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At least 775 records · Page 43Linked to original sources
USGS2025

Phytoplankton biomass dynamics in wet (2019) and dry (2023) years in Lake Pontchartrain estuary, Louisiana from Sentinel 2-MSI and PACE-OCI observations

This study provides a comprehensive assessment of phytoplankton biomass dynamics in Lake Pontchartrain, Louisiana, by combining monthly water quality data with multispectral and hyperspectral satellite observations using a machine learning algorithm. A machine learning model based on Variational Autoencoder (VAE), globally applicable, was used to estimate phytoplankton biomass via chlorophyll- a (Chl- a ) from Sentinel 2-MSI and NASA's new hyperspectral mission, PACE-OCI, enabling the first direct comparison between the two sensors. The model performed well in this complex estuarine system, with higher accuracy from PACE-OCI (MAE: 1.48, RMSE: 10.40, slope: 0.87) than Sentinel 2-MSI (MAE: 1.57, RMSE: 11.08, slope: 0.83). This approach enabled continuous high-resolution monitoring of phytoplankton biomass across space and time. Comparative analysis of 2019, a wet year with Bonnet Carré Spillway (BCS) openings, and 2023, a dry year with extremely low riverine inputs, revealed distinct biomass dynamics. In 2019, BCS discharge initially suppressed Chl- a within turbid waters (<5 mg Chl- a m −3 ) but later acted as a nutrient and hydrodynamic driver, transporting nutrients toward the lake outlet and Mississippi coast, promoting high biomass (25–45 mg Chl- a m −3 ) near the entrance. In contrast, dry conditions in 2023 led to more frequent-than-expected high biomass (>35 mg Chl- a m −3 ), persisting in the lake center. Similar spatial patterns were observed again in 2024, revealed for the first time by PACE-OCI. This study demonstrates the value of satellite-derived observations for capturing transient phytoplankton biomass events and highlights the potential of PACE-OCI's hyperspectral capabilities to better distinguish phytoplankton communities and improve understanding of their responses to freshwater inflows and associated processes driving pulses into estuaries.

Louisiana↗
USGS2018

AutoCNet: A Python library for sparse multi-image correspondence identification for planetary data

In this work we describe the AutoCNet library, written in Python, to support the application of Computer Vision techniques for n-image correspondence identication in remotely sensed planetary images and subsequent bundle adjustment. The library is designed to support exploratory data analysis, algorithm and processing pipeline development, and application at scale in High Performance Computing (HPC) environments for processing large data sets and generating foundational data products. We also present a brief case study illustrating high level usage for the Apollo 15 Metric camera.

SoftwareX↗
USGS2024

Spatio-temporal ecological models via physics-informed neural networks for studying chronic wasting disease

To mitigate the negative effects of emerging wildlife diseases in biodiversity and public health it is critical to accurately forecast pathogen dissemination while incorporating relevant spatio-temporal covariates. Forecasting spatio-temporal processes can often be improved by incorporating scientific knowledge about the dynamics of the process using physical models. Ecological diffusion equations are often used to model epidemiological processes of wildlife diseases where environmental factors play a role in disease spread. Physics-informed neural networks (PINN) are deep learning algorithms that constrain neural network predictions based on physical laws and therefore are powerful forecasting models useful even in cases of limited and imperfect training data. In this paper, we develop a novel ecological modeling tool using PINNs, which fits a feedforward neural network and simultaneously performs parameter identification in a partial differential equation (PDE) with varying coefficients. We demonstrate the applicability of our model by comparing it with the commonly used Bayesian stochastic partial differential equation method and traditional machine learning approaches, showing that our proposed model exhibits superior prediction and forecasting performance when modeling chronic wasting disease in deer in Wisconsin. Furthermore, our model provides the opportunity to obtain scientific insights into spatiotemporal covariates affecting spread and growth of diseases. This work contributes to future machine learning and statistical methodology development by studying spatio-temporal processes enhanced by prior physical knowledge.

Spatial Statistics↗
USGS2003

Data-based comparisons of moments estimators using historical and paleoflood data

This paper presents the first systematic comparison, using historical and paleoflood data, of moments-based flood frequency methods. Peak flow estimates were compiled from streamflow-gaging stations with historical and/or paleoflood data at 36 sites located in the United States, Argentina, United Kingdom and China, covering a diverse range of hydrologic conditions. The Expected Moments Algorithm (EMA) and the Bulletin 17B historical weighting procedure (B17H) were compared in terms of goodness of fit using 25 of the data sets. Results from this comparison indicate that EMA is a viable alternative to current B17H procedures from an operational perspective, and performed equal to or better than B17H for the data analyzed. We demonstrate satisfactory EMA performance for the remaining 11 sites with multiple thresholds and binomial censoring, which B17H cannot accommodate. It is shown that the EMA estimator readily incorporates these types of information and the LP-III distribution provided an adequate fit to the data in most cases. The results shown here are consistent with Monte Carlo simulation studies, and demonstrate that EMA is preferred overall to B17H. The Bulletin 17B document could be revised to include an option for EMA as an alternative to the existing historical weighting approach. These results are of practical relevance to hydrologists and water resources managers for applications in floodplain management, design of hydraulic structures, and risk analysis for dams. ?? 2003 Elsevier Science B.V. All rights reserved.

Journal of Hydrology↗
USGS2002

Processing, mosaicking and management of the Monterey Bay digital sidescan-sonar images

Sidescan-sonar imaging systems with digital capabilities have now been available for approximately 20 years. In this paper we present several of the various digital image processing techniques developed by the U.S. Geological Survey (USGS) and used to apply intensity/radiometric and geometric corrections, as well as enhance and digitally mosaic, sidescan-sonar images of the Monterey Bay region. New software run by a WWW server was designed and implemented to allow very large image data sets, such as the digital mosaic, to be easily viewed interactively, including the ability to roam throughout the digital mosaic at the web site in either compressed or full 1-m resolution. The processing is separated into the two different stages: preprocessing and information extraction. In the preprocessing stage, sensor-specific algorithms are applied to correct for both geometric and intensity/radiometric distortions introduced by the sensor. This is followed by digital mosaicking of the track-line strips into quadrangle format which can be used as input to either visual or digital image analysis and interpretation. An automatic seam removal procedure was used in combination with an interactive digital feathering/stenciling procedure to help minimize tone or seam matching problems between image strips from adjacent track-lines. The sidescan-sonar image processing package is part of the USGS Mini Image Processing System (MIPS) and has been designed to process data collected by any 'generic' digital sidescan-sonar imaging system. The USGS MIPS software, developed over the last 20 years as a public domain package, is available on the WWW at: http://terraweb.wr.usgs.gov/trs/software.html.

Marine Geology↗
USGS2003

Moment-tensor solutions estimated using optimal filter theory: Global seismicity, 2001

This paper is the 12th in a series published yearly containing moment-tensor solutions computed at the US Geological Survey using an algorithm based on the theory of optimal filter design ( Sipkin, 1982 and Sipkin, 1986b ). An inversion has been attempted for all earthquakes with a magnitude, m b or M S , of 5.5 or greater. Previous listings include solutions for earthquakes that occurred from 1981 to 2000 ( Sipkin, 1986b ; Sipkin and Needham, 1989 , Sipkin and Needham, 1991 , Sipkin and Needham, 1992 , Sipkin and Needham, 1993 , Sipkin and Needham, 1994a and Sipkin and Needham, 1994b ; Sipkin and Zirbes, 1996 and Sipkin and Zirbes, 1997 ; Sipkin et al., 1998 , Sipkin et al., 1999 , Sipkin et al., 2000a , Sipkin et al., 2000b and Sipkin et al., 2002 ). The entire USGS moment-tensor catalog can be obtained via anonymous FTP at ftp://ghtftp.cr.usgs.gov . After logging on, change directory to “momten”. This directory contains two compressed ASCII files that contain the finalized solutions, “mt.lis.Z” and “fmech.lis.Z”. “mt.lis.Z” contains the elements of the moment tensors along with detailed event information; “fmech.lis.Z” contains the decompositions into the principal axes and best double-couples. The fast moment-tensor solutions for more recent events that have not yet been finalized and added to the catalog, are gathered by month in the files “jan01.lis.Z”, etc. “fmech.doc.Z” describes the various fields.

Physics of the Earth and Planetary Interiors↗
USGS2003

Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data

Knowledge of the distribution of vegetation on the landscape can be used to investigate ecosystem functioning. The sizes and movements of animal populations can be linked to resources provided by different plant species. This paper demonstrates the application of imaging spectroscopy to the study of vegetation in Yellowstone National Park (Yellowstone) using spectral feature analysis of data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data, acquired on August 7, 1996, were calibrated to surface reflectance using a radiative transfer model and field reflectance measurements of a ground calibration site. A spectral library of canopy reflectance signatures was created by averaging pixels of the calibrated AVIRIS data over areas of known forest and nonforest vegetation cover types in Yellowstone. Using continuum removal and least squares fitting algorithms in the US Geological Survey's Tetracorder expert system, the distributions of these vegetation types were determined by comparing the absorption features of vegetation in the spectral library with the spectra from the AVIRIS data. The 0.68 μm chlorophyll absorption feature and leaf water absorption features, centered near 0.98 and 1.20 μm, were analyzed. Nonforest cover types of sagebrush, grasslands, willows, sedges, and other wetland vegetation were mapped in the Lamar Valley of Yellowstone. Conifer cover types of lodgepole pine, whitebark pine, Douglas fir, and mixed Engelmann spruce/subalpine fir forests were spectrally discriminated and their distributions mapped in the AVIRIS images. In the Mount Washburn area of Yellowstone, a comparison of the AVIRIS map of forest cover types to a map derived from air photos resulted in an overall agreement of 74.1% (kappa statistic=0.62).

Wyoming↗
USGS2000

A diurnal animation of thermal images from a day-night pair

Interpretation of thermal images is often complicated because the physical property information is contained in both the spatial and temporal variations of the data and thermal models are necessary to extract and display this information. A linearized radiative transfer solution to the surface flux has been used to derive a function that is invariant with respect to thermal inertia. This relationship makes it possible to predict the temperature variation at any time in the diurnal cycle using only two distinct measurements (e.g., noon and midnight). An animation can then be constructed from a pair of day-night images to view both the spatial and temporal temperature changes throughout the diurnal cycle. A more complete solution for the invariant function, using the method of Laplace transforms and based on the linearized solution, was introduced. These results indicate that the linear model does not provide a sufficiently accurate estimate. Using standard conditions (latitude 30??, solar declination 0??, acquisition times at noon and midnight), this new relationship was used to predict temperature throughout the diurnal cycle to an rms error of 0.2??C, which is close to the system noise of most thermal scanners. The method was further extended to include the primary effects of topographic slope with similar accuracy. The temperature was computed at 48 equally spaced times in the diurnal cycle with this algorithm using a co-registered day and night TIMS (Thermal Infrared Multispectral Scanner) data pair (330 pixels, 450 lilies) acquired of the Carlin, Nevada, area and a co-registered DEM (Digital Elevation Model). (Any reader can view the results by downloading the animation file from an identified tip site). The results illustrate the power of animation to display subtle temporal and spatial temperature changes, which can provide clues to structural controls and material property differences. This 'visual change' approach could significantly increase the use of thermal data for environmental, hazard, and resource studies. Published by Elsevier Science Inc., 2000.A linearized radiative transfer solution of determining the surface flux is proposed to predict the temperature variation at any time in the diurnal cycle using only two distinct measurements. An animation is constructed from a pair of day-night images to view the spatial and temporal temperature changes throughout the diurnal cycle. The results illustrate the effectiveness of animation to display subtle temporal and spatial temperature changes, which can provide clues to structural controls and material property differences.

Remote Sensing of Environment↗
USGS2003

The IASPEI Seismological Software Library

Since computers became widely available in the early 1960s, seismologists have been using them for data acquisition, processing, and analysis, as well as theoretical computation and modeling. For example, the book by Doornbos (1988) contains a collection of seismological algorithms with the corresponding computer programs available on tape or disk from the World Data Center A for Solid Earth Geophysics. The introduction of personal computers in the early 1980s further revolutionized the use of computers for scientific research. Instead of expensive mainframe computers that required a large staff to operate, inexpensive personal computers allowed creative applications to be implemented by individuals with a shoestring budget.

International Geophysics↗
USGS2001

1r2dinv: A finite-difference model for inverse analysis of two dimensional linear or radial groundwater flow

We have developed a program for inverse analysis of two-dimensional linear or radial groundwater flow problems. The program, 1r2dinv, uses standard finite difference techniques to solve the groundwater flow equation for a horizontal or vertical plane with heterogeneous properties. In radial mode, the program simulates flow to a well in a vertical plane, transforming the radial flow equation into an equivalent problem in Cartesian coordinates. The physical parameters in the model are horizontal or x-direction hydraulic conductivity, anisotropy ratio (vertical to horizontal conductivity in a vertical model, y-direction to x-direction in a horizontal model), and specific storage. The program allows the user to specify arbitrary and independent zonations of these three parameters and also to specify which zonal parameter values are known and which are unknown. The Levenberg-Marquardt algorithm is used to estimate parameters from observed head values. Particularly powerful features of the program are the ability to perform simultaneous analysis of heads from different tests and the inclusion of the wellbore in the radial mode. These capabilities allow the program to be used for analysis of suites of well tests, such as multilevel slug tests or pumping tests in a tomographic format. The combination of information from tests stressing different vertical levels in an aquifer provides the means for accurately estimating vertical variations in conductivity, a factor profoundly influencing contaminant transport in the subsurface. ?? 2001 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗
USGS2003

Experimental and textural constraints on mafic enclave formation in volcanic rocks

We have used experiments and textural analysis to investigate the process of enclave formation during magma mixing at Southwest Trident volcano, Alaska. Andesite enclaves are present throughout the four dacite lava flows produced by the eruption, and resemble mafic enclaves commonly found in other volcanic rocks. Our experiments replicate the pressure–temperature–time path taken by enclave-forming andesite magma as it is engulfed in dacite during magma mixing. Pressure and temperature information for the andesite and dacite are from [Coombs et al., Contrib. Mineral. Petrol. 140 (2000) 99–118]. The andesite was annealed at 1000°C, and then cooled to 890°C at rates of 110°C h −1 , 10°C h −1 , and 2°C h −1 . Once cooled to 890°C, andesite was held at this lower temperature from times ranging from 1 to 40 h. The andesite that was cooled at the slower rates of 2°C h −1 and 10°C h −1 most resembles enclave groundmass texturally and compositionally. Based on simple thermal calculations, these rates are more consistent with cooling of the andesite groundmass below an andesite–dacite interface than with cooling of enclave-sized spheres. If enclaves do crystallize as spheres, post-crystallization disaggregation must occur. Calculations using the MELTS algorithm [Ghiorso and Sack, Contrib. Mineral. Petrol. 119 (1995) 197–212] show that for incoming andesite to become less dense than the dacite ∼34 volume % of its groundmass must crystallize to undergo ∼18 volume % vesiculation; these values are similar to those determined for Southwest Trident enclaves. Thus such crystallization may lead to ‘flotation’ of enclaves and be a viable mechanism for enclave formation and dispersal. The residual melt in the cooling experiments did not evolve to rhyolitic compositions such as seen in natural enclaves due to a lack of a decompression step in the experiments. Decompression experiments on Southwest Trident dacite suggest an average ascent rate for the eruption of ∼2–3 MPa h −1 . An andesite experiment that was cooled and then decompressed at this rate contains melt that matches that of the natural enclaves. It is apparent that decompression (ascent)-induced crystallization occurs in enclaves, but not in the form of microlites as happens in the dacite host, due either to insufficient residence time at chamber temperatures or to the pre-existing microphenocrysts which act as sites for new growth.

Alaska↗
USGS2006

Chapter 13 Petrogenesis of the Campanian Ignimbrite: Implications for crystal-melt separation and open-system processes from major and trace elements and Th isotopic data

The Campanian Ignimbrite is a large-volume trachytic to phonolitic ignimbrite that was deposited at ≈39.3 ka and represents one of a number of highly explosive volcanic events that have occurred in the region near Naples, Italy. Thermodynamic modeling using the MELTS algorithm reveals that major element variations are dominated by crystal-liquid separation at 0.15 GPa. Initial dissolved H 2 O content in the parental melt is ∼3 wt.% and the magmatic system fugacity of oxygen was buffered along QFM+1. Significantly, MELTS results also indicate that the liquid line of descent is marked by a large change in the proportion of melt (from 0.46 to 0.09) at ∼884°C, which leads to a discontinuity in melt composition (i.e., a compositional gap) and different thermodynamic and transport properties of melt and magma across the gap. Crystallization of alkali feldspar and plagioclase dominates the phase assemblage at this pseudo-invariant point temperature of ∼884°C. Evaluation of the variations in the trace elements Zr, Nb, Th, U, Rb, Sm, and Sr using a mass balance equation that accounts for changing bulk mineral-melt partition coefficients as crystallization occurs indicates that crystal-liquid separation and open-system processes were important. Th isotope data yield an apparent isochron that is ∼20 kyr younger than the age of the deposit, and age-corrected Th isotope data indicate that the magma body was an open system at the time of eruption. Because open-system behavior can profoundly change isotopic and elemental characteristics of a magma body, these Th results illustrate that it is critical to understand the contribution that open-system processes make to magmatic systems prior to assigning relevance to age or timescale information derived from such systems. Fluid-magma interaction has been proposed as a mechanism to change isotopic and elemental characteristics of magma bodies, but an evaluation of the mass and thermal constraints on such a process suggests large-scale interaction is unlikely. In the case of the magma body associated with the Campanian Ignimbrite, the most likely source of the open-system signatures is assimilation of partial melts of compositionally heterogeneous basement composed of cumulates and intrusive equivalents of volcanic activity that has characterized the Campanian region for over 300 kyr.

Developments in Volcanology↗
USGS2022

The future of coastal monitoring through satellite remote sensing

Satellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.

Cambridge Prisms: Coastal Futures↗
USGS2022

Assessing reproducibility in sedimentary macroscopic charcoal count data

Current understanding of global late Quaternary fire history is largely drawn from sedimentary charcoal data. Since publication, CharAnalysis increasingly has been relied upon as a robust method for analyzing these data. However, several underlying assumptions of the algorithm have not been tested. This study uses replicated charcoal count data to examine the assumption of Poisson distribution and reproducibility of peak detection. Results show <10% of the replicate counts are Poisson distributed, a maximum peak replication rate of 60%, and, for >90% of the data, intra-level count differences were larger than the threshold used to identify significance in inter-level differences. A pronounced “edge effect” was observed at the beginning and end of the records, cautioning against validation of results based on sections corresponding to the historical period. The proximal cause for low reproducibility is likely a lack of spatial randomness of charcoal particles at the scale of a core diameter. Until and unless decomposition methods can be developed that accommodate the observed limitations inherent in particle count data, best practices for interpreting charcoal records may be to rely on qualitative interpretations based on smoothed influx values and minimum particle count values in the hundreds.

Quaternary Research↗
USGS2011

Tsunami modelling with adaptively refined finite volume methods

Numerical modelling of transoceanic tsunami propagation, together with the detailed modelling of inundation of small-scale coastal regions, poses a number of algorithmic challenges. The depth-averaged shallow water equations can be used to reduce this to a time-dependent problem in two space dimensions, but even so it is crucial to use adaptive mesh refinement in order to efficiently handle the vast differences in spatial scales. This must be done in a 'wellbalanced' manner that accurately captures very small perturbations to the steady state of the ocean at rest. Inundation can be modelled by allowing cells to dynamically change from dry to wet, but this must also be done carefully near refinement boundaries. We discuss these issues in the context of Riemann-solver-based finite volume methods for tsunami modelling. Several examples are presented using the GeoClaw software, and sample codes are available to accompany the paper. The techniques discussed also apply to a variety of other geophysical flows. ?? 2011 Cambridge University Press.

Acta Numerica↗
USGS2015

Photometric properties of Vesta

The Dawn spacecraft orbited Asteroid (4) Vesta for a year, and returned disk-resolved images and spectra covering visible and near-infrared wavelengths at scales as high as 20 m/pix. The visible geometric albedo of Vesta is ~ 0.36. The disk-integrated phase function of Vesta in the visible wavelengths derived from Dawn approach data, previous ground-based observations, and Rosetta OSIRIS observations is consistent with an IAU H-G phase law with H=3.2 mag and G=0.28. Hapke's modeling yields a disk-averaged single-scattering albedo of 0.50, an asymmetry factor of -0.25, and a roughness parameter of ~20 deg at 700 nm wavelength. Vesta's surface displays the largest albedo variations observed so far on asteroids, ranging from ~0.10 to ~0.76 in geometric albedo in the visible wavelengths. The phase function of Vesta displays obvious systematic variations with respect to wavelength, with steeper slopes within the 1- and 2-micron pyroxene bands, consistent with previous ground-based observations and laboratory measurement of HED meteorites showing deeper bands at higher phase angles. The relatively high albedo of Vesta suggests significant contribution of multiple scattering. The non-linear effect of multiple scattering and the possible systematic variations of phase function with albedo across the surface of Vesta may invalidate the traditional algorithm of applying photometric correction on airless planetary surfaces.

Proceedings of the International Astronomical Unio↗
USGS2024

3-D geological modeling for numerical flow simulation studies of gas hydrate reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. This study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-step gridding were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a 3-D trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

Alaska↗
USGS2023

Wide-area debris field and seabed characterization of a deep ocean dump site surveyed by autonomous underwater vehicles

Disposal of industrial and hazardous waste in the deep ocean was a pervasive global practice near coastlines in the 20th century. Uncertainty in the quantity, location, and contents of dumped materials at historical disposal sites underscores ongoing risks to marine ecosystems and human health. This study presents analysis of a 150-km2 wide-area sidescan sonar survey conducted in March 2021 with two autonomous underwater vehicles (AUVs) at an offshore dumpsite in San Pedro Basin, California. Previous camera surveys located 60 barrels and other debris; sediment analysis in the region showed varying concentrations of the insecticidal chemical Dichlorodiphenyl-trichloroethane (DDT), for which an estimated 350-700 metric tons was discarded in the San Pedro Basin between 1947 and 1961. A lack of primary historical documents from Montrose Chemical or California Salvage Company that specify the DDT acid waste disposal method has contributed to the ambiguity surrounding whether the dumping method was via bulk discharge or containerized units. Barrels and debris visually detected during previous surveys by Remotely Operated Vehicles (ROVs) Jason and SuBastian and AUV Sentry served as the basis for ground truth testing and object classification using size and acoustic intensity characteristics. Target detection and classification algorithms were developed using image and signal processing techniques that resulted in the identification of over 74,000 debris targets within the survey region. Statistical, spectral, and machine learning techniques are used to characterize seabed variability and for bottom-type classification. These analytical techniques combined with the survey capabilities of AUVs provide a framework for efficient mapping and characterization of uncharted deep-water disposal sites.

California↗