50025
2004 Southwest Florida Water Management District Lidar: Pasco District
swfwmd_pasco_m62_metadata
Data Set
Published / External
49401
Lidar - partner (no harvest)
Project
Completed
2005-05-10
This metadata record describes the ortho & lidar mapping of Pasco County, FL. The mapping consists of lidar data
collected using a Leica ALS-40 Lidar Sensor, contour generation, and production of natural color orthophotography with a 30-cm
GSD using imagery collected with a Leica ADS-40 Aerial Digital Camera.
Original contact information:
Contact Name: Steve Dicks
Contact Org: Southwest Florida Water Management District
Phone: 352-796-7211
The purpose of this mapping project is to create and deliver digital terrain models (DTM), capable of generating one-foot
contours and to produce orthophotography at a 200' scale.
10669
The Pasco County Lidar Evaluation Report may be viewed at:
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/62/supplemental/index.html
Theme
ISO 19115 Topic Category
elevation
Theme
EDI Thesaurus
Aerial Photography
Theme
EDI Thesaurus
Bathymetry/Topography
Theme
EDI Thesaurus
Contours
Theme
EDI Thesaurus
Digital Orthophotography
Theme
EDI Thesaurus
Digital Terrain Model (DTM)
Theme
EDI Thesaurus
LIDAR
Spatial
Geographic Names Information System
Florida
Spatial
Geographic Names Information System
Gulf Coast
Spatial
Geographic Names Information System
Pasco County
Spatial
Geographic Names Information System
Southwest Florida
Spatial
Geographic Names Information System
United States
Office for Coastal Management
Charleston
SC
Data Set
Unknown
Any conclusions drawn for the analysis of this information are not the responsibility of the Office for Coastal Management or its partners.
Data Steward
2005-05-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Distributor
2005-05-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Metadata Contact
2005-05-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Point of Contact
2005-05-10
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Publication Date
-82.815369
-82.04915
28.48311
28.166952
Range
2004-01-23
2004-05-15
Yes
Unclassified
This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer;
None
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.
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=62
Customized Download
Create custom data files by choosing data area, product type, map projection, file format, datum, etc.
https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/62/index.html
Bulk Download
Simple download of data files.
https://coast.noaa.gov
Online Resource
https://coast.noaa.gov/dataviewer
Online Resource
2017-03-20
Date that the source FGDC record was last modified.
2017-11-14
Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.
2018-02-08
Partial upload of Positional Accuracy fields only.
2018-03-13
Partial upload to move data access links to Distribution Info.
The generated contours were NOT produced to be fully compliant with NSSDA accuracy standards for 2'
contours. Contours were generated from lidar DTM as is without the benefit of photogrammetric breakline support. Lidar elevation
data meets National Map Accuracy Standards. The digital orthophotography meets national mapping accuracy standards for 200 scale
product.
The digital orthophotos fully comply with NMAS standards for production of orthophotos
at a horizontal natural ratio of 1 to 2,400 with a ground pixel resolution of 1 foot. Compiled to meet 1.1 m horizontal
accuracy at the 95% confidence level.
The digital elevation model is fully compliant with National Standard for Spatial Data
Accuracy (NSSDA) published by the Federal Geographic Data Committee (FGDC) in 1998. The NSSDA uses root-mean-square error
(RMSE) to estimate positional accuracy. RMSE is the square root of the average of the set of squared differences between
data set coordinate values and coordinate values from an independent source of higher accuracy for identical points. Accuracy
is reported in ground distances at the 95% confidence level. Accuracy reported at the 95% confidence level means that 95% of
the positions in the data set will have an error with respect to true ground position that is equal to or smaller than the
reported accuracy value. The reported accuracy value reflects all uncertainties, including those introduced by geodetic
control coordinates, compilation, and final computation of ground coordinate values in the product.
RMSE for the Lidar data is 11.064 cm.
Cloud Cover: 0
The following software is used for validation of the
1. Aerotriangulation - ISTAR Processing
2. DTM data - Z/I Imaging SSK
3. Digital Orthophotography - Z/I Imaging OrthoPro
Compliance with the accuracy standard was ensured by the placement of GPS ground control prior to the
acquisition of aerial photography. The following checks were performed.
1. The ground control and airborne GPS data stream were validated through a fully analytical bundle aerotriangulation adjustment.
The residuals of the adjustment met the required standards for accuracy which are 1 part in 10,000 of the flying height for the
horizontal position (X and Y) and 1 part in 9,000 or better of the flying height in elevation (Z).
2. The DTM (Digital Terrain Model) data were checked against the project control. The technician visited and confirmed the accuracy
of the project mass points during initial processing.
3. Digital orthophotography was validated through an inspection of edge matching and visual inspection for image quality.
Digital Aerial Photography of Pasco County, FL
2004-02-08
Range
2004-02-03
2004-02-08
14400
The digital aerial photographic mission was composed of a total of 2 lifts of flight lines. Photography
was obtained at an altitude of 9,450 feet above mean terrain. Digital photography was recorded in conjunction with airborne GPS;
the stationary GPS receiver was positioned over a control point located at the airport. Recorded digital imagery was shipped
via external hard drive to the production facility for processing.
| Source Geospatial Form: Profile | Type of Source Media: Firewire Drive
Lidar Acquisition of Pasco County, FL
2004-05-15
Range
2004-01-23
2004-05-15
The lidar acquisition for Pasco County consisted of 2 lifts of flight lines acquired in 3 sorties using
the Leica ALS40 sensor. The third sortie was used to fill gaps in the data coverage from the first two sorties. The data was
acquired at a flying height of 6,000 feet AMT with a scan rate of 13 Hz and a 25 degree field of view. Approximately 3.04
billion raw lidar points were collected at a nominal 2 meter post spacing.
| Source Geospatial Form: Profile | Type of Source Media: Firewire Drive
Report of Survey - SWFWMD, Pasco County, FL
2004-04-21
Discrete
2004-04-28
1200
Kevin Chappell, a Florida PSM, under contract to EarthData International established 10 photo identifiable
ground control points and 6 National Spatial Reference System (NSRS) stations after aerial imagery acquisition. The points
were surveyed using GPS for both vertical and horizontal coordinate values. Ground control references Florida West State
Plane NAD83, NAVD88 both in Meters.
| Source Geospatial Form: Diagram | Type of Source Media: Electronic mail system
1
New ground control was established to control and orient the photography, and included only photo-identifiable
features. The ground control network and airborne GPS data was integrated into a rigid network through the completion of a
fully analytical bundle aerotriangulation adjustment.
1. The digital aerial photo data was ingested into the ISTAR processing system by uploading the data from portable hard drives.
2. The coverage of the imagery was checked for gaps and a directory tree structure for the project was established on one of
the workstations. This project was then accessed by other workstations through the network. The criteria used for establishment
of the directory structure and file naming conventions accessed through the network avoids confusion or errors due to
inconsistencies in digital data. The project area was reviewed against the client-approved boundary. The technician verified
that the datum and units of measurement for the supplied control were consistent with the project requirements.
3. The photogrammetric technician performed an automatic triangulation of the data using the ISTAR processing system. The
aerotriangulation adjustment merged the airborne GPS, IMU, and ground control data into a project-wide network.
4. While ground control points (GCPs) were used, reliance on the GPS-/IMU-derived orientation parameters required significantly
fewer GCPs than are typically used in aerotriangulation.
5. The adjustment was performed for each sortie and then multiple sorties were merged to produce a project-wide adjustment.
6. The aerotriangulation component of the ISTAR suite utilized the airborne GPS as a separate control source and held the
IMU (Inertial Measurement Unit) parameters rigidly.
7. The accuracy of the final solution was verified by running the final adjustment, placing no constraints on any quality
control points. The RMSE values for these points must fall within the tolerances above for the solution to be acceptable.
2004-09-30T00:00:00
2
EarthData has developed a unique method for processing lidar data to identify and remove elevation points
falling on vegetation, buildings, and other aboveground structures. The algorithms for filtering data were utilized within
EarthData's proprietary software and commercial software written by TerraSolid. This software suite of tools provides efficient
processing for small to large-scale, projects and has been incorporated into ISO 9001 compliant production work flows. The
following is a step-by-step breakdown of the process.
1. Using the lidar data set provided by EarthData, the technician performs calibrations on the data set.
2. Using the lidar data set provided by EarthData, the technician performed a visual inspection of the data to verify that the
flight lines overlap correctly. The technician also verified that there were no voids, and that the data covered the project
limits. The technician then selected a series of areas from the data set and inspected them where adjacent flight lines
overlapped. These overlapping areas were merged and a process which utilizes 3-D Analyst and EarthData's proprietary software
was run to detect and color code the differences in elevation values and profiles. The technician reviewed these plots and
located the areas that contained systematic errors or distortions that were introduced by the lidar sensor.
3. Systematic distortions highlighted in step 2 were removed and the data was re-inspected. Corrections and adjustments can
involve the application of angular deflection or compensation for curvature of the ground surface that can be introduced by
crossing from one type of land cover to another.
4. The lidar data for each flight line was trimmed in batch for the removal of the overlap areas between flight lines. The data
was checked against a control network to ensure that vertical requirements were maintained. Conversion to the client-specified
datum and projections were then completed. The lidar flight line data sets were then segmented into adjoining tiles for batch
processing and data management.
5. The initial batch-processing run removed 95% of points falling on vegetation. The algorithm also removed the points that
fell on the edge of hard features such as structures, elevated roadways and bridges.
6. The operator interactively processed the data using lidar editing tools. During this final phase the operator generated
a TIN based on a desired thematic layer to evaluate the automated classification performed in step 5. This allowed the operator
to quickly re-classify points from one layer to another and recreate the TIN surface to see the effects of edits.
Geo-referenced images were toggled on or off to aid the operator in identifying problem areas. The data was also examined with
an automated profiling tool to aid the operator in the reclassification.
7. The data were separated into a bare-earth DEM. A grid-fill program was used to fill data voids caused by reflective objects
such as buildings and vegetation. The final DEM was written to an ASCII XYZ and LAS format.
8. The reflective surface data were also delivered in ASCII XYZ and LAS format.
9. Final TIN files are created and delivered.
2004-08-17T00:00:00
3
This process describes the method used to compile hydro-breaklines to support H&H modeling efforts. The
technical method used to produce hydro-breaklines for use in this project only included water features and they should not
be confused with traditional stereo-graphic or field survey derived breaklines. Watershed Concepts and EarthData utilized
techniques developed for FEMA floodmap modernization projects to synthesize 3D break lines using digital orthophotos and lidar
data.
1. For larger streams (widths greater than 50 feet), breaklines were collected on the left and right water edge lines.
The 2D lines defining streams and other water bodies were manually digitized into ArcView shape file format from the ADS-40
digital imagery. Flat water bodies such as ponds were collected by examining points near the edge of water, were a low point
could be quickly identified. This allowed the operators to draw an even-elevation breakline at that elevation around the water
body's perimeter.
2. A bounding polygon, created from the edge of bank lines, was used to remove all lidar points from within the channels of
streams and bodies of water. This step ensures that the lidar bare-earth point files match the breaklines.
3. The elevation component of the 3D streamlines (breaklines) was derived from the lowest adjacent bare earth lidar point and
was adjusted to ensure that the streams flow downstream. The best elevation that can be derived for the 3D streamlines will
be the water surface elevation on the date that the lidar data was acquired.
4. Automatic processes assigned elevations to the vertices of the centerline based on surrounding lidar points. The lines were
then smoothed to ensure a continuous downhill flow. Edge-of-bank vertices were adjusted vertically to match the stream
centerline vertices.
5. The new 3D lines were then viewed in profile to correct any anomalous vertices or remove errant points from the lidar DTM,
which cause unrealistic "spikes" or "dips" in the breaklines.
6. For this project, hydro breaklines were generated in the matter described above for all streams and water bodies.
a) A 2000 to identify any quality issues.
b) An automated routine was run to check the data for closure of water bodies.
c) An evaporation routine was run to remove lidar points from water bodies.
d) A final routine was run to check the generate TINs for anomalies including outside township/range boundary and elevation
extremes.
7. New TINs were then created from the remaining lidar points and newly created breaklines.
8. The breakline data set was then put into an ESRI shape file format
9. The 1 foot contours were generated in Microstation (using 2 foot specifications) with an overlay software package called
TerraSolid. Within TerraSolid, the module Terramodeler was utilized to first create the tin and then a color relief was created
to view for any irregularities before the contour generator was run. The contours were checked for accuracy over the DTM and
then the Index contours were annotated. At this point the technician identified any areas of heavy tree coverage by collecting
obscure shapes. Any contours that were found within these shapes are coded as obscure. The data set was viewed over the orthos
before the final conversion. The contours were then converted to Arc/Info where final QC AMLs were run to verify that no
contours were crossing. The contours were delivered in ESRI .shp format as a merged file.
Due to the nature of the breaklines collected in accordance with FEMA guidelines, the contours do not meet any specified
accuracy requirement and are delivered as is.
2005-04-15T00:00:00
4
The digital orthophotography was produced in natural color at a natural ratio of 1 to 2,400 with a 1 ft
pixel resolution. A step-by-step breakdown of the digital orthophoto production process follows.
1. Digital image swath files were visually checked for image quality on the networked ISTAR processing farm.
2. The digital image files were loaded onto the digital orthophoto production workstation. The following information was then
loaded onto the workstation. - The camera parameters and flight line direction - Ground control and pass point locations - The
exterior orientation parameters from the aerotriangulation process - ASCII file containing the corner coordinates of the
orthophotos - The digital elevation model. - Project-specific requirements such as final tile size and resolution. -Orientation
parameters developed from the aerotriangulation solution. A coordinate transformation based on the camera calibration fiducial
coordinates was then undertaken. This transformation allowed the conversion of every measured element of the images to a
sample/line location. Each pixel in an image was then referenced by sample and line (its horizontal and vertical position)
and matched to project control.
3. The newly re-sected image was visually checked for pixel drop-out and/or other artifacts that may degrade the final
orthophoto image.
4. DTM data were imported and written to the correct subdirectory on disk.
5. The DTM file was re-inspected for missing or erroneous data points.
6. A complete differential rectification was carried out using a cubic convolution algorithm that removed image displacement
due to topographic relief, tip and tilt of the aircraft at the moment of exposure, and radial distortion within the camera.
Each final orthophoto was produced at a natural scale of 1 to 2,400 with a 1ft pixel resolution. At this point in the process,
the digital orthophotos covered the full aerial frame.
7. Each digital orthophoto image was visually checked for accuracy on the workstation screen. Selected control points
(control panels or photo-identifiable points) that are visible on the original film were visited on the screen, and the X
and Y coordinates of the location of the panel or photo-identifiable point were measured. This information was cross-referenced
with the X and Y information provided by the original ground survey. If the orthophoto did not meet or exceed NMAS standards,
the rectification was regenerated. The digital orthophotos were then edge-matched using proprietary software that runs in
Z/I Imaging OrthoPro software package. Adjoining images were displayed in alternating colors of red and cyan. In areas of
exact overlap, the image appears in gray-scale rendition. Offsets were colored red or cyan, depending on the angle of
displacement. The operator panned down each overlap line at a map scale to inspect the overlap area. Any offset exceeding
accuracy standards was re-rectified after the DTM and AT information was rechecked.
2004-09-15T00:00:00
5
8. Once the orthos were inspected and approved for accuracy, the files were copied to the network and downloaded by the ortho
finishing department. This production unit was charged with radiometrically correcting the orthophotos prior to completing the
mosaicking and clipping of the final tiles. The image processing technician performed a histogram analysis of several images
that contained different land forms (urban, agricultural, forested, etc.) and established a histogram that best preserves
detail in highlight and shadow areas. EarthData International has developed a proprietary piece of software called
"Image Dodging." This radiometric correction algorithm was utilized in batch and interactive modes. Used in this fashion,
this routine eliminated density changes due to sun angle and changes in flight direction. A block of images were processed
through image dodging, in batch mode and displayed using Z/I Imaging OrthoPro software. At this point the images have been
balanced internally, but there are global differences in color and brightness that were adjusted interactively. The
technician assigned correction values for each orthophoto then displayed the corrected files to assess the effectiveness
of the adjustment. This process was repeated until the match was considered near seamless. The files then were returned
to digital orthophoto production to mosaic the images.
9. The processed images were mosaicked using the Z/I Imaging software. The mosaic lines were set up interactively by the
technician and were placed in areas that avoided buildings, bridges, elevated roadways, or other features that would
highlight the mosaic lines. File names were assigned.
10.The finishing department performed final visual checks for orthophoto image quality. The images were inspected using
Adobe Photoshop, which enabled the technician to remove dust and lint from the image files interactively. Depending on
the size and location of the flaw, Photoshop provided several tools to remove the flaw. Interactive removal of dust was
accomplished at high magnification so that repairs are invisible.
11.The final orthophoto images were written out into GeoTIFF format.
2004-09-15T00:00:00
6
The NOAA Office for Coastal Management (OCM) received the files in LAS format. The files contained Lidar
elevation measurements. The data was in Florida State Plane Projection and NAVD88 vertical datum. OCM performed the
following processing to the data to make it available within the LDART Retrieval Tool (LDART):
1. The data were converted from Florida State Plane West coordinates to geographic coordinates.
2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid03.
3. The LAS data were sorted by latitude and the headers were updated.
2008-01-25T00:00:00
gov.noaa.nmfs.inport:50025
Anne Ball
2017-11-15T15:23:49
SysAdmin InPortAdmin
2022-08-09T17:11:37
2022-03-16
OCM Partners
OCMP
1002
Public
No
2022-03-16
1 Year
2023-03-16