| 2016 USGS West Coast El-Nino Lidar DEM (WA, OR, CA) | identificationInfo|
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| (MI_Metadata) fileIdentifier: gov.noaa.nmfs.inport:48383 language: LanguageCode: eng characterSet: (MD_CharacterSetCode) UTF8 hierarchyLevel: (MD_ScopeCode) dataset contact: (CI_ResponsibleParty) organisationName: Office for Coastal Management contactInfo: (CI_Contact) phone: (CI_Telephone) voice: (missing) address: (CI_Address) role: (CI_RoleCode) resourceProvider contact: (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) pointOfContact dateStamp: DateTime: 2023-10-02T18:08:10 metadataStandardName: ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data metadataStandardVersion: ISO 19115-2:2009(E) return to top identificationInfo: (MD_DataIdentification) citation: (CI_Citation) title: 2016 USGS West Coast El-Nino Lidar DEM (WA, OR, CA) alternateTitle: west_coast_2016_el_nino_dem_m6260_metadata date: (CI_Date) date: 2017-04-12 dateType: (CI_DateTypeCode) publication identifier: (MD_Identifier) authority: (CI_Citation) title: NOAA/NMFS/EDM date: (inapplicable) code: Anchor: InPort Catalog ID 48383 citedResponsibleParty: (CI_ResponsibleParty) organisationName: (inapplicable) contactInfo: (CI_Contact) onlineResource: (CI_OnlineResource) linkage: https://www.fisheries.noaa.gov/inport/item/48383 protocol: WWW:LINK-1.0-http--link name: Full Metadata Record description: View the complete metadata record on InPort for more information about this dataset. function: (CI_OnLineFunctionCode) information role: (inapplicable) abstract: Towill collected approximately 75 square miles of coast in Oregon, 486 square miles of coast in Washington and California, and an additional 44 square miles for USACE defined harbors. The data was collected in a corridor approximately 500 meters wide. The nominal pulse spacing for this project was 1 point every 0.35 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground, 7-Low Noise, 9-Water, 10-Ignored Ground due to breakline proximity, 17- Bridges, 18-High Noise, 64- Flown Outside of Low Tide Window and 65- Temporal Ground. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless DEMs for the project area. The data was formatted according to the USNG tile naming convention with each tile covering an area of 1,500 meters by 1,500 meters. A total of 2377 UTM 10 DEM and LAS tiles and 487 UTM 11 DEM and LAS tiles were produced for the project. Original contact information: Contact Org: USGS Title: Program Manager Phone: (303) 202-4419 Email: kyoder@usgs.gov purpose: The purpose of this LiDAR data was to produce high accuracy 3D elevation products, including tiled LiDAR in LAS 1.4 format, 3D breaklines, and 0.5 meter cell size Digital Elevation Models (DEMs). All products comply with USGS Lidar Base Specification Version 1.2. status: (MD_ProgressCode) completed pointOfContact: (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) pointOfContact pointOfContact: (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) custodian resourceMaintenance: (MD_MaintenanceInformation) maintenanceAndUpdateFrequency: (MD_MaintenanceFrequencyCode) asNeeded graphicOverview: (MD_BrowseGraphic) fileName: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/6259/supplemental/west_coast_2016_el_nino_m6259.kmz fileDescription: This graphic shows the lidar footprint for the 2016 USGS West Coast El-Nino Lidar project along the coast of Washington, Oregon, and California. fileType: kmz descriptiveKeywords: (MD_Keywords) keyword: EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > TOPOGRAPHICAL RELIEF MAPS keyword: EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION type: (MD_KeywordTypeCode) theme thesaurusName: (CI_Citation) title: Global Change Master Directory (GCMD) Science Keywords date: (missing) edition: 12.3 descriptiveKeywords: (MD_Keywords) keyword: CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > CALIFORNIA keyword: CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > OREGON keyword: CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > WASHINGTON type: (MD_KeywordTypeCode) place thesaurusName: (CI_Citation) title: Global Change Master Directory (GCMD) Location Keywords date: (missing) edition: 12.3 descriptiveKeywords: (MD_Keywords) keyword: DEM keyword: DTM type: (MD_KeywordTypeCode) theme descriptiveKeywords: (MD_Keywords) keyword: DOC/NOAA/NOS/OCM > Office of Coastal Management, National Ocean Service, NOAA, U.S. Department of Commerce type: (MD_KeywordTypeCode) dataCentre thesaurusName: (CI_Citation) title: Global Change Master Directory (GCMD) Data Center Keywords date: (CI_Date) date: 2017-04-24 dateType: (CI_DateTypeCode) publication edition: 8.5 citedResponsibleParty: GCMD Landing Page descriptiveKeywords: (MD_Keywords) keyword: DEMs type: (MD_KeywordTypeCode) project thesaurusName: (CI_Citation) title: InPort date: (inapplicable) resourceConstraints: (MD_LegalConstraints) useConstraints: (MD_RestrictionCode) otherRestrictions otherConstraints: Cite As: Office for Coastal Management, [Date of Access]: 2016 USGS West Coast El-Nino Lidar DEM (WA, OR, CA) [Data Date Range], https://www.fisheries.noaa.gov/inport/item/48383. 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 useConstraints: (MD_RestrictionCode) otherRestrictions otherConstraints: Access Constraints: None | Use Constraints: None. However, users should be aware that temporal changes may have occurred since this data set was collected and that some parts of these data may no longer represent actual surface conditions. This data was produced for the USGS according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: U.S. Geological Survey, PO Box 25046, MS 510, Denver, CO 80225. Telephone (303) 202-4419. | Distribution Liability: This data was produced for the USGS according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: U.S. Geological Survey, PO Box 25046, MS 510, Denver, CO 80225. Telephone (303) 202-4419. Any conclusions drawn from the analysis of this information are not the responsibility of Dewberry, USGS, NOAA, the NOAA Office for Coastal Management (OCM) or its partners. resourceConstraints: (MD_SecurityConstraints) classification: (MD_ClassificationCode) unclassified classificationSystem: (missing) handlingDescription: (missing) 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: 48383 citedResponsibleParty: (CI_ResponsibleParty) organisationName: (inapplicable) contactInfo: (CI_Contact) onlineResource: (CI_OnlineResource) linkage: https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocm/dmp/pdf/48383.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) grid language: eng; US topicCategory: (MD_TopicCategoryCode) elevation environmentDescription: Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3 extent: (EX_Extent) geographicElement: (EX_GeographicBoundingBox) westBoundLongitude: -124.73467 eastBoundLongitude: -117.119944 southBoundLatitude: 32.533745 northBoundLatitude: 48.392673 temporalElement: (EX_TemporalExtent) extent: TimePeriod: description: | Currentness: Ground Condition beginPosition: 2016-04-28 endPosition: 2016-05-28 supplementalInformation: The USGS West Coast El-Nino Lidar Project Report may be accessed here: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/6259/supplemental/west_coast_2016_el_nino_m6259_lidar_report.pdf The USGS West Coast El-Nino Lidar Project Survey Control Report may be accessed here: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/6259/supplemental/west_coast_2016_el_nino_m6259_survey_report.pdf The lidar point data that the DEMs were created from may be custom downloaded here: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6259 Breaklines created from the lidar point data, in either gdb or gpkg format, may be accessed here: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/6259/breaklines. The DEM and breakline products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA, OCM, or its partners. return to top distributionInfo: (MD_Distribution) distributionFormat: (MD_Format) name: Zip version: (missing) distributionFormat: (MD_Format) name: GeoTIFF version: (missing) 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 transferOptions: (MD_DigitalTransferOptions) onLine: (CI_OnlineResource) linkage: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6260 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. function: (CI_OnLineFunctionCode) download transferOptions: (MD_DigitalTransferOptions) onLine: (CI_OnlineResource) linkage: https://coast.noaa.gov/htdata/raster2/elevation/West_Coast_El_Nino_DEM_2016_6260 protocol: WWW:LINK-1.0-http--link name: Bulk Download description: Simple download of data files. function: (CI_OnLineFunctionCode) download return to top dataQualityInfo: (DQ_DataQuality) scope: (DQ_Scope) level: (MD_ScopeCode) dataset report: (DQ_AbsoluteExternalPositionalAccuracy) nameOfMeasure: Horizontal Positional Accuracy evaluationMethodDescription: The DEMs are derived from the source LiDAR and 3D breaklines created from the LiDAR. Horizontal accuracy is not performed on the DEMs or breaklines. Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the LiDAR. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the LiDAR. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the LiDAR cannot always be tested.; Quantitative Value: 0.211 meters, Test that produced the value: The DEMs are derived from the source LiDAR and 3D breaklines created from the LiDAR. Horizontal accuracy is not performed on the DEMs or breaklines. Lidar vendors calibrate their lidar systems during installation of the system and then again for every project acquired. Typical calibrations include cross flights that capture features from multiple directions that allow adjustments to be performed so that the captured features are consistent between all swaths and cross flights from all directions. Dewberry tested the horizontal accuracy of the LiDAR by comparing photo-identifiable survey checkpoints to the LiDAR Intensity Imagery. As only three (3) checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value but the results of this testing are shown below. Using NSSDA methodology (endorsed by the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014)), horizontal accuracy at the 95% confidence level (called ACCURACYr) is computed by the formula RMSEr * 1.7308 or RMSExy * 2.448. Actual positional accuracy of this dataset was found to be RMSEx = 4.1 cm and RMSEy = 11.5 cm which equates to +/- 21.1 cm at 95% confidence level. result: (missing) report: (DQ_AbsoluteExternalPositionalAccuracy) nameOfMeasure: Vertical Positional Accuracy evaluationMethodDescription: The DEMs are derived from the source LiDAR and 3D breaklines created from the LiDAR. The DEMs are created using controlled and tested methods to limit the aSCunt of error introduced during DEM production so that any differences identified between the source LiDAR and final DEMs can be attributed to interpolation differences. DEMs are created by averaging several LiDAR points within each pixel which may result in slightly different elevation values at a given location when compared to the source LAS, which is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the LiDAR ground points. TINs do not average several LiDAR points together but interpolate (linearly) between two or three points to derive an elevation value. The vertical accuracy of the final bare earth DEMs was tested by Dewberry with 92 independent checkpoints. The same checkpoints that were used to test the source LiDAR data were used to validate the vertical accuracy of the final DEM products. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain, and urban terrain (50), and vegetated terrain, including forest, brush, tall weeds, crops, and high grass (42). The vertical accuracy is tested by extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations. All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). Project specifications required a NVA of 19.6 cm at the 95% confidence level based on RMSEz (10 cm) x 1.9600. All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Project specifications required a VVA of 29.4 cm based on the 95th percentile.; Quantitative Value: 0.116 meters, Test that produced the value: This DEM dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz =5.9 cm, equating to +/- 11.6 cm at 95% confidence level.; Quantitative Value: 0.204 meters, Test that produced the value: This DEM dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual VVA accuracy was found to be +/- 20.4 cm at the 95th percentile. The 5% outliers consisted of 2 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between -54.4 cm and 24.7 cm. result: (missing) report: (DQ_CompletenessCommission) nameOfMeasure: Completeness Report evaluationMethodDescription: A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. One small void in the data impacting tile 10SGD70353892 was identified. The void was accepted by USGS. An eight mile stretch of beach flown outside of the low tide window was identified. This area has been accepted by USGS. Data passes vertical accuracy specifications. There are a total of 2390 UTM 10 tiles in the tile grid but 2377 were produced for DEMs, intensity imagery, and Classified LAS due to water only tiles located within the boundary that did not have any data. There are a total of 488 UTM 11 tiles in the tile grid but 487 were produced for DEMs, intensity imagery, and Classified LAS due to a water only tile located within the boundary that did not have any data. result: (missing) report: (DQ_ConceptualConsistency) nameOfMeasure: Conceptual Consistency evaluationMethodDescription: Data covers the tile scheme provided for the project area. result: (missing) lineage: (LI_Lineage) statement: (missing) processStep: (LI_ProcessStep) description: Data for the West Coast El Nino LiDAR project was acquired by Towill. Towill collected approximately 75 square miles of coast in Oregon, 486 square miles of coast in Washington and California, and an additional 44 square miles for USACE defined harbors about 500 meters wide. LiDAR sensor data were collected with the Optech Orion M300 LiDAR system. The data was delivered in the UTM coordinate system, meters, zone 10 and Zone 11, horizontal datum NAD83(2011), vertical datum NAVD88, Geoid 12B. Deliverables for the project included a raw (unclassified) calibrated LiDAR point cloud, survey control, and a final acquisition/calibration report. The calibration process considered all errors inherent with the equipment including errors in GPS, IMU, and sensor specific parameters. Adjustments were made to achieve a flight line to flight line data match (relative calibration) and subsequently adjusted to control for absolute accuracy. Process steps to achieve this are as follows: Rigorous LiDAR calibration: all sources of error such as the sensor's ranging and torsion parameters, atmospheric variables, GPS conditions, and IMU offsets were analyzed and removed to the highest level possible. This method addresses all errors, both vertical and horizontal in nature. Ranging, atmospheric variables, and GPS conditions affect the vertical position of the surface, whereas IMU offsets and torsion parameters affect the data horizontally. The horizontal accuracy is proven through repeatability: when the position of features remains constant no matter what direction the plane was flying and no matter where the feature is positioned within the swath, relative horizontal accuracy is achieved. Absolute horizontal accuracy is achieved through the use of differential GPS with base lines shorter than 25 miles. The base station is set at a temporary monument that is 'tied-in' to the CORS network. The same position is used for every lift, ensuring that any errors in its position will affect all data equally and can therefore be removed equally. Vertical accuracy is achieved through the adjustment to ground control survey points within the finished product. Although the base station has absolute vertical accuracy, adjustments to sensor parameters introduces vertical error that must be normalized in the final (mean) adjustment. Final calibrated swaths were delivered in LAS format 1.4. The withheld and overlap bits are set and all headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools. dateTime: DateTime: 2016-05-01T00:00:00 processStep: (LI_ProcessStep) description: Dewberry utilizes a variety of software suites for inventory management, classification, and data processing. All LiDAR related processes begin by importing the data into the GeoCue task management software. The swath data is tiled according to project specifications (1,500 m x 1,500 m). The tiled data is then opened in Terrascan where Dewberry classifies edge of flight line points that may be geometrically unusable to a separate class. These points are separated from the main point cloud so that they are not used in the ground algorithms. Dewberry then uses proprietary ground classification routines to remove any non-ground points and generate an accurate ground surface. The ground routine consists of three main parameters (building size, iteration angle, and iteration distance); by adjusting these parameters and running several iterations of this routine an initial ground surface is developed. The building size parameter sets a roaming window size. Each tile is loaded with neighboring points from adjacent tiles and the routine classifies the data section by section based on this roaming window size. The second most important parameter is the maximum terrain angle, which sets the highest allowed terrain angle within the model. As part of the ground routine, low noise points are classified to class 7 and high noise points are classified to class 18. Once the ground routine has been completed, bridge decks are classified to class 17 using bridge breaklines compiled by Dewberry. Dewberry classified areas flown outside of low tide to class 64 and temporal ground areas to class 65. A manual quality control routine is then performed using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review is performed on all tiles and a supervisor manual inspection is completed on a percentage of the classified tiles based on the project size and variability of the terrain. After the ground classification and bridge deck corrections are completed, the dataset is processed through a water classification routine that utilizes breaklines compiled by Dewberry to automatically classify hydrographic features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. During this water classification routine, points that are within 1x NPS or less of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. Overage points are then identified in Terrascan and GeoCue is used to set the overlap bit for the overage points and the withheld bit is set on the withheld points previously identified in Terrascan before the ground classification routine was performed. A final QC is performed on the data. The LAS files are then converted from v1.2 to v1.4 using GeoCue software. At this time, all headers, appropriate point data records, and variable length records, including spatial reference information, are updated in GeoCue software and then verified using proprietary Dewberry tools. The data was classified as follows: Class 1 = Unclassified. This class includes vegetation, buildings, noise etc. Class 2 = Ground Class 7= Low Noise Class 9 = Water Class 10 = Ignored Ground due to breakline proximity Class 17 = Bridge Decks Class 18 = High Noise Class 64 = Flown Outside of Low Tide Window Class 65 = Temporal Ground The LAS header information was verified to contain the following: Class (Integer) Adjusted GPS Time (0.0001 seconds) Easting (0.003 m) Northing (0.003 m) Elevation (0.003 m) Echo Number (Integer) Echo (Integer) Intensity (scaled to 16 bit integer) Flight Line (Integer) Scan Angle (degree) dateTime: DateTime: 2014-08-01T00:00:00 processStep: (LI_ProcessStep) description: Dewberry used GeoCue software to produce intensity imagery and raster stereo Models from the source LiDAR. The raster resolution was 0.3 meters. dateTime: DateTime: 2016-05-01T00:00:00 processStep: (LI_ProcessStep) description: LiDAR intensity stereopairs were viewed in 3-D stereo using Socet Set for ArcGIS softcopy photogrammetric software. The breaklines are collected directly into an ArcGIS file geodatabase to ensure correct topology. The LiDARgrammetry was performed under the direct supervision of an ASPRS Certified Photogrammetrist. The breaklines were stereo-compiled in accordance with the Data Dictionary. Tidal breaklines were collected according to specifications for the West Coast El Nino LiDAR Project. dateTime: DateTime: 2016-07-01T00:00:00 processStep: (LI_ProcessStep) description: Dewberry digitzed 2D bridge deck polygons from the intensity imagery and used these polygons to classify bridge deck points in the LAS to class 17. As some bridges are hard to identify in intensity imagery, Dewberry then used ESRI software to generate bare earth elevation rasters. Bare earth elevation rasters do not contain bridges. As bridges are removed from bare earth DEMs but DEMs are continuous surfaces, the area between bridge abutments must be interpolated. The rasters are reviewed to ensure all locations where the interpolation in a DEM indicates a bridge have been collected in the 2D bridge deck polygons. dateTime: DateTime: 2016-07-01T00:00:00 processStep: (LI_ProcessStep) description: Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture. All breaklines are then compared to ESRI terrains created from ground only points prior to water classification. The horizontal placement of breaklines is compared to terrain features and the breakline elevations are compared to LiDAR elevations to ensure all breaklines match the LiDAR within acceptable tolerances. Some deviation is expected between breakline and LiDAR elevations due to monotonicity and connectivity. Once completeness, horizontal placement, and vertical variance is reviewed, all breaklines are reviewed for topological consistency and data integrity using a combination of ESRI Data Reviewer tools and proprietary tools. Corrections are performed within the QC workflow and re-validated. dateTime: DateTime: 2016-07-01T00:00:00 processStep: (LI_ProcessStep) description: Class 2 ground, Class 9 Water, and Class 10 ignored ground LiDAR points are exported from the LAS files into an Arc Geodatabase (GDB) in multipoint format. An ESRI Terrain is generated from this input and the 3D bridge breaklines. The surface type of the inputs is as follows: Ground Multipoint: Masspoints Bridge Breaklines: Hard Line dateTime: DateTime: 2016-10-01T00:00:00 processStep: (LI_ProcessStep) description: The ESRI Terrain is converted to a raster. The raster is created using linear interpolation with a 0.5 meter cell size. The DEM is reviewed with hillshades in both ArcGIS and Global Mapper. Hillshades allow the analyst to view the DEMs in 3D and to more efficiently locate and identify potential issues. Analysts review the DEM for missed LiDAR classification issues, incorrect breakline elevations, and artifacts that are introduced during the raster creation process. dateTime: DateTime: 2016-10-01T00:00:00 processStep: (LI_ProcessStep) description: The corrected and final DEM is clipped to individual tiles. Dewberry uses a proprietary tool that clips the DEM to each tile located within the final Tile Grid, names the clipped DEM to the Tile Grid Cell name, and verifies that final extents are correct. All individual tiles are loaded into Global Mapper for the last review. During this last review, an analsyt checks to ensure full, complete coverage, no issues along tile boundaries, tiles seamlessly edge-match, and that there are no remaining processing artifacts in the dataset. dateTime: DateTime: 2016-10-01T00:00:00 processStep: (LI_ProcessStep) description: The NOAA Office for Coastal Management (OCM) received 2377 files (UTM10) and 487 files (UTM11) files in IMG format from Dewberry. The DEM files contained elevation measurements in UTM Zones 10 and 11 coordinates in meters with vertical elevations referenced to NAVD88 (Geoid 12b) in meters. OCM ingested the files into the Digital Coast Data Access Viewer. dateTime: DateTime: 2017-03-24T00:00:00 processor: (CI_ResponsibleParty) organisationName: NOAA Office for Coastal Management contactInfo: (CI_Contact) phone: (CI_Telephone) voice: (843) 740-1202 address: (CI_Address) electronicMailAddress: coastal.info@noaa.gov role: (CI_RoleCode) processor processStep: (LI_ProcessStep) description: The Imagine format files were converted to cloud optimized GeoTiff format to facilitate cloud streaming and compression. The vertical coordinate system (NAVD88 meters) was added to the georeferencing. dateTime: DateTime: 2023-10-02T00:00:00 processor: (CI_ResponsibleParty) organisationName: NOAA Office for Coastal Management contactInfo: (CI_Contact) phone: (CI_Telephone) voice: (843) 740-1202 address: (CI_Address) electronicMailAddress: coastal.info@noaa.gov role: (CI_RoleCode) processor source: (LI_Source) sourceCitation: (CI_Citation) title: DEM tiles date: (missing) citedResponsibleParty: (CI_ResponsibleParty) organisationName: USGS role: (CI_RoleCode) originator | |