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 l Revealed limitations in the State’s flood hazard data and maps l Many maps compiled in the 1970s by approximate methods; no detailed H&H l Most of NC needed to be remapped digitally, consistent with FEMA’s Map Modernization Plan l Over 50 counties needed re-mapping immediately with new DFIRMs

DFIRM Components DFIRM = Flood Data Base + Topography +

Cooperating Technical State (CTS) l North Carolina, FEMA’s first CTS, is responsible for: 4 Re-surveying the State 4 Conducting flood hazard analyses 4 Producing updated DFIRMs l North Carolina Geodetic Survey (NCGS) serves as the State’s technical lead l Dewberry & Davis LLC serves as FEMA’s Map Coordination Contractor (MCC)

Phases I, II and III

Photogrammetry or LIDAR? l The North Carolina advertisement did not specify technologies to be used l Focus was on high-resolution and high-accuracy digital elevation data suitable for semi-automated H&H modeling l All firms proposed using LIDAR to generate the TINs and DEMs; but some proposed using photogrammetry to generate breaklines

Winning Teams l Watershed Concepts team includes: 4 EarthData International (LIDAR) 4 ESP Associates (ground surveying) l Greenhorne & O’Mara team includes: 4 3Di EagleScan (LIDAR) 4 McKim & Creed (ground surveying) 4 Hobbs, Upchurch & Assoc. (ground surveying)

Delivery Order No. 1 l Task 1: LIDAR Data Acquisition 4 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 4 This was a compromise from FEMA’s 15-cm LIDAR standard, considered unrealistic based on prior studies 4 Daily calibration at local test site l Task 2: Generation of Bare-Earth ASCII files (randomly spaced)

LIDAR Laser Sensor l Laser scanner with mirror measures scan angles and distances for up to 50,000 pulses per second l Airborne GPS measures position l Inertial Measuring Unit (IMU) measures roll, pitch, heading l 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) l Task 3: Generation of Triangulated Irregular Network (TIN) and breaklines l Task 4: Development of 5m x 5m DEMs in ESRI GRID Float Format l Task 5: Development of DEMs in Three Additional File Formats l Task 6: Preparation of Project Report l Task 7: Production of Optional Digital Orthophoto Images

Digital Elevation Models (DEMs) l DEMs typically have uniform “post spacing” where x/y coordinates are evenly divisible by 5m, 10m, 30m, etc. l Interpolated from TIN data; e.g., LIDAR. l Neither TIN nor DEM points are clearly defined on the ground.

TINs — Superior for 3-D Surface Modeling; e.g., H&H Modeling l 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. l Mass points can come from LIDAR or other source. l Best breaklines come from photogrammetry, then digital orthophotos.

Hydraulic Models Require “Representative” Cross Sections l Cross sections are carefully selected to be representative of reaches that are as long as possible, without permitting excessive conveyance change between sections. l Typically between 500’ and 2,500’ apart. l 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 l Surveyed cross sections at bridges l Hydro-enforced stream centerlines l Digital orthophoto breaklines at stream shorelines l LIDAR models stream banks and overbank areas Greenhorne & O’Mara l Surveyed cross sections at bridges l Hydro-enforced stream centerlines l Photogrammetric breaklines at tops and bottoms of stream banks l LIDAR models overbank areas

Issue: How best to handle “obscured areas” and “artifacts”

Issue: How best to compute RMSE z of bare-earth TINs/DEMs Since TIN/DEM points not clearly defined: l Survey a minimum of 20 checkpoints in all 5 major land cover categories representative of the floodplain l Choose checkpoints on flat or uniformly sloping terrain; interpolate LIDAR points l Use no checkpoints in vegetation known to be too dense for LIDAR penetration l Discard 5% of “outliers”

Issue: Check points in such areas skew RMSE calculations l LIDAR has fewer areas than photogrammetry where the terrain is obscured. l One “bad” checkpoint in such areas will over-ride 1,000 “good” checkpoints elsewhere, and thus skew the results.

LIDAR Advantages Compared with Photogrammetry l LIDAR needs only a single line-of-sight to measure through/between trees l High-altitude LIDAR data are more accurate than from photogrammetry l LIDAR generates higher-density TINs/DEMs at lower costs l LIDAR acquires data both day and night (but not through clouds)

LIDAR Disadvantages Compared with Photogrammetry l LIDAR returns on water are unreliable l LIDAR is ill-suited for breaklines; e.g., 5-m point spacing could “jump” across a breakline l LIDAR is new technology; standards have not yet been developed l Contour lines are not as smooth l Streams are not automatically hydro- enforced, must be done manually

LIDAR contours not hydro-enforced (same problem with TINs/DEMs)

Conclusions l 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 l This project will also be used to update FEMA standards

Issues and Answers in Quality Control of LIDAR DEMs for North Carolina DFIRMs Q UESTIONS ? ? ? ? ?