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138 results returned

  1. Title: Surficial geology of the Mesabi Iron Range, Minnesota, M-164

    Contributors:

    Summary: Quaternary geology map showing interpretations of Quaternary (Pleistocene [glacial] and Holocene [post-glacial]) surficial geology (distribution and type of materials at the land surface), of the Mesabi Iron Range, scale 1:100,000.

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  2. Title: Inland Trawl Blocks: California, 2006

    Contributors:

    Summary: For decades, California fishery reporting and management has been organized and documented using a 10 minute latitude-longitude (10 minute) grid, known colloquially as 'California Trawl Blocks'. In recent years, however, a need has developed for finer (smaller area) grid blocks to record catch and develop habitat maps and models, especially in coastal nearshore waters and for residential and sessile species. This polygon shapefile of 1 minute latitude-longitude (1 minute) blocks was created to nest within the original 10 minute latitude-longitude blocks, thus allowing the transfer of 10 minute historic and current catch data to each of the 100 1 minute cells within. The 1 minute blocks in this shapefile extend inland to include coastal areas, estuaries and bays. This shapefile is a polygon file, not a raster file, therefore, area for each 1 minute cell may be unique. This coverage provides a systematic polygonal grid that allows the ocean to be divided into 1 minute latitude-longitude administrative blocks for the purpose of management, analysis and defense of California's natural marine resources. Specifically, the California Recreational Fisheries Survey (CRFS) project has adopted these block sequence codes to gather recreational fisheries information statewide. Boundaries were drawn on Latitudinal and Longitudinal one minute lines from the furthest south and West Longitude and Latitude line to the furthest North and East. This Grid was then clipped to the Caltrawl ten nautical mile grid and the remaining blocks referenced and indexed. The vector drawing program used by ET Geowizards created artifacts in the form of slivers - Please see "Process Step" Tab for detailed instructions of how the Grid was created, edited and indexed. Reprojecting the shapefile may increase and/or decrease the magnitude of this error. King, Howatt and Wade, Gina. (2006). Inland Trawl Blocks: California, 2006. California. Department of Fish and Game. Marine Resources Region. Available at: http://purl.stanford.edu/rf806nt4939. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  3. Title: Causes of Forest Fragmentation in the United States (270 Meter Resolution), 1992

    Contributors:

    Summary: This raster image is a 270-meter resolution grid map of the conterminous United States in GeoTIFF format, created from National Land Cover Data (NLCD). The NLCD data was reclassified into four categories: forest, other natural (e.g. grassland, wetland, etc.), human land use (e.g. agriculture, urban, etc.), and nodata (water, ice and snow, and bare rock/sand). A 9 x 9-pixel moving window was then used to generate forest edge measurements for every pixel, regardless of its class. Within each window, the edges of all forest pixels were examined to determine what type of land cover shared each edge. Three new grids were created, one for each edge type (forest-forest, forest-natural, and forest-human). The values in these grids were calculated as the number of edges with the appropriate type in the window divided by the total number of forest edges, regardless of neighbor. These grids represented forest connectivity (forest-forest edges), naturally caused forest fragmentation (forest-natural edges), and human caused forest fragmentation (forest- human edges). In the map, forest connectivity is displayed in green, natural fragmentation in blue, and human fragmentation in red. Yellow indicates areas that are an approximately equal mix of connected forest and human fragmentation, while cyan indicates areas that are an approximately equal mix of connected forest and natural fragmentation. Black represents areas with no forest in the 9 x 9-pixel window; white represents ignored or nodata areas, such as water, ice and snow, and bare rock/sand. Forest fragmentation has been studied extensively and can be quantified in several ways. This map layer is the first to identify sources of forest fragmentation, separating fragmentation into human and natural components. The data may be a useful tool for decision makers in identifying areas for protection or restoration. Areas displayed in yellow represent transition zones between connected forest and human-fragmented forest. Because human land uses tend to expand over time, these areas will be the most likely to experience further degradation. In time, the transition zones may become highly fragmented and new transitional areas will appear deeper in the intact forest. Consequently, the yellow areas in the map may represent excellent opportunities for protection or restoration. Protecting transitional and adjacent areas may limit further expansion or degradation of the transitional areas. Restoration efforts to eliminate or reduce fragmentation may produce larger patches of connected forest. Wade, Tim. (2004). Causes of Forest Fragmentation in the United States (270 Meter Resolution), 1992. National Atlas of the United States. Available at: http://purl.stanford.edu/zt983db2960. Downloadable data is scaled from 0 to 100 and is meant to be used in analyses. For display purposes, it is recommended that the data be rescaled from 0 to 255 to capture the full spectrum of possible fragmentation combinations. Colors are subdued and yellows and cyans may be missing in the display, using data scaled from 0 to 100. These data are based on National Land Cover Data (NLCD). Information about NLCD is available online at: <http://landcover.usgs.gov/natllandcover.asp>. For additional information see Vogelmann, J.E., S.M. Howard, L. Yang, C.R. Larson, B.K. Wylie, and N. van Driel. 2001. Completion of the 1990s National land cover data set for the conterminous United States from Landsat Thematic Mapper data and ancillary data sources. Photogrammetric Engineering and Remote Sensing 67: 650-662. The data are stored in three bands, one each for forest connectivity (Pff), human fragmentation (Pfa), and natural fragmentation (Pfn). Values have been scaled from 0 to 100, with -9999 (nodata) where the NLCD identified water, ice and snow, or bare rock/sand (classes 11, 12 and 31). Values of 0 occur where the 9 x 9-pixel window contained no forest pixels or where all forest pixels were surrounded by nodata pixels. A value of 100 indicates a window where all forest pixel edges adjoin only one class. For example, a 100 in the forest connectivity band means all forest pixels in the window are adjacent to other forest pixels or a nodata pixel. It does not necessarily mean that all pixels in the window are forest. To display these data, it is highly recommended that their values be stretched to range from 0 to 255. This will brighten and enhance the contrast in the image. Detailed information on the algorithms used to process the NLCD data to create a global fragmentation map can be found in: Wade, T.G, K.H. Riitters, J.D. Wickham, and K.B. Jones, 2003. Distribution and causes of global forest fragmentation. Conservation Ecology 7(2): 7. [online] URL: <http://www.consecol.org/vol7/iss2/art7>. Similar procedures were used to create this map layer. The United States Environmental Protection Agency (EPA), through its Office of Research and Development (ORD), partially funded and collaborated in this work under Interagency Agreement DW12939283-01-0 with the United States Department of Agriculture. It has been subjected to Agency review and approved for publication. The associated world file is included as part of the GeoTIFF. The contents of the world file are: >270.0000 >0.000000 >0.000000 >-270.0000 >-2262865.0000 >1038776.0000 The following projection file can be used when using ESRI's ArcGIS to view the GeoTIFF (any line breaks should be removed): PROJCS["NAD_1983_Lambert_Azimuthal_Equal_Area",GEOGCS ["GCS_Sphere_ARC_INFO",DATUM["D_Sphere_ARC_INFO",SPHEROID ["Sphere_ARC_INFO",6370997.0,0.0]],PRIMEM["Greenwich",0.0], UNIT["Degree",0.0174532925199433]],PROJECTION ["Lambert_Azimuthal_Equal_Area"],PARAMETER["False_Easting",0.0], PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian", -100.0],PARAMETER["Latitude_Of_Origin",45.0],UNIT["Meter",1.0]] None. Acknowledgment of the National Atlas of the United States of America, the U.S. Environmental Protection Agency, the U.S. Forest Service, and (or) the U.S. Geological Survey would be appreciated in products derived from these data. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  4. Title: Causes of Forest Fragmentation in the United States (540 Meter Resolution), 1992

    Contributors:

    Summary: This raster layer is a 540 meter resolution grid map of the conterminous United States in GeoTIFF format, created from National Land Cover Data (NLCD). The NLCD data was reclassified into four categories: forest, other natural (e.g. grassland, wetland, etc.), human land use (e.g. agriculture, urban, etc.), and nodata (water, ice and snow, and bare rock/sand). A 9 x 9-pixel moving window was then used to generate forest edge measurements for every pixel, regardless of its class. Within each window, the edges of all forest pixels were examined to determine what type of land cover shared each edge. Three new grids were created, one for each edge type (forest-forest, forest-natural, and forest-human). The values in these grids were calculated as the number of edges with the appropriate type in the window divided by the total number of forest edges, regardless of neighbor. These grids represented forest connectivity (forest-forest edges), naturally caused forest fragmentation (forest-natural edges), and human caused forest fragmentation (forest- human edges). In the map, forest connectivity is displayed in green, natural fragmentation in blue, and human fragmentation in red. Yellow indicates areas that are an approximately equal mix of connected forest and human fragmentation, while cyan indicates areas that are an approximately equal mix of connected forest and natural fragmentation. Black represents areas with no forest in the 9 x 9-pixel window; white represents ignored or nodata areas, such as water, ice and snow, and bare rock/sand. This layer is part of the 1997-2014 edition of the National Atlas of the United States. Forest fragmentation has been studied extensively and can be quantified in several ways. This map layer is the first to identify sources of forest fragmentation, separating fragmentation into human and natural components. The data may be a useful tool for decision makers in identifying areas for protection or restoration. Areas displayed in yellow represent transition zones between connected forest and human-fragmented forest. Because human land uses tend to expand over time, these areas will be the most likely to experience further degradation. In time, the transition zones may become highly fragmented and new transitional areas will appear deeper in the intact forest. Consequently, the yellow areas in the map may represent excellent opportunities for protection or restoration. Protecting transitional and adjacent areas may limit further expansion or degradation of the transitional areas. Restoration efforts to eliminate or reduce fragmentation may produce larger patches of connected forest. Wade, Tim. (2004). Causes of Forest Fragmentation in the United States (540 Meter Resolution), 1992. National Atlas of the United States. Available at: http://purl.stanford.edu/hf653vx2307. Downloadable data is scaled from 0 to 100 and is meant to be used in analyses. For display purposes, it is recommended that the data be rescaled from 0 to 255 to capture the full spectrum of possible fragmentation combinations. Colors are subdued and yellows and cyans may be missing in the display, using data scaled from 0 to 100. These data are based on National Land Cover Data (NLCD). Information about NLCD is available online at: <http://landcover.usgs.gov/natllandcover.asp>. For additional information see Vogelmann, J.E., S.M. Howard, L. Yang, C.R. Larson, B.K. Wylie, and N. van Driel. 2001. Completion of the 1990s National land cover data set for the conterminous United States from Landsat Thematic Mapper data and ancillary data sources. Photogrammetric Engineering and Remote Sensing 67: 650-662. The data are stored in three bands, one each for forest connectivity (Pff), human fragmentation (Pfa) and natural fragmentation (Pfn). Values have been scaled from 0 to 100, with -9999 (nodata) where the NLCD identified water, ice and snow, or bare rock/sand (classes 11, 12 and 31). Values of 0 occur where the 9 x 9-pixel window contained no forest pixels or where all forest pixels were surrounded by nodata pixels. A value of 100 indicates a window where all forest pixel edges adjoin only one class. For example, a 100 in the forest connectivity band means all forest pixels in the window are adjacent to other forest pixels or a nodata pixel. It does not necessarily mean that all pixels in the window are forest. To display these data, it is highly recommended that their values be stretched to range from 0 to 255. This will brighten and enhance the contrast in the image. Detailed information on the algorithms used to process the NLCD data to create a global fragmentation map can be found in: Wade, T.G, K.H. Riitters, J.D. Wickham, and K.B. Jones, 2003. Distribution and causes of global forest fragmentation. Conservation Ecology 7(2): 7. [online] URL: <http://www.consecol.org/vol7/iss2/art7>. Similar procedures were used to create this map layer. The United States Environmental Protection Agency (EPA), through its Office of Research and Development (ORD), partially funded and collaborated in this work under Interagency Agreement DW12939283-01-0 with the United States Department of Agriculture. It has been subjected to Agency review and approved for publication. The associated world file is included as part of the GeoTIFF. The contents of the world file are: >540.0000 >0.000000 >0.000000 >-540.0000 >-2262730.0000 >1038730.0000 The following projection file can be used when using ESRI's ArcGIS to view the GeoTIFF (any line breaks should be removed): PROJCS["NAD_1983_Lambert_Azimuthal_Equal_Area",GEOGCS ["GCS_Sphere_ARC_INFO",DATUM["D_Sphere_ARC_INFO",SPHEROID ["Sphere_ARC_INFO",6370997.0,0.0]],PRIMEM["Greenwich",0.0], UNIT["Degree",0.0174532925199433]],PROJECTION ["Lambert_Azimuthal_Equal_Area"],PARAMETER["False_Easting",0.0], PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian", -100.0],PARAMETER["Latitude_Of_Origin",45.0],UNIT["Meter",1.0]] None. Acknowledgment of the National Atlas of the United States of America, the U.S. Environmental Protection Agency, the U.S. Forest Service, and (or) the U.S. Geological Survey would be appreciated in products derived from these data. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  5. Title: London, England, 1851 (Raster Image)

    Contributors:

    Summary: This layer is a georeferenced raster image of the historic paper map entitled: Reynolds's map of London : with the latest improvements, drawn & engraved by H. Martin. It was published by J. Reynolds in 1851. Scale [ca. 1:16,000]. The image inside the map neatline is georeferenced to the surface of the earth and fit to the British National Grid coordinate system (British National Grid, Airy Spheroid OSGB (1936) Datum). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, buildings, parks, docks, and more. Relief is shown by hachures. This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.

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  6. Title: Reynolds' large coloured map of London and its suburbs, with visitor's guide, street directory, views, etc.; At head of title: New edition;Title on map: Reynold's new map of London a d its suburbs

    Contributors:

    Summary: Includes index 1 map: col.; 64 x 96 cm., folded in cover text 40 p.; 19 cm.

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  7. Title: Reynolds's map of modern London : divided into quarter mile sections

    Contributors:

    Summary: 48 x 73 centimeters

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  8. Title: Simple Bouguer gravity map of Minnesota, Brainerd sheet, M-40

    Contributors:

    Summary: Bouguer gravity anomaly map (anomaly related to different densities of rocks in the upper crust, Bouguer anomaly is a corrected difference between an observed gravity measurement and value predicted from a generalized earth model), shown as contour lines (isolines) of equal value, Brainerd quadrangle, scale 1:250,000.

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  9. Title: Gutenko Nunataks: Antarctica

    Contributors:

    Summary: Projection: Lambert Conformal Conic Projection: Standard Parallels -76º40' and -79º20'; Series: USGS 1:250,000 Geologic Reconnaissance Series

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  10. Title: Alexandra Mountains: Antarctica

    Contributors:

    Summary: Projection: Lambert Conformal Conic Projection: Standard Parallels -76º40' and -79º20'; Series: USGS 1:250,000 Geologic Reconnaissance Series

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  11. Title: Guest Peninsula: Antarctica

    Contributors:

    Summary: Projection: Lambert Conformal Conic Projection: Standard Parallels -76º40' and -79º20'; Series: USGS 1:250,000 Geologic Reconnaissance Series

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  12. Title: Boyd Glacier: Antarctica

    Contributors:

    Summary: Projection: Lambert Conformal Conic Projection: Standard Parallels -76º40' and -79º20'; Series: USGS 1:250,000 Geologic Reconnaissance Series

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  13. Title: Twin Cities Metropolitan Area Urban Tree Canopy Assessment (2015)

    Contributors:

    Summary: A high-resolution (1-meter) tree canopy assessment was completed for the Twin Cities Metropolitan Area. Mapping of existing and potential tree canopy is critical for urban tree management at the landscape level. This classification was created from combined 2015 aerial imagery, LIDAR data, and ancillary thematic layers. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach through multi-resolution image segmentation and an iterative set of classification commands in the form of customized rulesets. eCognition Developer was used to develop the rulesets and produce raster classification products for TCMA. The results were evaluated using randomly placed and independent verified assessment points. The classification product was analyzed at regional scales to compare distributions of tree canopy spatially and at different resolutions. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of tree canopy with highly accurate results.

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  14. Title: Duluth 1-Meter Land Cover Classification (Urban Focused)] (2016)

    Contributors:

    Summary: A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland. We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.

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  15. Title: Twin Cities Metropolitan Area 1-Meter Land Cover Classification (Urban Focused) (2016)

    Contributors:

    Summary: A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland. We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.

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  16. Title: Rochester 1-Meter Land Cover Classification (Urban Focused)] (2016)

    Contributors:

    Summary: A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland. We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.

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  17. Title: Backscatter C (7125): Offshore of Bolinas, California, 2010

    Contributors:

    Summary: This layer is a georeferenced raster image containing acoustic-backscatter data for the offshore area of Bolinas, California. The acoustic-backscatter map was generated from data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. Therefore, note that the shaded relief map coverage (see Bathymetry Hillshade--Offshore of Bolinas, California, DS 781) does not match the acoustic-backscatter map coverage (see Backscatter A-E--Offshore of Bolinas, California, DS 781). Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes. This layer is part of USGS Data Series 781. In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP) to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats and geology within the 3-nautical-mile limit of California's State Waters. CSMP has divided coastal California into 110 map blocks, each to be published individually as United States Geological Survey Open-File Reports (OFRs) or Scientific Investigations Maps (SIMs) at a scale of 1:24,000. Maps display seafloor morphology and character, identify potential marine benthic habitats and illustrate both the seafloor geology and shallow (to about 100 m) subsurface geology. Data layers for bathymetry, bathymetric contours, acoustic backscatter, seafloor character, potential benthic habitat and offshore geology were created for each map block, as well as regional-scale data layers for sediment thickness, depth to transition, transgressive contours, isopachs, predicted distributions of benthic macro-invertebrates and visual observations of benthic habitat from video cruises over the entire state. This coverage can be used to aid in assessments and mitigation of geologic hazards in the coastal region and to provide sufficient geologic information for land-use and land-management decisions both onshore and offshore. These data are intended for science researchers, students, policy makers, and the general public. This information is not intended for navigational purposes.The data can be used with geographic information systems (GIS) software to display geologic and oceanographic information. Johnson, S.Y., Greene, H.G., Manson, M.W., Hartwell, S.R., Endris, C.A., and Watt, J.T. (2014). Backscatter C (7125): Offshore of Bolinas, California, 2010. California State Waters Map Series Data Catalog: U.S. Geological Survey Data Series 781. Available at: http://purl.stanford.edu/zy254qx0409. None This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  18. Title: Bathymetry Hillshade: Offshore of San Francisco, California, 2008

    Contributors:

    Summary: This layer is a georeferenced raster image containing shaded relief (hillshade) data for the offshore area of San Francisco, California. The bathymetric and shaded relief maps of the area were generated from data collected by Fugro Pelagos and by California State University, Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry (sheets 1, 2) from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. A large portion of this map area was re-mapped in 2009, however the older bathymetry data were used in this map due to co-registered, acoustic backscatter data. A map that shows these data is published in Open-File Report 2015-1068, "California State Waters Map Series--Offshore of San Francisco, California." This layer is part of USGS Data Series 781. In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP) to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats and geology within the 3-nautical-mile limit of California's State Waters. CSMP has divided coastal California into 110 map blocks, each to be published individually as United States Geological Survey Open-File Reports (OFRs) or Scientific Investigations Maps (SIMs) at a scale of 1:24,000. Maps display seafloor morphology and character, identify potential marine benthic habitats and illustrate both the seafloor geology and shallow (to about 100 m) subsurface geology. Data layers for bathymetry, bathymetric contours, acoustic backscatter, seafloor character, potential benthic habitat and offshore geology were created for each map block, as well as regional-scale data layers for sediment thickness, depth to transition, transgressive contours, isopachs, predicted distributions of benthic macro-invertebrates and visual observations of benthic habitat from video cruises over the entire state. This coverage can be used to to aid in assessments and mitigation of geologic hazards in the coastal region and to provide sufficient geologic information for land-use and land-management decisions both onshore and offshore. These data are intended for science researchers, students, policy makers, and the general public. This information is not intended for navigational purposes. Dartnell, P., Kvitek, R.G., and Bretz, C.K. (2014). Bathymetry Hillshade: Offshore of San Francisco, California, 2008. California State Waters Map Series Data Catalog: U.S. Geological Survey Data Series 781. Available at: http://purl.stanford.edu/rc243mn3658. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  19. Title: Contours: Offshore of San Francisco, California, 2008

    Contributors:

    Summary: This line shapefile contains bathymetric contours at 10 meter intervals for the offshore area of San Francisco, California. This layer was generated from bathymetry data collected by Fugro Pelagos and by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from the merged 2-m bathymetric surface. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes. A map that shows these data is published in Open-File Report 2015-1068, "California State Waters Map Series--Offshore of San Francisco, California." This layer is part of USGS Data Series 781. In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP) to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats and geology within the 3-nautical-mile limit of California's State Waters. CSMP has divided coastal California into 110 map blocks, each to be published individually as United States Geological Survey Open-File Reports (OFRs) or Scientific Investigations Maps (SIMs) at a scale of 1:24,000. Maps display seafloor morphology and character, identify potential marine benthic habitats and illustrate both the seafloor geology and shallow (to about 100 m) subsurface geology. Data layers for bathymetry, bathymetric contours, acoustic backscatter, seafloor character, potential benthic habitat and offshore geology were created for each map block, as well as regional-scale data layers for sediment thickness, depth to transition, transgressive contours, isopachs, predicted distributions of benthic macro-invertebrates and visual observations of benthic habitat from video cruises over the entire state. This coverage can be used to to aid in assessments and mitigation of geologic hazards in the coastal region and to provide sufficient geologic information for land-use and land-management decisions both onshore and offshore. These data are intended for science researchers, students, policy makers, and the general public. This information is not intended for navigational purposes.The data can be used with geographic information systems (GIS) software to display geologic and oceanographic information. Dartnell, P., Kvitek, R.G., and Bretz, C.K. (2014). Contours: Offshore of San Francisco, California, 2008. California State Waters Map Series Data Catalog: U.S. Geological Survey Data Series 781. Available at: http://purl.stanford.edu/qj154qf5227. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  20. Title: Backscatter C (8101): Offshore of San Francisco, California, 2008

    Contributors:

    Summary: This layer is a georeferenced raster image containing acoustic-backscatter data for the offshore area of San Francisco, California. The acoustic-backscatter map of the area was generated from backscatter data collected by Fugro Pelagos and by California State University, Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). A map that shows these data is published in Open-File Report 2015-1068, "California State Waters Map Series--Offshore of San Francisco, California." This layer is part of USGS Data Series 781. In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP) to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats and geology within the 3-nautical-mile limit of California's State Waters. CSMP has divided coastal California into 110 map blocks, each to be published individually as United States Geological Survey Open-File Reports (OFRs) or Scientific Investigations Maps (SIMs) at a scale of 1:24,000. Maps display seafloor morphology and character, identify potential marine benthic habitats and illustrate both the seafloor geology and shallow (to about 100 m) subsurface geology. Data layers for bathymetry, bathymetric contours, acoustic backscatter, seafloor character, potential benthic habitat and offshore geology were created for each map block, as well as regional-scale data layers for sediment thickness, depth to transition, transgressive contours, isopachs, predicted distributions of benthic macro-invertebrates and visual observations of benthic habitat from video cruises over the entire state. This coverage can be used to to aid in assessments and mitigation of geologic hazards in the coastal region and to provide sufficient geologic information for land-use and land-management decisions both onshore and offshore. These data are intended for science researchers, students, policy makers, and the general public. This information is not intended for navigational purposes.The data can be used with geographic information systems (GIS) software to display geologic and oceanographic information. Dartnell, P., Erdey, M.D., Kvitek, R.G., and Bretz, C.K. (2014). Backscatter C (8101): Offshore of San Francisco, California, 2008. California State Waters Map Series Data Catalog: U.S. Geological Survey Data Series 781. Available at: http://purl.stanford.edu/sn375qd1706. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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