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2018 - 2019 USGS QL2 Lidar: Northern California Wildfires
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      DateTime:  2024-02-29T00:00:00
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        citation:  (CI_Citation)
            title:  2018 - 2019 USGS QL2 Lidar: Northern California Wildfires
            alternateTitle:  ca2018_wildfire_ql2_m9036_metadata
            date:  (CI_Date)
                date:  2019-10-01
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                  Anchor:  InPort Catalog ID 58957
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B5a_2018/ept.json
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                        name:  USGS Entwine Point Tile (EPT) - USGS_LPC_CA_NoCAL_Wildfires_B5a_2018
                        description:  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.
                        function:  (CI_OnLineFunctionCode) download
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCal_Wildfires_GMEG_2018/ept.json
                        protocol:  WWW:LINK-1.0-http--link
                        name:  USGS Entwine Point Tile (EPT) - USGS_LPC_CA_NoCal_Wildfires_GMEG_2018
                        description:  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.
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/CA_NoCAL_Wildfires_TL_QL2_2018/ept.json
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                        name:  USGS Entwine Point Tile (EPT) - CA_NoCAL_Wildfires_TL_QL2_2018
                        description:  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.
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B1_2018/ept.json
                        protocol:  WWW:LINK-1.0-http--link
                        name:  USGS Entwine Point Tile (EPT) - USGS_LPC_CA_NoCAL_Wildfires_B1_2018
                        description:  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.
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B2_2018/ept.json
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                        name:  USGS Entwine Point Tile (EPT) - USGS_LPC_CA_NoCAL_Wildfires_B2_2018
                        description:  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.
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B3_2018/ept.json
                        protocol:  WWW:LINK-1.0-http--link
                        name:  USGS Entwine Point Tile (EPT) - USGS_LPC_CA_NoCAL_Wildfires_B3_2018
                        description:  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.
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B4_2018/ept.json
                        protocol:  WWW:LINK-1.0-http--link
                        name:  USGS Entwine Point Tile (EPT) - USGS_LPC_CA_NoCAL_Wildfires_B4_2018
                        description:  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.
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                        linkage: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B5b_2018/ept.json
                        protocol:  WWW:LINK-1.0-http--link
                        name:  USGS Entwine Point Tile (EPT) - USGS_LPC_CA_NoCAL_Wildfires_B5b_2018
                        description:  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.
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                        linkage: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/CA_NoCAL_3DEP_Supp_Funding_2018_D18/CA_NoCAL_Wildfires_B4_2018/reports/33371_USGS_NoCal_LiDAR_ProjectReport.pdf
                        protocol:  WWW:LINK-1.0-http--link
                        name:  Lidar Report
                        description:  Link to the lidar report.
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                        linkage: https://usgs.entwine.io/data/view.html?r=[%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B1_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B2_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B3_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B4_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B5a_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCAL_Wildfires_B5b_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_NoCal_Wildfires_GMEG_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/CA_NoCAL_Wildfires_TL_QL2_2018/ept.json%22]
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                        description:  Link to view the point cloud, using the Entwine Point Tile (EPT) format, in the 3D Potree viewer.
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                        linkage: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/CA_NoCAL_3DEP_Supp_Funding_2018_D18/CA_NoCAL_Wildfires_B3_2018/
                        protocol:  WWW:LINK-1.0-http--link
                        name:  USGS Additional Data
                        description:  This link is to the reports, breaklines, metadata, spatial metadata, and shapefiles.
                        function:  (CI_OnLineFunctionCode) download
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        abstract:  Product: These lidar data are processed Classified LAS 1.4 files, formatted to individual 1000 m x 1000 m tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary. Geographic Extent: 27 counties in California, covering approximately 16846 total square miles. Dataset Description: The Northern California - QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 2011 Contiguous USA Albers, Meter and vertical datum of NAVD88 GEOID 12B, Meter. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 43332 individual 1000 m x 1000 m tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1000 m x 1000 m schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in summer, fall, and winter 2018 and winter, spring, and summer 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 387 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 678 independent accuracy checkpoints, 380 in Bare Earth and Urban landcovers (380 NVA points), 298 in Tall Weeds categories (298 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. The NOAA Office for Coastal Management (OCM) downloaded this data set in 8 blocks from this USGS site: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/CA_NoCAL_3DEP_Supp_Funding_2018_D18/ The blocks downloaded were: CA_NoCAL_Wildfires_B1_2018 Number of files: 7491 CA_NoCAL_Wildfires_B2_2018 Number of files: 10,870 CA_NoCAL_Wildfires_B3_2018 Number of files: 7239 CA_NoCAL_Wildfires_B4_2018 Number of files: 6195 CA_NoCAL_Wildfires_B5a_2018 Number of files: 6302 CA_NoCAL_Wildfires_B5b_2018 Number of files: 4958 CA_NoCal_Wildfires_GMEG_2018 Number of files: 1048 CA_NoCAL_Wildfires_TL_QL2_2018 Number of files: 518 These files were processed to the Data Access Viewer (DAV). The total number of files downloaded and processed was 44,621. This data set contains point cloud data(' in LAZ (compressed LAS) format', ''). The data may have been reprojected or otherwise modified from the original data in an automated process. Disregard projection information in this abstract and refer to the spatial reference section.
        purpose:  To acquire detailed surface elevation data for use in conservation planning, design, research, floodplain mapping, dam safety assessments and elevation modeling, etc. Classified LAS files are used to show the manually reviewed bare earth surface. This allows the user to create intensity images, breaklines and raster DEMs. The purpose of these LiDAR data was to produce high accuracy 3D hydro-flattened digital elevation models (DEMs) with a 1 meter cell size. These raw LiDAR point cloud data were used to create classified LiDAR LAS files, intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.
        credit:  Quantum Spatial, Inc. The custom download may be cited as National Oceanic and Atmospheric Administration (NOAA) Digital Coast Data Access Viewer. Charleston, SC: NOAA Office for Coastal Management. Accessed 2025-06-04 at https://coast.noaa.gov/dataviewer.
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                    voice:  (843) 740-1202
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                    deliveryPoint:  2234 South Hobson Ave
                    city:  Charleston
                    administrativeArea:  SC
                    postalCode:  29405-2413
                    country: (missing)
                    electronicMailAddress:  coastal.info@noaa.gov
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        descriptiveKeywords:  (MD_Keywords)
            keyword:  EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
            keyword:  EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION
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                title:  Global Change Master Directory (GCMD) Science Keywords
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                edition:  17.0
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            keyword:  CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
            keyword:  CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CALIFORNIA
            keyword:  VERTICAL LOCATION > LAND SURFACE
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                edition:  20.8
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            keyword:  LIDAR > Light Detection and Ranging
            type:  (MD_KeywordTypeCode) instrument
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                title:  Global Change Master Directory (GCMD) Instrument Keywords
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                edition:  17.2
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            keyword:  Airplane > Airplane
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            keyword:  2018
            keyword:  2019
            type:  (MD_KeywordTypeCode) temporal
        descriptiveKeywords:  (MD_Keywords)
            keyword:  Continent > North America > United States Of America > California > Alameda County
            keyword:  Continent > North America > United States Of America > California > Butte County
            keyword:  Continent > North America > United States Of America > California > Carson City County
            keyword:  Continent > North America > United States Of America > California > Colusa County
            keyword:  Continent > North America > United States Of America > California > Contra Costa County
            keyword:  Continent > North America > United States Of America > California > El Dorado County
            keyword:  Continent > North America > United States Of America > California > Glenn County
            keyword:  Continent > North America > United States Of America > California > Humboldt County
            keyword:  Continent > North America > United States Of America > California > Lake County
            keyword:  Continent > North America > United States Of America > California > Lassen County
            keyword:  Continent > North America > United States Of America > California > Marin County
            keyword:  Continent > North America > United States Of America > California > Mendocino County
            keyword:  Continent > North America > United States Of America > California > Napa County
            keyword:  Continent > North America > United States Of America > California > Nevada County
            keyword:  Continent > North America > United States Of America > California > Placer County
            keyword:  Continent > North America > United States Of America > California > Plumas County
            keyword:  Continent > North America > United States Of America > California > Sacramento County
            keyword:  Continent > North America > United States Of America > California > San Francisco County
            keyword:  Continent > North America > United States Of America > California > Sierra County
            keyword:  Continent > North America > United States Of America > California > Solano County
            keyword:  Continent > North America > United States Of America > California > Sonoma County
            keyword:  Continent > North America > United States Of America > California > Sutter County
            keyword:  Continent > North America > United States Of America > California > Tehama County
            keyword:  Continent > North America > United States Of America > California > Trinity County
            keyword:  Continent > North America > United States Of America > California > Washoe County
            keyword:  Continent > North America > United States Of America > California > Yolo County
            keyword:  Continent > North America > United States Of America > California > Yuba County
            type:  (MD_KeywordTypeCode) place
        descriptiveKeywords:  (MD_Keywords)
            keyword:  Lidar - partner (no harvest)
            type:  (MD_KeywordTypeCode) project
            thesaurusName:  (CI_Citation)
                title:  InPort
                date: (inapplicable)
        resourceConstraints:  (MD_LegalConstraints)
            useConstraints:  (MD_RestrictionCode) otherRestrictions
            otherConstraints:   This data set was compiled dynamically. It will be removed 10 days after 2025-06-04 from the NOAA system. Cite As: OCM Partners, [Date of Access]: 2018 - 2019 USGS QL2 Lidar: Northern California Wildfires [Data Date Range], https://www.fisheries.noaa.gov/inport/item/58957.
        resourceConstraints:  (MD_Constraints)
            useLimitation:  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.
        resourceConstraints:  (MD_LegalConstraints)
            accessConstraints:  (MD_RestrictionCode) otherRestrictions
            otherConstraints:   This data set was compiled dynamically. It will be removed 10 days after 2025-06-04 from the NOAA system. Access Constraints: None
        resourceConstraints:  (MD_LegalConstraints)
            useConstraints:  (MD_RestrictionCode) otherRestrictions
            otherConstraints:   This data set was compiled dynamically. It will be removed 10 days after 2025-06-04 from the NOAA system. 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.
        resourceConstraints:  (MD_LegalConstraints)
            useLimitation:  (MD_RestrictionCode) otherRestrictions
            otherConstraints:   This data set was compiled dynamically. It will be removed 10 days after 2025-06-04 from the NOAA system. Distribution Liability: Any conclusions drawn from the analysis of this information are not the responsibility of Quantum Spatial, Inc., USGS, NOAA, the Office for Coastal Management or its partners.
        resourceConstraints:  (MD_SecurityConstraints)
            classification:  (MD_ClassificationCode) unclassified
            classificationSystem: (missing)
            handlingDescription: (missing)
        aggregationInfo:  (MD_AggregateInformation)
            aggregateDataSetName:  (CI_Citation)
                title:  2018 - 2019 USGS QL1 Lidar: Northern California Wildfires
                date: (unknown)
                identifier:  (MD_Identifier)
                    authority:  (CI_Citation)
                        title:  NOAA/NMFS/EDM
                        date: (inapplicable)
                    code:  59131
            associationType:  (DS_AssociationTypeCode) crossReference
        aggregationInfo:  (MD_AggregateInformation)
            aggregateDataSetName:  (CI_Citation)
                title:  NOAA Data Management Plan (DMP)
                date: (unknown)
                identifier:  (MD_Identifier)
                    authority:  (CI_Citation)
                        title:  NOAA/NMFS/EDM
                        date: (inapplicable)
                    code:  58957
                citedResponsibleParty:  (CI_ResponsibleParty)
                    organisationName: (inapplicable)
                    contactInfo:  (CI_Contact)
                        onlineResource:  (CI_OnlineResource)
                            linkage: https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocmp/dmp/pdf/58957.pdf
                            protocol:  WWW:LINK-1.0-http--link
                            name:  NOAA Data Management Plan (DMP)
                            description:  NOAA Data Management Plan for this record on InPort.
                            function:  (CI_OnLineFunctionCode) information
                    role: (inapplicable)
            associationType:  (DS_AssociationTypeCode) crossReference
        spatialRepresentationType:  (MD_SpatialRepresentationTypeCode) vector
        language:  eng; US
        topicCategory:  (MD_TopicCategoryCode) elevation
        environmentDescription:  MicroStation Version 8; TerraScan Version 18; TerraModeler Version 18; GeoCue Version 2017.1.14.1; Esri ArcGIS 10.3; Global Mapper 19; Leica Cloud Pro 1.2.4, RiProcess 1.8.5; Windows 10 Operating System \\point_cloud\tilecls\*.las
        extent:  (EX_Extent)
            geographicElement:  (EX_GeographicBoundingBox)
                westBoundLongitude:  -124.428962
                eastBoundLongitude:  -119.853493
                southBoundLatitude:  37.727043
                northBoundLatitude:  41.386852
            temporalElement:  (EX_TemporalExtent)
                extent:
                  TimePeriod:
                    description:   | Currentness: Ground Condition
                    beginPosition:  2018-07-07
                    endPosition:  2019-09-05
        supplementalInformation:  Contract No. G16PC00016, Task Order No. 140G0218F0251; CONTRACTOR: Quantum Spatial, Inc. The following are the USGS lidar fields in JSON: { "ldrinfo" : { "ldrspec" : "USGS-NGP Base Specification v1.3", "ldrsens" : "Riegl VQ1560i", "ldrmaxnr" : "unlimited", "ldrnps" : "0.71", "ldrdens" : "2.0", "ldranps" : "0.48", "ldradens" : "4.34", "ldrfltht" : "2000", "ldrfltsp" : "160", "ldrscana" : "29", "ldrscanr" : "46", "ldrpulsr" : "100", "ldrpulsd" : "3", "ldrpulsw" : "0.36", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.18", "ldrswatw" : "2217.0", "ldrswato" : "55", "ldrgeoid" : "GEOID 12B", "ldrcrs" : "NAD 1983 2011 Contiguous USA Albers, Meter" }, "ldrinfo" : { "ldrspec" : "USGS-NGP Base Specification v1.3", "ldrsens" : "Leica ALS70", "ldrmaxnr" : "4", "ldrnps" : "0.71", "ldrdens" : "2.0", "ldranps" : "0.6", "ldradens" : "2.78", "ldrfltht" : "2200", "ldrfltsp" : "140", "ldrscana" : "15", "ldrscanr" : "46", "ldrpulsr" : "245", "ldrpulsd" : "4", "ldrpulsw" : "0.48", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.22", "ldrswatw" : "1179.0", "ldrswato" : "30", "ldrgeoid" : "GEOID 12B", "ldrcrs" : "NAD 1983 2011 Contiguous USA Albers, Meter" }, "ldrinfo" : { "ldrspec" : "USGS-NGP Base Specification v1.3", "ldrsens" : "Leica ALS80", "ldrmaxnr" : "unlimited", "ldrnps" : "0.71", "ldrdens" : "2.0", "ldranps" : "0.6", "ldradens" : "2.78", "ldrfltht" : "2300", "ldrfltsp" : "140", "ldrscana" : "14", "ldrscanr" : "60", "ldrpulsr" : "240", "ldrpulsd" : "2.5", "ldrpulsw" : "0.51", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.22", "ldrswatw" : "1147.0", "ldrswato" : "30", "ldrgeoid" : "GEOID 12B", "ldrcrs" : "NAD 1983 2011 Contiguous USA Albers, Meter" }, "ldrinfo" : { "ldrspec" : "USGS-NGP Base Specification v1.3", "ldrsens" : "Riegl VQ1560i", "ldrmaxnr" : "unlimited", "ldrnps" : "0.71", "ldrdens" : "2.0", "ldranps" : "0.6", "ldradens" : "2.78", "ldrfltht" : "2300", "ldrfltsp" : "140", "ldrscana" : "30", "ldrscanr" : "165", "ldrpulsr" : "800", "ldrpulsd" : "3", "ldrpulsw" : "0.41", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.18", "ldrswatw" : "2656.0", "ldrswato" : "30", "ldrgeoid" : "GEOID 12B", "ldrcrs" : "NAD 1983 2011 Contiguous USA Albers, Meter" }, "ldraccur" : { "ldrchacc" : "0", "rawnva" : "0.087", "rawnvan" : "374", "clsnva" : "0.086", "clsnvan" : "380", "clsvva" : "0.27", "clsvvan" : "298" }, "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 identified in these files using the standard LAS overlap bit.", "lasintr" : "16", "lasclass" : { "clascode" : "1", "clasitem" : "Processed, but Unclassified" }, "lasclass" : { "clascode" : "2", "clasitem" : "Bare-Earth Ground" }, "lasclass" : { "clascode" : "7", "clasitem" : "Low Noise" }, "lasclass" : { "clascode" : "9", "clasitem" : "In-land Water" }, "lasclass" : { "clascode" : "17", "clasitem" : "Bridge Decks" }, "lasclass" : { "clascode" : "18", "clasitem" : "High Noise" }, "lasclass" : { "clascode" : "20", "clasitem" : "Ignored Ground" }, "lasclass" : { "clascode" : "21", "clasitem" : "Snow (where identifiable)" }, "lasclass" : { "clascode" : "22", "clasitem" : "Temporal Exclusion (if applicable)" } }}
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    distributionInfo:  (MD_Distribution)
        distributionFormat:  (MD_Format)
            name:  Zip
            version: (missing)
            fileDecompressionTechnique:  Zip
        distributionFormat:  (MD_Format)
            name:  LAS/LAZ - LASer
            version: (missing)
            fileDecompressionTechnique:  LAZ
        distributor:  (MD_Distributor)
            distributorContact:  (CI_ResponsibleParty)
                organisationName:  NOAA Office for Coastal Management
                contactInfo:  (CI_Contact)
                    phone:  (CI_Telephone)
                        voice:  (843) 740-1202
                    address:  (CI_Address)
                        deliveryPoint:  2234 South Hobson Ave
                        city:  Charleston
                        administrativeArea:  SC
                        postalCode:  29405-2413
                        country: (missing)
                        electronicMailAddress:  coastal.info@noaa.gov
                    onlineResource:  (CI_OnlineResource)
                        linkage: https://coast.noaa.gov
                        protocol:  WWW:LINK-1.0-http--link
                        name:  NOAA Office for Coastal Management Website
                        description:  NOAA Office for Coastal Management Home Page
                        function:  (CI_OnLineFunctionCode) information
                role:  (CI_RoleCode) distributor
        distributor:  (MD_Distributor)
            distributorContact:  (CI_ResponsibleParty)
                organisationName:  U.S. Geological Survey
                contactInfo:  (CI_Contact)
                    phone:  (CI_Telephone)
                        voice: (missing)
                    address:  (CI_Address)
                        deliveryPoint:  12201 Sunrise Valley Drive
                        city:  Reston
                        administrativeArea:  VA
                        postalCode:  20191
                        country:  USA
                        electronicMailAddress: (missing)
                    onlineResource:  (CI_OnlineResource)
                        linkage: https://usgs.gov
                        protocol:  WWW:LINK-1.0-http--link
                        name:  USGS Home
                        description:  Home page for USGS
                        function:  (CI_OnLineFunctionCode) information
                role:  (CI_RoleCode) distributor
        transferOptions:  (MD_DigitalTransferOptions)
            onLine:  (CI_OnlineResource)
                linkage: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9036
                protocol:  WWW:LINK-1.0-http--link
                name:  Customized Download
                description:  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.
                function:  (CI_OnLineFunctionCode) download
        transferOptions:  (MD_DigitalTransferOptions)
            onLine:  (CI_OnlineResource)
                linkage: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/CA_NoCAL_3DEP_Supp_Funding_2018_D18/
                protocol:  WWW:LINK-1.0-http--link
                name:  Bulk Download
                description:  Bulk download of data files in LAZ format, NAD 1983 2011 Contiguous USA Albers, meters projection and orthometric heights in meters.
                function:  (CI_OnLineFunctionCode) download
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    dataQualityInfo:  (DQ_DataQuality)
        scope:  (DQ_Scope)
            level:  (MD_ScopeCode) dataset
        report:  (DQ_AbsoluteExternalPositionalAccuracy)
            nameOfMeasure:  Vertical Positional Accuracy
            evaluationMethodDescription:  The specifications require that only nonvegetated vertical accuracy (NVA) be computed for raw LiDAR data swath files. The vertical accuracy was tested with 374 independent survey points located in open terrain. These check points were not used in the calibration or post processing of the LiDAR data. The survey check points were distributed throughout the project area. Tested 0.087 meters NVA at a 95% confidence level using 374 independent survey points located in open terrain. The survey check points were distributed throughout the project area. The 374 independent check points were surveyed using GPS techniques. See survey report for additional survey methodologies. Elevations from the unclassified LiDAR surface were measured for the x,y location of each checkpoint. Elevations interpolated from the LiDAR surface were then compared to the elevation values of the surveyed control points. The root mean square error vertical (RMSEz) was computed to be 0.044 meters. AccuracyZ has been tested to meet 19.0 cm NVA at 95-percent confidence level using (RMSEz * 1.9600) as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using American Society of Photogrammetry and Remote Sensing (ASPRS) Guidelines.
            result: (missing)
        report:  (DQ_CompletenessCommission)
            nameOfMeasure:  Completeness Report
            evaluationMethodDescription:  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 the data pass Non-Vegetated Vertical Accuracy specifications.
            result: (missing)
        report:  (DQ_ConceptualConsistency)
            nameOfMeasure:  Conceptual Consistency
            evaluationMethodDescription:  Data covers the entire area specified for this project.
            result: (missing)
        lineage:  (LI_Lineage)
            statement:  The NOAA Office for Coastal Management (OCM) downloaded laz files from the USGS rockyweb site (https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/CA_NoCAL_3DEP_Supp_Funding_2018_D18/) and processed the data to be available for custom download from the NOAA Digital Coast Data Access Viewer (DAV). These are the folders that were downloaded: CA_NoCAL_Wildfires_B1_2018 CA_NoCAL_Wildfires_B2_2018 CA_NoCAL_Wildfires_B3_2018 CA_NoCAL_Wildfires_B4_2018 CA_NoCAL_Wildfires_B5a_2018 CA_NoCAL_Wildfires_B5b_2018 CA_NoCal_Wildfires_GMEG_2018 CA_NoCAL_Wildfires_TL_QL2_2018
            processStep:  (LI_ProcessStep)
                description:  Raw Data and Boresight Processing: The boresight for each lift was done individually as the solution may change slightly from lift to lift. The following steps describe the Raw Data Processing and Boresight process: 1) Technicians processed the raw data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was used as source data for boresight. 2) Technicians first used Quantum Spatial, Inc. proprietary and commercial software to calculate initial boresight adjustment angles based on sample areas selected in the lift. These areas cover calibration flight lines collected in the lift, cross tie, and production flight lines. These areas are well distributed in the lift coverage and cover multiple terrain types that are necessary for boresight angle calculation. The technicians then analyzed the results and made any necessary additional adjustment until it was acceptable for the selected areas. 3) Once the boresight angle calculation was completed for the selected areas, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technicians utilized commercial and proprietary software packages to analyze how well flight line overlaps matched for the entire lift and adjusted as necessary until the results met the project specifications. 4) Once all lifts were completed with individual boresight adjustment, the technicians checked and corrected the vertical misalignment of all flight lines and also the matching between data and ground truth. The relative accuracy was less than or equal to 7 cm RMSEz within individual swaths and less than or equal to 10 cm RMSEz or within swath overlap (between adjacent swaths). 5) The technicians ran a final vertical accuracy check of the boresighted flight lines against the surveyed checkpoints after the z correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level (Required Accuracy) was met.
                dateTime:
                  DateTime:  2019-01-01T00:00:00
            processStep:  (LI_ProcessStep)
                description:  LAS Point Classification: The point classification was performed as described below. The bare earth surface was manually reviewed to ensure correct classification on the Class 2 (Ground) points. After the bare-earth surface was finalized, it was then used to generate all hydro-breaklines through heads-up digitization. All ground (ASPRS Class 2) LiDAR data inside of the Lake Pond and Double Line Drain hydro-flattened breaklines were then classified to Water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 1 meter was also used around each hydro-flattened feature to classify these ground (ASPRS Class 2) points to Ignored ground (ASPRS Class 20). All Lake Pond Island and Double Line Drain Island features were checked to ensure that the ground (ASPRS Class 2) points were reclassified to the correct classification after the automated classification was completed. All overlap data was processed through automated functionality provided by TerraScan to classify the overlapping flight line data to approved classes. The overlap data was classified using standard LAS overlap bit. These classes were created through automated processes only and were not verified for classification accuracy. Due to software limitations within TerraScan, these classes were used to trip the withheld bit within various software packages. These processes were reviewed and accepted through numerous conference calls and pilot study areas. All data were manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler. Global Mapper was used as a final check of the bare earth dataset. GeoCue was then used to create the deliverable industry-standard LAS files for both the All Point Cloud Data and the Bare Earth. Quantum Spatial, Inc. proprietary software was used to perform final statistical analysis of the classes in the LAS files, on a per tile level to verify final classification metrics and full LAS header information.
                dateTime:
                  DateTime:  2019-01-01T00:00:00
            processStep:  (LI_ProcessStep)
                description:  The NOAA Office for Coastal Management (OCM) downloaded this data set in 7 blocks from this USGS site: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/CA_NoCAL_3DEP_Supp_Funding_2018_D18/ The blocks downloaded were: CA_NoCAL_Wildfires_B1_2018 Number of files: 7491 CA_NoCAL_Wildfires_B2_2018 Number of files: 10,870 CA_NoCAL_Wildfires_B3_2018 Number of files: 7239 CA_NoCAL_Wildfires_B4_2018 Number of files: 6195 CA_NoCAL_Wildfires_B5a_2018 Number of files: 6302 CA_NoCAL_Wildfires_B5b_2018 Number of files: 4958 CA_NoCal_Wildfires_GMEG_2018 Number of files: 1048 The total number of files downloaded and processed was 44,103. The data were in Albers Equal Area (NAD83 2011), meters coordinates and NAVD88 (Geoid12B) elevations in meters. The data were classified as: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 9 - Water, 17 - Bridge Decks, 18 - High Noise, 20 - Ignored Ground. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 3, 7, 9, 17, 18, 20. OCM performed the following processing on the data for Digital Coast storage and provisioning purposes: 1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges. 2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid 12B model, to convert from Albers Equal Area (NAD83 2011) coordinates in meters to geographic coordinates, to assign the geokeys, to sort the data by gps time and zip the data to database.
                dateTime:
                  DateTime:  2020-03-02T00:00:00
                processor:  (CI_ResponsibleParty)
                    organisationName:  Office for Coastal Management
                    role:  (CI_RoleCode) processor
            processStep:  (LI_ProcessStep)
                description:  The NOAA Office for Coastal Management (OCM) downloaded 518 laz files from the TL (tribal lands) folder from the USGS rockyweb site. This data was released after the above blocks of data were processed. This is the URL for that data: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/CA_NoCAL_3DEP_Supp_Funding_2018_D18/CA_NoCAL_Wildfires_TL_QL2_2018/LAZ/ The data were in Albers Equal Area (NAD83 2011), meters coordinates and NAVD88 (Geoid12B) elevations in meters. The data were classified as: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 9 - Water, 17 - Bridge Decks, 18 - High Noise, 20 - Ignored Ground. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 3, 7, 9, 17, 18, 20. OCM performed the following processing on the data for Digital Coast storage and provisioning purposes: 1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges. 2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid 12B model, to convert from Albers Equal Area (NAD83 2011) coordinates in meters to geographic coordinates, to assign the geokeys, to sort the data by gps time and zip the data to database.
                dateTime:
                  DateTime:  2023-10-31T00:00:00
                processor:  (CI_ResponsibleParty)
                    organisationName:  Office for Coastal Management
                    role:  (CI_RoleCode) processor
            source:  (LI_Source)
                description:  Source Contribution: This data source was used (along with airborne GPS/IMU data) to georeference the LiDAR point cloud data.
                sourceCitation:  (CI_Citation)
                    title:  Ground Control for the Northern California - QL2 Project
                    date:  (CI_Date)
                        date:  2019-10-01
                        dateType:  (CI_DateTypeCode) publication
                    citedResponsibleParty:  (CI_ResponsibleParty)
                        organisationName:  Quantum Spatial, Inc.
                        role:  (CI_RoleCode) originator
                sourceExtent:  (EX_Extent)
                    temporalElement:  (EX_TemporalExtent)
                        extent:
                          TimeInstant:
                            timePosition:  2018-11-29
            source:  (LI_Source)
                sourceCitation:  (CI_Citation)
                    title:  USGS LAZ Data Download
                    date: (missing)
                    citedResponsibleParty:  (CI_ResponsibleParty)
                        organisationName:  USGS
                        contactInfo:  (CI_Contact)
                            onlineResource:  (CI_OnlineResource)
                                linkage: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/CA_NoCAL_3DEP_Supp_Funding_2018_D18/
                                protocol:  WWW:LINK-1.0-http--link
                                name:  Source Citation URL
                                description:  Source Citation URL
                                function:  (CI_OnLineFunctionCode) information
                        role:  (CI_RoleCode) publisher
            processStep:  (LI_ProcessStep)
                description:   The dataset has been mosaiced, reprojected, and clipped as needed from the original input files using PDAL and GDAL commands.
                dateTime:
                  DateTime:  2025-06-04
                processor:  (CI_ResponsibleParty)
                    individualName:  NOAA Office for Coastal Management
                    contactInfo:  (CI_Contact)
                        address:  (CI_Address)
                            electronicMailAddress:  coastal.info@noaa.gov
                    role:  (CI_RoleCode) processor