2018 USGS Lidar: Upper St. Johns, FL
Data Set (DS) | OCM Partners (OCMP)GUID: gov.noaa.nmfs.inport:59708 | Updated: March 4, 2026 | Published / External
Keywords
Theme Keywords
| Thesaurus | Keyword |
|---|---|
| Global Change Master Directory (GCMD) Science Keywords |
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
|
| Global Change Master Directory (GCMD) Science Keywords |
EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION
|
| ISO 19115 Topic Category |
elevation
|
| UNCONTROLLED | |
| None | beach |
| None | erosion |
Spatial Keywords
| Thesaurus | Keyword |
|---|---|
| Global Change Master Directory (GCMD) Location Keywords |
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
|
| Global Change Master Directory (GCMD) Location Keywords |
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > FLORIDA
|
| Global Change Master Directory (GCMD) Location Keywords |
VERTICAL LOCATION > LAND SURFACE
|
| UNCONTROLLED | |
| None | Continent > North America > United States Of America > Florida > Brevard County |
Instrument Keywords
| Thesaurus | Keyword |
|---|---|
| Global Change Master Directory (GCMD) Instrument Keywords |
LIDAR > Light Detection and Ranging
|
Platform Keywords
| Thesaurus | Keyword |
|---|---|
| Global Change Master Directory (GCMD) Platform Keywords |
Airplane > Airplane
|
Physical Location
| Organization: | Office for Coastal Management |
|---|---|
| City: | Charleston |
| State/Province: | SC |
Data Set Information
| Data Set Scope Code: | Data Set |
|---|---|
| Data Set Type: | Elevation |
| Maintenance Frequency: | None Planned |
| Data Presentation Form: | Model (digital) |
| 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. |
| Data Set Credit: | Dewberry, USGS |
Support Roles
Data Steward
| Date Effective From: | 2020 |
|---|---|
| Date Effective To: | |
| Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
| Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
| Email Address: | coastal.info@noaa.gov |
| Phone: | (843) 740-1202 |
| URL: | https://coast.noaa.gov |
Distributor
| Date Effective From: | 2020 |
|---|---|
| Date Effective To: | |
| Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
| Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
| Email Address: | coastal.info@noaa.gov |
| Phone: | (843) 740-1202 |
| URL: | https://coast.noaa.gov |
Metadata Contact
| Date Effective From: | 2020 |
|---|---|
| Date Effective To: | |
| Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
| Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
| Email Address: | coastal.info@noaa.gov |
| Phone: | (843) 740-1202 |
| URL: | https://coast.noaa.gov |
Point of Contact
| Date Effective From: | 2020 |
|---|---|
| Date Effective To: | |
| Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
| Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
| Email Address: | coastal.info@noaa.gov |
| Phone: | (843) 740-1202 |
| URL: | https://coast.noaa.gov |
Extents
| Currentness Reference: | Ground Condition |
|---|
Extent Group 1
Extent Group 1 / Geographic Area 1
| W° Bound: | -81.113032 | |
|---|---|---|
| E° Bound: | -80.659865 | |
| N° Bound: | 28.900197 | |
| S° Bound: | 28.088417 |
Extent Group 1 / Time Frame 1
| Time Frame Type: | Range |
|---|---|
| Start: | 2018-03-21 |
| End: | 2018-06-13 |
Spatial Information
Spatial Resolution
| Horizontal Distance: | 0.2 Meter |
|---|
Spatial Representation
Representations Used
| Grid: | No |
|---|---|
| Vector: | Yes |
| Text / Table: | No |
| TIN: | No |
| Stereo Model: | No |
| Video: | No |
Vector Representation 1
| Point Object Present?: | Yes |
|---|---|
| Point Object Count: | 76688391334 |
Reference Systems
Reference System 1
Coordinate Reference System |
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Access Information
| Security Class: | Unclassified |
|---|---|
| Data Access Procedure: |
Data is available online for bulk and custom downloads. |
| Data Access Constraints: |
None |
| Data 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 Information
Distribution 1
| Download URL: | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9082/details/9082 |
|---|---|
| Distributor: | NOAA Office for Coastal Management (NOAA/OCM) (2020 - Present) |
| File 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. |
| File Type (Deprecated): | Zip |
| Compression: | Zip |
Distribution 2
| Download URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9082/index.html |
|---|---|
| Distributor: | NOAA Office for Coastal Management (NOAA/OCM) (2020 - Present) |
| File Name: | Bulk Download |
| Description: |
Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum. |
| File Type (Deprecated): | LAZ |
| Distribution Format: | LAS/LAZ - LASer |
| Compression: | Zip |
URLs
URL 1
| URL: | https://coast.noaa.gov/dataviewer/ |
|---|---|
| Name: | NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) |
| URL Type: |
Online Resource
|
| File Resource Format: | HTML |
| 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. |
URL 2
| URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9082/supplemental/fl2018_up_st_johns_m9082.kmz |
|---|---|
| Name: | Browse graphic |
| URL Type: |
Browse Graphic
|
| File Resource Format: | KML |
| Description: |
This graphic displays the footprint for this lidar data set. |
URL 3
| URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9082/supplemental/Topographic_Lidar_Project_Report_UpperStJohns.pdf |
|---|---|
| Name: | Dataset report |
| URL Type: |
Online Resource
|
| File Resource Format: | |
| Description: |
Link to data set report. |
URL 4
| URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9082/breaklines/ |
|---|---|
| Name: | Breaklines |
| URL Type: |
Online Resource
|
| Description: |
Link to data set breaklines. |
Data Quality
| Horizontal Positional Accuracy: |
Horizontal accuracy testing requires well-defined checkpoints that can be identified in the dataset. Elevation datasets, including lidar datasets, do not always contain well-defined checkpoints suitable for horizontal accuracy assessment. However, the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) recommends at least half of the NVA vertical check points should be located at the ends of paint stripes or other point features visible on the lidar intensity image, allowing them to double as horizontal check points. Nineteen checkpoints were determined to be photo-identifiable in the intensity imagery and were used to test the horizontal accuracy of the lidar dataset. As only nineteen (19) checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value, but the results of the testing are provided. 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. No horizontal accuracy requirements or thresholds were provided for this project. However, lidar datasets are generally calibrated by methods designed to ensure a horizontal accuracy of 1 meter or less at the 95% confidence level. This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 1.34 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 = 0.35 ft (11 cm) and RMSEy = 0.40 ft (12 cm) which equates to +/- 0.92 ft (28 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. |
|---|---|
| Vertical Positional Accuracy: |
For the vertical accuracy assessment, ninety (90) check points were surveyed for the project and are located within bare earth/open terrain, grass/weeds/crops, and forested/fully grown land cover categories. Please see the survey report which details and validates how the survey was completed for this project. Checkpoints were evenly distributed throughout the project area so as to cover as many flight lines as possible using the “dispersed method” of placement. NVA (Non-vegetated Vertical Accuracy) is determined with check points located only in nonvegetated terrain, including open terrain (grass, dirt, sand, and/or rocks) and urban areas, where there is a very high probability that the lidar sensor will have detected the bare-earth ground surface and where random errors are expected to follow a normal error distribution. The NVA determines how well the calibrated lidar sensor performed. With a normal error distribution, the vertical accuracy at the 95% confidence level is computed as the vertical root mean square error (RMSEz) of the checkpoints x 1.9600. For the Upper Saint Johns lidar project, vertical accuracy must be 0.64 ft (19.6 cm) or less based on an RMSEz of 0.33 ft (10 cm) x 1.9600. VVA (Vegetated Vertical Accuracy) is determined with all checkpoints in vegetated land cover categories, including tall grass, weeds, crops, brush and low trees, and fully forested areas, where there is a possibility that the lidar sensor and post-processing may yield elevation errors that do not follow a normal error distribution. VVA at the 95% confidence level equals the 95th percentile error for all checkpoints in all vegetated land cover categories combined. The Upper Saint Johns lidar project VVA standard is 0.96 ft (29.4 cm) based on the 95th percentile. The VVA is accompanied by a listing of the 5% outliers that are larger than the 95th percentile used to compute the VVA; these are always the largest outliers that may depart from a normal error distribution. Here, Accuracyz differs from VVA because Accuracyz assumes elevation errors follow a normal error distribution where RMSE procedures are valid, whereas VVA assumes lidar errors may not follow a normal error distribution in vegetated categories, making the RMSE process invalid. This lidar 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 =0.26 ft (7.9 cm), equating to +/- 0.51 ft (15.5 cm) at 95% confidence level. Actual VVA accuracy was found to be +/- 0.52 ft (15.8 cm) at the 95th percentile. |
| Completeness Report: |
These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications. |
| Conceptual Consistency: |
Data covers the entire area specified for this project. |
Data Management
| Have Resources for Management of these Data Been Identified?: | Yes |
|---|---|
| Approximate Percentage of Budget for these Data Devoted to Data Management: | Unknown |
| Do these Data Comply with the Data Access Directive?: | Yes |
| Actual or Planned Long-Term Data Archive Location: | NCEI-CO |
| How Will the Data Be Protected from Accidental or Malicious Modification or Deletion Prior to Receipt by the Archive?: |
Data is backed up to tape and to cloud storage. |
Lineage
Sources
Ground Control Point Survey Report, Upper St. John's River Basin North Lidar Project
| Contact Role Type: | Originator |
|---|---|
| Contact Type: | Organization |
| Contact Name: | Dewberry Engineers, Inc. |
| Publish Date: | 2018-05-04 |
| Extent Type: | Discrete |
| Extent Start Date/Time: | 2018 |
| Scale Denominator: | 1640 |
| Source Contribution: |
This data source was used (along with airborne GPS/IMU data) to georeference the lidar point cloud data. |
Process Steps
Process Step 1
| Description: |
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 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 technician then analyzed the results and made any necessary additional adjustment until it is 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 match 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 6 cm RMSEz within individual swaths and less than or equal to 8 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 check points after the z correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level (Required Accuracy) was met. Point classification was performed according to USGS Lidar Base Specification 1.2, and breaklines were collected for water features. Bare earth DEMs were exported from the classified point cloud using collected breaklines for hydroflattening. |
|---|---|
| Process Date/Time: | 2018-01-01 00:00:00 |
Process Step 2
| Description: |
LAS Point Classification: The point classification is performed as described below. The bare earth surface is then manually reviewed to ensure correct classification on the Class 2 (Ground) points. After the bare-earth surface is finalized, it is 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 flattening breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 0.25 m was also used around each hydro-flattened feature to classify these ground (ASPRS Class 2) points to Ignored ground (ASPRS Class 10). 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 by USGS. 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 by USGS through numerous conference calls and pilot study areas. All data was manually reviewed and any remaining artifacts removed using functionality provided by TerraScan and TerraModeler. Global Mapper us 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. Dewberry 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. |
|---|---|
| Process Date/Time: | 2018-12-01 00:00:00 |
Process Step 3
| Description: |
The NOAA Office for Coastal Management (OCM) downloaded this data set from this USGS site: ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_FL_Upper_Saint_Johns_2017_LAS_2019 The total number of files downloaded and processed was 973. The data were in Florida State Plane East (NAD83 2011), US survey feet coordinates and NAVD88 (Geoid12B) elevations in feet. From the provided report, the data were classified as: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 9 - Water, 10 - Ignored Ground, 17 - Bridge Decks, 18 - High Noise. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available in the DAV are: 1, 2, 7, 9, 10, 17, 18. 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 Geoid12B model, to convert from Florida State Plane East (NAD83 2011), US survey feet coordinates to geographic coordinates, to convert from elevations in feet to meters, to assign the geokeys, to sort the data by gps time and zip the data to database and to http. |
|---|---|
| Process Date/Time: | 2020-05-18 00:00:00 |
| Process Contact: | Office for Coastal Management (OCM) |
| ROR: | https://ror.org/05v14bq57 |
Catalog Details
| Catalog Item ID: | 59708 |
|---|---|
| GUID: | gov.noaa.nmfs.inport:59708 |
| Metadata Record Created By: | Rebecca Mataosky |
| Metadata Record Created: | 2020-05-19 10:33+0000 |
| Metadata Record Last Modified By: | SysAdmin InPortAdmin |
| Metadata Record Last Modified: | 2026-03-04 19:17+0000 |
| Metadata Record Published: | 2022-03-16 |
| Owner Org: | OCMP |
| Metadata Publication Status: | Published Externally |
| Do Not Publish?: | N |
| Metadata Last Review Date: | 2022-03-16 |
| Metadata Review Frequency: | 1 Year |
| Metadata Next Review Date: | 2023-03-16 |
