73205 Data Set Published / External 49401 Lidar - partner (no harvest) Project Completed 2021 2022-02-23 LIDAR-derived binary (.las) files containing classified points of all returns. We have seven (7) classifications Unclassified, Ground, Low Noise, Water, Bridge Decks, High Noise and Ignore Ground. These files adhere to USGS-NGP Lidar Base Specification 2020 rev. A Quality Level 1 (QL1) standards, eight points or greater per square meter. These files are delivered in tile format (1500x1500m). This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services. This task is for providing a fall leaf-off 2021 lidar survey to be collected over an Area of Interest (AOI) of approximately 124 square miles in southern California covering a portion of Riverside County. This project will support the USGS Earth MRI (Mapping Resources Initiative), USGS GMEG (Geology, Minerals, Energy, and Geophysics) Science Center, and the 3DEP mission. The project has 378 tiles (1500m by 1500m) for the QL1 area. USGS Task Order 140G0221F0290-CA_SanBernardino_EarthMRI_2021_D21 The following are the USGS lidar fields in JSON: { "ldrinfo" : { "ldrspec" : "USGS-NGP Base Lidar Specification 2020 Rev A", "ldrsens" : "Optech Galaxy Prime Airborne Laser Terrain Mappers (ALTM) 5060380", "ldrmaxnr" : "8", "ldrnps" : "0.7", "ldrdens" : "2", "ldranps" : "0.7", "ldradens" : "2", "ldrfltht" : "3400", "ldrfltsp" : "170", "ldrscana" : "40", "ldrscanr" : "72", "ldrpulsr" : "700", "ldrpulsd" : "3.5", "ldrpulsw" : "1.7", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.25", "ldrswatw" : "2475", "ldrswato" : "20", "ldrgeoid" : "National Geodetic Survey (NGS) Geoid18" }, "ldraccur" : { "ldrchacc" : "0", "rawnva" : "0.0", "rawnvan" : "0" }, "lasinfo" : { "lasver" : "1.4", "lasprf" : "6", "laswheld" : "Withheld (ignore) points were identified in these files using the standard LAS withheld bit.", "lasolap" : "Swath "overage" points were not identified in these files using the standard LAS overlap bit.", "lasintr" : "12", "lasclass" : { "clascode" : "1", "clasitem" : "Unclassified" }, "lasclass" : { "clascode" : "2", "clasitem" : "Ground" }, "lasclass" : { "clascode" : "7", "clasitem" : "Low Noise" }, "lasclass" : { "clascode" : "9", "clasitem" : "Water" }, "lasclass" : { "clascode" : "17", "clasitem" : "Bridge" }, "lasclass" : { "clascode" : "18", "clasitem" : "High Noise" }, "lasclass" : { "clascode" : "20", "clasitem" : "Ignore Breakline" } }} Theme Global Change Master Directory (GCMD) Science Keywords EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION Theme ISO 19115 Topic Category elevation Spatial Global Change Master Directory (GCMD) Location Keywords CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA Spatial Global Change Master Directory (GCMD) Location Keywords CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CALIFORNIA Spatial Global Change Master Directory (GCMD) Location Keywords VERTICAL LOCATION > LAND SURFACE Instrument Global Change Master Directory (GCMD) Instrument Keywords LIDAR > Light Detection and Ranging Platform Global Change Master Directory (GCMD) Platform Keywords Airplane > Airplane Office for Coastal Management Charleston SC Data Set Elevation Unknown Model (digital) Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners. Merrick-Surdex Joint Venture, LLP, USGS Data Steward 2024 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Distributor 2024 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Distributor 2022 Organization U.S. Geological Survey 12201 Sunrise Valley Drive Reston VA 20191 USA https://usgs.gov USGS Home Home page for USGS Online Resource Metadata Contact 2024 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Point of Contact 2024 Organization NOAA Office for Coastal Management NOAA/OCM coastal.info@noaa.gov 2234 South Hobson Ave Charleston SC 29405-2413 (843) 740-1202 https://coast.noaa.gov NOAA Office for Coastal Management Home Page Online Resource Ground Condition -114.76 -114.51 33.99 33.74 Range 2021-11-06 2021-11-16 No Yes No No No Projected EPSG:3857 WGS 84 / Pseudo-Mercator World Geodetic System 1984 WGS 84 6378137 298.257223563 WGS 84 Popular Visualisation Pseudo-Mercator Popular Visualisation Pseudo Mercator Latitude of natural origin 0° 0' 0" N Longitude of natural origin 0° 0' 0" E False easting 0 metre False northing 0 metre 1 Easting X metre east 2 Northing Y metre north Vertical EPSG:5703 NAVD88 height North American Vertical Datum 1988 1 Gravity-related height H metre up Custom Unclassified Data is available online for bulk and custom downloads None 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. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10164/details/10164 2024 Organization NOAA Office for Coastal Management Customized Download Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options. Not Applicable Zip https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/CA_SanBernardino_EarthMRI_2021_D21/CA_SanBern_EMRI_1_2021/LAZ/ 2022 Organization U.S. Geological Survey Bulk Download Bulk download of data files in LAZ format, UTM Zone 11N NAD83(2011), meters coordinates and elevation values in NAVD88(GEOID18) meters. LAS/LAZ - LASer LAZ https://coast.noaa.gov/dataviewer/ NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) Online Resource HTML 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. https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/CA_SanBernardino_EarthMRI_2021_D21/CA_SanBern_EMRI_1_2021/ USGS Additional Info Online Resource Link to the reports, breaklines, metadata, and spatial metadata. https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/CA_SanBernardino_EarthMRI_2021_D21/CA_SanBern_EMRI_1_2021/reports/lidar_report/140G0221F0290_CA_SanBernardino_EarthMRI_2021_D21_Lidar_WU_ID223531_229143_Mapping_Report.pdf Lidar Report Online Resource pdf Link to the lidar report. https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/CA_SanBernardino_EarthMRI_2021_D21/USGS_CA_SanBernardino_EarthMRI_2021_D21_Project_Report.pdf USGS Project Report Online Resource pdf Link to the USGS Project Report that provides information about the project, vertical accuracy results, and the point classes and sensors used. https://s3-us-west-2.amazonaws.com/usgs-lidar-public/CA_SanBern_EMRI_1_2021/ept.json USGS Entwine Point Tile (EPT) Online Resource json Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud. https://usgs.entwine.io/data/view.html?r=%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/CA_SanBern_EMRI_1_2021%22 3D View (Potree USGS) Online Resource Link to view the point cloud, using the Entwine Point Tile (EPT) format, in the 3D Potree viewer. This data set was produced to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class. USGS Determined Vertical Accuracy: Tested NVA RMSEz = 5.4 cm Tested 95th percentile value for VVA is : 11.12 cm For more information see the USGS project report and the lidar report. The links to these reports are provided in the URL section of this metadata record. These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications. Data covers the entire area specified for this project. Yes Unknown Yes NCEI-NC Data is backed up to cloud storage. The NOAA Office for Coastal Management (OCM) ingested references to the USGS Entwine Point Tiles (EPT) hosted on Amazon Web Services (AWS) into the Digital Coast Data Access Viewer (DAV). The DAV accesses the point cloud as it resides on AWS under the usgs-lidar-public-container. USGS AWS Entwine Point Tile (EPT) Organization USGS Publisher https://s3-us-west-2.amazonaws.com/usgs-lidar-public/CA_SanBern_EMRI_1_2021/ept.json Entwine Point Tile for CA_SanBern_EMRI_1_2021 1 Lidar data was collected using Optech Galaxy Prime sensor. The raw data was verified in MARS software for complete coverage of the project area, and boresighted to align the flightlines. Raw data files were parsed into manageable client-specific tiles. These tiles were then processed through automated filtering that separates the data into different classification groups: unclassified points, ground points, low noise, water, bridge decks, high noise and ignore ground. The data was next taken into MARS to reclassify the erroneous points that may remain in the lidar point cloud after auto filter. Eight points per square meter (QL1). 2022-02-23T00:00:00 2 LiDAR swath data was measured to have an average of 0.245 meter nominal pulse spacing and 16.72 pulses per meter. The method used was counting first return points within each swath, then dividing by the area of the extent of the corresponding swath to get density. NPS was mathematically derived from this density number. This was performed on each swath then averaged to generate the two numbers above. This USGS method does not consider swath sidelap in these calculations. 2022-02-23T00:00:00 3 Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 web mercator (EPSG 3857) and and the vertical units of meters (NAVD88 GEOID18) were retained. Organization U.S. Geological Survey 12201 Sunrise Valley Drive Reston VA 20191 USA https://usgs.gov USGS Home Home page for USGS Online Resource 4 The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tile (EPT) that was ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container. This is the AWS URL being accessed: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/CA_SanBern_EMRI_1_2021/ept.json 2024-08-01T00:00:00 Organization Office for Coastal Management OCM https://ror.org/05v14bq57 2234 South Hobson Avenue Charleston SC 29405-2413 https://www.coast.noaa.gov/ 73587 Data Set Cross Reference 73204 Data Set Cross Reference gov.noaa.nmfs.inport:73205 Rebecca Mataosky 2024-08-01T19:50:23 SysAdmin InPortAdmin 2026-03-04T19:17:17 2024-08-02 OCM Partners OCMP 1002 Public No No 2024-08-01 1 Year 2025-08-01