| 2017 USGS Lidar DEM: Suwannee River, FL | identificationInfo|
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| (MI_Metadata) fileIdentifier: gov.noaa.nmfs.inport:62980 language: LanguageCode: eng characterSet: (MD_CharacterSetCode) UTF8 hierarchyLevel: (MD_ScopeCode) dataset hierarchyLevelName: Elevation contact: (CI_ResponsibleParty) organisationName: OCM Partners 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: Website description: NOAA Office for Coastal Management Home Page function: (CI_OnLineFunctionCode) information role: (CI_RoleCode) pointOfContact dateStamp: DateTime: 2020-09-22T15:30:12 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: 2017 USGS Lidar DEM: Suwannee River, FL date: (CI_Date) date: 2017 dateType: (CI_DateTypeCode) creation date: (CI_Date) date: 2020 dateType: (CI_DateTypeCode) publication identifier: (MD_Identifier) authority: (CI_Citation) title: NOAA/NMFS/EDM date: (inapplicable) code: Anchor: InPort Catalog ID 62980 citedResponsibleParty: (CI_ResponsibleParty) organisationName: (inapplicable) contactInfo: (CI_Contact) onlineResource: (CI_OnlineResource) linkage: https://coast.noaa.gov/htdata/lidar4_z/geoid18/data/9118/supplemental/Suwannee_River_Lidar_Project_Report_20170904_Final.pdf protocol: WWW:LINK-1.0-http--link name: Dataset report description: Link to data set report. function: (CI_OnLineFunctionCode) download role: (inapplicable) citedResponsibleParty: (CI_ResponsibleParty) organisationName: (inapplicable) contactInfo: (CI_Contact) onlineResource: (CI_OnlineResource) linkage: https://coast.noaa.gov/htdata/lidar4_z/geoid18/data/9118/breaklines/ protocol: WWW:LINK-1.0-http--link name: Breaklines description: Link to the data set breaklines. function: (CI_OnLineFunctionCode) download role: (inapplicable) citedResponsibleParty: (CI_ResponsibleParty) organisationName: (inapplicable) contactInfo: (CI_Contact) onlineResource: (CI_OnlineResource) linkage: https://coast.noaa.gov/dataviewer/ protocol: WWW:LINK-1.0-http--link name: NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) description: 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. function: (CI_OnLineFunctionCode) download role: (inapplicable) presentationForm: (unknown) abstract: Digital Aerial Solution (DAS) collected 921 square miles over 3 Areas of Interest (AOIs) to include portions of Baker, Alachua and Levy Counties in Florida. The nominal pulse spacing for this project was 1 point every 0.7 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- Bridge Decks, 18-High Noise. Dewberry produced 3D breaklines and combined these with the final ground classified lidar data to produce seamless bare earth, hydro flattened DEMs for the project area. The data was formatted according to the Florida State Grid tile naming convention with each tile covering an area of 5,000 feet by 5,000 ft. A total of 1378 DEM tiles were produced for the entire project. The NOAA Office for Coastal Management (OCM) received the DEM files from the Suwannee River Water Management District and processed the files to the Digital Coast. The breaklines were also downloaded and are available for download at the link provided in the URL section of this metadata record. Please note that this product has not been reviewed by OCM and any conclusions drawn from the analysis of this information are not the responsibility of NOAA or OCM. 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 2.5 foot cell size hydro flattened Digital Elevation Models (DEMs). All products follow and comply with USGS Lidar Base Specification Version 1.2. credit: U.S. Geological Survey 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: 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: 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://coast.noaa.gov/htdata/lidar4_z/geoid18/data/9118/supplemental/fl2017_suwannee_m9118.kmz fileDescription: This graphic displays the footprint for this lidar data set. fileType: KML descriptiveKeywords: (MD_Keywords) keyword: Earth Science > Land Surface > Topography > Terrain Elevation 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) descriptiveKeywords: (MD_Keywords) keyword: Continent > North America > United States Of America keyword: Continent > North America > United States Of America > Florida keyword: Continent > North America > United States Of America > Florida > Alachua County keyword: Continent > North America > United States Of America > Florida > Baker County keyword: Continent > North America > United States Of America > Florida > Levy County keyword: Suwannee River keyword: USA keyword: Vertical Location > Land Surface type: (MD_KeywordTypeCode) place thesaurusName: (CI_Citation) title: Global Change Master Directory (GCMD) Location Keywords date: (missing) descriptiveKeywords: (MD_Keywords) keyword: Earth Remote Sensing Instruments > Active Remote Sensing > Profilers/Sounders > Lidar/Laser Sounders > LIDAR > Light Detection and Ranging type: (MD_KeywordTypeCode) instrument thesaurusName: (CI_Citation) title: Global Change Master Directory (GCMD) Instrument Keywords date: (missing) descriptiveKeywords: (MD_Keywords) keyword: Aircraft > Aircraft type: (MD_KeywordTypeCode) platform thesaurusName: (CI_Citation) title: Global Change Master Directory (GCMD) Platform Keywords date: (missing) descriptiveKeywords: (MD_Keywords) keyword: DEMs - partner (no harvest) type: (MD_KeywordTypeCode) project thesaurusName: (CI_Citation) title: InPort date: (inapplicable) 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: 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: Any conclusions drawn from the analysis of this information are not the responsibility of Dewberry, 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: NOAA Data Management Plan (DMP) date: (unknown) identifier: (MD_Identifier) authority: (CI_Citation) title: NOAA/NMFS/EDM date: (inapplicable) code: 62980 citedResponsibleParty: (CI_ResponsibleParty) organisationName: (inapplicable) contactInfo: (CI_Contact) onlineResource: (CI_OnlineResource) linkage: https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocmp/dmp/pdf/62980.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 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: -82.775476 eastBoundLongitude: -82.000046 southBoundLatitude: 28.962929 northBoundLatitude: 30.610655 temporalElement: (EX_TemporalExtent) extent: TimePeriod: description: | Currentness: Ground Condition beginPosition: 2017-01-14 endPosition: 2017-02-10 supplementalInformation: A complete description of this dataset is available in the Final Project Report that was submitted to the U.S. Geological Survey. return to top distributionInfo: (MD_Distribution) distributionFormat: (MD_Format) name: Zip version: (missing) fileDecompressionTechnique: Zip 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: 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=9179/details/9179 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. function: (CI_OnLineFunctionCode) download transferOptions: (MD_DigitalTransferOptions) onLine: (CI_OnlineResource) linkage: https://coast.noaa.gov/htdata/raster5/elevation/USGS_sewannee_FL_2015_9179 protocol: WWW:LINK-1.0-http--link name: Bulk Download description: Bulk download of data files in original projection and units. 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: 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. 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. This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 1.35 ft (41 cm) RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 3.28 ft (1 meter) at a 95% confidence level. Nineteen (19) checkpoints were photo-identifiable but do not produce a statistically significant tested horizontal accuracy value. Using this small sample set of photo-identifiable checkpoints, positional accuracy of this dataset was found to be RMSEx = 1.34 ft (40.8 cm)) and RMSEy = 0.75 ft (22.9 cm) which equates to +/- 2.65 ft (80.8 cm) at 95% confidence level. While not statistically significant, the results of the small sample set of checkpoints are within the produced to meet horizontal accuracy. result: (missing) report: (DQ_AbsoluteExternalPositionalAccuracy) nameOfMeasure: Vertical Positional Accuracy evaluationMethodDescription: The vertical accuracy of the lidar was tested by Dewberry with 144 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain (93 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (51 checkpoints), including forest, brush, tall weeds, crops, and high grass. The vertical accuracy is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the lidar ground points. Checkpoints are always compared to interpolated surfaces created from the lidar point cloud because it is unlikely that a survey checkpoint will be located at the location of a discrete lidar point. The same 144 checkpoints that were used to test the vertical accuracy of the lidar were used to validate the vertical accuracy of the final DEM products as well. Accuracy results may vary between the source lidar and final DEM deliverable. DEMs are created by averaging several lidar points within each pixel which may result in slightly different elevation values at each survey checkpoint when compared to the source LAS, which does not average several lidar points together but may interpolate (linearly) between two or three points to derive an elevation value. The vertical accuracy of the DEM 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. Dewberry typically uses LP360 software to test the swath lidar vertical accuracy, Terrascan software to test the classified lidar vertical accuracy, and Esri ArcMap to test the DEM vertical accuracy so that three different software programs are used to validate the vertical accuracy for each project. This DEM dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 0.33 ft (10 cm) RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz = 0.19 ft (5.8) cm, equating to +/- 0.36 ft (11 cm) at 95% confidence level. Actual VVA accuracy was found to be +/- 0.51 ft (15.5 cm) at the 95th percentile. result: (missing) report: (DQ_CompletenessCommission) nameOfMeasure: Completeness Report evaluationMethodDescription: A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. No void or missing data and data passes vertical accuracy specifications. result: (missing) report: (DQ_ConceptualConsistency) nameOfMeasure: Conceptual Consistency evaluationMethodDescription: Data covers the project boundary. result: (missing) lineage: (LI_Lineage) statement: NOAA OCM received the bare earth DEM files from the SRWMD. processStep: (LI_ProcessStep) description: Data for the FL Suwannee River Lidar Project was acquired by Digital Aerial Solutions (DAS). The project area included approximately 921 contiguous square miles or 2385.38 square kilometers for the counties of Baker, Alachua, and Levy in Florida. Lidar sensor data were collected with the Leica ALS80 HP lidar system. The data was delivered in the State Plane coordinate system, US Survey Feet, Florida North, 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. 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: 2017-02-01T00:00:00 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 (5,000 ft x 5,000 ft). The tiled data is then opened in Terrascan where Dewberry identifies edge of flight line points that may be geometrically unusable with the withheld bit. These points are separated from the main point cloud so that they are not used in the ground algorithms. Overage points are then identified with the overlap bit. 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. 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. A final QC is performed on the data. 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 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 (16 bit integer) Flight Line (Integer) Scan Angle (degree) dateTime: DateTime: 2017-03-01T00:00:00 processStep: (LI_ProcessStep) description: The final bare-earth lidar points are used to create a terrain. The final 3D breaklines collected for the project are also enforced in the terrain. The terrain is then converted to raster format using linear interpolation. For most projects, a single terrain/DEM can be created for the whole project. For very large projects, multiple terrains/DEMs may be created. The DEM(s) is reviewed for any issues requiring corrections, including remaining lidar mis-classifications, erroneous breakline elevations, poor hydro-flattening or hydro-enforcement, and processing artifacts. After corrections are applied, the DEM(s) is then split into individual tiles following the project tiling scheme. The tiles are verified for final formatting and then loaded into Global Mapper to ensure no missing or corrupt tiles and to ensure seamlessness across tile boundaries. dateTime: DateTime: 2020-09-21T00:00:00 processStep: (LI_ProcessStep) description: NOAA OCM received the bare earth digital elevation model files from the SRWMD. The data were in ESRI GRID format, Florida State Plane North projection and NAVD88 vertical datum using geoid12b, with all units in US survey feet. OCM used internal scripts to convert the files to cloud-optimized geoTIFF format (COGs) and assign the geokeys. processor: (CI_ResponsibleParty) organisationName: Office for Coastal Management role: (CI_RoleCode) processor source: (LI_Source) sourceCitation: (CI_Citation) title: USGS date: (missing) | |