Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.

JALBTCX National Coastal Mapping Program Derived Products: Great Lakes & Ohio River DivisionThe layers depicted in this web map were developed to serve regional geospatial data needs of USACE Districts and agency partners to discover and download products derived from USACE National Coastal Mapping Program (NCMP) high resolution, topo-bathymetric lidar and imagery. The USACE NCMP acquires high-resolution, high-accuracy topographic/bathymetric lidar elevation and imagery on a recurring basis along the sandy shorelines of the US. The program's survey footprint includes an approximately 1-mile wide swath of topography, bathymetry and imagery 500-m onshore and 1000-m offshore. The standard suite of NCMP data products include topographic/bathymetric lidar point clouds, digital surface and elevation models, shoreline vectors and both true-color and hyperspectral imagery mosaics. Value-added derivative information products may include laser reflectance images, landcover classification images, volume change metrics, and the products to help address District project requirements. USACE Headquarters initiated the NCMP in 2004. The program's update cycle follows counter-clockwise along the US West Coast, Gulf Coast, East Coast and Great Lakes approximately every 5 years. Surveys in support of USACE project-specific missions and external partners are included constituent to the current NCMP schedule and reimbursable funding. All work is coordinated with Federal mapping partners through the Interagency Working Group on Ocean and Coastal Mapping (IWGOCM) and the 3D Elevation Program (3DEP).NCMP operations are executed by the Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX). The JALBTCX mission is to perform operations, research and development in airborne lidar bathymetry and complementary technologies to support the coastal mapping and charting requirements of the US Army Corps of Engineers, the US Naval Meteorology and Oceanography Command and the National Oceanic and Atmospheric Administration. Survey operations are conducted worldwide using the Coastal Zone Mapping and Imaging (CZMIL) system and other industry-based coastal mapping and charting systems. CZMIL is JALBTCX's in-house survey capability that includes and Optech International, CZMIL 03-1 lidar instrument with simultaneous topographic and bathymetric capabilities. CZMIL is integrated with an Itres CASI-1500 hyperspectral imager and an 80 MP Leica RCD30 RGBN camera. CZMIL collects 10-kHz lidar data with spatially- and temporally-concurrent digital true-color and hyperspectral imagery.

This dataset contains an inventory of landslides in many of the most landslide-prone parts of Minnesota. This project was created to improve our understanding of the landslide hazard in Minnesota and to provide a nearly statewide base map of landslide data. The mapping was performed by geologists from the U.S. Geological Survey, the Freshwater Society, and several academic institutions where undergraduate students, graduate students and faculty performed mapping. Contributing academic institution include the University of Minnesota Duluth, the University of Minnesota Twin Cities, the University of Wisconsin-Superior, Gustavus Adolphus College, Winona State University, Minnesota State University, Mankato, St. Thomas University, and North Dakota State University. These landslides were identified using several methods. These include analysis of historical records, direct field observation, location using satellite or aerial imagery, and identification in topographic data products derived from the statewide lidar data coverage. Most of the mapped landslides were identified using lidar derivatives and have not been evaluated in the field by geologists or engineers. These data should be considered a preliminary survey and are not intended to represent a complete and accurate inventory of landslides for these areas. There may be a range in the accuracy, detail, and completeness with which landslides are mapped, and in the information associated with a given landslide; however, all mapped landslides were reviewed by USGS personnel and the senior project members. Mapping procedures including the assignment of numerical values for confidence follow guidelines found in DOGAMI Special Paper 42: https://www.oregongeology.org/pubs/sp/p-SP-42.htm. Site-specific investigations should be completed before using these data for land development or management decisions. This Data Release consists of: 1) Minnesota_Landslides_v1_1.gdb.zip which contains the landslide inventory mapping data and the areas that were mapped, to be used in a GIS, 2) Minnesota_Landslides_v1_3.sd which is an ESRI service layer definition file that enables use of the data in online and offline GIS, 3) MN_Landslide_Photos.zip that contains a collection of geotagged photos showing landslides; these can be imported into a GIS, and 4) metadata.xml which contains metadata for all included files. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

CDFW BIOS GIS Dataset, Contact: Emily Perkins, Description: The FPAs were designed to conserve as much of the Biological Core and Linkage Area (BCLA) as possible, minimize preserve fragmentation, maximize use of existing public lands and open space, and maintain private property rights and economic viability (MHCP Executive Summary 2003). Some areas are designated hardline and some softline. The hardline areas are designated primarily for conservation while the softline areas may be further delineated to development or conservation.

This is a web map service generated from the 2017 North Western Ontario Orthophotography Project (NWOOP). As part of Ontario's Digital Data Directive, this Imagery is now part of LIO's open data catalogue and is free to use. This webmap can be leveraged in a web browser mapping application or can be used as a basemap in a users GIS software. Please see the related GeoHub record for more specifics around the capture of this imagery.ArcMap - Item linkArcGIS Pro - Item linkArcGIS REST Server linkOpen Geospatial Consortium OGC) - Web Map Tiled Service (WMTS)

Populations of many cold-water species are likely to decline this century with global warming, but declines will vary spatially and some populations will persist even under extreme climate change scenarios. Especially cold habitats could provide important refugia from both future environmental change and invasions by non-native species that prefer warmer waters. The Climate Shield website hosts geospatial data and related information that describes specific locations of cold-water refuge streams for native Cutthroat Trout (Oncorhynchus clarkii) and Bull Trout (Salvelinus confluentus) across the American West. Forecasts about the locations of refugia could enable the protection of key watersheds, inform support among multiple stakeholders, and provide a foundation for planning climate-smart conservation networks that improve the odds of preserving native trout populations through the 21st century. The Northern Rockies Adaptation Partnership provided a valuable forum that accelerated this work. The Great Northern and North Pacific Landscape Conservation Cooperatives generously funded the NorWeST project, which serves as the foundation for Climate Shield. The Climate Shield Cutthroat Trout and Bull Trout models were developed from fish surveys conducted at more than 4,500 locations in over 500 streams, as described in the cited peer-reviewed studies and agency reports. Resources in this dataset:Resource Title: Digital Maps and ArcGIS Shapefiles. File Name: Web Page, url: https://www.fs.fed.us/rm/boise/AWAE/projects/ClimateShield/maps.html Information is available here to download as easy-to-use digital maps (.pdf files) and ArcGIS shapefiles for all streams within the historical ranges of native trout across the northwestern U.S. The geographic areas match the NorWeST production units because those stream temperature scenarios are integral to Climate Shield.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

The data release for geologic maps of Ravalli Group and other Mesoproterozoic Belt Supergroup strata in northern Idaho and northwestern Montana is a digital, Geologic Map Schema (GeMS)-compliant version of maps published in U.S. Geological Survey (USGS) Open-File Report 2001-438 (Boleneus and others, 2001). The new digital data include attribute tables and geospatial features (points, lines, and polygons) in the format that meets GeMS requirements. This data release presents the geologic maps as shown on the plates and captured in geospatial data for the published maps. The database represents the geology for the 2.7 million acre, geologically complex study area in eleven plates at a publication scale of 1:48,000, and two plates at a publication scale of 1:12,000. The maps cover primarily Sanders, Shoshone, Kootenai, and Lincoln Counties, but also include minor parts of Benewah and Bonner Counties. Geologic mapping was undertaken between 1979 and 1984 by ASARCO Inc. as part of their program to explore for sediment-hosted stratiform copper deposits in northern Idaho and western Montana. Geologic mapping was primarily focused on formations of the Ravalli Group, which resulted in large unmapped areas within the map boundary. In 2001 maps were scanned, georeferenced, and published by USGS (Boleneus and others, 2001). Boleneus, D.E., Applegate, L.M., Joseph, N.L., and Brandt, T.R., 2001, Raster Images of Geologic Maps of Middle Proterozoic Belt strata in parts of Benewah, Bonner, Kootenai and Shoshone Counties, Idaho and Lincoln, Mineral and Sanders Counties, Montana: U.S. Geological Survey Open-File Report OF-2001-438, scales 1:48,000 and 1:12,000, https://doi.org/10.3133/ofr2001438.

This dataset provides a representation of the valley networks in the northwestern Hellas region. We mapped the valley networks as vector-based polylines within ArcGIS software, using the ~5 m/pixel CTX mosaics with THEMIS daytime IR mosaics as the regional background. Additionally, we used the 200 m/pixel MOLA-HRSC blended DEM for detailed identification, mapping, and derivation of topographic and morphologic parameters of valley networks. The dataset includes the whole valley networks within the study region, the mainstreams of the valley networks, single valleys, and extracted junction angles. Attribute tables are associated with the dataset, providing useful information and morphologic parameters of the valley networks such as length, sinuosity, stream order for each valley networks.

The datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).

This raster dataset represents predicted Relative Nest Site Density (RND) for golden eagles. This surface shows continuous RND values ranging from 0-1. Development of golden eagle RND models are described in Dunk JR, Woodbridge B, Lickfett TM, Bedrosian G, Noon BR, LaPlante DW, et al. (2019) Modeling spatial variation in density of golden eagle nest sites in the western United States. PLoS ONE 14(9): e0223143 (https://doi.org/10.1371/journal.pone.0223143). Additional information on model products (including RND and AAF surfaces), and guidance for their use is provided at https://ecos.fws.gov/ServCat/Reference/Profile/112631. Model data and products are available for download at https://ecos.fws.gov/ServCat/Reference/Profile/111283.

The purpose of Colorado Geological Survey’s (CGS) Open File Report 14-12, Geologic Map of the Craig Quadrangle, Moffat County, Colorado, is to describe the geology, mineral resources, and geologic hazards of this 7.5-minute quadrangle located near Craig in northwestern Colorado. Digital PDF and ESRI ArcGIS download. OF-14-12D

Annual average wind resource potential of the northwestern United States at a 50 meter height. Data derived from 400m cell resolutioin. This dataset was clipped from the Northwest US Wind Resource Dataset, and has been reprojected. For the most up to date data, consult the NREL website http://www.nrel.gov/gis/data_analysis.html.

The datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).

The purpose of Colorado Geological Survey’s (CGS) LO7 Hill Quadrangle Geologic Map, Rio Blanco County, Colorado is to describe the geology of this 7.5-minute quadrangle located south of the town of Meeker in northwestern Colorado. Downloadable Adobe PDF and ESRI ArcGIS files. OF-13-02

Water supply lakes are the primary source of water for many communities in northern and western Missouri. Therefore, accurate and up-to-date estimates of lake capacity are important for managing and predicting adequate water supply. Many of the water supply lakes in Missouri were previously surveyed by the U.S. Geological Survey in the early 2000s (Richards, 2013) and in 2013 (Huizinga, 2014); however, years of potential sedimentation may have resulted in reduced water storage capacity. Periodic bathymetric surveys are useful to update the area/capacity table and to determine changes in the bathymetric surface. From July 2019 to June 2020, the U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources and various cities in northwestern Missouri, completed bathymetric surveys of twelve (12) lakes using a marine-based mobile mapping unit, which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Bathymetric data were collected as the vessel traversed longitudinal transects to provide nearly complete coverage of the lake. The MBES was electronically tilted in some areas to improve data collection along the shoreline, in coves, and in areas that are shallower than about 2.0 meters deep (the practical limit of reasonable and safe data collection with the MBES). At some lakes, supplemental data were collected in shallow areas using an acoustic Doppler current profiler (ADCP) mounted on a remote-controlled vessel equipped with a differential global positioning system (DGPS). Bathymetric quality-assurance data also were collected at each lake to evaluate the vertical accuracy of the gridded bathymetric point data from the MBES. As part of the survey at each of these lakes, one or more reference marks or temporary bench marks were established to provide a point of known location and elevation from which the water surface could be measured or another survey could be referenced at a later date. In addition, the elevation of a primary spillway or intake was surveyed, when present. These points were surveyed using a real-time kinematic (RTK) Global Navigation Satellite System (GNSS) receiver connected to the Missouri Department of Transportation real-time network (RTN), which provided real-time survey-grade horizontal and vertical positioning, using field procedures as described in Rydlund and Densmore (2012) for a Level II real-time positioning survey. Bethany New Lake was resurveyed in March 2020 because the original data collected in July 2019 were found to have corrupted position data. Mozingo Lake and Maryville Reservoir were surveyed in June 2020 as part of the group of lakes surveyed in 2020. However, extraordinary interest in the bathymetry at Mozingo Lake by the city of Maryville necessitated these data being released earlier than the other 2020 lakes. The MBES data can be combined with light detection and ranging (lidar) data to prepare a bathymetric map and a surface area and capacity table for each lake. These data also can be used to compare the current bathymetric surface with any previous bathymetric surface. Data from each of the surveys are provided in ESRI Shapefile format (ESRI, 2021). Each of the 10 lakes surveyed in 2019 has a child page containing the metadata and two zip files, one for the bathymetric data, and the other for the bathymetric quality-assurance data. Data from the surveys at Mozingo Lake and Maryville Reservoir in 2020 are in four zip files on a single child page, one for the bathymetric data and one for the bathymetric quality assurance data for each of the two lakes, and a single summary metadata file. The zip files follow the format of "####YYYY_bathy_pts.zip" or ####YYYY_QA_raw.zip", where "####" is the lake name, and "YYYY" is the survey year. Each of these zip files contains a shapefile with an attribute table. Attribute/column labels of each table are described in the "Entity and attribute" section of the metadata file. The various reference marks and additional points from all the lake surveys are provided in ESRI Shapefile format (ESRI, 2021) with an attribute table on the main landing page. Attribute/column labels of this table are described in the "Entity and attribute" section of the metadata file. References Cited: Environmental Systems Research Institute, 2021, ArcGIS: accessed May 20, 2021, at http://www.esri.com/software/arcgis/ Huizinga, R.J., 2014, Bathymetric surveys and area/capacity tables of water-supply reservoirs for the city of Cameron, Missouri, July 2013: U.S. Geological Survey Open-File Report 2014–1005, 15 p., http://dx.doi.org/10.3133/ofr20141005. Richards, J.M., 2013, Bathymetric surveys of selected lakes in Missouri—2000–2008: U.S. Geological Survey Open-File Report 2013–1101, 9 p. with appendix, http://pubs.usgs.gov/of/2013/1101. Rydlund, P.H., Jr., and Densmore, B.K., 2012, Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey: U.S. Geological Survey Techniques and Methods, book 11, chap. D1, 102 p. with appendixes, https://doi.org/10.3133/tm11D1. First posted - May 27, 2021 Revised - September 30, 2021, ver 1.1 Version History 1.1

443 MB ZIP FILE Contains File Geodabase. Elevation values are referenced to NADV88.

This is a polygon GIS data layer showing the location and extent of various sidescan, multibeam and swath bathymetry surveys conducted by the USGS, Coastal and Marine Geology Program. Outlines of individual mosaic areas were combined to create one comprehensive layer that could be used to illustrate areas surveyed by USGS/CMGP seafloor mapping programs.

This data release contains the GIS data supporting U.S. Geological Survey Open-File Report (OFR) 2005-1252, "The Geologic Map of Seattle—A Progress Report," published in 2005 by Kathy Goetz Troost, Derek B. Booth, Aaron P. Wisher, and Scott A. Shimel (https://doi.org/10.3133/ofr20051252). The OFR was prepared for the 2005 Washington Hydrogeology Symposium and describes the status of geologic mapping for Seattle, Washington, at the time. The map is the result of field mapping and compilation of subsurface geologic data during the years 1999–2004 and was funded by the City of Seattle and the U.S. Geological Survey. Data from more than 36,000 exploration points, geotechnical borings, monitoring wells, excavations, and outcrops were used in making the map. The northern part of the 2005 OFR and the supporting GIS data were subsequently published as two geologic maps: Booth, D.B., Troost, K.G., and Shimel, S.A., 2005, Geologic map of northwestern Seattle (part of the Seattle North 7.5’ ...