Issues and Answers in Quality
Control of LIDAR DEMs for
North Carolina DFIRMs
Gary W. Thompson, RLS
North Carolina Geodetic Survey
David F. Maune, Ph.D., C.P.
Dewberry & Davis LLC, Fairfax, VA
Hurricane Floyd — 1999
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Revealed limitations in the State’s flood
hazard data and maps
Many maps compiled in the 1970s by
approximate methods; no detailed H&H
Most of NC needed to be remapped
digitally, consistent with FEMA’s Map
Modernization Plan
Over 50 counties needed re-mapping
immediately with new DFIRMs
DFIRM Components
Base
+
=
Topography
+
Flood Data
DFIRM
Cooperating Technical State (CTS)
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North Carolina, FEMA’s first CTS, is
responsible for:
 Re-surveying the State
 Conducting flood hazard analyses
 Producing updated DFIRMs
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North Carolina Geodetic Survey (NCGS)
serves as the State’s technical lead
Dewberry & Davis LLC serves as FEMA’s
Map Coordination Contractor (MCC)
Phases I, II and III
Photogrammetry or LIDAR?
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The North Carolina advertisement did
not specify technologies to be used
Focus was on high-resolution and
high-accuracy digital elevation data
suitable for semi-automated H&H
modeling
All firms proposed using LIDAR to
generate the TINs and DEMs; but some
proposed using photogrammetry to
generate breaklines
Winning Teams
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Watershed Concepts team includes:
 EarthData International (LIDAR)
 ESP Associates (ground surveying)
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Greenhorne & O’Mara team includes:
 3Di EagleScan (LIDAR)
 McKim & Creed (ground surveying)
 Hobbs, Upchurch & Assoc. (ground
surveying)
Delivery Order No. 1
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Task 1: LIDAR Data Acquisition
 Vertical RMSE = 20 cm in coastal areas
and 25 cm inland (equivalent contour
interval of 2.16’ and 2.70’), the highest
accuracy realistically achievable
 This was a compromise from FEMA’s
15-cm LIDAR standard, considered
unrealistic based on prior studies
 Daily calibration at local test site
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Task 2: Generation of Bare-Earth ASCII
files (randomly spaced)
LIDAR Laser Sensor
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Laser scanner with
mirror measures scan
angles and distances
for up to 50,000
pulses per second
Airborne GPS
measures position
Inertial Measuring
Unit (IMU) measures
roll, pitch, heading
Record first/last
returns
Issue: How best to perform
LIDAR system calibration
Courtesy of EarthData International
Issue: How best to post-process LIDAR
(These are “raw” images)
Courtesy U.S. Army Topographic Engineering Center
Bare-earth data (post processed for
vegetation/building removal)
Courtesy U.S. Army Topographic Engineering Center
Delivery Order No. 1 (continued)
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Task 3: Generation of Triangulated
Irregular Network (TIN) and breaklines
Task 4: Development of 5m x 5m DEMs
in ESRI GRID Float Format
Task 5: Development of DEMs in Three
Additional File Formats
Task 6: Preparation of Project Report
Task 7: Production of Optional Digital
Orthophoto Images
Digital Elevation Models (DEMs)
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DEMs typically have
uniform “post spacing”
where x/y coordinates
are evenly divisible by
5m, 10m, 30m, etc.
Interpolated from TIN
data; e.g., LIDAR.
Neither TIN nor DEM
points are clearly
defined on the ground.
TINs — Superior for 3-D Surface
Modeling; e.g., H&H Modeling
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A TIN is a set of adjacent,
non-overlapping triangles
computed from irregularly
spaced mass points with x,y
coordinates and z values, plus
breaklines.
Mass points can come from
LIDAR or other source.
Best breaklines come from
photogrammetry, then digital
orthophotos.
Hydraulic Models Require
“Representative” Cross Sections
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Cross sections are carefully
selected to be representative
of reaches that are as long as
possible, without permitting
excessive conveyance change
between sections.
Typically between 500’ and
2,500’ apart.
In addition to surveyed cross
sections, others can be “cut”
from the LIDAR data.
Issue: How best to generate
Cross Sections
Issue: How best to generate
Breaklines
Watershed Concepts
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Surveyed cross
sections at bridges
Hydro-enforced
stream centerlines
Digital orthophoto
breaklines at stream
shorelines
LIDAR models
stream banks and
overbank areas
Greenhorne & O’Mara
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Surveyed cross
sections at bridges
Hydro-enforced
stream centerlines
Photogrammetric
breaklines at tops
and bottoms of
stream banks
LIDAR models
overbank areas
Issue: How best to handle
“obscured areas” and “artifacts”
Issue: How best to compute
RMSEz of bare-earth TINs/DEMs
Since TIN/DEM points not clearly defined:
 Survey a minimum of 20 checkpoints in
all 5 major land cover categories
representative of the floodplain
 Choose checkpoints on flat or uniformly
sloping terrain; interpolate LIDAR points
 Use no checkpoints in vegetation known
to be too dense for LIDAR penetration
 Discard 5% of “outliers”
Issue: Check points in such
areas skew RMSE calculations
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LIDAR has fewer
areas than
photogrammetry
where the terrain is
obscured.
One “bad” checkpoint
in such areas will
over-ride 1,000
“good” checkpoints
elsewhere, and thus
skew the results.
LIDAR Advantages Compared
with Photogrammetry
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LIDAR needs only a single line-of-sight
to measure through/between trees
High-altitude LIDAR data are more
accurate than from photogrammetry
LIDAR generates higher-density
TINs/DEMs at lower costs
LIDAR acquires data both day and
night (but not through clouds)
LIDAR Disadvantages Compared
with Photogrammetry
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LIDAR returns on water are unreliable
LIDAR is ill-suited for breaklines; e.g.,
5-m point spacing could “jump” across a
breakline
LIDAR is new technology; standards
have not yet been developed
Contour lines are not as smooth
Streams are not automatically hydroenforced, must be done manually
LIDAR contours not hydro-enforced
(same problem with TINs/DEMs)
Conclusions
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This project will demonstrate the
do’s and don’ts of LIDAR for H&H
modeling and serve as a model for
years to come
This project will also be used to
update FEMA standards
Issues and Answers in Quality
Control of LIDAR DEMs for
North Carolina DFIRMs
QUESTIONS
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