ISO Table View
Alternate Views:
Get Data,
FAQ,
ISO Rubric,
CSW,
HTML,
Components, XML
Metadata Identifier: gov.noaa.csc.maps:2004_FL_SWFWMD_Lake_Hancock_m76
MD_DataIdentification
| 1 |
|
2004 Southwest Florida Water Management District (SWFWMD) Lidar: Lake
Hancock District
|
The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select
areas within Southwest Florida. These data were produced for the Southwest Florida
Water Management District (SWFWMD). This metadata record describes the ortho & LIDAR
mapping of Lake Hancock, in Polk County, FL. The mapping consists of LIDAR data collection,
contour generation, and production of natural color orthophotography with a 1ft pixel
using imagery collected with a Wild RC-30 Aerial Camera.
|
SV_Identification
| 1 |
|
2004 Southwest Florida Water Management District (SWFWMD) Lidar: Lake Hancock District |
|
|
| 1 |
|
EDI Thesaurus |
|
|
| 1 |
|
Geographic Names Information System |
|
|
| 1 |
|
LIDAR Acquisition of Lake Hancock |
|
|
| 1 |
|
Lake Hancock Aerial Photography |
|
|
| 1 |
|
Lidar Final Report |
|
|
| 1 |
|
North American Datum 1983 |
|
|
| 1 |
|
Report of Survey of Lake Hancock/Winter Haven Polk County, FL |
|
|
| 1 |
|
|
|
|
|
resourceProvider |
http://www.epsg-registry.org/export.htm?gml=urn:ogc:def:crs:EPSG::4269 |
| 1 |
|
|
|
Citation URL |
|
|
ftp://ftp.csc.noaa.gov/pub/crs/beachmap/qa_docs/fl/swfwmd/Lake_Hancock_Report_Topographic_Survey.pdf |
| 1 |
NOAA CSC (originator) |
|
DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic
and Atmospheric Administration, U.S. Department of Commerce
|
|
csc.info@noaa.gov |
originator |
|
| 1 |
NOAA CSC (publisher) |
|
DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic
and Atmospheric Administration, U.S. Department of Commerce
|
|
csc.info@noaa.gov |
publisher |
|
| 1 |
NOAA CSC(distributor) |
|
DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic
and Atmospheric Administration, U.S. Department of Commerce
|
|
csc.info@noaa.gov |
distributor |
|
| 1 |
NOAA CSC (processor) |
|
DOC/NOAA/NOS/CSC > Coastal Services Center, National Ocean Service, National Oceanic
and Atmospheric Administration, U.S. Department of Commerce
|
|
csc.info@noaa.gov |
processor |
|
| 1 |
|
|
EarthData Aviation, LLC |
|
|
originator |
|
| 1 |
|
|
EarthData Aviations |
|
|
originator |
|
| 1 |
EPSG Registry |
|
European Petroleum Survey Group |
|
|
publisher |
http://www.epsg-registry.org/ |
| 1 |
|
|
Kevin J. Chappell, PSM |
|
|
originator |
|
| 1 |
|
Mapping and GIS Section |
Southwest Florida Water Management District |
|
|
pointOfContact |
|
| 1 |
Mike Sutherland(author) |
Mike Sutherland |
DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department
of Commerce
|
|
mike.sutherland@noaa.gov |
author |
|
| 1 |
Mike Sutherland |
Mike Sutherland |
DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department
of Commerce
|
|
mike.sutherland@noaa.gov |
distributor |
|
| 1 |
|
Pamela Grothe |
DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department
of Commerce
|
|
|
processor |
|
| 3 |
|
Raquel Charrois |
EarthData International |
Project Manager |
metadata@earthdata.com |
processor |
|
| 1 |
|
|
Southwest Florida Water Management District (SWFWMD) |
|
|
originator |
|
| 1 |
|
ftp://ftp.csc.noaa.gov/pub/crs/beachmap/qa_docs/fl/swfwmd/Lake_Hancock_Report_Topographic_Survey.pdf |
Lidar Final Report |
|
information |
| 1 |
|
http://www.epsg-registry.org/ |
European Petroleum Survey Group Geodetic Parameter Registry |
Registry that accesses the EPSG Geodetic Parameter Dataset, which is a structured
dataset of Coordinate Reference Systems and Coordinate Transformations.
|
search |
| 1 |
|
http://www.epsg-registry.org/export.htm?gml=urn:ogc:def:crs:EPSG::4269 |
NAD83 |
Link to Geographic Markup Language (GML) description of reference system. |
information |
| 1 |
|
Ellipsoid in Meters |
| 1 |
|
urn:ogc:def:crs:EPSG::4269 |
|
Bounding Box |
Temporal Extent |
| 1 |
|
|
-081.992800 |
-081.747900 |
28.166600 |
27.892000 |
|
|
| 1 |
|
|
|
|
|
|
2004-04-26 |
2004-04-27 |
| 1 |
|
|
|
|
|
|
|
|
| 1 |
|
|
|
|
|
|
2004-02-02 |
2004-02-03 |
| 1 |
|
-081.992800 |
-081.747900 |
28.166600 |
27.892000 |
| 2 |
|
|
|
| 1 |
|
2004-04-26 |
2004-04-27 |
| 1 |
|
2004-02-02 |
2004-02-03 |
| 1 |
Lidar Use Limitation |
These data depict the elevations at the time of the survey and are only
accurate for that time. 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. Any conclusions
drawn from analysis of this information are not the responsibility of NOAA
or any of its partners. These data are NOT to be used for navigational purposes.
|
| 1 |
Ellipsoid |
Ellipsoid in Meters |
|
| 1 |
NAD83 |
urn:ogc:def:crs:EPSG::4269 |
North American Datum 1983 |
| 1 |
|
Lidar Final Report |
|
crossReference |
| 1 |
|
LIDAR Acquisition of Lake Hancock |
2004-05-01 |
Source Contribution: Aerial Lidar Acquisition. The LIDAR acquisition
for Lake Hancock was acquired in two sorties using the Leica ALS40 sensor. The data
was acquired at a flying height of 6,000 feet AMT with a scan rate of 26 Hz and a
25 degree field of view. Source Type: Fire wire
|
| 1 |
|
Lake Hancock Aerial Photography |
2004-09-02 |
Source Contribution: Aerial Photography. The aerial photographic mission
was composed of a total of 613 exposures in 19 North-South oriented flight lines.
Photography was obtained at an altitude of 4,100 feet above mean terrain. Aerial photography
was exposed in conjunction with airborne GPS; the stationary GPS receiver was positioned
over a control point located at the airport. Aerial photography was exposed on natural
color negative film using Wild RC-30 camera 5086, with 153.277 mm (6 inch) focal length
lens cone number 13112. Photography was exposed on Agfa X-100 film, emulsion number
67663036. Source Type: Filmstrip
|
| 1 |
|
Report of Survey of Lake Hancock/Winter Haven Polk County, FL |
2004-07-23 |
Source Contribution: Ground Control Data. Kevin Chappell, a Florida
PSM, under contract to EarthData International established 27 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
|
| 1 |
|
2004-07-27T00:00:00 |
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. The softcopy
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.
|
| 1 |
|
2004-10-26T00:00:00 |
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 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. 6. The data was 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 was also delivered in ASCII XYZ and
LAS format. 8. Final TIN files are created and delivered.
|
| 1 |
|
2004-12-10T00:00:00 |
This process describes the method used to compile breaklines to support
the lidar digital elevation model data. Around the perimeter of the lidar data 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
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 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.
|
| 1 |
|
2008-01-25T00:00:00 |
The NOAA Coastal Services Center (CSC) received the files in LAS format.
The files contained Lidar intensity and elevation measurements. The data was in Florida
State Plane Projection and NAVD88 vertical datum. CSC 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 Geoid 03. 3. The LAS data were sorted by latitude and the headers were
updated.
|
| 1 |
|
2009-07-20T00:00:00 |
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 format. 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 of 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 to the ellipsoid (either GRS80 or ITRF94), allowing for
the ability to apply the most up to date geoid model when transforming to orthometric
heights.
|
|
