@proceedings {7383, title = {Web-based Visualization of Integrated NextGeneration S-100 Hydrographic Datasets}, year = {2022}, month = {October 17-20}, address = {Hampton Roads, VA}, abstract = {

This paper discusses a variety of next-generation data products for marine navigation, many of which are encompassed by existing or planned S-100 standards developed by the International Hydrograph Organization. This includes electronic charts, bathymetric surfaces, shoreline lidar, and marine traffic and infrastructure features extracted from textual publications. A web-based visualization interface is presented, which demonstrates how these different data sources can be integrated together to support safer marine navigation, illustrate sailing directions, and aid efficient voyage planning.

}, keywords = {ENC, marine navigation, S-100, shoreline lidar, streamline flow visualization, web-based visualization}, doi = {10.1109/OCEANS47191.2022.9977133.}, author = {Butkiewicz, Thomas and Ilya Atkin and Briana M Sullivan and Christos Kastrisios and Andrew H. Stevens and Kindrat Beregovyi} } @article {7131, title = {New Hampshire Continental Shelf Geophysical Database: 2002-2005 Jeffreys Ledge Field Campaign {\textendash} Seafloor Photographs and Sediment Data}, year = {2021}, publisher = {University of New Hampshire}, chapter = {Center for Coastal and Ocean Mapping}, address = {Durham, NH}, abstract = {

Jeffreys Ledge is a major physiographic feature in the western Gulf of Maine (WGOM) located ~50 km off the coast of New Hampshire, although coming within ~10 km of shore by Cape Ann, Massachusetts. Jeffreys Ledge rises up as much as ~150 m from the seafloor of the adjacent basins (i.e., Scantum Basin or Wilkinson Basin) to depths less than 50 m on the ridge surface. The ridge extends over 100 km along its north-northeast to south-southwest axes while generally only being 5 to 10 km in width (~20 km maximum). Jeffreys Ledge and the surrounding region, like many features in the Gulf of Maine, most likely owes its origin and morphologic and sedimentologic features to a combination of fluvial erosion in the late Neogene (formerly Tertiary) which left topographic highs, subsequent glaciations and sea-level fluctuations in the Quaternary, and late Pleistocene and Holocene marine processes.

In 1998, the National Marine Fisheries Service established the WGOM Closure which encompasses the northern and middle reaches of Jeffreys Ledge. The closure, one of the largest in the world, extends ~110 km north-south and is ~30 km in width. A year-round prohibition of bottom gillnets and otter trawls was implemented in an effort to help rebuild the groundfish stocks in the WGOM (e.g., cod, haddock, other gadids, and flatfish), as well as to help protect habitat.

From 2002 to 2004, the University of New Hampshire (UNH) Center for Coastal and Ocean Mapping (CCOM) was part of an interdisciplinary effort to evaluate the effect of the WGOM Closure on bottom habitats. The study focused on an approximately 18.5 by 27.8 km area (~515 km2) on Jeffreys Ledge \– referred to as the UNH Study Area \– that encompassed similar seafloor types inside and outside of the closure (Figure 2). During this study, high resolution multibeam echosounder (MBES) surveys were completed, bottom sediment samples were collected and processed for grain size, and seafloor video was obtained along bottom transects.

The \“New Hampshire Continental Shelf Geophysical Database: 2002-2005 Jeffreys Ledge Field Campaign \– Seafloor Photographs and Sediment Data\” presented here was developed by the UNH Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC) and includes 687 seafloor photographs, grain size data and classifications for 123 bottom sediment samples, and bottom sediment classifications based on video for 142 stations from the UNH Study Area.

}, keywords = {continental shelf, Jeffreys Ledge, Photographs, seafloor, Sediment, Western Gulf of Maine}, doi = {https://dx.doi.org/10.34051/d/2021.8}, author = {Larry G Ward and Raymond E Grizzle and Rachel C Morrison} } @article {7091, title = {New Hampshire Continental Shelf Geophysical Database: 2016-2017 Field Campaign {\textendash} Seafloor and Sample Photographs and Sediment Data}, year = {2021}, publisher = {University of New Hampshire}, chapter = {Center for Coastal and Ocean Mapping}, address = {Durham, NH}, abstract = {

The \"New Hampshire Continental Shelf Geophysical Database: 2016-2017 Field Campaign - Seafloor and Sample Photographs and Sediment Data \" contains photographs of the seafloor from sampling locations, photographs of the sediment samples, and grain size data from a major field campaign conducted in 2016- 2017 and from the UNH Ocean Engineering 972 Hydrographic Field Course classes in 2012, 2014, and 2018. In total, sixteen one-day cruises provided 150 samples for grain size analysis. The database provides complete descriptions for each sample including identification, station and sample characteristics, sediment classifications, grain size statistics, and grain size distribution. Presented here are tables with the station locations and types of data available followed by single sample summaries for each sample collected and analyzed. Included in each summary are location information, seafloor photographs, photographs of the sample (in field and laboratory) where available, collection information, sediment classifications, grain size statistics, and grain size distribution. Samples were analyzed with standard sieve and pipette analyses after Folk (1980). The sediment grain size classifications include: CMECS (Coastal and Marine Ecological Classification Standard; FGDC, 2012); Gradistat (Blot and Pye, 2001); and Wentworth (Wentworth, 1922; described in Folk, 1954, 1980). Statistics are based on the phi scale and include the graphic mean, sorting, skewness, and kurtosis (Folk, 1980).

}, keywords = {Grain Size, New Hampshire Continental Shelf, Seafloor Photographs, Sediment Photographs, Western Gulf of Maine}, doi = {https://dx.doi.org/10.34051/d/2021.1}, author = {Larry G Ward and Rachel C Morrison and Zachary S. McAvoy} } @article {7092, title = {New Hampshire Continental Shelf Geophysical Database: 2016-2017 Field Campaign - Stations and Sediment Data}, year = {2021}, publisher = {University of New Hampshire}, chapter = {Center for Coastal and Ocean Mapping}, address = {Durham, NH}, abstract = {

The \"New Hampshire Continental Shelf Geophysical Database: 2016-2017 Field Campaign - Stations and Sediment Data\" contains sediment grain size data from a major field campaign conducted in 2016-2017 and from the UNH Ocean Engineering 972 Hydrographic Field Course classes in 2012, 2014, and 2018. In total, sixteen one-day cruises provided 150 samples for grain size analysis. The database provides complete descriptions for each sample including identification, station and sample characteristics, sediment classifications, grain size statistics, and grain size distribution. Samples were analyzed with standard sieve and pipette analyses after Folk (1980). The sediment grain size classifications include: CMECS (Coastal and Marine Ecological Classification Standard; FGDC, 2012); Gradistat (Blot and Pye, 2001); and Wentworth (Wentworth, 1922; described in Folk, 1954, 1980). Statistics are based on the phi scale and include the graphic mean, sorting, skewness, and kurtosis (Folk, 1980).

}, keywords = {Grain Size, New Hampshire Continental Shelf, seafloor sediments, Western Gulf of Maine}, doi = {https://dx.doi.org/10.34051/d/2021.2}, author = {Larry G Ward and Rachel C Morrison and Zachary S. McAvoy} } @article {7094, title = {New Hampshire Continental Shelf Geophysical Database: 2016-2017 Field Campaign {\textendash} Seafloor Photographs}, year = {2021}, publisher = {University of New Hampshire}, chapter = {Center for Coastal and Ocean Mapping}, address = {Durham, NH}, abstract = {

The \"New Hampshire Continental Shelf Geophysical Database: 2016-2017 Field Campaign \– Seafloor Photographs\” was developed by the University of New Hampshire (UNH) Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC). The field campaign was conducted to provide ground truth for surficial geology maps for the continental shelf off New Hampshire (NH) and focused on the inner shelf between the coast and the Isles of Shoals. Station locations were chosen where high-resolution bathymetry was available, including multibeam echosounder (MBES) surveys conducted by the UNH CCOM/JHC Hydrographic Field Course (Ocean Engineering 972), MBES surveys by the NOAA National Ocean Service (NOS), and a topo-bathy lidar (Shoals) survey by the United States Geological Survey (USGS) (see Ward et al., 2021c for details). In total, seafloor videography was collected at 151 stations and 855 photographs were extracted from the video. In addition, 150 sediment samples were collected from 85 of the stations and analyzed for grain size. The bottom sediment grain size data is available at the University of New Hampshire Scholars Repository (see Ward et al., 2021 https://dx.doi.org/10.34051/d/2021.2.

}, keywords = {New Hampshire Continental Shelf, Seafloor Photos, Surficial Geology, Western Gulf of Maine}, doi = {https://dx.doi.org/10.34051/d/2021.5}, author = {Larry G Ward and Rachel C Morrison and Zachary S. McAvoy} } @article {7095, title = {New Hampshire Continental Shelf Geophysical Database: Vibracore Logs and Sediment Data}, year = {2021}, publisher = {University of New Hampshire}, chapter = {Center for Coastal and Ocean Mapping}, address = {Durham, NH}, abstract = {

The \"New Hampshire Continental Shelf Geophysical Database: Vibracore Logs and Sediment Data\" contains complete core logs and sediment grain size data from twenty-three vibracores taken on the New Hampshire shelf in 1984 and 1988. During the present program, the original core descriptions, data, and photographs were verified and significantly expanded, synthesized, and presented in uniform core logs.The vibracore logs, sediment data, and the depositional environments are discussed in detail in Ward et al., 2021 (https://dx.doi.org/10.34051/p/2021.26).

}, keywords = {New Hampshire Continental Shelf, Sediment Grain Size Data, Surficial Geology, Vibracores, Western Gulf of Maine}, doi = {https://dx.doi.org/10.34051/d/2021.4}, author = {Larry G Ward and Rachel C Morrison and Zachary S. McAvoy and M. Vallee-Anziani} } @article {7093, title = {New Hampshire Continental Shelf Historical Geophysical Database: 1971 to 2015 - Sediment Data}, year = {2021}, publisher = {University of New Hampshire}, chapter = {Center for Coastal and Ocean Mapping}, address = {Durham, NH}, abstract = {

The UNH CCOM/JHC \"New Hampshire Continental Shelf Historical Geophysical Database: 1971 to 2015 - Sediment Data\" contains sediment grain size data and classifications from studies conducted between 1971 and 2015. In total, grain size data was available for 725 bottom sediment samples. Included are sample identification information, station and sample characteristics, sediment classifications, grain size statistics, and grain size distribution. Not all of these parameters were available for every study. Samples were analyzed with standard sieve and pipette analyses after Folk (1980). The sediment grain size classifications include: CMECS (Coastal and Marine Ecological Classification Standard; FGDC, 2012); Gradistat (Blot and Pye, 2001); and Wentworth (Wentworth, 1922; described in Folk, 1954, 1980). Statistics are based on the phi scale and include the graphic mean, sorting, skewness, and kurtosis (Folk, 1980).

}, keywords = {Grain Size, New Hampshire Continental Shelf, seafloor sediments, Western Gulf of Maine}, doi = {https://dx.doi.org/10.34051/d/2021.3}, author = {Larry G Ward and Rachel C Morrison and Zachary S. McAvoy} } @article {6798, title = {External and Internal Grouping Characteristics of Juvenile Walleye Pollock in the Eastern Bering Sea}, volume = {32}, year = {2019}, month = {August 26}, publisher = {EDP Sciences}, abstract = {

Size and shape patterns of fish groups are collective outcomes of interactions among members. Consequently, group-level patterns are often affected when any member responds to changes in their internal state, external state, and environment. To determine how groups of fish respond to components of their physical and ecological environment, and whether the response is influenced by a component of their external state (i.e., fish age), we used a multibeam system to collect three-dimensional grouping characteristics of 5 age categories of juvenile walleye pollock (age 1, age 2, age 3, mixed ages 1 and 2, and mixed ages 2 and 3) across the eastern Bering Sea shelf over two consecutive years (2009\–2010). Grouping data were expressed as metrics that described group size (length, height), shape (roundness, spread), internal structure (density, internal heterogeneity), and position (depth, distance above bottom). Physical data (water temperature measurements) were collected with temperature-depth probes, and ecological data (densities of predators and prey \− adult walleye pollock and euphausiids, respectively) were collected with an EK60 vertical echosounder. Juvenile pollock maintained a relatively constant shape, size-dependent density (number fish/mean body length3), and internal horizontal heterogeneity among age categories and in the presence of predators and prey. There were changes to group structure in the face of local physical forcing. Groups tended to move towards the seafloor when bottom waters became warmer, and groups became vertically shorter, denser, and had more variation in horizontal internal density as group depth increased. These results are explored in relation to the value and limitations of using multibeam data to describe how external and internal group structure map onto environmental influences.

}, keywords = {fish groups, predator, prey, Walleye pollock}, doi = {https://doi.org/10.1051/alr/2019016}, author = {Stienessen, Sarah C and Christopher D Wilson and Thomas C Weber and Parrish, Julia K} } @article {6526, title = {High Resolution Mapping of Morphologic Features and Seafloor Sediments of the New Hampshire and Vicinity Continental Shelf, Western Gulf of Maine}, year = {2019}, month = {March 17-19}, pages = {Portland, ME}, abstract = {

The Western Gulf of Maine (WGOM) seafloor is extremely complex with extensive bedrock outcrops, marine modified glacial deposits, marine formed shoals, and muddy offshore basins. Many of the depositional features found on the shelf are dominated by remnant glacial features (e.g., drumlins, eskers, moraines) that were significantly modified by marine processes as sea-level fluctuated following deglaciation. The glacial deposits were eroded, leaving very coarse lag deposits, while supplying sand and fine gravel to develop wave formed features (shoals). A number of the nearshore glacial and other physiographic features found on the shelf continue onshore. As a result, the New Hampshire continental shelf\’s morphologic features and sediment are highly diverse and vary significantly over short distances.

Over the last decade, the geology (primarily morphology, depositional systems, and controlling processes) of the New Hampshire and vicinity continental shelf has been extensively studied based on archived databases (subbottom seismics, vibracores and surficial sediments), as well as more recently available high resolution multibeam echosounder (MBES) bathymetry and backscatter. In addition, field campaigns were conducted in 2016-2017 to obtain additional ground truth (bottom sediment samples and videography). From this database, high resolution seafloor maps were developed using various seafloor classifications, but primarily the Coastal and Marine Ecological Classification Standard (CMECS). Although much of the mapping effort ultimately relies on human interpretation or expert opinion, new approaches using acoustics are being evaluated such as BRESS (Bathymetry- and Reflectivity-Based Estimator for Seafloor Segmentation: see Masetti et al. 2018). The overall mapping effort is focusing on morphologic features (geoforms), classification of the grain size of surficial sediment, and description of selected sand and gravel deposits. The new surficial geology maps represent a major advance in our efforts to understand and characterize the New Hampshire and vicinity continental shelf.

}, keywords = {morphology, seafloor sediments, Western Gulf of Maine}, doi = {doi: 10.1130/abs/2019NE-328549}, url = {https://gsa.confex.com/gsa/2019NE/meetingapp.cgi/Paper/328549}, author = {Larry G Ward and Zachary S. McAvoy and Giuseppe Masetti and Rachel C Morrison} } @article {6111, title = {Bottom Characterization by Using Airborne Lidar Bathymetry (ALB) Waveform Features Obtained from Bottom Return Residual Analysis}, volume = {206}, year = {2018}, month = {March 1}, pages = {260-274}, publisher = {Elsevier}, abstract = {

Airborne Lidar Bathymetry (ALB) surveys are traditionally used for measuring depths in shallow nearshore and back-bay areas. In this paper, we present a novel ALB waveform processing procedure, namely bottom return residual analysis, for bottom characterization. Waveform features obtained from the bottom return residual analysis are used in a supervised classification approach, i.e. Support Vector Machine, to differentiate between: 1) sand and rock bottoms and subsequently, 2) fine and coarse sand bottoms. The classification procedure was tested on ALB survey data collected with an Optech SHOALS-1000T ALB system that covers a ~7 km2 area within 1 km from shore in the western Gulf of Maine, USA. The bottom classification results, when compared to ground-truth measurements, indicate a 96\% overall accuracy for sand and rock classification and 86\% overall accuracy for fine and coarse sand classification. Results of ALB-based bottom classification are compared with interpretations of a multibeam echosounder acoustic backscatter mosaic collected from the survey area.\ 

}, keywords = {airborne lidar bathymetry, seafloorcharacterization, supervised classsification, waveform}, doi = {https://doi.org/10.1016/j.rse.2017.12.035}, url = {https://www.sciencedirect.com/science/article/pii/S003442571730620X?via\%3Dihub}, author = {Eren, Firat and S. Pe{\textquoteright}eri and Yuri Rzhanov and Larry G Ward} } @article {6192, title = {Comparing Acoustic- and Aerial Imagery-based Methods of Eelgrass Mapping at Two New England Sites}, year = {2017}, month = {November 5-9}, pages = {Providence, RI}, abstract = {

Eelgrass is an important part of many temperate coastal ecosystems and is often used as a bio-indicator for environmental issues such as water quality. Many eelgrass monitoring programs rely on the analysis of optical remote sensing data, including aerial or satellite imagery. However, these methods are often inhibited by natural attenuation of light with water depth and clarity. Acoustic methods have the potential to complement these optical remote sensing-based datasets. The method described here uses water column data from a multi-beam echo-sounder. It can provide geo-referenced acoustic imagery and depth information needed to document the location, structure, and spatial heterogeneity of eelgrass beds, with more spatial coverage than existing acoustic tools that mostly utilize single-beam echo-sounders. Presented here are two acousticallyderived datasets from Wellfleet, Massachusetts, and Kittery, Maine, classified to characterize the presence/absence, percent cover and canopy height of eelgrass. These data are compared to optical-remote-sensing-derived datasets and sidescan sonar imagery using standard accuracy assessment techniques i.e., error matrices. Analysis also includes correlations of classification accuracies with parameters such as water depth, slope and rugosity. Preliminary results indicate that boundaries of eelgrass beds in acoustic and aerial datasets agree more in shallower water than at the deeper edges, and that eelgrass is detected at lower densities in the acoustic data than in the aerial imagery. These differences are due to the differences in horizontal positioning accuracy and resolution and inherent differences in data collection methods (i.e., continuous transects vs. pixel-based imagery).

}, keywords = {eelgrass, habitat mapping, multi-beam sonar, seagrass, water column}, author = {Ashley R Norton and Semme J Dijkstra} } @article {6226, title = {In Situ Quantitative Characterisation of the Ocean Water Column Using Acoustic Multibeam Backscatter Data}, year = {2017}, month = {December 11-15}, pages = {New Orleans, LA}, abstract = {

Detecting liquid, solid or gaseous features in the ocean is generating considerable interest in the geoscience community, because of their potentially high economic values (oil \& gas, mining), their significance for environmental management (oil/gas leakage, biodiversity mapping, greenhouse gas monitoring) as well as their potential cultural and traditional values (food, freshwater). Enhancing people\&$\#$39;s capability to quantify and manage the natural capital present in the ocean water goes hand in hand with the development of marine acoustic technology, as marine echosounders provide the most reliable and technologically advanced means to develop quantitative studies of water column backscatter data. This is not developed to its full capability because (i) of the complexity of the physics involved in relation to the constantly changing marine environment, and (ii) the rapid technological evolution of high resolution multibeam echosounder (MBES) water-column imaging systems. The Water Column Imaging Working Group is working on a series of multibeam echosounder (MBES) water column datasets acquired in a variety of environments, using a range of frequencies, and imaging a number of water-column features such as gas seeps, oil leaks, suspended particulate matter, vegetation and freshwater springs. Access to data from different acoustic frequencies and ocean dynamics enables us to discuss and test multifrequency approaches which is the most promising means to develop a quantitative analysis of the physical properties of acoustic scatterers, providing rigorous cross calibration of the acoustic devices. In addition, high redundancy of multibeam data, such as is available for some datasets, will allow us to develop data processing techniques, leading to quantitative estimates of water column gas seeps. Each of the datasets has supporting ground-truthing data (underwater videos and photos, physical oceanography measurements) which provide information on the origin and chemistry of the seep content. This is of first importance when assessing the physical properties of water column scatterers from backscatter acoustic measurement.

}, keywords = {seep, water column, WCIWG}, url = {https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/290213}, author = {Geoffroy Lamarche and Yves Le Gonidec and Vanessa Lucieer and Xavier Lurton and Jens Greinert and St{\'e}phanie Dupr{\'e} and Amy Nau and Erin Heffron and Marc Roche and Yoann Ladroit and Peter Urban} } @article {6113, title = {Ping Once Use many times: NOAA Wilmington NC 2016 Field Season}, year = {2017}, month = {March 20-23}, pages = {Galveston, TX}, abstract = {NOAA Coast Survey and The National Centers for Coastal Ocean Science (NCCOS) collaborated during the 2016 Field Season to map the continental shelf near Wilmington, North Carolina for habitat analysis and the safety of navigation. The Wilmington project has epitomized the Integrated and Coastal Ocean Mapping (IOCM) effort within NOAA: from data discovery and communication of mapping priorities between stakeholders; to the sharing of expertise and data; doing more with limited resources. Past habitat surveys were refined for charting. Scientists from Coast Survey, NCCOS, and UNH JHC/CCOM came together to share best practices. A bottom camera attached to the grab sampler prototype developed by UNH JHC/CCOM scientists was tested. Bottom photos, sediment samples, backscatter, and bathymetry were collected, to meet both habitat analysis and charting needs. This opportunity has opened discussions on how we can collect data that meets multiple needs, and how to serve that data to our stakeholders. The hydrographic community wears many hats: we are sailors, scientists, and explorers. We muster considerable resources, face a considerable risk, to gather data to see the world better. For the safety of navigation; for solving environmental problems; and to model our world, we work together.}, keywords = {Bottom sample imagery, Communicating priorities, IOCM, NC, UNH Drop Camera, Wilmington}, author = {Starla Robinson}, editor = {Juliet Kinney and Chris Taylor} } @article {6216, title = {A Ray-Tracing Uncertainty Estimation Tool for Ocean Mapping}, volume = {6}, year = {2017}, month = {11 December 2017}, pages = { 2136 - 2144}, publisher = {IEEE}, abstract = {

A tool to estimate the ray-tracing component of the surveyed depth uncertainty was created and made publicly available through web services and a Web GIS. The estimation is based on a spatial variability analysis at the time of validity of two popular, global-scope sources of oceanographic environmental data. The tool has potential applications in all the phases of ocean mapping, from survey planning to data collection and processing.

}, keywords = {Acoustic applications, computational modeling, Geographic Information Systems, oceanographic techniques, ray tracing, underwater acoustics, web services}, doi = {https://doi.org/10.1109/ACCESS.2017.2781801}, url = {http://ieeexplore.ieee.org/document/8183436/}, author = {Giuseppe Masetti and John G Kelley and Paul Johnson and Beaudoin, Jonathan} } @article {6228, title = {Seep Detection Using E/V Nautilus Integrated Seafloor Mapping and Remotely Operated Vehicles on the United States West Coast}, year = {2017}, month = {December 11-15}, pages = {New Orleans, LA}, abstract = {

Exploration Vessel (E/V) Nautilus has been mapping the seafloor off the west coast of the United States, from Washington to California, for the past three years with a Kongsberg EM302 multibeam sonar. This system simultaneously collects bathymetry, seafloor and water column backscatter data, allowing an integrated approach to mapping to more completely characterize a region, and has identified over 1,000 seafloor seeps.

Hydrographic multibeam sonars like the EM302 were designed for mapping the bathymetry. It is only in the last decade that major mapping projects included an integrated approach that utilizes the seabed and water column backscatter information in addition to the bathymetry. Nautilus mapping in the Eastern Pacific over the past three years has included a number of seep-specific expeditions, and utilized and adapted the preliminary mapping guidelines that have emerged from research.

The likelihood of seep detection is affected by many factors:

Nautilus integrated seafloor mapping provided multiple indicators of seep locations, but it remains difficult to assess the probability of seep detection. Even when seeps were detected, they have not always been located during ROV dives. However, the presence of associated features (methane hydrate and bacterial mats) serve as evidence of potential seep activity and reinforce the transient nature of the seeps. Not detecting a seep in the water column data does not necessarily indicate that there is not a seep at a given location, but with multiple passes over an area and by the use of other contextual data, an area may be classified as likely or unlikely to host seeps.

}, keywords = {backscatter, bathymetry, e/v nautilus, multibeam, seep, water column}, url = {https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/289727}, author = {Lindsay Gee and Nicole A Raineault and Renato Kane and Miles Saunders and Erin Heffron and Robert W Embley and Susan G. Merle} } @article {6376, title = {Visualization of Nautical Information (VONI) Workshop 2017}, year = {2017}, month = {12/7/2016}, pages = {2}, institution = {International Hydrographic Organization}, address = {Monaco}, abstract = {

At the NIPWG2 meeting the question was raised \“once the standards are in place how will the Hydrographic Offices (HO) implement them?\” The answer was silence and a shrug of the shoulders. It was then proposed by UNH to host a workshop to help each HO answer that question with confidence and direction.

}, keywords = {IHO, NIPWG, Visualization, Workshop}, url = {https://www.iho.int/mtg_docs/com_wg/NIPWG/NIPWG3/NIPWG\%203-39.1\%20VONI_workshop.pdf}, author = {Briana M Sullivan} } @article {5752, title = {Airborne Lidar Bathymetry (ALB) Waveform Analysis for Bottom Return Characteristics}, year = {2016}, month = {Apr 17 - 21}, address = {Baltimore, MD}, abstract = {

Airborne Lidar Bathymetry (ALB) waveforms provide a time log for the interaction of the laser pulse with the environment (water surface, water column and seafloor) along its ray-path geometry. Using the water surface return and the bottom return, it is possible to calculate the water depth. In addition to bathymetry, the ALB bottom return can provide information on seafloor characteristics. The main environmental factors that contribute to the ALB bottom return measurements are: slope, roughness, vegetation, and mineral composition of the surface geology. Both the environment and the ALB hardware affect the bottom return and contribute to the measurement uncertainties. In this study, the ALB bottom return waveform was investigated spatially (i.e., area contributing to the return) and temporally (i.e. the shape of the waveform return) for seafloor characterization. A system-agnostic approach was developed in order to distinguish between the spatial variations of different bottom characteristics. An empirical comparison of bottom characteristics was conducted near the Merrimack River Embayment, Gulf of Maine, USA. The study results showed a good correlation to acoustic backscatter collected over the same area.

}, keywords = {airborne lidar bathymetry, alb, bottom return characteristics, waveform analysis}, author = {Eren, Firat and S. Pe{\textquoteright}eri and Yuri Rzhanov} } @article {5951, title = {Western Gulf of Maine Bathymetry and Backscatter Synthesis}, volume = {BOEM/New Hampshire Cooperative Agreement (Contract M14ACOOO10) Technical Report}, year = {2016}, pages = {18}, institution = {Bureau of Ocean Energy Management (BOEM) Marine Minerals Branch,}, address = {Herndon, VA}, abstract = {

In July 2014 a Cooperative Agreement between the Bureau of Ocean Energy Management, the University of New Hampshire Center for Coastal and Ocean Mapping/Joint Hydrographic Center, and the New Hampshire Geological Survey was developed to assess the potential sand and gravel resources on the New Hampshire shelf and vicinity for the primary purpose of beach nourishment to enhance coastal resiliency. Of major importance to the effort was the development of high resolution bathymetric maps of the region to provide an understanding of the seafloor and to be used as a base for subsequent mapping products. Fortunately, over the last decade a number of high resolution multibeam echosounder bathymetric surveys were completed in the Western Gulf of Maine including the New Hampshire shelf. In addition, many of these multibeam echosounder surveys collected backscatter, which is the intensity of the returned acoustic signal from the seafloor and often reveals a great deal of information about the characteristics of the substrate.

Utilizing the high resolution multibeam echosounder bathymetry, as well as several older extant surveys, a synthesis was constructed for the Western Gulf of Maine. The original surveys used in this compilation were gridded over a large range (0.50 to 25 m). Therefore, the surveys were re-gridded at 4 m and 8 m for map development. Composites were also constructed of multibeam echosounder backscatter for the Western Gulf of Maine (gridded at 2m). However, due to the difficulties of combining varying surveys, the synthesis for the backscatter surveys was limited to a region off New Hampshire.

The composites for the Western Gulf of Maine Bathymetry and Backscatter Synthesis are presently available through the Center for Coastal and Ocean Mapping/Joint Hydrographic Center website at http://ccom.unh.edu/gis/maps/WGOM_4m/ (for bathymetry gridded at 4 m), http://ccom.unh.edu/gis/maps/WGOM_8m/ (for bathymetry gridded at 8 m), and http://ccom.unh.edu/gis/maps/WGOM_BS/ (for the backscatter gridded at 2 m).

}, keywords = {backscatter, bathymetry, Western Gulf of Maine}, doi = {https://dx.doi.org/10.34051/p/2021.27 }, author = {Larry G Ward and Paul Johnson and Erin Nagel and Zachary S. McAvoy and M. Vallee-Anziani} } @mastersthesis {5721, title = {Estimating Surficial Seafloor Sediment Properties Using an Empirical Orthogonal Decomposition on Acoustic Backscatter Waveform Properties}, volume = {Oceanography}, year = {2015}, month = {04/2015}, pages = {87}, school = {University of New Hampshire}, address = {Durham, NH}, abstract = {

Seafloor classification and environmental assessment in shallow marine waters are crucial to habitat mapping, coastal management policies and maintaining navigational waterways. There are existing methods for remotely estimating some bottom properties, but the large variety of desired measured sediment properties frequently leads to insufficient quantifiable data to support marine policy decisions. This problem is exacerbated by the highly variable bottom composition of typical coastal and estuarine environments. In this work, field observations from an Odom Echotrac vertical-incidence echosounder with a 200 khz transducer were used to estimate seafloor sediment characteristics in regions with variable bottom types. Observations were obtained in water depths ranging 0.5-24 m of the Little Bay, New Hampshire, during February and March, 2013. Backscatter waveforms (the acoustic return representing the first interaction with the bottom) were analyzed and their properties compared to sediment grain size distributions. These comparisons showed varied degrees of predictive capability and require subjective a priori selection. In an effort to better capture the collective effects of seafloor sediment\&$\#$39;s composition on acoustic returns, empirical orthogonal functions (EOF\&$\#$39;s) were computed from an ensemble of seven waveform properties and compared with observed surficial sediment size fractions, bulk density, and porosity. A simple logarithmic model relating first mode EOF spatial variability to observed mud fractions explained 43\% of the variability and well estimated the spatial pattern of mud across the bay (RMS errors in mud fraction of 10-15\%) from deep channels (with no mud) to high concentrations of mud on the shallower flats near the sides of the estuary. This method produced greater coverage and higher resolution predictions of mud fraction than could be obtained using traditional sediment measuring techniques. Deviations from the model are shown to be correlated with lower sediment porosity most likely due to river inflow from the Bellamy River draining into the Bay. Application of the model coefficients to new data obtained in the Great Bay in 2014 with the same sonar and acoustic settings, showed similar predicted mud fractions with RMS errors of 11.9 and 13.2\% along two surveyed lines. This empirical analysis provides a first order objective means to interpret acoustic backscatter, an important step towards a widespread quantitative assessment of shallow water seafloor sediments.

}, keywords = {orthogonal decomposition, surficial seafloor sediment, waveform}, author = {Humberston, Joshua} } @article {5042, title = {Application of landscape mosaics for the biological quality assessment of subtidal macroalgae communities using the CFR index}, year = {2013}, keywords = {CFR index, Landscape mosaics, Sample size, Subtidal macroalgae, WaterFrameworkDirective}, url = {http://www.journals.elsevier.com/deep-sea-research-part-i-oceanographic-research-papers/}, author = {Guinda Salsamendi, Xabier and Gracia, A. and Puente, A. and Juanes, J.A. and Yuri Rzhanov and Larry A Mayer} } @proceedings {5137, title = {Characterization of optical communication in a leader-follower unmanned underwater vehicle formation}, volume = {8724}, year = {2013}, month = {April 29 - May 3}, publisher = {SPIE}, address = {Baltimore, MD, USA}, abstract = {

As part of theresearchto development an optical communication design of a leader-follower formation between unmanned underwater vehicles (UUVs), this paper presents light field characterization and design configuration of the hardware required to allow the use of distance detection between UUVs. The studyspecifically is targeting communication between remotely operated vehicles (ROVs). As an initial step in this study, the light field produced from a light source mounted on the leader UUV was empirically characterized and modeled. Based on the light field measurements, a photo-detector array for the follower UUV was designed. Evaluation of the communication algorithms to monitor the UUV\’s motion was conducted through underwater experiments in the Ocean Engineering Laboratory at the University of New Hampshire. The optimal spectral range was determined based on the calculation of the diffuse attenuation coefficients by using two different light sources and a spectrometer. The range between the leader and the follower vehicles for a specific water type was determined. In addition, the array design and the communication algorithms were modified according to the results from the light field.

}, keywords = {light attenuation, optical communication, simulation, Unmanned underwater vehicle, water clarity}, author = {Eren, Firat and S. Pe{\textquoteright}eri and May-Win Thein} } @article {4782, title = {Extracting More Data from LiDAR in Forested Areas by Analyzing Waveform Shape}, volume = {4}, year = {2012}, month = {12 March 2012}, pages = {682-702}, publisher = {MDPI Publishing}, address = {Basel, Switzerland}, abstract = {

Abstract: Light Detection And Ranging (LiDAR) in forested areas is used for constructing Digital Terrain Models (DTMs), estimating biomass carbon and timber volume and estimating foliage distribution as an indicator of tree growth and health. All of these purposes are hindered by the inability to distinguish the source of returns as foliage, stems, understorey and the ground except by their relative positions. The ability to separate these returns would improve all analyses significantly. Furthermore, waveform metrics providing information on foliage density could improve forest health and growth estimates. In this study, the potential to use waveform LiDAR was investigated. Aerial waveform LiDAR data were acquired for a New Zealand radiata pine plantation forest, and Leaf Area Density (LAD) was measured in the field. Waveform peaks with a good signal-to-noise ratio were analyzed and each described with a Gaussian peak height, half-height width, and an exponential decay constant. All parameters varied substantially across all surface types, ruling out the potential to determine source characteristics for individual returns, particularly those with a lower signal-to-noise ratio. However, pulses on the ground on
average had a greater intensity, decay constant and a narrower peak than returns from coniferous foliage. When spatially averaged, canopy foliage density (measured as LAD) varied significantly, and was found to be most highly correlated with the volume-average exponential decay rate. A simple model based on the Beer-Lambert law is proposed to
explain this relationship, and proposes waveform decay rates as a new metric that is less affected by shadowing than intensity-based metrics. This correlation began to fail when peaks with poorer curve fits were included.

}, keywords = {Beer-Lambert law, deconvolution, forests, Gaussian fitting, LAD, leaf area density, waveform LiDAR, Weiner deconvolution}, url = {http://www.mdpi.com/2072-4292/4/3/682/}, author = {Adams, Thomas and Beets, Peter and Christopher E Parrish} } @article {4958, title = {Geological interpretation of a low-backscatter anomaly found on the New Jersey continental margin}, volume = {326-328}, year = {2012}, month = {24-08-2012}, pages = {46-54}, publisher = {Elsevier}, abstract = {

An enigmatic low-backscatter, acoustic anomaly occurs on the New Jersey continental margin between Hudson and Wilmington Canyon channels. The presence of the low-backscatter anomaly, as seen with 6.5- and 12-kHz data, indicates a change in the physical properties of the seafloor or near sub-surface. Analyses of seafloor and sub-surface acoustic data with previously collected sediment cores suggest the low-backscatter feature corresponds to an outcrop of older strata uncovered by erosion and non-deposition by the Western Boundary Undercurrent (WBUC). The decrease in backscatter strength is enhanced by the presence of gas in the sub-surface sediments found in the buried Chesapeake Drift.\ 

}, keywords = {Chesapeake Drift, continental slope, multibeam backscatter, submarine canyons, U.S. mid-Atlantic continental margin, Western Boundary Undercurrent}, author = {Sweeney, Ed and James V. Gardner and Johnson, Joel and Larry A Mayer} } @inbook {4920, title = {An Overview of ALS Technology}, booktitle = {Airborne Topographic Lidar Manual}, year = {2012}, pages = {pp. 7-97}, publisher = {American Society for Photogrammetry and Remote Sensing (ASPRS)}, organization = {American Society for Photogrammetry and Remote Sensing (ASPRS)}, chapter = {2}, address = {Bethesda, Maryland}, keywords = {airborne, laser, LIDAR, scanning, waveform}, author = {Pack, R.T. and Brooks, V. and Young, J. and Vila{\c c}a, N. and Vatslid, S. and Rindle, P. and Kurz, S. and Christopher E Parrish and Craig, R. and Smith, P.W.} } @article {2882, title = {Detection of Deep Water Benthic Macroalgae Using Image-based Classification Techniques on Multibeam Backscatter at Cashes Ledge, Gulf of Maine, USA}, volume = {91}, year = {2011}, month = {1 January 2011}, pages = {87-101}, publisher = {Elsevier}, address = {New York, NY, USA}, keywords = {backscatter, classification, image-based, kelps, macroalgae, multibeam sonar, Water Column Mapping}, url = {http://www.sciencedirect.com/science/article/pii/S0272771410003586}, author = {McGonigle, C and Grabowski, J and Craig Brown and Thomas C Weber and Quin, R} } @proceedings {, title = {Application of JPEG 2000 Wavelet Compression to Multibeam Echosounder Mid-water Acoustic Refectivity Measurements}, year = {2010}, month = {Jun 21 - Jun 23}, address = {Quebec City, Quebec, Canada}, keywords = {Water Column Mapping}, author = {Beaudoin, Jonathan} } @article {, title = {Fine-scale Prey Aggregations and Foraging Ecology of Humpback Whales (Megaptera Novaeangliae)}, volume = {395}, year = {2009}, pages = {75-89}, publisher = {Inter-Research}, address = {Nordbunte, Oldendorf, Germany}, keywords = {Whale Tracking}, author = {Hazen, E L and Friedlaender, A S and Thompson, Michael A and Colin Ware and Weinrich, M T and Halpin, P N and David N Wiley} } @article {, title = {Consecutive Acoustic Observations of an Atlantic Herring School in the Northwest Atlantic}, volume = {66}, year = {2009}, pages = {1270-1277}, publisher = {Elsevier}, address = {New York, NY, USA}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Pena, H and Jech, J M} } @article {, title = {Dirl Changes in Humpback Whale (Megaptera Novaeangliae) Feeding Behavior in Response to Sand Lance (Ammodytes SPP.) Behavior and Distribution}, volume = {395}, year = {2009}, pages = {91-100}, publisher = {Inter-Research}, address = {Nordbunte, Oldendorf, Germany}, keywords = {Whale Tracking}, author = {Friedlaender, A S and Hazen, E L and Nowacek, D P and Halpin, P N and Colin Ware and Weinrich, M T and Hurst, T and David N Wiley} } @article {, title = {Measurements of Acoustic Backscatter and Density of Captive Atlantic Cod with Synchronized 300-kHz Multibeam and 120-kHz Split-Beam Echosounders}, volume = {66}, year = {2009}, pages = {1303-1309}, publisher = {Elsevier}, address = {New York, NY, USA}, keywords = {Water Column Mapping}, author = {Gurshin, C W and Jech, J M and Howell, W H and Thomas C Weber and Larry A Mayer} } @article {3420, title = {Advances in the study of marine mammal predator-prey interactions: a novel real-time visualization of independently collected echosounder data using GeoZui4D}, year = {2009}, month = {Oct 12 - Oct 16}, chapter = {18th Biennial Conference}, address = {Quebec City, Quebec, Canada}, keywords = {Whale Tracking}, author = {Roland Arsenault and Friedlaender, A S and Hazen, E L and Colin Ware and David N Wiley} } @proceedings {, title = {Marine Technology Advances to Reduce Incidence of Whale Ship Strikes}, year = {2008}, month = {Apr 8 - Apr 11}, chapter = {Kobe-Techno}, address = {Kobe, Kobe, Japan}, keywords = {Whale Tracking}, author = {McGillivary, Philip A and Schwehr, Kurt and Curcio, J and Hine, E and Terrill, S and Wiggins, E and Roth, Ethan H. and Fall, Kevin} } @mastersthesis {1825, title = {Underwater Tracking of Humpback Whales with High-frequency Pingers and Acoustic Recording Tags}, year = {2008}, pages = {68}, keywords = {Whale Tracking}, author = {Val Schmidt} } @proceedings {, title = {Multibeam and single-beam sonar observations of Atlantic herring in the Gulf of Maine}, year = {2007}, month = {Nov 27 - Dec 1}, pages = {0-0}, edition = {154th}, chapter = {Meeting of the }, address = {New Orleans, LA, USA}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Pena, H and Jech, J M} } @proceedings {, title = {Combining Single Frequency Multibeam with Multifrequency Singlebeam Sonars: An Example with Atlantic Herring}, year = {2007}, month = {Jun 25 - Jun 29}, pages = {0-0}, edition = {2nd}, chapter = {International}, address = {Crete, Greece, Greece}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Pena, H} } @article {, title = {{\textquoteright}Megaclicks{\textquoteright}: Acoustic Click Trains and Buzzes Produced During Night-time Foraging of Humpback Whales (Megaptera Novaeangliae)}, volume = {3}, number = {5}, year = {2007}, pages = {467-470}, publisher = {Royal Society Publishing}, keywords = {Whale Tracking}, author = {Stimpert, A K and David N Wiley and Au, W W and Johnson, M P and Roland Arsenault} } @proceedings {, title = {Identify Bubble Clustering: Comparisons of the Coherent and Incoherent Fields}, year = {2007}, month = {Jun 25 - Jun 29}, pages = {0-0}, edition = {2nd}, chapter = {International Conference}, address = {Heraklion, Crete, Greece}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Anthony P. Lyons and Bradley, David L} } @article {, title = {Oceanographic Structuring of Fish Distribution and Fine Scale Foraging of Humpback Whales (Megaptera novaeangliae), Stellwagen Bank Marine Sanctuary}, year = {2007}, month = {May 10 - May 11}, address = {Scituate, MA, USA}, keywords = {Whale Tracking}, author = {Hazen, E L and Friedlaender, A S and David N Wiley and Thompson, Michael A and Colin Ware and Weinrich, M T} } @proceedings {, title = {Multibeam sonar observations of near-surface bubbles during a storm}, year = {2007}, month = {Nov 27 - Dec 1}, pages = {0-0}, edition = {154th}, chapter = {Meeting of the }, address = {New Orleans, LA, USA}, keywords = {Water Column Mapping}, author = {Thomas C Weber} } @proceedings {, title = {Whale tracking underwater: high frequency acoustic pingers and the instrumented tag (DTAG)}, year = {2007}, month = {Nov 27 - Dec 1}, pages = {0-0}, edition = {154th}, chapter = {Meeting of the }, address = {New Orleans, LA, USA}, keywords = {Whale Tracking}, author = {Val Schmidt and Thomas C Weber and Colin Ware and Roland Arsenault and David N Wiley and Johnson, M P and Dawe, E and Friedlaender, A S} } @article {3481, title = {Three Dimensional Prey Aggregations and Fine Scale Foraging Patterns of Humpback whales (Megaptera novaengliae), Stellwagen Bank Marine Sanctuary}, year = {2007}, month = {Sep 17 - Sep 21}, address = {Heraklion, Crete, Greece}, keywords = {Whale Tracking}, author = {Hazen, E L and Friedlaender, A S and David N Wiley and Thompson, Michael A and Colin Ware and Weinrich, M T} } @article {2804, title = {Visualizing the Underwater Behavior of Humpback Whales}, volume = {26}, number = {4}, year = {2006}, pages = {14-18}, publisher = {IEEE}, address = {Washington DC, Washington DC, USA}, keywords = {Whale Tracking}, author = {Colin Ware and Roland Arsenault and Plumlee, Matt D} } @proceedings {, title = {A Novel Sound Recorded in Association with Bottom Feeding in Humpback Whales}, year = {2005}, month = {Dec 12 - Dec 16}, pages = {0-0}, edition = {16th}, address = {San Diego, CA, USA}, keywords = {Whale Tracking}, author = {Stimpert, A K and David N Wiley and Shorter, K A and Barton, K L and Johnson, M P and Colin Ware and Roland Arsenault and Lammers, M O and Au, W W} } @proceedings {, title = {Underwater behavior of humpback whales in a western North Atlantic foraging area}, year = {2005}, month = {Dec 12 - Dec 16}, edition = {16th}, address = {San Diego, CA, USA}, keywords = {Whale Tracking}, author = {David N Wiley and Colin Ware and Barton, K L and Shorter, K A and Johnson, M P and Roland Arsenault and Moller, J C and Weinrich, M T} } @proceedings {, title = {Concurrent optical and acoustic scattering measurements in bubble clouds}, year = {2005}, month = {Jun 28 - Jul 1}, pages = {0-0}, edition = {1st}, chapter = {International Conference}, address = {Heraklion, Crete, Greece}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Anthony P. Lyons and Bradley, David L} } @proceedings {, title = {The Use of Multibeam Sonars to Image Bubbly Shipwakes}, year = {2005}, month = {Jun 28 - Jul 1}, pages = {0-0}, edition = {1st}, chapter = {International Conference}, address = {Heraklion, Crete, Greece}, keywords = {Water Column Mapping}, author = {Culver, R L and Thomas C Weber and Bradley, David L} } @proceedings {, title = {Multibeam sonar observations of hydrodynamic forcing functions and bubble persistence in a ship wake}, year = {2004}, month = {Nov 15 - Nov 19}, pages = {0-0}, edition = {148th}, chapter = {Meeting of the }, address = {San Diego, CA, USA}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Anthony P. Lyons and Bradley, David L} } @proceedings {, title = {The effects of fluctuating spatial structures in bubble clouds on the statistics of acoustic propagation}, year = {2004}, month = {Sep 12 - Sep 15}, pages = {0-0}, edition = {4th}, address = {Plymouth, Devon, UK}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Anthony P. Lyons and Bradley, David L} } @proceedings {, title = {Acoustic Propagation Through Bubbles: An Exploration of the 1st and 2nd Moments in Various Flow Conditions}, year = {2004}, month = {Aug 11 - Aug 15}, pages = {448-469}, edition = {6th}, address = {Honolulu, HI, USA}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Bradley, David L and Anthony P. Lyons and Bjorno, L} } @proceedings {, title = {Measuring Ambient Ocean Bubble Fields Uusing a Multibeam Sonar}, year = {2003}, month = {Apr 25 - May 2}, pages = {0-0}, edition = {145th}, chapter = {Meeting of the }, address = {Austin, TX, USA}, keywords = {Water Column Mapping}, author = {Adelman, S G and Bradley, David L and Culver, R L and Thomas C Weber} } @proceedings {, title = {Laboratory Measurements of the 1st and 2nd Moments of Propagation Through Bubbles in a Flow}, year = {2003}, month = {Nov 10 - Nov 14}, pages = {0-0}, edition = {146th}, chapter = {Meeting of the }, address = {Austin, TX, USA}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Bradley, David L and Culver, R L and Anthony P. Lyons} } @proceedings {, title = {Inferring the Vertical Turbulent Diffusion Coefficient from Backscatter Measurements with a Multibeam Sonar}, year = {2003}, month = {Nov 10 - Nov 14}, pages = {0-0}, edition = {146th}, chapter = {Meeting of the }, address = {Austin, TX, USA}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Bradley, David L and Culver, R L and Anthony P. Lyons} } @proceedings {, title = {Measurements of ambient bubble populations with a multibeam sonar}, year = {2002}, month = {Dec 2 - Dec 6}, pages = {0-0}, edition = {144th}, chapter = {Meeting of the }, address = {St. Andrews, New Brunswick, Canada}, keywords = {Water Column Mapping}, author = {Thomas C Weber and Bradley, David L and Culver, R L and Anthony P. Lyons and Adelman, S G} } @article {, title = {The dependence of target strength of the northern right whale (Eubalaena glacialis) on the acoustic properties of blubber}, volume = {106}, number = {4}, year = {1999}, pages = {0-2163}, publisher = {Acoustical Society of America}, address = {Melville, NY, USA}, keywords = {Whale Tracking}, author = {Miller, J H and Thomas C Weber and Tuttle, A and Potter, D C} } @article {, title = {The target strength of the northern right whale (Eubalaena glacialis)}, volume = {105}, number = {2}, year = {1999}, pages = {0-992}, publisher = {Acoustical Society of America}, address = {Melville, NY, USA}, keywords = {Whale Tracking}, author = {Miller, J H and Potter, D C and Thomas C Weber and Felix, J} }