- 2004-09-30T00:00:00 - New ground control was established to control and orient the photography, and included
both photo-identifiable features and artificial targets. 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 original aerial film
was scanned at a resolution of 1,210 DPI. The scans were produced using Z/I Imaging
PhotoScan flatbed metric scanners. Each unit has a positional accuracy of 1.5 microns
and a radiometric resolution of 1,024 gray levels for each of three color layers.
2. The raster scans were given a preliminary visual check on the scanner workstation
to ensure that the raster file size is correct and to verify that the tone and contrast
were acceptable. 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 defined using the relevant camera
information that was obtained from the USGS camera calibration report for the aerial
camera and the date of photography. The raster files were rotated to the correct orientation
for mensuration on the softcopy workstation. The rotation of the raster files was
necessary to accommodate different flight directions from one strip to the next. 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 interior orientation for the frames in the project area. Thesoftcopy
systems that were used by the technicians have the ability to set up predefined fiducial
templates for the aerial camera(s) used for the project. Using the template that was
predefined in the interior orientation setup, the software identified and measured
the eight fiducial positions for all the frames. Upon completion, the results were
reviewed against the tolerance threshold. Any problems that occurred during the automatic
interior orientation would cause the software to reject the frame and identify it
as a potential problem. The operator then had the option to measure the fiducials
manually. 4. The operator launched the point selection routine which automatically
selected pass and tie points by an autocorrelation process. The correlation tool that
is part of the routine identified the same point of contrast between multiple images
in the Von Gruber locations. The interpolation tool can be adjusted by the operator
depending on the type of land cover in the triangulation block. Factors that influence
the settings include the amount of contrast and the sharpness of features present
on the photography. A preliminary adjustment was run to identify pass points that
had high residuals. This process was accomplished for each flight line or partial
flight line to ensure that the network has sufficient levels of accuracy. The points
were visited and the cause for any inaccuracy was identified and rectified. This process
also identified any gaps where the point selection routine failed to establish a point.
The operator interactively set any missing points. 5. The control and pass point measurement
data was run through a final adjustment on the Z/I SSK PhotoT workstations. The PhotoT
program created a results file with the RMSE results for all points within the block
and their relation to one another. The photogrammetrist performing the adjustments
used their experience to determine what course of action to take for any point falling
outside specifications. 6. The bundle adjustment was run through the PhotoT software
several times. The photogrammetrist increased the accuracy parameters for each subsequent
iteration so, when the final adjustment was run, the RMSE for the project met the
accuracy of 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). The errors
were expressed as a natural ratio of the flying height utilizing a one-sigma (95%)
confidence level. 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.
8. The final adjustment generates three files. The .txt file has all the results from
the adjustment with the RMSE values for each point measured. The .XYZ file contains
the adjusted X, Y, Z,coordinates for all the measured points and the .PHT file contains
the exterior orientation parameters of each exposure station.
- 2005-02-01T00:00:00 - 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 dataset 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 layers 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. 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. 7. The reflective surface
data were also delivered in ASCII XYZ and LAS format. 8. Final TIN files are created
- 2005-02-01T00:00:00 - This process describes the method used to compile breaklines to support the lidar
digital elevation model data. Around the perimeter of the lidardata set to complete
the surface model, breaklines were photogrammetrically derived . The following step-by-step
procedures were utilized for breakline development. The breakline file contains three
dimensionally accurate line strings describing topographical features. The relationship
of lidar points to breaklines will vary depending on the complexity and severity of
the terrain. Breaklines were collected where necessary to support the final product.
Examples of some such locations include along the edges of roads, stream banks and
centerlines, ridges, and other features where the slope of the terrain changes. 1.
Using the imagery provided by EarthData Aviations, breakline data was captured in
the MicroStation environment, which allowed the photogrammetrist to see graphically
where each lidar X, Y, and Z point and any breaklines fall in relation to each other.
This unique approach allowed for interactive editing of the breakline by the photogrammetrist.
The technician generated a set of temporary contours for the stereo model in the ZI
work environment to provide further guidance on the breakline placement. The technician
added and/or repositioned breaklines to improve the accuracy as required. Once these
processes were completed, the temporary guidance contours were deleted, and the data
were passed to the editing department for quality control and formatting. 4. The breakline
data set was then put into an ESRI shape file format 5. The 1 foot contours were generated
in Microstation (using 2 foot specifications) with an overlay software package called
TerraSolid. Within TerraSolid, the module Terramodler 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 do not meet Map Accuracy Standards and are coded as obscure.
The dataset 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 shp format as a merged file.
- 2004-09-01T00:00:00 - 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. A representative number of raster image files were
visually checked for image quality on the workstation. 2. The digital image files
were oriented on the digital orthophoto production workstation. The following information
was then loaded onto the workstation. - The camera calibration 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 in a MGE format - 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 plates 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 resected 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 photoidentifiable 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 photoidentifiable 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. 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 were accomplished at high magnification so that repairs are invisible. 11.
The final orthophoto images were written out into TIFF format with the corresponding
georeference files for ESRI platforms.
- 2013-09-19T00:00:00 - The NOAA Coastal Services Center (CSC) received the files in ascii format. The files
contained LiDAR elevation (x,y.z). The data were in state place Florida West (0902,
feet) coordinates and NAVD88 (Geoid03) vertical datum (feet). CSC performed the following
processing for data storage and Digital Coast provisioning purposes: 1. The ascii
files were parsed to LAS format. 2. The LAS files were retiled to a larger geographic
footprint and all points were reclassified to class 2 (ground) 3. The points were
convereted from State Plane Florida West (0902) coordinates to geographic coordinates.
4. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid)
heights using Geoid03. 3. The data were sorted by time. 4. The data were converted
to LAZ format.
- 2013-10-17T00:00:00 - The NOAA National Geophysical Data Center (NGDC) received lidar data files via ftp
transfer from the NOAA Coastal Services Center. The data are currently
being served via NOAA CSC Digital Coast at http://www.csc.noaa.gov/digitalcoast/.
The data can be used to re-populate the system. The data are archived in LAS or LAZ
The LAS format is an industry standard for LiDAR data developed by the American Society
of Photogrammetry and Remote Sensing (ASPRS); LAZ is a loseless compressed version
LAS developed by Martin Isenburg (http://www.laszip.org/). The data are exclusively
in geographic coordinates (either NAD83 or ITRF94). The data are referenced vertically
the ellipsoid (either GRS80 or ITRF94), allowing for the ability to apply the most
up to date geoid model when transforming to orthometric heights.
- Report of Survey - SWFWMD, Citrus County, FL
- Description of Source: Source Contribution: Kevin Chappell, a Florida PSM, under contract to EarthData International
established 53 aerial targets and photo identifiable ground control points prior to
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 Type: electronic mail system
- Temporal extent used:
2004-01-25 to 2004-01-28
- LIDAR Acquisition of Citrus County, FL
- Description of Source: Source Contribution: The LIDAR acquisition for Citrus County consisted of 38 flight
lines acquired in one sortie using the Leica ALS40 sensor. The data was acquired at
a flying height of 5,800 feet AMT with a scan rate of 13 Hz and a 40 degree field
of view. Source Type: Fire wire Drive
- Temporal extent used: