The main sources of information for the species distribution are the habitat description and geographic range contained in the published FAO Catalogues of Species (more details at http://www.fao.org/fishery/fishfinder ). Terms used in the descriptive context of the FAO Catalogues were converted in standard depth, geographic and ecological regions and inserted into a Geographic Information System.

The main sources of information for the species distribution are the habitat description and geographic range contained in the published FAO Catalogues of Species (more details at http://www.fao.org/fishery/fishfinder ). Terms used in the descriptive context of the FAO Catalogues were converted in standard depth, geographic and ecological regions and inserted into a Geographic Information System.

The main sources of information for the species distribution are the habitat description and geographic range contained in the published FAO Catalogues of Species (more details at http://www.fao.org/fishery/fishfinder ). Terms used in the descriptive context of the FAO Catalogues were converted in standard depth, geographic and ecological regions and inserted into a Geographic Information System.

This product represents the predicted spatial patterns of selected temperate shark and ray species abundance. Species selection was based on ecological risk assessments, threatened species listings and data availability. The maps are based on existing CSIRO National Fish Collection maps, supplemented with fishery catch data, independent survey data and the expert knowledge of 20 shark and ray experts from the region. Structure equates to total species distribution, core distribution – an estimate of where 90% of the population will occur and where possible, nursery areas. The product can be used to identify movement corridors, breeding and feeding areas that overlap between species. This allows managers to identify areas of overlap that are of key conservation value to the species of interest.

These datasets contain the raw data of X-ray element distribution images of Si, Ca, Al, Mg, Na and Fe and back-scattered-electron (BSE) images of kyanite-bearing garnet pyroxenites from the Gföhl Unit of the Moldanubian Zone, Lower Austria, obtained with the electron-probe micro analyzer (EPMA).

AquaMaps are computer-generated predictions of natural occurrence of marine species, based on the environmental tolerance of a given species with respect to depth, salinity, temperature, primary productivity, and its association with sea ice or coastal areas. These 'environmental envelopes' are matched against an authority file which contains respective information for the Oceans of the World. Independent knowledge such as distribution by FAO areas or bounding boxes are used to avoid mapping species in areas that contain suitable habitat, but are not occupied by the species. Maps show the color-coded likelihood of a species to occur in a half-degree cell, with about 50 km side length near the equator. Experts are able to review, modify and approve maps.

Environmental envelopes are created in part (FAO areas, bounding boxes, depth ranges) from respective information in species databases such as FishBase and in part from occurrence records available from OBIS or GBIF. AquaMaps predictions have been validated successfully for a number of species using independent data sets and the model was shown to perform equally well or better than other standard species distribution models, when faced with the currently existing suboptimal input data sets (Ready et al. 2010).

The creation of AquaMaps is supported by the following projects: MARA, Pew Fellows Program in Marine Conservation, INCOFISH, Sea Around Us, and Biogeoinformatics of Hexacorals.

Kaschner, K., D.P. Tittensor, J. Ready, T Gerrodette and B. Worm (2011). Current and Future Patterns of Global Marine Mammal Biodiversity. PLoS ONE 6(5): e19653. PDF

Ready, J., K. Kaschner, A.B. South, P.D Eastwood, T. Rees, J. Rius, E. Agbayani, S. Kullander and R. Froese (2010). Predicting the distributions of marine organisms at the global scale. Ecological Modelling 221(3): 467-478. PDF

Copyright Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. (CC-BY-NC) You are welcome to include maps from www.aquamaps.org in your own web sites for non-commercial use, given that such inserts are clearly identified as coming from AquaMaps, with a backward link to the respective source page.

Contacts Rainer Froese, GEOMAR, Coordinator rfroese@geomar.de Kristin Kaschner, Uni Freiburg, model development Kristin.Kaschner@biologie.uni-freiburg.de Ma. Lourdes D. Palomares, UBC, extension to non-fish marine organisms m.palomares@fisheries.ubc.ca Sven Kullander, NRM, extension to freshwater ve-sven@nrm.se Jonathan Ready, NRM, implementation jonathan.ready@gmail.com Tony Rees, formerly with CSIRO, mapping tools Tony.Rees@marinespecies.org Paul Eastwood, SOPAC, validation Paul.Eastwood@sopac.org Andy South, CEFAS, validation andy.south@cefas.co.uk Josephine Rius-Barile, Q-quatics, database programming / data collection j.barile@q-quatics.org Cristina Garilao, GEOMAR, web programming cgarilao@geomar.de Kathleen Kesner-Reyes, Q-quatics, map validation k.reyes@q-quatics.org Elizabeth Bato, Q-quatics, map validation (non-fish) e.david@q-quatics.org

Citing AquaMaps

General citation Kaschner, K., K. Kesner-Reyes, C. Garilao, J. Rius-Barile, T. Rees, and R. Froese. 2019. AquaMaps: Predicted range maps for aquatic species. World wide web electronic publication, www.aquamaps.org, version 10/2019.

Cite individual maps as, e.g., Computer Generated Map for Gadus morhua (Atlantic cod). www.aquamaps.org, version 10/2019 (accessed 01 Oct 2019).

Reviewed Native Distribution Map for Gadus morhua (Atlantic cod). www.aquamaps.org, version 10/2019 (accessed 01 Oct 2019).

Cite biodiversity maps as, e.g., Shark and Ray Biodiversity Map. www.aquamaps.org, version 10/2019 (accessed 01 Oct 2019).

Cite the environmental dataset as, e.g., Kesner-Reyes, K., Segschneider, J., Garilao, C., Schneider, B., Rius-Barile, J., Kaschner, K., and Froese, R.(editors). AquaMaps Environmental Dataset: Half-Degree Cells Authority File (HCAF). World Wide Web electronic publication, www.aquamaps.org/main/envt_main.php, ver. 7, 10/2019.

Using Full or Large Sets of AquaMaps Data We encourage partnering with the AquaMaps team for larger research projects or publications that would make intensive use of AquaMaps to ensure that you have access to the latest version and/or reviewed maps, the limitations of the data set are clearly understood and addressed, and that critical maps and/or unlikely results are recognized as such and double-checked for correctness prior to drawing conclusions and/or subsequent publication.

The AquaMaps team can be contacted through Rainer Froese (rfroese@geomar.de) or Kristin Kaschner (Kristin.Kaschner@biologie.uni-freiburg.de).

Privacy Policy AquaMaps uses log data generate usage statistics. Like most websites, AquMaps gathers information about internet protocol (IP) addresses, browser, referring pages, operating system, date/time, clicks, and visited pages, and store it in log files. This information is used to find errors in our website, analyze trends, and determine country of origin of our users. The log files are stored indefinitely. Only the administrators of the AquaMaps server has direct access to the log files. The information is used to inform further development of AquaMaps. Usage statistics may be shared with third parties for non-commercial purposes.

Disclaimer AquaMaps generates standardized computer-generated and fairly reliable large scale predictions of marine and freshwater species. Although the AquaMaps team and their collaborators have obtained data from sources believed to be reliable and have made every reasonable effort to ensure its accuracy, many maps have not yet been verified by experts and we strongly suggest you verify species occurrences with independent sources before usage. We will not be held responsible for any consequence from the use or misuse of these data and/or maps by any organization or individual.

Copyright This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License (CC-BY-NC). You are welcome to include text, numbers and maps from AquaMaps in your own web sites for non-commercial use, given that such inserts are clearly identified as coming from AquaMaps, with a backward link to the respective source page. Note that although species photos and drawings draw mainly from FishBase and SeaLifeBase, they belong to the indicated persons or organizations and have their own copyright statements.

Our Phase I study demonstrated that muons, the long-range charged component of GCR showers, can penetrate SSBs on the order of a km in diameter or less, providing information on their interior structure. Muons produced in Earth’s atmosphere have been applied to image the interior of large objects, such as the Great Pyramids and volcanos. In Phase I, we found that the production of muons in the solid surfaces of airless bodies is much smaller than in Earth’s atmosphere. Nevertheless, the flux of transmitted muons is sufficient to detect inclusions within an asteroid or comet in a reasonable period of time, ranging from hours to weeks, depending on the size of the SSB and the density contrast, position and size of the inclusion. The intrinsic spatial resolution of muon radiography (“muography”) is on the scale of a few meters. The spatial resolution that can be achieved in practice depends on signal intensity and integration time, the angular resolution of the muon tracker (hodoscope) and details of data reduction and analysis methodology.

Our Phase II project will continue to assess remaining unknowns for the application of muography to determining the interior structure of SSBs, assess risks for implementation, and provide a roadmap for development of SSB muography beyond the NIAC program. To achieve our objectives, we will work on four interrelated tasks:

• Signal and background characterization: Characterize the production and transmission of muons and secondary particle backgrounds made by cosmic ray showers in SSBs;
• Imaging studies: Develop methods to determine the density structure of SSB interiors and near-surface features from radiographic and tomographic data;
• Instrument design: Using simulations and bench-top laboratory experiments, investigate specific concepts for the design of compact hodoscopes that can be deployed on a spacecraft or in situ;
• Synthesis: Determine the range of applicability of the concept, identify the steps needed for maturation of the concept, and explore concepts for a pilot muography mission.

Successful implementation of SSB muography requires a thorough understanding of muon production and transmission as well as sources of background. Phase I demonstrated that muon production is sensitive to the density of the top-most meter of the regolith. Thus, unknown variations in regolith density may obscure interior structure. Limb imaging of muons and the use of radar data to remotely map near-surface density will be explored as possible ways to mitigate variations in muon production. A compact, inexpensive system that could be deployed on a spacecraft or in situ appears to be feasible and warrants further study. A successful design must be capable of separately measuring the transmitted muon signal from the primary GCRs and secondary particles that scatter into the field-of-view of the hodoscope. This can be accomplished, for example, using Cherenkov radiators to reject lower energy scattered particles and to determine particle direction. Concepts for imaging systems identified in Phase I will be scrutinized.

Phase II will be carried out by a multidisciplinary project team with broad experience in cosmic ray physics, remote sensing, meteoritics and planetary science. While the development of muography for SSBs is risky, the potential benefits are significant. There are presently no established methods to directly characterize the interior structure and macroporosity of an asteroid or comet. Muography could provide a direct and cost-effective means of probing the interior density structure.

Redmap is a primarily a website that invites the community to spot, log and map marine species that are uncommon in their region, or along particular parts of their coast. The information collected is mapped and displayed on the site, demonstrating, in time, how species distributions may be changing.

Sightings are divided into two categories – those with a photo that can be ‘verified’ by a marine biologist, and sightings without photos that we call community sightings (anecdotal). All the information collected, with and without photos, is mapped and will be used in the following years to map out a ‘story’ of changes occurring in our marine environment.

The main data collected includes the species sighted (normally selected from a list comprising preselected species of interest), the location, date/time and activity being undertaken. Other optional information gathered include biological data such as sex, size and weight and environmental data such as water depth and temperature and habitat.

This record is associated with live data (and will subsequently change over time) and spatial elements have reduced accuracy. It is also subject to a three year embargo (ie. does not contain data less than three years old). If you wish to discuss obtaining a citable, static dataset, that is current and/or contains accurate spatial elements, please see Point of Contact.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands†from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Refugio Beach map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and ... Visit https://dataone.org/datasets/c60046f2-c27d-4c56-bc2f-38b41051b7e8 for complete metadata about this dataset.

This digital data release presents contour data from multiple subsurface geologic horizons as presented in previously published summaries of the regional subsurface configuration of the Michigan and Illinois Basins. The original maps that served as the source of the digital data within this geodatabase are from the Geological Society of America’s Decade of North American Geology project series, “The Geology of North America” volume D-2, chapter 13 “The Michigan Basin” and chapter 14 “Illinois Basin Region”. Contour maps in the original published chapters were generated from geophysical well logs (generally gamma-ray) and adapted from previously published contour maps. The published contour maps illustrated the distribution sedimentary strata within the Illinois and Michigan Basin in the context of the broad 1st order supercycles of L.L. Sloss including the Sauk, Tippecanoe, Kaskaskia, Absaroka, Zuni, and Tejas supersequences. Because these maps represent time-transgressive surfaces, contours frequently delineate the composite of multiple named sedimentary formations at once. Structure contour maps on the top of the Precambrian basement surface in both the Michigan and Illinois basins illustrate the general structural geometry which undergirds the sedimentary cover. Isopach maps of the Sauk 2 and 3, Tippecanoe 1 and 2, Kaskaskia 1 and 2, Absaroka, and Zuni sequences illustrate the broad distribution of sedimentary units in the Michigan Basin, as do isopach maps of the Sauk, Upper Sauk, Tippecanoe 1 and 2, Lower Kaskaskia 1, Upper Kaskaskia 1-Lower Kaskaskia 2, Kaskaskia 2, and Absaroka supersequences in the Illinois Basins. Isopach contours and structure contours were formatted and attributed as GIS data sets for use in digital form as part of U.S. Geological Survey’s ongoing effort to inventory, catalog, and release subsurface geologic data in geospatial form. This effort is part of a broad directive to develop 2D and 3D geologic information at detailed, national, and continental scales. This data approximates, but does not strictly follow the USGS National Cooperative Geologic Mapping Program's GeMS data structure schema for geologic maps. Structure contour lines and isopach contours for each supersequence are stored within separate “IsoValueLine” feature classes. These are distributed within a geographic information system geodatabase and are also saved as shapefiles. Contour data is provided in both feet and meters to maintain consistency with the original publication and for ease of use. Nonspatial tables define the data sources used, define terms used in the dataset, and describe the geologic units referenced herein. A tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and accompanying nonspatial tables.

Redmap is a primarily a website that invites the community to spot, log and map marine species that are uncommon in their region, or along particular parts of their coast. The information collected …Show full descriptionRedmap is a primarily a website that invites the community to spot, log and map marine species that are uncommon in their region, or along particular parts of their coast. The information collected is mapped and displayed on the site, demonstrating, in time, how species distributions may be changing. Sightings are divided into two categories – those with a photo that can be ‘verified’ by a marine biologist, and sightings without photos that we call community sightings (anecdotal). All the information collected, with and without photos, is mapped and will be used in the following years to map out a ‘story’ of changes occurring in our marine environment. The main data collected includes the species sighted (normally selected from a list comprising preselected species of interest), the location, date/time and activity being undertaken. Other optional information gathered include biological data such as sex, size and weight and environmental data such as water depth and temperature and habitat. This record is associated with live data (and will subsequently change over time) and spatial elements have reduced accuracy. It is also subject to a three year embargo (ie. does not contain data less than three years old). If you wish to discuss obtaining a citable, static dataset, that is current and/or contains accurate spatial elements, please see Point of Contact.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands†from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Coal Oil Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and... Visit https://dataone.org/datasets/c27eb10d-58ce-427a-b40b-b8398ab9e64f for complete metadata about this dataset.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands†from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Ventura map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photog... Visit https://dataone.org/datasets/09922c17-87f2-4a54-9836-dd73cb7d381f for complete metadata about this dataset.

This GIS dataset depicts the surficial geology of the Ray Lake Area (NTS 84D/NW) (GIS data, polygon features). The data were created in geodatabase format and output for public distribution in shapefile format. These data comprise the polygon features of Alberta Geological Survey Map 557, Surficial Geology of the Ray Lake Area (NTS 84D/NW).

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, ...

Abstract ======== This data set consists of the MESSENGER XRS reduced data record observations, also known as RDRs, which are derived from the calibrated data records, CDRs. Each XRS observation results in four X-ray spectra. When an X-ray interacts with one of the four detectors, a charge or voltage pulse is generated. This signal is converted into one of 2^8 (256) channels, which are correlated to energy. Over a commanded integration time period a histogram of counts as a function of energy (channel number) is recorded. The EDRs are the number of events in each channel of the four detectors accumulated over the integration period. Channels above or below the useful energy range of the detectors are not transmitted. The result is three 244-channel GPC histograms and one 231-channel solar monitor histogram, each of which is designated as a single X-ray spectrum. Each observation is calibrated and processed into the CDR data set and then further processed to produce a map of elemental ratios, the maps of which compose the RDR data set.

Credit report of Rays Distribution Pty Ltd contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Fossils, including those that occasionally preserve decay-prone soft-tissues, are mostly made of minerals. Accessing their chemical composition provides unique insight into their past biology and/or the mechanisms by which they preserve, leading to a series of developments in chemical and elemental imaging. However, the mineral composition of fossils, particularly where soft-tissues are preserved, is often only inferred indirectly from elemental data, while X-ray diffraction that specifically provides phase identification received little attention. Here, we show the use of synchrotron radiation to generate not only X-ray fluorescence elemental maps of a fossil, but also mineralogical maps in transmission geometry using a two-dimensional area detector placed behind the fossil. This innovative approach was applied to millimetre-thick cross-sections prepared through three-dimensionally preserved fossils, as well as to compressed fossils. It identifies and maps mineral phases and their distribution at the microscale over centimetre-sized areas, benefitting from the elemental information collected synchronously, and further informs on texture (preferential orientation), crystallites size and local strain. Probing such crystallographic information is instrumental in defining mineralization sequences, reconstructing the fossilization environment and constraining preservation biases. Similarly, this approach could potentially provide new knowledge on other (bio)mineralization processes in environmental sciences. We also illustrate that mineralogical contrasts between fossil tissues and/or the encasing sedimentary matrix can be used to visualize hidden anatomies in fossils.

Methods Data were collected at the DiffAbs beamline of the SOLEIL Synchrotron source (France). Synchronous synchrotron rapid scanning X-ray fluorescence and diffraction mapping (SRS-XRFD) was performed using an incident X-ray beam of 16.2 or 18 keV, monochromatised using a Si(111) double-crystal monochromator, with a beam size diameter reduced down to 50 or 100 µm using platinum pinholes, or focused down to ~10 µm using Kirkpatrick-Baez mirrors. XRF was collected using a 4-element silicon drift detector (SDD, Vortex ME4, Hitachi High-Technologies Science America, Inc., total active area: 170 mm2) oriented at 90° to the incident beam, in the horizontal plane. XRD was collected in transmission geometry using a 2D hybrid pixel detector (XPAD S140, 240×560 pixels of 130 µm each), placed behind the sample at a distance of typically 200–300 mm such to intercept diffraction rings over an angular range of ~7° in scattering angle (2θ). Two-dimensional scanning was done by moving laterally the fossils in a plane rotated around the vertical axis by 20° to the primary beam (i.e., incident angle), to limit X-ray beam footprint on the sample but also such that the sample exhibits its surface to the SDD detector (no shadowing of the reflected XRD signal, figure 1a). Mapping over the entire fossils at a 35–100 µm lateral resolution was performed on the fly using the FLYSCAN platform. A full XRF spectrum and one or several XRD images were collected at each pixel.

The present dataset includes 6 types of data:

(1) Synchrotron X-Ray Fluorescence elemental maps

Methods: All elemental distributions presented in the paper correspond to integrated intensities around emission lines of elements of interest (XRF peaks), represented using linear (expect figure 1b, logarithmic) grey or color scales that go from dark to light, respectively for low to high intensities.

Data: figure1b_AsPb-map_DATA_XRF.txt; figure1b_Mn-map_DATA_XRF.txt; figure1b_Zn-map_DATA_XRF.txt; figure1b_stackRGB_DATA_XRF.tif; figure2b_Ca-map_DATA_XRF.txt; figure2b_Fe-map_DATA_XRF.txt; figure2b_Y-map_DATA_XRF.txt; figure2b_stackRGB_DATA_XRF.tif; figure5f_Y-map_DATA_XRF.txt

(2) Synchrotron X-Ray Diffraction detector images

Methods: A few XPAD detector images are shown in the paper, either simply after flat correction (figure 1c) or after conversion to (2θ-Ѱ) coordinates (figure 2e). These images are represented using logarithmic color scales that go from dark to light, respectively for low to high intensities.

Data: figure1c_left_DATA_XRD.txt; figure1c_right_DATA_XRD.txt; figure2e_DATA_XRD.xlsx

(3) Diffractograms

Methods: XPAD detector images were processed (azimuthal data regrouping along y direction) to extract their respective diffractograms (Intensity vs. 2θ profiles). Phase identification and 2θ calibration were performed using powder XRD diffractograms obtained on fragments of the sedimentary matrix (and of the fossil when possible) using the Match! software (Crystal Impact) making use of the International Centre for Diffraction Data (ICDD)- PDF 2015 database. Additional peaks in the XRD maps could then be identified using Match/ICDD database, as well as from the elemental information provided by the XRF data.

Data: figure1d_DATA_XRD.xlsx; figure2f_DATA_XRD.xlsx

(4) Synchrotron X-Ray Diffraction mineral maps

Methods: During XPAD detector images processing 4D datasets (x, y, 2θ, intensity) were also generated, and then particular XRD contrast maps. Phase identification and 2θ calibration is discussed above. All phase distributions presented in the paper correspond to integrated intensities of XRD peaks of interest, represented using linear grey or color scales that go from dark to light, respectively for low to high intensities.

Data: figure1e_left_DATA_XRD.txt; figure1e_center_DATA_XRD.txt; figure1e_right_DATA_XRD.txt; figure2c_A211-map_DATA_XRD.txt; figure2c_C006-map_DATA_XRD.txt; figure2c_Q101-map_DATA_XRD.txt; figure2c_stackRGB_DATA_XRD.tif; figure2d_C012-map_DATA_XRD.txt; figure2d_C113-map_DATA_XRD.txt; figure2d_C202-map_DATA_XRD.txt; figure2d_stackRGB_DATA_XRD.tif; figure4a_17p97-map_DATA_XRD.txt; figure4a_25p09-map_DATA_XRD.txt; figure4a_26p01-map_DATA_XRD.txt; figure4a_stackRGB_DATA_XRD.tif; figure4b_22p51-map_DATA_XRD.txt; figure4b_26p97-map_DATA_XRD.txt; figure4b_27p63-map_DATA_XRD.txt; figure4b_stackRGB_DATA_XRD.tif; figure5b_FAp002-map-head_DATA_XRD.txt; figure5b_FAp211-map-head_DATA_XRD.txt; figure5b_phyll-map-head_DATA_XRD.txt; figure5b_stackRGB-head_DATA_XRD.tif; figure5b_FAp002-map-tail_DATA_XRD.txt; figure5b_FAp211-map-tail_DATA_XRD.txt; figure5b_phyll-map-tail_DATA_XRD.txt; figure5b_stackRGB-tail_DATA_XRD.tif; figure5c_FAp002-map-cropped_DATA_XRD.txt; figure5e_FAp002-map_DATA_XRD.txt

(5) Crystallite sizes

Methods: By Gaussian fitting the 2θ profile of XRD peaks attributed to different crystalline phases, corresponding crystallite sizes were extracted (for each pixel of the maps) by converting their full width at half maximum (FWHM) using Scherrer’s formula. It was assumed that only the crystallite size is contributing to the broadening, and an instrument resolution function measured as ~0.035° (amounting several 10 %, and up to 50 % of the measured peak FWHM) was also taken into account for FWHM deconvolution. Crystallite size distributions are represented in the paper using linear color scales that go from dark to light, respectively for low to high intensities.

Data: figure2g_A211-crystSize-map_DATA_XRD.txt; figure2g_C006-crystSize-map_DATA_XRD.txt; figure2g_Q101-crystSize-map_DATA_XRD:txt; figure2g_stackRGB_DATA_XRD.tif

(6) Local texture measurements

Methods: In order to confirm some microstructure results obtained using the local probe XRD approach, supplementary local texture measurements were performed. This was done by scanning it in azimuth (Φ, rotation around the sample surface normal) and elevation (Ѱ, rotation around the projection of the impinging X-ray beam on the sample surface), while recording, at each position, the X-ray scattered signal. The resulting intensity is represented in a map, in polar coordinates (azimuth angle and elevation, e.g. figures 3f–h). In this way, when one or several crystallites are oriented such that the Bragg law is fulfilled for the particular inter-reticular distance probed (or the particular Bragg angle 2θ), high signal is found in the particular corresponding regions of the polar map, allowing: i) to retrieve the particular orientation of the grains (j, y), and ii) to possibly quantify the volume ratio of that particular orientation, compared to other orientations on the map. Rapid texture measurements were performed using the XPAD area detector. The sample was illuminated by the impinging X-ray beam (of size ~ 150 × 150 µm2 in this case) and the azimuth (Φ) and elevation (Ѱ) angles were scanned, the first one continuously. An image was recorded in each point, then texture maps for various 2θ angles (i.e. volumes) were reconstructed. Then, a similar dataset was recorded at the next vertical position on the sample. Local texture measurements are represented in the paper using logarithmic color scales that go from dark to light, respectively for low to high intensities.

Data: Figure3b-d_DATA_XRD.xlsx; figure3f_left_DATA_XRD.txt; figure3f_right_DATA_XRD.txt; figure3g_left_DATA_XRD.txt; figure3g_right_DATA_XRD.txt; figure3h_left_DATA_XRD.txt; figure3h_right_DATA_XRD.txt

This GIS dataset depicts the surficial geology of the Ray Lake Area (NTS 84D/NW). The data were created in geodatabase format and output for public distribution in shapefile format. These data comprise the point features of Alberta Geological Survey Map 557, Surficial Geology of the Ray Lake Area (NTS 84D/NW).

We show a dataset composed by Radio Maps Estimation (RME) and Cells Maps Estimation (CME) for the 5GHz band WIFI in indoor scenarios: it has 60 indoor constructions plans and 1000 distributions initially for a training process and 20 indoor constructions plans and 50 distributions aditionals for a test process of access points to even construction. These distributions are random and several WLAN's structures: 1 to 5 access points.

The above explain that we got a total of 61000 RME and CME, this presents that is a model without interference between channels.

Every coverage map have like maximum power delivered is Pr = Pt = 26 dBm (according to data from current commercial equipment) and like minimum power a value noise established in Pr = KTB, where K is the Boltzmann's constant, T the enviroment temperatura equal to 290°K and B the band width equal to 80MHz.

Dataset DeepFIRP is the result of a lot of simulations by a own software developed in MATLAB that work with the IEEE 802.11ax channel model.

The pictures have a depth of 8 bits and size of 256pixels X 256pixels equivalents to indoor constructions of 20 X 20 m². These ones make reference to offices's spaces at general or classroom. We present file CSV with the data of coverage to use, too.

A application to this dataset and the codes used for generate it is found here, where we implement a U-Net model for theRME and CME in indoor enviroments. This investigation contribute in novels methods for estimate by fast way coverage and cells maps using deep-learning in comparation with the conventional phisics methods like dominath-path model or ray-tracing. Whats allows save a lot of amount time in the WLANs's designs.