gov.noaa.nmfs.inport:62987
eng
UTF8
dataset
Elevation
OCM Partners
resourceProvider
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
Website
NOAA Office for Coastal Management Home Page
information
pointOfContact
2020-09-25T16:22:35
ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data
ISO 19115-2:2009(E)
2020 USGS Topobathy CoNED DEM: Northern California
2020-08-10
publication
NOAA/NMFS/EDM
62987
https://coast.noaa.gov/
WWW:LINK-1.0-http--link
NOAA's Office for Coastal Management (OCM) website
Information on the NOAA Office for Coastal Management (OCM)
download
https://coast.noaa.gov/dataviewer/
WWW:LINK-1.0-http--link
NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV)
The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.
download
To support the modeling of storm-induced flooding, the USGS Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for the Northern California Coast. High-resolution coastal elevation data is required to identify flood, hurricane, and sea-level rise inundation hazard zones and other earth science applications, such as the development of sediment transport and storm surge models. This TBDEM consists of the best available multi-source topographic and bathymetric elevation data for the onshore and offshore areas in Northern California. The Northern California TBDEM integrates 26 different topographic and bathymetric data sources including LiDAR point clouds, hydrographic surveys, single-beam acoustic surveys, and multi-beam acoustic surveys obtained from USGS, NOAA, and USACE. The topographic and bathymetric surveys were sorted and prioritized based on survey date, accuracy, spatial distribution, and point density to develop a model based on the best available elevation data. Because bathymetric data are typically referenced to tidal datums (such as Mean High Water or Mean Low Water), all tidally-referenced heights were transformed into orthometric height based on a common geoid (Geoid09) that are normally used for mapping elevation on land based on the North American Vertical Datum of 1988. Every input data source in the TBDEM has been horizontally referenced to UTM Zone 10, NSRS2007. The spatial resolution is 1-meter with the general location ranging from the Golden Gate Bridge to the Oregon border, and extending inland to an elevation of at least +10 m and offshore to the 3-nautical-mile limit of California's State Waters. The overall temporal range of the input topography and bathymetry is 1986 to 2019. The topography surveys are from 2009-2019. The bathymetry is from 1986-2019. The nearshore void zone (not covered by lidar or sonar) was filled by interpolating points from adjacent datasets.
As part of the vision for a 3D Nation, the USGS CoNED Applications Project is working collaboratively with the USGS National Geospatial Program, NOAA, and the USACE through the Interagency Working Group on Ocean and Coastal Mapping to build integrated elevation models in the coastal zone by assimilating the land surface topography with littoral zone and continental shelf bathymetry. The USGS CoNED Applications Project integrates disparate light detection and ranging (LiDAR) and bathymetric data sources into a common 3D database aligned both vertically and horizontally to a common reference system. CoNED Project TBDEM elevation model development is focused in select regions around the U.S. Coast, such as in the Northern Gulf of Mexico (NGOM), the Hurricane Sandy Region in the northeast, the California Coast Region, the Pacific Northwest, and the North Slope of Alaska. CoNED Project topobathymetric digital elevation models (TBDEMs) provide a required seamless elevation product for several science application studies such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, tsunami impact assessment, and also to analyze the impact of various climate change scenarios on coastal regions. The raster elevation topobathymetric elevation product, the Federal Geographic Data Committee (FGDC) metadata, and the spatially referenced metadata are contained in the downloadable bundle. Spatially referenced metadata are contained within an ESRI geodatabase that contains footprints for each of the input source areas. References: Danielson, J.J., Poppenga, S.K., Brock, J.C., Evans, G.A., Tyler, D.J., Gesch, D.B., Thatcher, C.A., and Barras, J.A. , 2016, Topobathymetric elevation model development using a new methodology-Coastal National Elevation Database: Journal of Coastal Research, SI no. 76, p. 75-89, at http://dx.doi.org/10.2112/SI76-008. Thatcher, C.A., Brock, J.C., Danielson, J.J., Poppenga, S.K., Gesch, D.B., Palaseanu-Lovejoy, M.E., Barras, J.A., Evans, G.A., and Gibbs, A.E., 2016, Creating a Coastal National Elevation Database (CoNED) for science and conservation applications: Journal of Coastal Research, SI no. 76, p. 64-74, at http://dx.doi.org/10.2112/SI76-007. Gesch, Dean B., Oimoen, Michael J., and Evans, Gayla A., 2014, Accuracy assessment of the U.S. Geological Survey National Elevation Dataset, and comparison with other large-area elevation datasets-SRTM and ASTER: U.S. Geological Survey Open-File Report 2014-1008, 10 p., at http://dx.doi.org/10.3133/ofr20141008. Sugarbaker, L.J., Constance, E.W., Heidemann, H.K., Jason, A.L., Lukas, Vicki, Saghy, D.L., and Stoker, J.M., 2014, The 3D Elevation Program initiative—A call for action: U.S. Geological Survey Circular 1399, 35 p Carswell, W.J., Jr., 2013, The 3D Elevation Program—Summary for California: U.S. Geological Survey Fact Sheet 2013–3056, 2 p., http://pubs.usgs.gov/fs/2013/3056/.
Please refer to the Data Quality Section, Source Citations for original source data information., Tyler, D.J. Danielson, J.J. Hockenberry, R.J. Beverly, S.D. U.S. Geological Survey (USGS)
completed
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
Website
NOAA Office for Coastal Management Home Page
information
pointOfContact
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
Website
NOAA Office for Coastal Management Home Page
information
custodian
asNeeded
3D Elevation Program
3DEP
Acoustic Sonar
Bathymetric
Bathymetry
Coastal Marine and Geology Program
Coastal National Elevation Database
Coastal Zone
CoNED
DEM
Digital Elevation Model
Digital Terrain Model
Flood Inundation Modeling
Hydrologic Modeling
LiDAR
Light Detection and Ranging
National Standards for Spatial Digital Accuracy
Topobathy
Topobathymetric
U.S. Geological Survey
USGS
theme
Earth Science > Land Surface > Topography > Terrain Elevation
Earth Science > Oceans > Bathymetry/Seafloor Topography > Seafloor Topography
Earth Science > Oceans > Coastal Processes > Coastal Elevation
theme
Global Change Master Directory (GCMD) Science Keywords
Continent > North America > United States Of America
Vertical Location > Land Surface
Vertical Location > Seafloor
place
Global Change Master Directory (GCMD) Location Keywords
Central Coastal California
County of Monterey
County of San Francisco
County of San Luis Obispo
County of San Mateo
County of Santa Barbara
County of Santa Cruz
State of California
place
Geographic Names Information System
U.S. Coastline
place
CA
place
U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D.C., National Instit
U.S.
United States
USA
place
U.S. Department of Commerce, 1995, Countries, dependencies, areas of special sovereignty, and their principal administrative divisions, Federal Information Processing Standard 10-4,): Washington, D.C., National Institute of Standards and Technology
Earth Remote Sensing Instruments > Active Remote Sensing > Profilers/Sounders > Lidar/Laser Sounders > LIDAR > Light Detection and Ranging
instrument
Global Change Master Directory (GCMD) Instrument Keywords
Aircraft > Aircraft
platform
Global Change Master Directory (GCMD) Platform Keywords
DEMs - partner (no harvest)
project
InPort
NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose.
otherRestrictions
otherRestrictions
Access Constraints: None | Use Constraints: Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. | Distribution Liability: Although these data have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made by the USGS regarding the use of the data on any other system, nor does the act of distribution constitute any such warranty. Data may have been compiled from various outside sources. Spatial information may not meet National Map Accuracy Standards. This information may be updated without notification. The USGS shall not be liable for any activity involving these data, installation, fitness of the data for a particular purpose, its use, or analyses results.
Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners
unclassified
NOAA Data Management Plan (DMP)
NOAA/NMFS/EDM
62987
https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocmp/dmp/pdf/62987.pdf
WWW:LINK-1.0-http--link
NOAA Data Management Plan (DMP)
NOAA Data Management Plan for this record on InPort.
information
crossReference
eng; US
elevation
environment
geoscientificInformation
oceans
Environment as of Metadata Creation: USGS Metadata Wizard 2.0.6 ; Esri ArcGIS 10.7.1 Service Pack N/A (Build N/A)
-124.5719
-122.4453
37.7702
42.0126
| Currentness: Ground Condition
1986-01-01
2019-01-01
The data obtained through ScienceBase at https://www.sciencebase.gov/catalog/item/5ebc4ba682ce25b51365d660 are considered to be the "best available" data from the USGS. For questions on distribution, please refer to the Distribution Section, Contact Information. For processing, please refer to the Data Quality Section, Processing Step, Contact Information.
false
eng
false
USGS
Zip
Zip
GeoTIFF
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
Website
NOAA Office for Coastal Management Home Page
information
distributor
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9181/details/9181
WWW:LINK-1.0-http--link
Customized Download
Create custom data files by choosing data area, map projection, file format, etc. A new metadata will be produced to reflect your request using this record as a base.
download
https://coast.noaa.gov/htdata/raster5/elevation/CA_north_coned_DEM_2020_9181
WWW:LINK-1.0-http--link
Bulk Download
Bulk download of data files in the original coordinate system.
download
dataset
Horizontal Positional Accuracy
The horizontal accuracy for the integrated topobathymetric model was not assessed quantitatively.
Vertical Positional Accuracy
Integrated TBDEM Vertical Accuracy Assessment (GEOID09).
The TBDEM root mean square error (RMSE) over the land area is 0.22 meters versus 40 NOAA NGS GPS bench mark control points distributed throughout the study area.
Completeness Report
Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
Conceptual Consistency
No formal logical accuracy tests were conducted.
The principal methodology for developing the integrated topobathymetric elevation model can be organized into three main components. The "topographic component" consists of the land-based elevation data, which is primarily comprised from high-resolution LiDAR data. The topographic source data will include LiDAR data from different sensors (Topographic, Bathymetric) with distinct spectral wavelengths (NIR-1064nm, Green-532nm). The "bathymetric component" consists of hydrographic sounding (acoustic) data collected using boats rather than bathymetry acquired from LiDAR. The most common forms of bathymetry that are used include: multi-beam, single-beam, and swath. The final component, "Integration", encompasses the assimilation of the topographic and bathymetric data along the near-shore based on a predefined set of priorities. The land/water interface (+1 m- -1.5 m) is the most critical area, and green laser systems, such as the Experimental Advanced Airborne Research LiDAR (EAARL-B) and the Coastal Zone Mapping and Imaging LiDAR (CZMIL) that cross the near-shore interface are valuable in developing a seamless transition. The end product from the topography and bathymetry components is a raster with associated spatial masks and metadata that can be passed to the integration component for final model incorporation. Topo/Bathy Creation Steps: Topography Processing Component: a) Quality control check the vertical and horizontal datum and projection information of the input lidar source to ensure the data is referenced to NAVD88 and NAD83, UTM. If the source data is not NAVD88, transform the input LiDAR data to NAVD88 reference frame using current National Geodetic Survey (NGS) geoid models and VDatum. Likewise, if required, convert the input source data to NAD83 and reproject to UTM. b) Check the classification of the topographic LiDAR data to verify the data are classified with the appropriate classes. If the data have not been classified, then classify the raw point cloud data to non-ground (class 1) ground (class 2), and water (class 9) classes using LP360-Classify. c) Derive associated breaklines from the classified LiDAR to capture internal water bodies, such as lakes and ponds and inland waterways. Inland waterways and water bodies will be hydro-flattened where no bathymetry is present. d) Extract the ground returns from the classified LiDAR data and randomly spatial subset the points into two point sets based on the criteria of 95 percent of the points for the "Actual Selected" set and the remaining 5 percent for the "Test Control" set. The "Actual Selected" points will be gridded in the terrain model along with associated breaklines and masks to generate the topographic surface, while the "Test Control" points will be used to compute the interpolation accuracy (Root Mean Square Error) from the derived surface. e) Generate the minimum convex hull boundary from the classified ground LiDAR points that creates a mask that extracts the perimeter of the exterior LiDAR points. The mask is then applied in the terrain to remove extraneous terrain artifacts outside of the extent of the ground LiDAR points. f) Using a terrain model based on triangulated irregular networks (TINs), grid the "Actual Selected" ground points using breaklines and the minimum convex hull boundary mask at a 1-meter spatial resolution using a natural neighbor interpolation algorithm. g) Compute the interpolation accuracy by comparing elevation values in the "Test Control" points to values extracted from the derived gridded surface; report the results in terms of Root Mean Square Error (RMSE).
2020-04-28T00:00:00
Bathymetry Processing Component: a) Quality control check the vertical and horizontal datum and projection information of the input bathymetric source to ensure the data is referenced to NAVD88 and NAD83, UTM. If the source data is not NAVD88, transform the input bathymetric data to NAVD88 reference frame using VDatum. Likewise, if required, convert the input source data to NAD83 and reproject to UTM. b) Prioritize and spatially sort the bathymetry based on date of acquisition, spatial distribution, accuracy, and point density to eliminate any outdated or erroneous points and to minimize interpolation artifacts. c) Randomly spatial subset the bathymetric points into two point sets based on the criteria of 95 percent of the points for the "Actual Selected" set and the remaining 5 percent for the "Test Control" set. The "Actual Selected" points will be gridded in the empirical bayesian kriging model along with associated masks to generate the bathymetric surface, while the "Test Control" points will be used to compute the interpolation accuracy (Root Mean Square Error) from the derived surface. d) Spatially interpolate bathymetric single-beam, multi-beam, and hydrographic survey source data using an empirical bayesian krigging gridding algorithm. This approach uses a geostatistical interpolation method that accounts for the error in estimating the underlying semivariogram (data structure - variance) through repeated simulations. e) Cross validation - Compare the predicted value in the geostatistical model to the actual observed value to assess the accuracy and effectiveness of model parameters by removing each data location one at a time and predicting the associated data value. The results will be reported in terms of RMSE. f) Compute the interpolation accuracy by comparing elevation values in the "Test Control" points to values extracted from the derived gridded surface; report the results in terms of RMSE.
2020-04-28T00:00:00
Mosaic Dataset Processing (Integration) Component: a) Determined priority of input data based on project characteristics, including acquisition dates, cell size, retention of features, water surface treatment, visual inspection and presence of artifacts. b) Develop an ArcGIS geodatabase (Mosaic Dataset) and spatial seamlines for each individual topographic (minimum convex hull boundary) and bathymetric raster layer included in the integrated elevation model. c) Generalize seamline edges to smooth transition boundaries between neighboring raster layers and split complex raster datasets with isolated regions into individual unique raster groups. d) Develop an integrated shoreline transition zone from the best available topographic and bathymetric data to blend the topographic and bathymetric elevation sources. Where feasible, use the minimum convex hull boundary, create a buffer to logically mask input topography/bathymetry data. Then, through the use of TINs, interpolate the selected topographic and bathymetric points, if required, to gap-fill any near-shore holes in the bathymetric coverage. Topobathymetric LiDAR data sources such as the EAARL-B or CZMIL systems provide up-to-date, high-resolution data along the critical land/water interface within inter-tidal zone. e) Prioritize and spatially sort the input topographic and bathymetric raster layers based on date of acquisition and accuracy to sequence the raster data in the integrated elevation model. f) Based on the prioritization, spatially mosaic the input raster data sources to create a seamless topobathymetric composite at a cell size of 1 meter using blending (spatial weighting). g) Performed a visual quality assurance (Q/A) assessment on the output composite to review the mosaic seams for artifacts. h) Generate spatially referenced metadata for each unique data source. The spatially referenced metadata consists of a group of geospatial polygons that represent the spatial footprint of each data source used in the generation of the topobathymetric dataset. Each polygon is to be populated with attributes that describe the source data, such as, resolution, acquisition date, source name, source organization, source contact, source project, source URL, and data type (topographic LiDAR, bathymetric LiDAR, multi-beam bathymetry, single-beam bathymetry, etc.).
2020-04-28T00:00:00
NOAA OCM retrieved the Topobathy DEM file from the USGS at the following link:
https://www.sciencebase.gov/catalog/item/5ebc4ba682ce25b51365d660
That data were in UTM 10N, NAD83(NSRS2007) and NAVD88 heights using geoid09, with all units in meters.
The data were in a single tiff file. To process to the Digital Coast, NOAA OCM used the gdal_retile python script to break the file into smaller tiles. Additionally, the gdal cloud_optimize python script was used to assign the geokeys and add compression.
Office for Coastal Management
processor
Source Contribution: Topographic, bathymetric, and acoustic elevation data along the entire California coastline.
2013 NOAA Coastal California TopoBathy Merge Project
2013-10-30
publication
OCM Partners (OCMP)
https://inport.nmfs.noaa.gov/inport/item/49649
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2008
2009
Source Contribution: Intermittent coverage (as determined by areas provided in pre-release request) between Point Sal and San Simeon Beach State Park. Only the bathymetric component of the dataset was included.
2015 USACE NCMP Topobathy Lidar: California
2017-01-01
publication
USACE
https://coast.noaa.gov/htdata/raster2/elevation/USACE_CA_Topobathy_DEM_2015_8482/
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2015
Source Contribution: Arena Cove
Arena Cove Topobathy NOAA 10m
2009-01-01
publication
NOAA
https://www.ngdc.noaa.gov/mgg/coastal/coastal.html
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2009-01-01
Source Contribution: Bodega Bay.
Bodega Bay Bathymetry
2017-01-01
publication
USACE
https://www.arcgis.com/apps/opsdashboard/index.html#/4b8f2ba307684cf597617bf1b6d2f85d
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2017-01-01
Source Contribution: Bolinas Lagoon
Bolinas Lagoon Bathymetry
2016-01-01
publication
USGS & PWA/ESA for Marin County Parks
https://www.usgs.gov/centers/pcmsc/data-tools
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2016-01-01
Source Contribution: Crescent City
Crescent City Bathymetry
2019-01-01
publication
USACE
https://www.arcgis.com/apps/opsdashboard/index.html#/4b8f2ba307684cf597617bf1b6d2f85d
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2019-01-01
Source Contribution: Crescent City
Crescent City Topobathy NOAA 10m
2010-01-01
publication
NOAA
https://www.ngdc.noaa.gov/mgg/coastal/coastal.html
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2010-01-01
Source Contribution: Drakes Estero
Drakes Estero Bathymetry
1986-01-01
publication
USGS
http://pubs.er.usgs.gov/djvu/OFR/1991/ofr_91_145.djvu
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
1986-01-01
Source Contribution: Eel River.
Eel River Topobathy
2014-01-01
publication
NCALM
http://opentopo.sdsc.edu/datasetMetadata?otCollectionID=OT.122016.26910.1
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2014-01-01
Source Contribution: Eureka
Eurkea Topobathy NOAA 10m
2009-01-01
publication
NOAA
https://www.ngdc.noaa.gov/mgg/coastal/coastal.html
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2009-01-01
Source Contribution: Fort Bragg.
Fort Bragg Topobathy NOAA 10m
2012-01-01
publication
NOAA
https://www.ngdc.noaa.gov/mgg/coastal/coastal.html
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2012-01-01
Source Contribution: Humboldt Bay, Eureka.
Humboldt Bay Lidar 2019
2019-01-01
publication
City of Eureka
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9026/details/9026
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2019-01-01
Source Contribution: Humboldt Bay.
Humboldt Bay Sea Level Rise
2014-01-01
publication
Coastal Conservancy
http://www.coastalecosystemsinstitute.org/humboldt-bay-slr-vulnerability-and-adaptation-planning/
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2014-01-01
Source Contribution: Klamath River
Klamath River Topobathy
2018-01-01
publication
USGS 3DEP
https://nationalmap.gov
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2018-01-01
Source Contribution: Marin County.
Marin County Lidar
2019-01-01
publication
Golden Gate National Parks Conservancy
https://gis.marinpublic.com/arcgis/rest/services/LIDAR
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2019-01-01
Source Contribution: Mendocino County.
Mendocino County Lidar 2017
2017-01-01
publication
USGS 3DEP
https://nationalmap.gov
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2017-01-01
Source Contribution: West of Golden Gate where other high-resolution bathymetry does not exist. Bathymetric Attributed Grids (BAGS) H12111 (2009), and H12112 (2009). Resolution varies from 1 m to 4 m.
NOAA Bathymetry in raster (BAG) format
2018-01-01
publication
NOAA/NCEI
https://maps.ngdc.noaa.gov/viewers/bathymetry/
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
Source Contribution: Marin County, Northern Mendocino County, Southern Humboldt County
Northern California Wildfire Lidar
2018-01-01
publication
USGS 3DEP
https://nationalmap.gov
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2018-01-01
Source Contribution: Noyo River
Noyo River Bathymetry
2018-01-01
publication
USACE
https://www.arcgis.com/apps/opsdashboard/index.html#/4b8f2ba307684cf597617bf1b6d2f85d
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2018-01-01
Source Contribution: Rodeo Lagoon, Marin County.
Rodeo Lagoon Bathymetry
2006-01-01
publication
Golden Gate National Recreation Area
2006-01-01
Source Contribution: Lower Russian River.
Russian River Bathymetry
2009-01-01
publication
Sonoma Co Water Agency
2009-01-01
Source Contribution: San Francisco.
San Francisco Topobathy NOAA 10m
2010-01-01
publication
NOAA
https://www.ngdc.noaa.gov/mgg/coastal/coastal.html
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2010-01-01
Source Contribution: Sonoma County.
Sonoma County Lidar
2013-01-01
publication
USGS 3DEP
https://nationalmap.gov
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2013-01-01
Source Contribution: Humboldt Bay
USACE - Humboldt Bay
2019-01-01
publication
USACE
https://www.arcgis.com/apps/opsdashboard/index.html#/4b8f2ba307684cf597617bf1b6d2f85d
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2019-01-01
Source Contribution: Coastal California.
WA_El_NiNO_2016_USGS_CMHRP
2016-01-01
publication
USGS
https://nationalmap.gov/,http://lidarportal.dnr.wa.gov/
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2016-01-01