Hydro-Flattened Digital Elevation Models (DEMs)

Raster Dataset

Thumbnail Not Available

Tags
Elevation, Breaklines, USA, Florida, DEM, DTM, Lidar, LAS, City of Palm Coast, Hydro Flattened


Summary

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.

Description

Digital Aerial Solutions LLC collected 185.5 square miles in the City of Palm Coast in Florida. 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: 1-Unclassified, 2-Ground, 7-Low Noise, 9-Water, 10-Ignored Ground due to breakline proximity, 17- Overpasses and Bridges, 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 FDEM statewide tiling scheme with each tile covering an area of 5,000 ft by 5,000 ft. A total of 161 LAS tiles and 161 DEM tiles were produced for the entire project.

Credits

Use limitations

This data was produced for the St. Johns River Water Management District according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: St. Johns River Water Management District, 4049 Reid Street, P.O. Box 1429, Palatka, Fl 32178-1429. Telephone (386) 329-4500.

Extent

West  -81.381478    East  -81.144998
North  29.656386    South  29.408425

Scale Range

ArcGIS Metadata 

Topics and Keywords 

Themes or categories of the resource  elevation


*Content type  Downloadable Data


Place keywords  USA, Florida, City of Palm Coast

Theme keywords  Elevation, Breaklines, DEM, DTM, Lidar, LAS, Hydro Flattened

Citation 

Title Hydro-Flattened Digital Elevation Models (DEMs)
Publication date 2017-10-01
Indeterminate time unknown


Presentation formats* digital map
FGDC geospatial presentation format  Elevation Data


Citation Contacts 

Responsible party
Organization's name St. Johns River Water Management District
Contact's role  originator


Resource Details 

Dataset languages  English (UNITED STATES)


Status  completed
Spatial representation type* grid


Supplemental information
A complete description of this dataset is available in the Final Project Report submitted to St. Johns River Water Management District.

Processing environment Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.4.1


ArcGIS item properties
*Name Palm_Coast.img
*Location file://\\gisimage\ImageT\LiDAR\PalmCoast\DEM\IMG\Palm_Coast.img
*Access protocol Local Area Network

Extents 

Extent
Description
ground condition

Temporal extent
Beginning date 2017-03-28
Ending date 2017-03-29

Extent
Geographic extent
Bounding rectangle
West longitude -81.381478
East longitude -81.14499762
South latitude 29.40842538
North latitude 29.65638572

Extent
Geographic extent
Bounding rectangle
Extent type  Extent used for searching
*West longitude -81.381478
*East longitude -81.144998
*North latitude 29.656386
*South latitude 29.408425
*Extent contains the resource Yes

Extent in the item's coordinate system
*West longitude 535000.000000
*East longitude 610000.000000
*South latitude 1845000.000000
*North latitude 1935000.000000
*Extent contains the resource Yes

Resource Points of Contact 

Point of contact
Organization's name St. Johns River Water Management District
Contact's position Project Manager
Contact's role  point of contact


Contact information
Phone
Voice (386) 329-4500

Address
Type both
Delivery point 4049 Reid Street, P.O. Box 1429
City Palatka
Administrative area Fl
Postal code 32178-1429
Country US
e-mail addressbvansickle@sjrwmd.com



Resource Maintenance 

Resource maintenance
Update frequency  as needed


Resource Constraints 

Constraints
Limitations of use
This data was produced for the St. Johns River Water Management District according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: St. Johns River Water Management District, 4049 Reid Street, P.O. Box 1429, Palatka, Fl 32178-1429. Telephone (386) 329-4500.

Spatial Reference 

ArcGIS coordinate system
*Type Projected
*Geographic coordinate reference GCS_NAD_1983_2011
*Projection NAD_1983_2011_StatePlane_Florida_East_FIPS_0901_Ft_US
*Coordinate reference details
Projected coordinate system
Well-known identifier 103022
X origin -17791300
Y origin -41645400
XY scale 137249422.94257641
Z origin -100000
Z scale 3048.0060960121923
M origin -100000
M scale 10000
XY tolerance 0.0032808333333333331
Z tolerance 0.0032808333333333331
M tolerance 0.001
High precision true
Latest well-known identifier 6438
VCSWKID  105703
LatestVCSWKID  105703
Well-known text PROJCS["NAD_1983_2011_StatePlane_Florida_East_FIPS_0901_Ft_US",GEOGCS["GCS_NAD_1983_2011",DATUM["D_NAD_1983_2011",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",656166.6666666665],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-81.0],PARAMETER["Scale_Factor",0.9999411764705882],PARAMETER["Latitude_Of_Origin",24.33333333333333],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",6438]],VERTCS["NAVD_1988_Foot_US",VDATUM["North_American_Vertical_Datum_1988"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Foot_US",0.3048006096012192],AUTHORITY["Esri",105703]]

Reference system identifier
*Value 6438
*Codespace EPSG
*Version 8.2.10(10.3.1)


Spatial Data Properties 

Georectified Grid
Number of dimensions 2


Axis dimensions properties
Dimension type  row (y-axis)
Dimension size 2000
*Resolution  2.500000 ftUS

Axis dimensions properties
Dimension type  column (x-axis)
Dimension size 2000
*Resolution  2.500000 ftUS

Axis dimensions properties
Dimension type  vertical (z-axis)
Dimension size 1

*Cell geometry  area
*Point in pixel  center


*Transformation parameters are available Yes


*Check points are available No


Corner points
*Point 535000.000000 1845000.000000
*Point 535000.000000 1935000.000000
*Point 610000.000000 1935000.000000
*Point 610000.000000 1845000.000000

*Center point 572500.000000 1890000.000000




ArcGIS Raster Properties
General Information
*Pixel depth 32
*Compression type None
*Number of bands 1
*Raster format IMAGINE Image
*Source type continuous
*Pixel type floating point
*No data value -3.4028235e+038
*Has colormap No
*Has pyramids Yes




Spatial Data Content 

Image Description
*Type of information  image


Band information
*Description Layer_1
*Maximum value 123.081062
*Minimum value -1.849931
*Number of bits per value 32


Data Quality 

Scope of quality information
Resource level  dataset




Data quality report - Conceptual consistency
Measure description
Data covers the project boundary.





Data quality report - Completeness omission
Measure description
A visual qualitative assessment was performed to ensure data completeness and full tiles. No void or missing data exists.





Data quality report - Absolute external positional accuracy
Dimension horizontal


Measure description
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 test results
Value 1.81 ft (55.1 cm)


Evaluation method
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. 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. Four (4) 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 = 0.67 ft (20.4 cm) and RMSEy = 0.80 ft (24.4 cm) which equates to +/- 1.81 ft (55.1 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.





Data quality report - Absolute external positional accuracy
Dimension vertical


Measure description
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 36 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 (26 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (10 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.



Quantitative test results
Value 0.28 ft (8.5 cm)


Evaluation method
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 =0.14 ft (4.2 cm), equating to +/- 0.28 ft (8.5 cm) at 95% confidence level.





Lineage 

Process step
When the process occurred 2017-03-01
Description
Data for St. Johns River Water Management District QL2 Lidar Project was acquired by Digital Aerial Solutions LLC. The project area included approximately 185.5 contiguous square miles or 480.44 square kilometers for the City of Palm Coast in Florida. Lidar sensor data were collected with the Leica ALS80 HP lidar system. The data was delivered in NAD83(2011) State Plane Florida East, U.S. Survey Feet and NAVD88 (Geoid12B), U.S. Survey Feet. 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.





Process step
When the process occurred 2017-10-01
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 step
When the process occurred 2017-09-01
Description
Class 2, ground, and Class 8, model key points, lidar points are exported from the LAS files into an Arc Geodatabase (GDB) in multipoint format. The 3D breaklines, Inland Lakes and Ponds and Streams and Tidal 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 Tidal : Hard Replace





Process step
When the process occurred 2017-10-01
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 step
When the process occurred 2017-10-01
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 step
When the process occurred 2017-09-01
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 step
When the process occurred 2017-06-01
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)





Process step
When the process occurred 2017-06-01
Description
Dewberry used GeoCue software to produce intensity imagery and raster stereo models from the source lidar for use in lidargrammetry techniques. Dewberry then produced full point cloud intensity imagery, bare earth ground models, density models, and slope models. These files were ingested into eCognition software, segmented into polygons, and training samples were created to identify water. eCognition used the training samples and defined parameters to identify water segments throughout the project area. Water segments were then reviewed for completeness, separated into project defined feature classes, merged, and smoothed. Elevations derived from a bare earth lidar terrain were applied to each feature for 3D attribution. The delineation of lakes and ponds and tidal waters, or other water bodies at a constant elevation, was achieved using eCognition software. Lidargrammetry was used to monotonically collect streams and rivers, or features that have gradient 3D elevations. All breaklines were collected according to specifications for the project.





Process step
When the process occurred 2017-09-01
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.





Distribution 

Distribution format
*Name Raster Dataset


Metadata Details 

Metadata language English (UNITED STATES)
Metadata character set  utf8 - 8 bit UCS Transfer Format


Scope of the data described by the metadata  dataset
Scope name* dataset


Last update 2017-10-01


ArcGIS metadata properties
Metadata format ArcGIS 1.0


Created in ArcGIS for the item 2018-04-26 07:57:43
Last modified in ArcGIS for the item 2018-04-26 08:38:49


Automatic updates
Last update 2018-04-26 08:38:49


Metadata Contacts 

Metadata contact
Individual's name Bill VanSickle
Organization's name St. Johns River Water Management District
Contact's position Project Manager
Contact's role  point of contact


Contact information
Phone
Voice (386) 329-4500

Address
Type both
Delivery point 4049 Reid Street, P.O. Box 1429
City Palatka
Administrative area Fl
Postal code 32178-1429
Country US
e-mail addressbvansickle@sjrwmd.com



Thumbnail and Enclosures 

Thumbnail

Enclosure
Enclosure type  File
Description of enclosure original metadata
Original metadata document, which was translated yes
Source metadata format fgdc

FGDC Metadata (read-only) 

Identification 

Citation
Citation Information
OriginatorSt. Johns River Water Management District
Publication Date2017-10
Publication TimeUnknown
Title
Hydro-Flattened Digital Elevation Models (DEMs)
Geospatial Data Presentation FormElevation Data

Description
Abstract
                            Digital Aerial Solutions LLC collected 185.5 square miles in the City of Palm Coast in Florida. 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:  1-Unclassified, 2-Ground, 7-Low Noise, 9-Water, 10-Ignored Ground due to breakline proximity, 17- Overpasses and Bridges, 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 FDEM statewide tiling scheme with each tile covering an area of 5,000 ft by 5,000 ft.  A total of 161 LAS tiles and 161 DEM tiles were produced for the entire project.
                          
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.
                          
Supplemental Information
                            A complete description of this dataset is available in the Final Project Report submitted to St. Johns River Water Management District.
                          
Time Period of Content
Time Period Information
Range of Dates/Times
Beginning Date2017-03-28
Ending Date2017-03-29
Currentness Reference
                            ground condition
                          
Status
ProgressComplete
Maintenance and Update FrequencyAs needed

Spatial Domain
Bounding Coordinates
West Bounding Coordinate-81.38147800
East Bounding Coordinate-81.14499762
North Bounding Coordinate29.65638572
South Bounding Coordinate29.40842538

Keywords
Theme
Theme Keyword ThesaurusNone
Theme KeywordDTM
Theme KeywordElevation
Theme KeywordLidar
Theme KeywordLAS
Theme KeywordDEM
Theme KeywordHydro Flattened
Theme KeywordBreaklines

Place
Place Keyword ThesaurusNone
Place KeywordFlorida
Place KeywordCity of Palm Coast
Place KeywordUSA

Access Constraints
                        None
                      
Use Constraints
                        This data was produced for the St. Johns River Water Management District according to specific project requirements.  This information is provided "as is".   Further documentation of this data can be obtained by contacting: St. Johns River Water Management District, 4049 Reid Street, P.O. Box 1429, Palatka, Fl 32178-1429.  Telephone (386) 329-4500.
                      
Point of Contact
Contact Information
Contact Organization Primary
Contact OrganizationSt. Johns River Water Management District
Contact PositionProject Manager
Contact Address
Address Typemailing and physical address
Address4049 Reid Street, P.O. Box 1429
CityPalatka
State or ProvinceFl
Postal Code32178-1429
CountryUNITED STATES

Contact Voice Telephone(386) 329-4500
Contact Electronic Mail Addressbvansickle@sjrwmd.com

Native Data Set Environment
Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.4.1

Data Quality 

Logical Consistency Report
                        Data covers the project boundary.
                      
Completeness Report
                        A visual qualitative assessment was performed to ensure data completeness and full tiles. No void or missing data exists.
                      
Positional Accuracy
Horizontal Positional Accuracy
Horizontal Positional Accuracy Report
                                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 Horizontal Positional Accuracy Assessment
Horizontal Positional Accuracy Value1.81 ft (55.1 cm)
Horizontal Positional Accuracy Explanation
                                    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.   

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. Four (4) 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 = 0.67 ft (20.4 cm) and RMSEy = 0.80 ft (24.4 cm) which equates to +/- 1.81 ft (55.1 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
Vertical Positional Accuracy Report
                                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 36 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 (26 checkpoints), including bare earth, open terrain, and urban terrain, and vegetated terrain (10 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.
                              
Quantitative Vertical Positional Accuracy Assessment
Vertical Positional Accuracy Value0.28 ft (8.5 cm)
Vertical Positional Accuracy Explanation
                                    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 =0.14 ft (4.2 cm), equating to +/-  0.28 ft (8.5 cm) at 95% confidence level.
                                  
Quantitative Vertical Positional Accuracy Assessment
Vertical Positional Accuracy Value0.35 ft (10.7 cm)
Vertical Positional Accuracy Explanation
                                    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 +/- 0.35 ft(10.7 cm) at the 95th percentile.
                                  
Lineage
Process Step
Process Description
                                Data for St. Johns River Water Management District QL2 Lidar Project was acquired by Digital Aerial Solutions LLC.

The project area included approximately 185.5 contiguous square miles or 480.44 square kilometers for the City of Palm Coast in Florida.
Lidar sensor data were collected with the Leica ALS80 HP lidar system.  The data was delivered in NAD83(2011) State Plane Florida East, U.S. Survey Feet and NAVD88 (Geoid12B), U.S. Survey Feet. 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.
                              
Process Date2017-03


Process Step
Process 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)
                              
Process Date2017-06


Process Step
Process Description
                                Dewberry used GeoCue software to produce intensity imagery and raster stereo models from the source lidar for use in lidargrammetry techniques.  Dewberry then produced full point cloud intensity imagery, bare earth ground models, density models, and slope models.  These files were ingested into eCognition software, segmented into polygons, and training samples were created to identify water.  eCognition used the training samples and defined parameters to identify water segments throughout the project area.  Water segments were then reviewed for completeness, separated into project defined feature classes, merged, and smoothed.  Elevations derived from a bare earth lidar terrain were applied to each feature for 3D attribution. 

The delineation of lakes and ponds and tidal waters, or other water bodies at a constant elevation, was achieved using eCognition software. Lidargrammetry was used to monotonically collect streams and rivers, or features that have gradient 3D elevations.  All breaklines were collected according to specifications for the project.
                              
Process Date2017-06


Process Step
Process 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 Date2017-09


Process Step
Process 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 Date2017-10


Process Step
Process 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 Date2017-09


Process Step
Process Description
                                Class 2, ground, and Class 8, model key points, lidar points are exported from the LAS files into an Arc Geodatabase (GDB) in multipoint format.  The 3D breaklines,  Inland Lakes and Ponds and Streams and Tidal 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
Tidal : Hard Replace
                              
Process Date2017-09


Process Step
Process 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 Date2017-10


Process Step
Process 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 Date2017-10


Spatial Data Organization 

Direct Spatial Reference MethodRaster


Raster Object Information
Raster Object TypeGrid Cell
Row Count2000
Column Count2000
Vertical Count1

Spatial Reference 

Horizontal Coordinate System Definition
Planar
Planar Coordinate Information
Planar Coordinate Encoding Methodcoordinate pair
Coordinate Representation
Abscissa Resolution2.5
Ordinate Resolution2.5
Planar Distance UnitsU.S. Survey Feet

Geodetic Model
Horizontal Datum NameNorth American Datum of 1983(2011)
Ellipsoid NameGeodetic Reference System 80
Semi-major Axis6378137.000000
Denominator of Flattening Ratio298.257222

Vertical Coordinate System Definition
Altitude System Definition
Altitude Datum NameNorth American Vertical Datum of 1988 (Geoid 12B)
Altitude Resolution0.000100
Altitude Distance UnitsU.S. Survey Feet
Altitude Encoding MethodExplicit elevation coordinate included with horizontal coordinates

Metadata Reference 

Metadata Date2017-10
Metadata Contact
Contact Information
Contact Organization Primary
Contact OrganizationSt. Johns River Water Management District
Contact PersonBill VanSickle
Contact PositionProject Manager
Contact Address
Address Typemailing and physical address
Address4049 Reid Street, P.O. Box 1429
CityPalatka
State or ProvinceFl
Postal Code32178-1429
CountryUNITED STATES

Contact Voice Telephone(386) 329-4500
Contact Electronic Mail Addressbvansickle@sjrwmd.com

Metadata Standard NameFGDC Content Standards for Digital Geospatial Metadata
Metadata Standard VersionFGDC-STD-001-1998
Metadata Time Conventionlocal time


Metadata Extensions
Online Linkagehttp://www.esri.com/metadata/esriprof80.html
Profile NameESRI Metadata Profile