dimensional HD models using DEMs modified by the RiBaSIC algorithm and corresponding Manning’s roughness factors are employed for discharge estimation. The proposed algorithm can represent river planform and conveyance in single-channeled, meandering, wandering, and braided river reaches. Additionally, the HD models estimated discharge within 14–19% relative root mean squared error (RRMSE) in simulation of five years period. Full article

We defined the bathymetry of Shelikof Strait and the western Gulf of Alaska (WGOA) from the edges of the land masses down to about 7000 m deep in the Aleutian Trench. This map was produced by combining soundings from historical National Ocean Service (NOS) smooth sheets (2.7 million soundings); shallow multibeam and LIDAR (light detection and ranging) data sets from the NOS and others (subsampled to 2.6 million soundings); and deep multibeam (subsampled to 3.3 million soundings), single-beam, and underway files from fisheries research cruises (9.1 million soundings). These legacy smooth sheet data, some over a century old, were the best descriptor of much of the shallower and inshore areas, but they are superseded by the newer multibeam and LIDAR, where available. Much of the offshore area is only mapped by non-hydrographic single-beam and underway files. We combined these disparate data sets by proofing them against their source files, where possible, in an attempt to preserve seafloor features for research purposes. We also attempted to minimize bathymetric data errors so that they would not create artificial seafloor features that might impact such analyses. The main result of the bathymetry compilation is that we observe abundant features related to glaciation of the shelf of Alaska during the Last Glacial Maximum including abundant end moraines, some medial moraines, glacial lineations, eskers, iceberg ploughmarks, and two types of pockmarks. We developed an integrated onshore–offshore geomorphic map of the region that includes glacial flow directions, moraines, and iceberg ploughmarks to better define the form and flow of former ice masses. Full article

The U.S. Geological Survey (USGS) and the National Oceanic Atmospheric Administration (NOAA) have collected approximately 5400 km² of geophysical and hydrographic data on the Atlantic continental shelf between Delaware and Virginia over the past decade and a half. Although originally acquired for different objectives, the comprehensive coverage and variety of data (bathymetry, backscatter, imagery and physical samples) presents an opportunity to merge collections and create high-resolution, broad-scale geologic maps of the seafloor. This compilation of data repurposes hydrographic data, expands the area of geologic investigation, highlights the versatility of mapping data, and creates new geologic products that would not have been independently possible. The data are classified using a variety of machine learning algorithms, including unsupervised and supervised methods. Four unique classes were targeted for classification, and source data include bathymetry, backscatter, slope, curvature, and shaded-relief. A random forest classifier used on all five source data layers was found to be the most accurate method for these data. Geomorphologic and sediment texture maps are derived from the classified acoustic data using over 200 ground truth samples. The geologic data products can be used to identify sediment sources, inform resource management, link seafloor environments to sediment texture, improve our understanding of the seafloor structure and sediment pathways, and demonstrate how ocean mapping resources can be useful beyond their original intent to maximize the footprint and scientific impact of a study. Full article

Over the past two decades, persistent occurrences of harmful algal blooms (HAB; Karenia brevis) have been reported in Charlotte County, southwestern Florida. We developed data-driven models that rely on spatiotemporal remote sensing and field data to identify factors controlling HAB propagation, provide a same-day distribution (nowcasting), and forecast their occurrences up to three days in advance. We constructed multivariate regression models using historical HAB occurrences (213 events reported from January 2010 to October 2017) compiled by the Florida Fish and Wildlife Conservation Commission and validated the models against a subset (20%) of the historical events. The models were designed to capture the onset of the HABs instead of those that developed days earlier and continued thereafter. A prototype of an early warning system was developed through a threefold exercise. The first step involved the automatic downloading and processing of daily Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua products using SeaDAS ocean color processing software to extract temporal and spatial variations of remote sensing-based variables over the study area. The second step involved the development of a multivariate regression model for same-day mapping of HABs and similar subsequent models for forecasting HAB occurrences one, two, and three days in advance. Eleven remote sensing variables and two non-remote sensing variables were used as inputs for the generated models. In the third and final step, model outputs (same-day and forecasted distribution of HABs) were posted automatically on a web map. Our findings include: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, sea surface temperature (SST), ocean chlorophyll three-band algorithm for MODIS [chlorophyll-a OC3M] and distance from the river mouth, and (2) the model predictions were 90% successful for same-day mapping and 65%, 72% and 71% for the one-, two- and three-day advance predictions, respectively. The adopted methodologies are reliable at a local scale, dependent on readily available remote sensing data, and cost-effective and thus could potentially be used to map and forecast algal bloom occurrences in data-scarce regions. Full article

We created a new, 100 m horizontal resolution bathymetry raster and used it to define 29 canyons of the eastern Bering Sea (EBS) slope area off of Alaska, USA. To create this bathymetry surface we proofed, edited, and digitized 18 million soundings from over 200 individual sources. Despite the vast size (~1250 km long by ~3000 m high) and ecological significance of the EBS slope, there have been few hydrographic-quality charting cruises conducted in this area, so we relied mostly on uncalibrated underway files from cruises of convenience. The lack of hydrographic quality surveys, anecdotal reports of features such as pinnacles, and reliance on satellite altimetry data has created confusion in previous bathymetric compilations about the details along the slope, such as the shape and location of canyons along the edge of the slope, and hills and valleys on the adjacent shelf area. A better model of the EBS slope will be useful for geologists, oceanographers, and biologists studying the seafloor geomorphology and the unusually high productivity along this poorly understood seafloor feature. Full article

The paper discusses the results of a study of short-period internal waves (IWs) in the Black and Caspian Seas from their surface manifestations in satellite imagery. Since tides are negligible in these seas, they can be considered non-tidal. Consequently, the main generation mechanism of IWs in the ocean—interaction of barotropic tides with bathymetry—is irrelevant. A statistically significant survey of IW occurrences in various regions of the two seas is presented. Detailed maps of spatial distribution of surface manifestations of internal waves (SMIWs) are compiled. Factors facilitating generation of IWs are determined, and a comprehensive discussion of IW generation mechanisms is presented. In the eastern and western coastal zones of the Black Sea, where large rivers disembogue, intrusions of fresh water create hydrological fronts that are able to generate IWs. At the continental shelf edge, on the west and northwest of the Black Sea and near the Crimean Peninsula, IWs are generated primarily due to relaxation of coastal upwelling and inertial oscillations associated with hydrological fronts. In addition, IWs can be formed at sea fronts associated with the passage of cold eddies. In the Caspian Sea, seiches are the main source of the observed IWs. Full article

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. Full article

This study compiled a wide range of modern and historic geospatial datasets to examine ecological and geomorphic change at Diego Garcia Atoll across a 38-year period (1967–2005). This remarkable collection of spatially referenced information offered an opportunity to advance our understanding of the nature and extent of environmental change that has taken place with the construction of the military airbase at Diego Garcia. Changes assessed included movements of the lagoon rim shorelines, changes in the terrestrial vegetation on the lagoon rim and amendments to the bathymetry of the lagoon basin through dredging activities. Data compiled included detailed shoreline and vegetation maps produced as part of the H.M.S. Vidal Indian Ocean Expedition (1967), three Ikonos satellite images acquired in 2005 that collectively covered the complete Atoll area, a ground truthing field dataset collected in the northern section of the lagoon for the purpose of seafloor mapping (2005), observational evidence of shoreline erosion including photographs and descriptions of seawater inundations and bathymetric soundings from five independent surveys of the lagoon floor (1967, 1985, 1987, 1988 and 1997). Results indicated that much of the change along the lagoon rim is associated with the expansion of the inner lagoon shoreline as a result of the construction of the military airbase, with an estimated increase in land area of 3.01 km² in this portion of the atoll rim. Comparisons of 69 rim width transects measured from 1967 and 2005 indicated that shorelines are both eroding (26 transects) and accreting (43 transects). Within a total vegetated area of 24 km², there was a notable transition from Cocos Woodland to Broadleaf Woodland for a land area of 5.6 km². From the hydrographic surveys, it was estimated that approximately 0.55 km³ of carbonate sediment material has been removed from the northwest quadrant of the lagoon, particularly in the vicinity of the Main Passage. As no previous record of benthic character exists, a complete benthic habitat map of the atoll was derived through classification of the three IKONOS satellite images. Management implications arising from this overall appraisal of geomorphic and ecological change at Diego Garcia included the need for ongoing monitoring of shoreline change at a representative set of sites around the atoll rim, monitoring of the water flow regime through the northern channels between the open ocean and the lagoon basin and an ongoing mapping campaign to record periodic changes in the character of the benthic surface ecology. Full article