2017 SJRWMD Lidar DEM: Ft. Drum, FL
OCM Partners
Data Set
(DS)
| ID: 68474
| Published / External
Created: 2022-11-18
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Last Modified: 2024-01-10
Project (PRJ) | ID: 49404
ID: 68474
Data Set (DS)
* Discovery• First Pass
» Metadata Rubric
Item Identification
* » Title | 2017 SJRWMD Lidar DEM: Ft. Drum, FL |
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Short Name | fl2017_ft_drum_m9669_metadata |
* Status | Completed |
Creation Date | 2017 |
Revision Date | |
• Publication Date | 2017-10 |
* » Abstract |
Digital Aerial Solutions (DAS) collected 485 square miles of the Ft. Drum area of interest located with the Florida counties of Brevard, Osceola, Indian River, Okeechobee and St Lucie. The nominal pulse spacing for this project was 1 point every 0.25 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 lidar data to produce seamless hydro flattened DEMs for the project area. The data was formatted according to the Florida Statewide tile naming convention with each tile covering an area of 5,000 feet by 5,000 ft. A total of 541 LAS tiles and 541 DEM tiles were produced for the entire project. These data were received by the NOAA Office for Coastal Management (OCM) from the St. Johns River Water Management District (SJRWMD). NOAA OCM processed the data to be available for custom and bulk downloads from the NOAA Digital Coast Data Access Viewer (DAV). In addition to these bare earth Digital Elevation Model (DEM) data, the lidar point data that these DEM data were created from, are also available. These data are available for custom download at the link provided in the URL section of this metadata record. |
* 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. |
Notes | |
Other Citation Details | |
• Supplemental Information |
A complete description of this dataset is available in the Final Project Report submitted to the USGS. |
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Keywords
Theme Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Science Keywords | EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION |
Global Change Master Directory (GCMD) Science Keywords | EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM) |
Global Change Master Directory (GCMD) Science Keywords | EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION |
ISO 19115 Topic Category | elevation |
Temporal Keywords
Thesaurus | Keyword |
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* Spatial Keywords
Thesaurus | Keyword |
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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 |
Stratum Keywords
Thesaurus | Keyword |
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Instrument Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Instrument Keywords | LIDAR > Light Detection and Ranging |
Platform Keywords
Thesaurus | Keyword |
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Global Change Master Directory (GCMD) Platform Keywords | Airplane > Airplane |
Physical Location
• » Organization | Office for Coastal Management |
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• » City | Charleston |
• » State/Province | SC |
• Country | |
• » Location Description |
Data Set Information
* Data Set Scope Code | Data Set |
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• Data Set Type | Elevation |
• Maintenance Frequency | As Needed |
Maintenance Note | |
» Data Presentation Form | Model (digital) |
• Entity Attribute Overview | |
Entity Attribute Detail Citation | |
Entity Attribute Detail URL | |
Distribution Liability |
Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners. |
Data Set Credit | St. Johns River Water Management District |
Support Roles
* » Support Role | Data Steward |
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* » Date Effective From | 2022 |
Date Effective To | |
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 |
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Mobile | |
URL | https://coast.noaa.gov |
Business Hours | |
Contact Instructions |
* » Support Role | Distributor |
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* » Date Effective From | 2022 |
Date Effective To | |
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 |
Fax | |
Mobile | |
URL | https://coast.noaa.gov |
Business Hours | |
Contact Instructions |
* » Support Role | Metadata Contact |
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* » Date Effective From | 2022 |
Date Effective To | |
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 |
Fax | |
Mobile | |
URL | https://coast.noaa.gov |
Business Hours | |
Contact Instructions |
* » Support Role | Point of Contact |
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* » Date Effective From | 2022 |
Date Effective To | |
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 |
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URL | https://coast.noaa.gov |
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Extents
Currentness Reference | Ground Condition |
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Extent Group 1
Extent Description |
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Extent Group 1 / Geographic Area 1
* » W° Bound | -80.926507 |
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* » E° Bound | -80.52368 |
* » N° Bound | 27.910025 |
* » S° Bound | 27.455369 |
* » Description |
Extent Group 1 / Vertical Extent
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Extent Group 1 / Time Frame 1
* » Time Frame Type | Range |
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* » Start | 2017-04-06 |
End | 2017-04-20 |
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Spatial Information
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Spatial Representation
Grid Representation Used? | Yes |
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Reference Systems
Reference System
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EPSG Code | EPSG:6438 | ||||||||||||||||||||||||||||
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Access Information
Data License | |
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Data License Statement | |
* » Security Class | Unclassified |
* Security Classification System | |
Security Handling Description | |
• Data Access Policy | |
» 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. |
Metadata Access Constraints | |
Metadata Use Constraints |
Distribution Information
Start Date | 2022-11-18 |
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End Date | Present |
» Download URL | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9669/details/9669 |
Distributor | NOAA Office for Coastal Management (NOAA/OCM) (2022 - Present) |
File Name | Customized Download |
Description |
Create custom data files by choosing data area, map projection, file format, etc. A new metadata will be produced to reflect your request using this record as a base. |
File Date/Time | |
File Type (Deprecated) | Zip |
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Compression | Zip |
Review Status |
Start Date | 2022-11-18 |
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End Date | Present |
» Download URL | https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/FL_Ft_Drum_DEM_2017_9669/index.html |
Distributor | NOAA Office for Coastal Management (NOAA/OCM) (2022 - Present) |
File Name | Bulk Download |
Description |
Bulk download of data files in the original coordinate system. |
File Date/Time | |
File Type (Deprecated) | GeoTIFF |
Distribution Format | GeoTIFF |
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Archive Information
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URLs
URL | https://coast.noaa.gov/ |
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Name | NOAA's Office for Coastal Management (OCM) website |
URL Type | Online Resource |
File Resource Format | HTML |
Description |
Information on the NOAA Office for Coastal Management (OCM) |
URL | https://coast.noaa.gov/dataviewer/ |
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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 | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9781/details/9781 |
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Name | Custom Point Download |
URL Type | Online Resource |
File Resource Format | Zip |
Description |
Link to custom download, from the Data Access Viewer (DAV), the lidar point data from which these raster Digital Elevation Model (DEM) data were created. |
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Issues
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Technical Environment
Description |
Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.3 |
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Data Quality
Representativeness | |
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Accuracy | |
Analytical Accuracy | |
Horizontal Positional Accuracy |
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. |
Vertical Positional Accuracy |
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 amount 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 171 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 (56 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (115 checkpoints), including forest, brush, tall weeds, crops, and high grass. 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 0.64 ft (19.6 cm) at the 95% confidence level based on RMSEz (0.33 ft/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 0.96 ft (29.4 cm) based on the 95th percentile. 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 =0.12 ft (3.7 cm), equating to +/- 0.24 ft (7.3 cm) at 95% confidence level. 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 VVA accuracy was found to be +/- 0.75 ft (22.9 cm) at the 95th percentile. The 5% outliers consisted of 6 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between 0.76 ft (23.2 cm) and 1.77 ft (53.9 cm). |
Quantitation Limits | |
Bias | |
Comparability | |
Completeness Measure | |
Precision | |
Analytical Precision | |
Field Precision | |
Sensitivity | |
Detection Limit | |
Completeness Report |
A visual qualitative assessment was performed to ensure data completeness and full tiles. No void or missing data exists. |
Conceptual Consistency |
Data covers the project boundary. |
» Quality Control Procedures Employed |
Data Management
» Have Resources for Management of these Data Been Identified? | |
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» Approximate Percentage of Budget for these Data Devoted to Data Management | |
» Do these Data Comply with the Data Access Directive? | |
» Is Access to the Data Limited Based on an Approved Waiver? | |
» If Distributor (Data Hosting Service) is Needed, Please Indicate | |
» Approximate Delay Between Data Collection and Dissemination | |
» If Delay is Longer than Latency of Automated Processing, Indicate Under What Authority Data Access is Delayed |
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» Actual or Planned Long-Term Data Archive Location | |
» If World Data Center or Other, Specify | |
» If To Be Determined, Unable to Archive, or No Archiving Intended, Explain |
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» Approximate Delay Between Data Collection and Archiving | |
» How Will the Data Be Protected from Accidental or Malicious Modification or Deletion Prior to Receipt by the Archive? |
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Lineage
» Lineage Statement |
This data set was collected by Dewberry for the St. Johns River Water Management District (SJRWMD). The data set was provided to the NOAA Office for Coastal Management (OCM) for the data to be made available for custom download from the NOAA Digital Coast Data Access Viewer and for bulk download from https. |
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Sources
Citation Title | St. Johns River Water Management District (SJRWMD) |
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Contact Role Type | Originator |
Contact Type | Organization |
Contact Name | SJRWMD |
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Citation URL | https://www.sjrwmd.com/ |
Citation URL Name | SJRWMD |
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Process Steps
Process Step Number | 1 |
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» Description |
Data for the Ft. Drum Lidar Project was acquired by Digital Aerial Solutions (DAS). The project area included approximately 485 contiguous square miles or 1256.14 square kilometers for the counties of Brevard, Osceola, Indian River, Okeechobee and St Lucie in Florida. Lidar sensor data were collected with the Leica ALS80 lidar system. The data was delivered in the State Plane coordinate system, U.S. Survey Feet, Florida East, 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 overlap bit is 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. |
Process Date/Time | 2017-04-01 00:00:00 |
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Process Step Number | 2 |
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» 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). 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) |
Process Date/Time | 2017-08-01 00:00:00 |
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Process Step Number | 3 |
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» Description |
Dewberry used GeoCue software to produce intensity imagery and raster stereo models from the source lidar. The raster resolution was 2.5 feet. |
Process Date/Time | 2017-09-01 00:00:00 |
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Process Step Number | 4 |
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» 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. |
Process Date/Time | 2017-09-01 00:00:00 |
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Process Step Number | 5 |
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» Description |
The bridge deck polygons are loaded into Terrascan software. Lidar points and surface models created from ground lidar points are reviewed and 3D bridge breaklines are compiled in Terrascan. Typically, two breaklines are compiled for each bridge deck-one breakline along the ground of each abutment. The bridge breaklines are placed perpendicular to the bridge deck and extend just beyond the extents of the bridge deck. Extending the bridge breaklines beyond the extent of the bridge deck allows the compiler to use ground elevations from the ground lidar data for each endpoint of the breakline. |
Process Date/Time | 2017-09-01 00:00:00 |
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Process Step Number | 6 |
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» 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 hydrographic breakline and lidar elevations due to monotonicity, connectivity, and flattening rules that are enforced on the hydrographic breaklines. 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. |
Process Date/Time | 2017-09-01 00:00:00 |
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Process Step Number | 7 |
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» Description |
Class 2, ground, lidar points are exported from the LAS files into an Arc Geodatabase (GDB) in multipoint format. The 3D breaklines, Inland Lakes and Ponds, Streams and Rivers, and Below Bridge Breaklines are imported into the same GDB. An ESRI Terrain is generated from these inputs. The surface type of each input is as follows: Ground Multipoint: Masspoints Inland Lakes and Ponds: Hard Replace Streams and Rivers: Hard Line Below Bridge Breaklines: Hard Line |
Process Date/Time | 2017-10-01 00:00:00 |
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Process Step Number | 8 |
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» Description |
The ESRI Terrain is converted to a raster. The raster is created using linear interpolation with a 2.5 foot 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, incorrect hydro-flattening, and artifacts that are introduced during the raster creation process. |
Process Date/Time | 2017-10-01 00:00:00 |
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Process Step Number | 9 |
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» 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. |
Process Date/Time | 2017-10-01 00:00:00 |
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Process Step Number | 10 |
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» Description |
SJRWMD mosaiced the DEM into one raster and made edits to the delivered DEM. Revisions were made to the Fellsmere area that included hydro-flattening some areas. |
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Process Step Number | 11 |
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» Description |
The NOAA Office for Coastal Management (OCM) received one DEM file in GeoTiff format from the SJRWMD. The data were in Florida State Plane East NAD83(2011), US Survey feet coordinates and NAVD88 (GEOID12B) elevations in feet. The bare earth raster file was at a 2.5 ft grid spacing. OCM performed the following processing on the data for Digital Coast storage and provisioning: 1. Used an internal script to assign the EPSG codes (Horizontal EPSG: 6438 and Vertical EPSG: 6360) to the GeoTiff formatted file. 2. Copied the file to https. |
Process Date/Time | 2022-11-17 00:00:00 |
Process Contact | Office for Coastal Management (OCM) |
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Acquisition Information
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Data Set (DS) | Cross Reference |
2017 SJRWMD Lidar: Ft. Drum, FL |
Catalog Details
Catalog Item ID | 68474 |
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Metadata Record Created By | Rebecca Mataosky |
Metadata Record Created | 2022-11-18 19:04+0000 |
Metadata Record Last Modified By | Kirk Waters |
» Metadata Record Last Modified | 2024-01-10 19:28+0000 |
Metadata Record Published | 2024-01-10 |
Owner Org | OCMP |
Metadata Publication Status | Published Externally |
Do Not Publish? | N |
Metadata Workflow State | Published / External |
Metadata Last Review Date | 2022-11-18 |
Metadata Review Frequency | 1 Year |
Metadata Next Review Date | 2023-11-18 |
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