This service hosts a raster image generated from raw DEM (Digital Elevation Model) data gathered for the Shuttle Radar Topography Mission (SRTM). The mission was co-sponsored by the National Aeronautics and Space Administration (NASA) and National Geospatial-Intelligence Agency (NGA). NASA's Jet Propulsion Laboratory (JPL) performed preliminary processing of SRTM data and forwarded it to the NGA for further processing and distribution. The raster image hosted by this service was generated using ArcGIS tools to convert DEM data for the state of California into a raster image. The results were reprojected into World Mercator (WKID: 54004) for display purposes. Pixel size is approximately 90 meters and vertical units are defined in meters. ESRI reserves the right to change or remove this service at any time and without notice. Copyright: Copyright:© 2010 ESRI

This Digital Raster Graphic (DRG) was created using scanned U.S. Geological Survey 7.5-minute 1 to 24,000 scale maps georeferenced in Universal Transverse Mercator (UTM) grid. DRGs can be acquired with or without collar information for use in Geographic Information System (GIS) environment. Collarless DRGs can be edge matched creating a continuous collection of topographic maps.

One foot contours developed from Delta LIDAR. LIDAR was developed under a contract between California DWR and URS Corporation (DRMS contract), with Fugro EarthData as lead LIDAR survey contractor. Flights were conducted in 2007 with 9% reflown in 2008. Final products delivered to DWR in 2009. Survey points of accuracy theoretically capable of supporting 1 foot contours. Using processed bare earth point data, Fugro EarthData generated/supplied these contours in raw and smoothed format, and the feature class here are smoothed contours. These data are public domain. Additional information can be obtained from California DWR.

This map shows distribution of the time-averaged shear-wave velocity in the upper 30 m (Vs30) for California. Vs30 is used as a proxy for local geologic site condition in ground motion hazard calculations. The map is produced using data provided by Thompson (ver. 2.0, July 2022), which is based on the method described by Thompson and others (2014) with adjustments (see Thompson, 2022 for detail). Vs30 unit is m/s. Data resolution is 3 arcseconds (approximately 90 m).Due to software limitations, symbology cannot be added to this service. To match the symbology used in the MS48 Additional Maps application, use the following configuration: Esri Color Ramp: Yellow to Dark RedNumber of Classes: 5Classes & Hex Codes:176.1 - 300: #F4FE93300 - 450: #F6DC6A450 - 600: #F2B841600 - 725: #BA671A725 - 1,473.3: #810A01

This map presents land cover and detailed topographic maps for the United States. It uses the USA Topographic Map service. The map includes the National Park Service (NPS) Natural Earth physical map at 1.24km per pixel for the world at small scales, i-cubed eTOPO 1:250,000-scale maps for the contiguous United States at medium scales, and National Geographic TOPO! 1:100,000 and 1:24,000-scale maps (1:250,000 and 1:63,000 in Alaska) for the United States at large scales. The TOPO! maps are seamless, scanned images of United States Geological Survey (USGS) paper topographic maps.

The maps provide a very useful basemap for a variety of applications, particularly in rural areas where the topographic maps provide unique detail and features from other basemaps.

To add this map service into a desktop application directly, go to the entry for the USA Topo Maps map service.

Tip: Here are some famous locations as they appear in this web map, accessed by including their location in the URL that launches the map:

Grand Canyon, Arizona

Golden Gate, California

The Statue of Liberty, New York

Washington DC

Canyon De Chelly, Arizona

Yellowstone National Park, Wyoming

Area 51, Nevada

A GIS polygon shapefile outlining the boundaries of the native input datasets used to construct a seamless, 2-meter resolution digital elevation model (DEM) was constructed for the open-coast region of the San Francisco Bay Area (outside of the Golden Gate Bridge), extending from Half Moon Bay to Bodega Head along the North-central California coastline. The goal was to integrate the most recent high-resolution bathymetric and topographic datasets available (for example, Light Detection and Ranging (lidar) topography, multibeam and single-beam sonar bathymetry) into a seamless surface model extending offshore at least 3 nautical miles and inland beyond the +20 m elevation contour.

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 High Resolution Digital Elevation Model (HRDEM) product is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The complete coverage of the Canadian territory is gradually being established. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps. The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements. In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generally generated. Most of these datasets have optical digital images as their source data. They are generated at a 2 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km. For some locations in the north, DSM and DTM datasets can also be generated from airborne LiDAR data. In this case, these products will be generated with the same specifications as those generated from airborne LiDAR in the southern part of the country. The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada. Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project. The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. Collaboration is a key factor to the success of the National Elevation Data Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

CanVec contains more than 60 topographic features classes organized into 8 themes: Transport Features, Administrative Features, Hydro Features, Land Features, Manmade Features, Elevation Features, Resource Management Features and Toponymic Features. This multiscale product originates from the best available geospatial data sources covering Canadian territory. It offers quality topographic information in vector format complying with international geomatics standards. CanVec can be used in Web Map Services (WMS) and geographic information systems (GIS) applications and used to produce thematic maps. Because of its many attributes, CanVec allows for extensive spatial analysis. Related Products: Constructions and Land Use in Canada - CanVec Series - Manmade Features Lakes, Rivers and Glaciers in Canada - CanVec Series - Hydrographic Features Administrative Boundaries in Canada - CanVec Series - Administrative Features Mines, Energy and Communication Networks in Canada - CanVec Series - Resources Management Features Wooded Areas, Saturated Soils and Landscape in Canada - CanVec Series - Land Features Transport Networks in Canada - CanVec Series - Transport Features Elevation in Canada - CanVec Series - Elevation Features Map Labels - CanVec Series - Toponymic Features

This report is a digital database package containing both plotfiles and Geographic Information Systems (GIS) databases of shaded relief maps of the San Francisco Bay Region. The data are provided for both the entire region and each county within the region, in two formats. The data is provided as ARC/INFO (Environmental Systems Research Institute, Redlands, CA) GRIDs for use in GIS packages, and as PostScript plotfiles of formatted maps similar to traditional U.S. Geological Survey map products.

[Summary provided by the USGS.]

The data set for the Butler Peak quadrangle has been prepared by the Southern California Areal Mapping Project (SCAMP), a cooperative project sponsored jointly by the U.S. Geological Survey and the California Division of Mines and Geology, as part of an ongoing effort to utilize a Geographical Information System (GIS) format to create a regional digital geologic database for southern California. This regional database is being developed as a contribution to the National Geologic Map Data Base of the National Cooperative Geologic Mapping Program of the USGS. Development of the data set for the Butler Peak quadrangle has also been supported by the U.S. Forest Service, San Bernardino National Forest.

The digital geologic map database for the Butler Peak quadrangle has been created as a general-purpose data set that is applicable to other land-related investigations in the earth and biological sciences. For example, the U.S. Forest Service, San Bernardino National Forest, is using the database as part of a study of an endangered plant species that shows preference for particular rock type environments. The Butler Peak database is not suitable for site-specific geologic evaluations at scales greater than 1:24,000 (1 in = 2,000 ft).

This data set maps and describes the geology of the Butler Peak 7.5' quadrangle, San Bernardino County, California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of the following items: (1) a map coverage showing geologic contacts and units,(2) a scanned topographic base at a scale of 1:24,000, and (3) attribute tables for geologic units (polygons), contacts (arcs), and site-specific data (points). In addition, the data set includes the following graphic and text products: (1) A PostScript graphic plot-file containing the geologic map on a 1:24,000 topographic base accompanied by a Description of Map Units (DMU), a Correlation of Map Units (CMU), and a key to point and line symbols; (2) PDF files of the DMU and CMU, and of this Readme, and (3) this metadata file.

The geologic map data base contains original U.S. Geological Survey data generated by detailed field observation and by interpretation of aerial photographs. The map was created by transferring lines from the aerial photographs to a 1:24,000 mylar orthophoto-quadrangle and then to a base-stable topographic map. This map was then scribed, and a .007 mil, right-reading, black line clear film made by contact photographic processes.The black line was scanned and auto-vectorized by Optronics Specialty Company, Northridge, CA. The non-attributed scan was imported into ARC/INFO, where the database was built. Within the database, geologic contacts are represented as lines (arcs), geologic units as polygons, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum and link it to other tables (.rel) that provide more detailed geologic information.

A cartographic enhancement representing map tiles across the municipal boundaries of the City of London.

A high-resolution (10-meter per pixel) digital elevation model (DEM) was created for the Sacramento-San Joaquin Delta using both bathymetry and topography data. This DEM is the result of collaborative efforts of the U.S. Geological Survey (USGS) and the California Department of Water Resources (DWR). The base of the DEM is from a 10-m DEM released in 2004 and updated in 2005 (Foxgrover and others, 2005) that used Environmental Systems Research Institute(ESRI), ArcGIS Topo to Raster module to interpolate grids from single beam bathymetric surveys collected by DWR, the Army Corp of Engineers (COE), the National Oceanic and Atmospheric Administration (NOAA), and the USGS, into a continuous surface. The Topo to Raster interpolation method was specifically designed to create hydrologically correct DEMs from point, line, and polygon data (Environmental Systems Research Institute, Inc., 2015). Elevation contour lines were digitized based on the single beam point data for control of chan ...

To approximate the distribution of shrubland species based on their postfire reproductive strategy (resprouter, seeder, and facultative seeder) across Southern California, we created a raster layer subdividing the landscape into a number of different facet classes. This raster dataset is at 30 meters pixel resolution and contains 12 different landscape facet classes based on vegetation and physiography. Specifically, the facets included several different vegetation types based on the California Wildlife Habitat Relations (WHR) classification (three shrubland categories, annual grasslands, valley-foothill riparian woodland, and ‘other’ vegetation types) which were intersected with aspect (two classes: north or south facing) and topography (summit, ridges, slopes, valleys, flats, and depressions). The combination of factors is intended to capture warmer, more exposed vegetation types dominated by seeder species (occurring on south-facing slopes, summits and ridges) versus cooler, less exposed vegetation types associated with resprouter species (occurring on north-facing slopes, valleys, depressions, and flats).

The dataset is a key input into a tool developed for resource managers to aid in the prioritization of restoration activities in shrublands postfire. The tool is available at https://github.com/adhollander/postfire and described in the following technical guide:

Underwood, Emma C., and Allan D. Hollander. 2019. “Post-Fire Restoration Prioritization for Chaparral Shrublands Technical Guide.” https://github.com/adhollander/postfire/blob/master/Postfire_Restoration_Priorization_Tool_Technical_Guide.pdf

Methods The following are the GIS processing workflow steps used to create this dataset. A diagram illustrating this workflow is in the attached file collection (SoCal_Veg_Topo_Facets_Workflow.png).

1) Compile GIS layers. There were two input layers to the GIS workflow, a 30 meter digital elevation model for California (dem30) and a vegetation raster layer of the state from the California Department of Forestry and Fire Protection (fveg15). The 30 meter DEM was downloaded from the USGS National Map (https://www.usgs.gov/core-science-systems/national-geospatial-program/national-map). The vegetation data is the FVEG dataset published in 2015 by the California Department of Forestry and Fire Protection's Fire and Resource Assessment Program (https://frap.fire.ca.gov/media/10894/fveg15_1.zip). This is a 30 meter raster representation of statewide vegetation using the California Wildlife Habitat Relationships vegetation classification system (https://wildlife.ca.gov/Data/CWHR).

2) Import data into GIS. Both data layers were imported into GRASS 7 for further processing, using a mask of the Southern California study region (encompassing the Angeles, Cleveland, Los Padres, and San Bernardino National Forests) to filter processing to the study footprint.

3) Calculate aspect for elevation model. Using the command r.slope.aspect, we generated a raster layer (aspect) giving the topographic aspect (0-360 degrees) of slopes across the study region.

4) Generate north-south aspect layer. Using the command r.mapcalc, we subdivided the aspect layer into north and south-facing slopes through creating a raster layer (nsaspect) with two categories for north and south.

5) Generate geomorphons for study region. The geomorphon raster layer derives from the dem30m surface and classifies the landscape into 10 discrete landform types, examples being ridges, slopes, hollows, and valleys. The algorithm for geomorphon classification uses a pattern recognition approach based on line of sight analysis (Jasiewisc and Stepinski 2013) and was generated using the r.geomorphons extension for GRASS 7.

6) Merge geomorphons with north-south aspect layer. In this step we combined the north-south aspect layer with the geomorphons layer to create a layer entitled nsgeomorphon2a. In so doing we grouped the geomorphon types spurs, slopes, and hollows into a single “slope” category and assigned these to north-facing slopes and south-facing slopes depending upon the value of the north-south aspect layer.

7) Regroup merged layer into three groupings. In this step we took the merged nsgeomorphon2a layer and assigned the classes in it to three different physiographic groups, namely 1) flats 2) valleys, depressions, and north-facing slopes/spurs/hollows/footslopes/shoulders and 3) summits and ridges and south-facing slopes/spurs/hollows/footslopes/shoulders. This grouped layer was named nsgeomorphon2d.

8) Reclass vegetation layer to main habitat types. The vegetation layer fveg15 contains information about many details of the vegetation, including canopy size, canopy cover, and main habitat type. This reclass step extracts the main habitat type into a separate raster named fveg15whr.

9) Combine vegetation layer with physiography layer. Using the command r.cross, we combined the layers fveg15whr and nsgeomorphon2d into a new layer nsgeoxfvegwhr with a separate category for each combination of the raster values from the two input layers.

10) Reclass combined layer into small set of groupings. Taking the nsgeoxfvegwhr layer, we recategorized the 196 combinations of raster values into a set of 12 different combinations using the command r.reclass. This layer is named nsgeoxfvegnbclasses. The 12 different classes generated as an output are the following, with their raster values paired with their classes:

0 Annual grassland: south-facing slopes; summits; ridges

1 Annual grassland: north-facing slopes; valleys; depressions; flats

2 Chamise-redshanks chaparral: south-facing slopes; summits; ridges

3 Chamise-redshanks chaparral: north-facing slopes; valleys; depressions; flats

4 Mixed or montane chaparral: south-facing slopes; summits; ridges

5 Mixed or montane chaparral: north-facing slopes; valleys; depressions; flats

6 Valley-foothill riparian: south-facing slopes; summits; ridges

7 Valley-foothill riparian: north-facing slopes; valleys; depressions; flats

8 Coastal scrub: south-facing slopes; summits; ridges

9 Coastal scrub: north-facing slopes; valleys; depressions; flats

10 Other: south-facing slopes; summits; ridges

11 Other: north-facing slopes; valleys; depressions; flats

11) Export dataset. Using the command r.out.gdal, we exported the nsgeoxfvegnbclasses layer as the raster geotiff file SoCal_Veg_Topo_Facets.tif.

The GRASS commands used for these 11 steps are below:

r.in.gdal input="/home/adh/CARangelands/Vegetation/fveg15_11.tif" output="fveg15" memory=300 offset=0

r.proj input="dem1sec_calif" location="CAllnad83" mapset="statewide" output="dem30m" method="bilinear" memory=300 resolution=30

r.slope.aspect elevation=dem30m@statewide slope=slope aspect=aspect

r.mapcalc 'nsaspect = if(aspect <= 180, 1, 2)'

r.geomorphon --overwrite dem=dem30m@statewide forms=SoCalgeomorphons search=11 skip=4 flat=1 dist=0

r.mapcalc --overwrite 'nsgeomorphon = if((SoCalgeomorphons@socalNF == 5 ||| SoCalgeomorphons@socalNF == 6 ||| SoCalgeomorphons@socalNF == 7) &&& nsaspect == 1, 11, if(((SoCalgeomorphons@socalNF == 5 ||| SoCalgeomorphons@socalNF == 6 ||| SoCalgeomorphons@socalNF == 7) &&& nsaspect == 2), 12, SoCalgeomorphons@socalNF))'

r.reclass input=nsgeomorphon2a@socalNF output=nsgeomorphon2d rules=/home/adh/SantaClaraRiver/PostfireRestoration/jupyter/datasets/nsgeomorphon-reclass2d.lut

r.reclass input="fveg15@statewide" output="fveg15whr" rules="/home/adh/CARangelands/Vegetation/fveg15whr.lut"

r.cross --overwrite input=fveg15whr@statewide,nsgeomorphon2d@socalNF output=nsgeoxfvegwhr

r.reclass --overwrite input=nsgeoxfvegwhr@socalNF output=nsgeoxfvegnbclasses rules=/home/adh/SantaClaraRiver/PostfireRestoration/datasets/fvegwhrtonbclasses.lut

r.out.gdal --overwrite input=nsgeoxfvegnbclasses@socalNF output=SoCal_Veg_Topo_Facets.tif format=GTiff type=Byte createopt=COMPRESS=DEFLATE

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 Tomales 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/55cbf4ba-e03a-4904-a101-2a38a96a08ed for complete metadata about this dataset.

This map presents a tour of the City of Redlands, California using the detailed map of Redlands included in the community basemap. The City of Redlands is located in Southern California, about 65 miles east of Los Angeles. The map tour highlights some of the unique features in the history of Redlands as well as several of the places and events that make it a very livable community today.The map features a detailed basemap for the City of Redlands, California, including buildings, parcels, vegetation, land use, landmarks, streets, and more. The map features special detail for areas of high interest within the City, including local parks, landmarks, and the ESRI campus.The map references detailed GIS data provided by the City of Redlands, Department of Innovation and Technology, GIS Division. The map was authored using map templates available from ESRI, including:Topographic Map Template - Large ScalesCampus Basemap TemplateThe map was published as part of ESRI's Community Maps Program and is one of several detailed maps of cities and counties in the World Topographic Map.

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 Salt Point to Drakes Bay 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 p... Visit https://dataone.org/datasets/01d4111d-4e8f-4d07-879a-18aeca16345d 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 Point Reyes 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 ph... Visit https://dataone.org/datasets/25012c1d-fe26-4256-ad47-705e41dcb6cb for complete metadata about this dataset.

A GIS polygon shapefile outlining the extent of the 14 individual DEM sections that comprise the seamless, 2-meter resolution DEM for the open-coast region of the San Francisco Bay Area (outside of the Golden Gate Bridge), extending from Half Moon Bay to Bodega Head along the north-central California coastline. The goal was to integrate the most recent high-resolution bathymetric and topographic datasets available (for example, Light Detection and Ranging (lidar) topography, multibeam and single-beam sonar bathymetry) into a seamless surface model extending offshore at least 3 nautical miles and inland beyond the +20 meter elevation contour.

Digitally reproduced and georeferenced maps from original One Inch to One Mile Topographic Series held in the Map, Data & GIS Library. Maps are displayed as a seamless mosaic.

Reproduced from sheets: Niagara 30M3 (1908) Welland 30L14 (1916) Fort Erie 30L15 (1917)