Precise Airborne LiDAR Surveying For Coastal Research And Geohazards Applications

PRECISE AIRBORNE LIDAR SURVEYING FOR COASTAL RESEARCH AND GEOHAZARDS APPLICATIONS

Roberto Gutierrez, James C. Gibeaut, Rebecca C. Smyth, Tiffany L. Hepner, John R. Andrews

Bureau of Economic Geology, The University of Texas at Austin, Austin, Texas, USA

oskar@mail.utexas.eduChristopher Weed

Center for Space Research, The University of Texas at Austin, Austin, Texas, USA

William Gutelius

Optech, Inc., Toronto, Canada

Mark Mastin

U.S. Geological Survey, Tacoma, Washington, USA

KEYWORDS: LIDAR, laser, ALSM, calibration, natural hazards, shoreline mappingABSTRACT

The monitoring and analysis of many natural hazards requires repeated measurements of a topographic surface whose change reflects somegeologic or hydrologic process. The development of airborne laser surface mapping (ALSM) allows the study of natural hazards over areastens to hundreds of kilometers in extent with a horizontal resolution of 1 meter or less and a vertical accuracy of 0.10-to-0.15m. Changedetection requires that repeated ALSM surveys be precise and accurate. Repeatability is a function of the stability and calibration of theinstrument, the accuracy of GPS aircraft trajectories, the density and completeness of ALSM data coverage, the availability of “ground truth”information, and the accuracy and flexibility of ALSM data classification. Since 1997 The University of Texas at Austin (UT) has mappedvarious portions of the Texas Gulf coast using several small-footprint, scanning ALSM systems developed by Optech, Inc. During summer2000, UT comprehensively mapped the Texas coast from Sabine Pass on the Texas-Louisiana border to the mouth of the Rio Grande River.These data provide a series of Gulf shorelines for estimating beach erosion rates and computing volumetric sand loss. The high-resolutionbeach and dune topography derived from ALSM will help characterize the susceptibility of the coast to hurricane overwash and storm-relatedflooding. In another project UT collaborated with Optech and the U.S. Geological Survey in March 2000 to survey fifteen municipalities inHonduras with ALSM as part of the USAID Hurricane Mitch Recovery program. Digital elevation models produced from these data arebeing used for flood and landslide hazard analysis. During these and other projects, UT began implementing procedures for instrumentcalibration, data classification, and ground GPS surveying that enhance the repeatability of our ALSM surveys.

1 INTRODUCTION

The Bureau of Economic Geology (BEG), a geologic andenvironmental research group within the University of Texas atAustin (UT), is the state agency responsible for providingshoreline information to the Texas legislature and stateregulatory agencies. Because of the requirement for accurateshoreline data, the BEG began a program in airborne lasersurface mapping (ALSM) in collaboration with the UT Centerfor Space Research, and Optech, Inc. This program began with ashoreline survey in December 1997 using an ALSM systemprovided by Optech (Gutierrez et al, 1998). In July 2000, UTacquired an Optech ALTM 1225 instrument, a 25kHz scanninglaser mapping system. In this paper we describe our currentALSM program and how we are implementing geodetictechniques into our operations. We also discuss some resultsfrom our Texas shoreline mapping and a flood-hazard mappingproject in Honduras, C.A.

2 METHODS

NASA began developing ALSM technology in the 1980’s andseveral instruments (RASCAL, SLICER, AOL, LVIS, ATM)were developed for terrain, vegetation, and ice sheet mapping(Rabine et al, 1996; Harding et al, 2000; Krabill et al, 1995;Blair et al, 1999, Krabill et al, 2000). Commercial ALSMsystems became available as the technology matured. Optechdeveloped the ALTM 1020, a compact scanning ALSM systemwith a 5kHz laser repetition pulse rate, in 1995. Increases inlaser power, laser pulse rate, and overall system performancewere incorporated by Optech in subsequent models with the

ALTM 1225 system appearing in 1999. The ALTM 1225 has thefollowing specifications: Operating altitude410-2,000 m AGL Laser pulse rate25 kHz Laser scan anglevariable from 0 to ± 20° from nadir Scanning frequencyvariable, 28 Hz at the 20° scan angle. Beam divergence0.2 milliradian (half angle, 1/e)

The ALTM 1225 does not digitize and record the waveform of thelaser reflection, but records the range and backscatter intensity ofthe first and last laser reflection using a constant-fractiondiscriminator and two Timing Interval Meters (TIM).

ALSM elevation points are computed using three sets of data: laserranges and their associated scan angles, platform position andorientation information, and calibration data and mountingparameters (Wehr and Lohr, 1999). Global Positioning System(GPS) receivers in the aircraft and on the ground provide platformpositioning. The GPS receivers record pseudo-range and phaseinformation for post-processing. Platform orientation informationcomes from an Inertial Measurement Unit (IMU) containing threeorthogonal accelerometers and gyroscopes. An aided-InertialNavigation System (INS) solution for the aircraft’s attitude isestimated from the IMU output and the GPS information.2.1 Calibration

There are no standard instrument calibration procedures, eachequipment manufacturer and ALSM group have developed its owntechniques (Wehr and Lohr, 1999). The instrument calibration forour Optech ALTM 1225 includes the estimation of the scanner roll

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and pitch bias corrections, a scanner scale correction, and atiming correction for each TIM. These corrections were initiallymeasured in the manufacturer's laboratory facility and refined byflight testing. In the laboratory, range corrections were alsotabulated for varying intensities of laser backscatter. We re-estimate the instrument calibration by flight-testing before andafter an ALSM survey. Estimating GPS datum or ranging errorsrequires flying the instrument against "ground truth" - an area(e.g. road or airport runway) surveyed by ground GPS orconventional means. However, the scanner roll, pitch and scalebiases can be accurately estimated through the careful

comparison of overlapping flightlines (Burman, 2000).

Figure 1

. Laser backscatter intensity image of calibration area.

Figure 2. Roll and scale errors before and after adjustment.Figure 1 is a laser backscatter intensity image constructed fromseveral flightlines on the Texas coast. Indicated on the image isa kinematic GPS ground survey on a paved road oriented normalto the direction of four crossing flightlines. Figure 2 shows theelevation differences (+) between the ground GPS and one ofthese crossing ALSM flightlines processed using nominalcalibration settings. We estimated calibration corrections fromfour flights spaced over two weeks (July 12 through July 27,2001) of surveying. Plotted for comparison are the elevationdifferences (Ο) between the ground GPS and the same flightlineafter calibration adjustment. The consistency of the fourcalibration flights indicates that the ALSM system’s pointing

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accuracy has a RMS of ≤0.01° and a scanner scale RMS of≤0.0006.2.2 GPS

The absolute positioning of the ALSM platform comes from GPS.Therefore planning the GPS component of the ALSM survey,operating the air and ground GPS equipment, and estimating theaircraft trajectory from the GPS observations are critical steps. Weconduct ALSM surveys during periods when the Dilution ofPrecision (DOP) is ≤3.5 as estimated for a 15° elevation mask. Weoccupy ground GPS base stations that have an unobstructed sky-view down to 10°-to-15° above the horizon and are free of RFinterference or significant multi-pathing. We use dual-frequency,12-channel GPS receivers in the aircraft (Ashtech Z-12) and on theground (Ashtech Z-12 or Trimble 4000SSi) to record data at 1Hz.The ground receivers use Dorne & Margolin chokering antennas toreduce multi-pathing and a Dorne & Margolin C146-2-1 antenna ismounted in the aircraft. All antennas have been calibrated by theNational Geodetic Survey’s (NGS) Geosciences ResearchDivision. The NGS measures the antenna’s L1 and L2 phase centervariations as a function of GPS satellite elevation (see figure 3).Unless our GPS observations are corrected for these phase centervariations, errors as large as a decimeter can be introduced into theheight component of the aircraft trajectory.

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Figure 3. Phase center error as a function of satellite elevation forthe C146-2-1 antenna.

We use the NGS’s kinematic GPS processing software, KARS(Mader, 1992), to estimate a double-differenced, ionospherically-corrected (L3), ambiguity-fixed, phase solution for the aircrafttrajectory. We use precise GPS ephemerides, computed by theInternational GPS Service (IGS) or the NGS, instead of thebroadcast orbits in the trajectory solution.

On July 17, 2001, we mapped the Texas shoreline from SabinePass to Galveston Island (see figure 4). A Trimble 4000SSireceiver occupied a tide gauge benchmark at Sabine Pass and anAshtech Z-12 occupied a tide gauge benchmark at Port Bolivar.During the almost three-hour survey, the aircraft was alwayswithin 50 km of one GPS base station, but could be as far as 150km from the other basestation (see figure 5).

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Figure 4. The Galveston Bay - Bolivar Peninsula area.

Figure 5. Baseline distance during 17 July shoreline survey.

Figure 6. Difference in HAE between the Port Bolivar andSabine Pass aircraft trajectories for July 17, 2001 shorelinesurvey.

We computed KARS trajectories for the aircraft using both thePort Bolivar and Sabine Pass GPS base station data. Thedifferences between the two trajectories in the east and north,components are under 0.05m. The HAE differences between thetwo trajectories are under 0.05m when the aircraft is within50km of both base stations. The HAE differences are under0.10m even when the aircraft is more than 100 km from one ofthe base stations (see figure 6).2.3 Data Coverage

Small foot-print ALSM systems operating with a 25kHz orhigher laser pulse repetition rate can generate ALSM coverage

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with a sub-meter laser point spacing during a single pass.However, vegetation, buildings, and topography can causeshadowing that may significantly reduce the ground surfacecoverage. For area surveys we fly an orthogonal grid, two sets offlightlines at right angles, to minimize data gaps. Scanning from anumber of different aircraft positions allows us to more accuratelyreconstruct the morphology of topographic or cultural features. ForALSM surveys that are route-oriented, e.g. a shoreline survey,parallel swaths can be spaced laterally so as to scan both sides of aroute-parallel obstruction such as a dune line.2.5 Ground Truth

We conduct ground GPS surveys within each ALSM survey areato acquire ground “truth” information. We re-occupy the ALSMGPS base stations and survey an open area with an unambiguoussurface (road, soccer fields, large building) using kinematic GPStechniques. The ALSM data are sorted to find LIDAR points thatfall within 0.5m of a ground GPS survey point. The meanelevation difference between the ALSM (last returns only) and theground GPS are used to estimate and remove an elevation biasfrom the ALSM. The standard deviation of the elevationdifferences provide an estimate of the LIDAR precision. Selectedportions from each ALSM data set (last return only) are used togenerate a high-resolution (1m × 1m or 0.5m × 0.5m) digitalelevation model (DEM) or laser intensity image. The kinematicGPS data are superimposed on the DEM or intensity image andexamined for any horizontal mismatch.

Figure 7 is a 0.5m × 0.5m laser backscatter intensity image of thesoccer field in Juticalpa, Honduras. The chalk markings on thefield are discernible. On the right panel, the survey points from aGPS survey of the chalk marks and two transects across the fieldare superimposed on the intensity image. The GPS and ALSMmatch to within the resolution of the image indicating an ALSMhorizontal error of <0.5m. There were 417 ALSM points that fellwithin 0.5m of a GPS ground survey point on the soccer field. Themean elevation difference between the GPS and ALSM was –

0.169m with a RMS of 0.088m.

Figure 7. Intensity image of soccer field with GPS ground surveyoverlain.

2.4 Data classification

ALSM generates a semi-random cloud of elevation points thatrequires classification into reflections from ground and vegetation.As a preliminary step towards constructing digital elevation

models, we have classified ALSM data using algorithmsdeveloped by TopScan GmbH (Petzold et al, 1999) and by theUT Center for Space Research (Neunschwander et al, 2000).The TopScan algorithm identifies points as either “ground” or“non-ground” by iteratively improving an initial terrain surface.The initial terrain surface is generated from the minimum valueof elevation points within a large, moving window. All theelevation points that exceed a specified threshold above theterrain are classified as non-ground points and removed. Using asmaller moving window, the remaining elevation points are usedto create a new terrain surface. The ALSM data are againcompared to a threshold value and the non-ground points areremoved. This process is repeated for a set number of iterations.The window size and threshold values are terrain-dependent andrequire a high level of user interaction.

The UT method classifies elevation points as ground, vegetation,or buildings using an image-based processing algorithm. TheALSM data are gridded to create a high-resolution topographicimage. The average topographic surface is estimated andsubtracted from the high-resolution image. The resultingresidual image contains the high-frequency content of thevegetation and the building edges. The lower envelope of high-frequency residuals represents the ground surface in the ing the lower envelope, an initial ground surface is estimated.A gradient-based method is used to detect and remove any largebuildings remaining in the estimated ground surface. Afterinterpolating across gaps, the final ground surface is used toclassify the ALSM data. Building classification is accomplishedby first detecting planar surfaces representing roofs. Thebuilding boundaries are delineated by extending the edges usinga gradient-flood fill method. The building surface is then used toclassify ALSM points as man-made features. A building outlinecan be distorted by laser multi-pathing, therefore ALSM first-returns are used for building classification.

Figure 8 is a 1m × 1m DEM constructed from first-return ALSMdata of the Mayan ruins at Copan, Honduras. An aerialphotograph is shown for comparison. Figure 9 is a 1m × 1mDEM of the Copan ruins constructed from last-return ALSMdata filtered to remove the trees using the envelope detector andgradient based method developed at UT. The elevation pointsrepresenting the Mayan archeological structures were classifiedand added to the ground points before the DEM was computed.For comparison is a site map constructed from a HarvardUniversity ground survey.

Figure 8. Left: ALSM DEM of Copan. Right: aerial photograph.

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Figure 9. Left: vegetation-filtered ALSM. Right: ground survey.

3 COASTAL MAPPING

3.1 Texas Gulf Shoreline Change Project

In 1999, with the support of the Texas General Land Office, theBEG developed the Texas Shoreline Change Project. The project’sgoal is to establish a state-of-the-art regional shoreline-monitoringand shoreline-change analysis program that will help solve coastalerosion and storm hazard problems along the bay and Gulfshorelines of Texas. ALSM is a key component of the TexasShoreline Change Project; it is important in identifying "criticalcoastal erosion areas" and in the monitoring of historical shorelineerosion rates.

During 2000 we mapped the entire Texas Gulf shoreline using theOptech 1225 system from Sabine Pass, at the Texas-Louisianaborder, to the mouth of the Rio Grande River, a distance of over600 kilometers. We mapped the shoreline in three sections: SabinePass to Freeport (212km), Freeport to Corpus Christi (215km), andCorpus Christi to the Rio Grande (174km). During a typicalshoreline survey, the aircraft flew two to four passes along theshoreline with parallel swaths overlapping by about 50 percent.The survey altitude varied from 450m to 760m AGL and theground speed was usually held to 51m/sec (100 knots). Theresulting ALSM coverage of the beach, dunes, and back-barrierarea is 500m to 700m wide and has an average ground pointspacing of <1m.

Three ground GPS receivers, Ashtech Z-12 or Trimble 4000SSi,operated during the ALSM mapping. One GPS receiver wassituated at each end of the 200km section of coastline and the thirdwas located approximately in the middle of the survey area. Six ofthe nine GPS base stations occupied benchmarks at NOAA orTexas Coastal Ocean Observation Network (TCOON) tide gauges.These gauges are at Sabine Pass, Port Bolivar, Port O’Connor, PortAransas, Port Mansfield, and South Padre Island. The remainingthree GPS ground stations were monuments established by eitherthe NGS, the U.S. Army Corps of Engineers, or UT.

GPS data processing was conducted in the International TerrestrialReference Frame 1997 (ITRF97) and the ALSM elevation pointswere output in Universal Transverse Mercator (UTM) coordinatesand height above the GRS-80 ellipsoid (HAE). The ALSM datawere compared to GPS ground surveys for the estimation of

ALSM elevation biases. Shorelines were delineated from 1m ×1m digital elevation models (DEM). Long and short ALSMranges (e.g. clouds, birds, and multi-paths) were edited andALSM elevation biases were removed. The edited and bias-corrected ALSM data were then imported into ARC/INFO andinterpolated using the TOPOGRID module, which is based onthe ANUDEM interpolation method of Hutchinson (1989). TheDEM’s were converted from HAE to orthometric height usingthe G99SSS gravimetric geoid model (Smith and Roman, 2000)and adjusted vertically so that the zero-elevation conformed tomean sea level (MSL) at the nearest tide station.3.2 Rollover Pass

Rollover Pass is a small artificial inlet on the southeast Texascoast that connects East Bay of the Galveston Bay system withthe Gulf of Mexico. The channel was dredged across a narrowportion of Bolivar Peninsula in 1954/55 and has stabilized at awidth of 61m. Bolivar Peninsula is an area of naturally higherosion rates, however the shape of the shoreline shows that theartificial inlet has altered rates of shoreline movement bychanging the littoral drift rate in the area.

From 1996 to 1999, Tropical Storms Josephine and Francescaused a total of 27m of scarp retreat 3.2km to the west ofRollover Pass. The process of shoreline retreat in the RolloverPass area involves episodic and dramatic scarp retreat duringstorms followed by post-storm recovery and widening of thebeach in front of the scarp. Eventually, the long-term erosionprocess resumes and the beach begins to narrow, allowing asubsequent storm to erode the scarp again.

We collected ALSM data along Bolivar Peninsula beforeTropical Storm Frances on August 6, 1998, and after the stormon September 17, 1998 using an Optech 1020 ALSM system.All the HAE were transformed into orthometric heights usingthe National Geodetic Survey G96SSS geoid model. All theALSM data were adjusted by –0.35m vertically so that the zero-elevation would conform to the local mean sea level asmeasured at the Port Bolivar tide gauge.

Figure 10. ALSM shaded relief images of Rollover Pass. Upperpanel is the pre-Tropical Storm Frances shoreline with the 1mcontour in white. The lower panel is the post-Frances shoreline.

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We computed pre- and post-Frances 2m × 2m DEMs from thevertically adjusted data sets. Figure 10 shows the coastaltopography at Rollover Pass before and after Frances. The 1melevation is the white contour line on both shaded relief images.We digitized the 1m contour lines along the beach for a distance of10km on either side of Rollover Pass. Figure 11 shows theshoreline change as represented by the movement of the 1mcontour from August 6 to September 17, 1998. The shoreline datashow a complex pattern of erosion. This pattern reflects theinteraction of factors including offshore topography and waverefraction, piers and other man-made shoreline structures, and pre-storm beach morphology in determining the response of the beachto the storm. Except for a small area within 300m west of RolloverPass where as much as 30m of retreat occurred, it appears that thepass had no unusual effect on beach erosion during this storm.

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Figure 11. Change in 1m contour at Rollover Pass during

due to Tropical storm Frances.

Figure 12. Geotube installed in front of the beach scarp at BolivarPeninsula during July 2001

International Archives of Photogrammetry and Remote Sensing, Volume XXXIV-3/W4 Annapolis, MD, 22-24 Oct. 2001

Figure 13. ALSM shaded relief image of Rollover Pass on 17 July 20001 showing geotubes installed behind the beach and in front of theeroding beach scarp. The 1m elevation contour is shown in white. A shore-normal beach profile (GLO-21) is to the left of Rollover Pass.In 1999, communities on Galveston Island and Bolivar Peninsulabegan installing geotextile tubes (geotubes) along the mosterosion-prone stretches of shoreline. The geotubes are sand-filledsleeves of geotextile fabric with an approximately 4m oval crosssection (see figure 12). The ALTM 1225 system was used to mapthe Galveston and Bolivar shorelines, including the geotubes, on17 and 18 July, 2001 (see figure 13).

Kinematic GPS and a total station were used to measure a set ofshore-normal profiles after the ALSM surveys were flown. Theprofiles extended across the geotubes, the beach, and for 100-200m offshore. Figure 14 compares the topography measured byALSM with the total station profile at location GLO-21 (seefigure 13). The ALSM elevations agree well with the groundcontrol except were dense vegetation behind the geotubes masksthe true ground surface. Thick deposits of sargassum on the back-beach also cause the ALSM elevations to be slightly higher thanthe true ground surface. These new data will be used to study theresponse of the beach and geotubes to coastal processes.

HAE(m)Shore-normal Distance (m)

an estimated $900 million loss. Honduras is still rebuilding thehousing and infrastructure destroyed by Hurricane Mitch. Tominimize future flood disasters, the Honduran government needsmaps that accurately delineate probable areas of inundation byflooding.

From February to March 2000, the BEG, the U.S. GeologicalSurvey (USGS) and Optech collaborated to map the channelgeometry of the floodplains within 15 Honduran municipalitiesusing ALSM. Between January 7-21, 2001, the USGS and BEGcollaborated again to measure the geometry and location of 21bridges in these 15 municipalities using a total station and GPSequipment. The USGS will use the bridge geometry and ALSMdata to generate new, accurate 50-year flood inundation maps foreach Honduran municipality.

The construction of the Honduran inundation maps involved threegeneral steps. We estimated the 50-year stream discharges for therivers in each municipality using a statistical analysis ofprecipitation and a rainfall-runoff model. We then computedwater-surface elevations using channel geometry informationfrom ALSM-derived DEM’s and the HEC-RAS hydraulicsimulation model (U.S. Corps of Engineers, 1998). HEC-GeoRAS, an ArcView extension, was used to define the streamthalweg, banks, overbank centerlines, and extract channel cross-sections from the DEM’s (U.S. Corps of Engineers, 2000). Oftena shaded relief image of the DEM was used as background tohelp locate these various lines. Manning roughness coefficients,n, were estimated by the hydrologists from field observations orby reviewing a shaded relief image of the DEM. The shadedrelief image gave a good view of the density of vegetation in thestream channel – the higher densities were given higher n values.Finally, the simulated water levels from the hydraulic mode wereplotted as depth and area of inundation over the DEM.4.2 Tegucigalpa

We installed the ALTM 1225 system in a Beech King Air A-90aircraft in the U.S. and ferried the aircraft to Toncontin Airport inTegucigalpa, Honduras. Tegucigalpa was mapped during 1-2March, 2000. We operated the instrument at a laser repetition rateof 25kHz, a laser scanning rate of 28Hz, and a laser scan angle of±20° off nadir. We flew the aircraft at an average airspeed of 140knots (72 m/s). This resulted in a spacing of about 2.6m betweenlaser scan lines. The aircraft altitude varied between 800m to1200m above ground level (AGL). To generate an approximately1m × 1m ground point spacing, we mapped the city with a grid oforthogonal flight lines with approximately 30 percent side-lapbetween adjacent swaths (see figure 15).

Figure 14. A beach profile across a geotube measured with totalstation on 19 July, 2001 is compared to ALSM data collected on17 July, 2001.

4 FLOOD HAZARD MAPPING

4.1 Hurricane Mitch

From October 27 to November 1, 1998, Central America wasdevastated by Mitch, a category 5 hurricane on the Saffir-Simpson scale with winds up to 155 mph. Mitch is responsiblefor over nine thousand deaths, making it one of the deadliestAtlantic tropical cyclones in history and comparable to the greatGalveston storm of 1900. In Honduras, the human toll is anestimated 5,000 deaths. Whole villages were washed away and anestimated 70-to-80 percent of the transportation infrastructurewas destroyed. At least 70 percent of the crops were destroyed;

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Figure 15. Flightlines over the 10 km x 10 km survey area forTegucigalpa, Honduras.

These flights produced a uniform and dense ALSM data pointcoverage over an approximately 10km × 10km area ofTegucigalpa. Figure 16 shows the point “cloud” distribution overthe city center at the confluence of the Rio Grande O Cholutecaand the Rio Guacerique. The only data gaps are on the riverswhere the water surface was often too specular to provide good

laser returns.

Figure 16. ALSM point cloud for central Tegucigalpa. Theindividual laser returns are colored to represent elevation.Channel cross-sections are shown in white.

We edited the ALSM data, compared them to ground surveys,and corrected for elevation biases. We generated a 1.5m × 1.5m“all points” DEM using all the ALSM last-return data. We thenapplied the TopScan vegetation-filtering algorithm to the last-return ALSM data. The filter parameters were chosen so thatreflections from trees were removed, but most reflections fromthe ground surface and buildings were retained. We constructed asecond, 1.5m × 1.5m “vegetation-removed” DEM from thefiltered ALSM data. We then used HEC-GeoRAS to define theriver channels and extract cross-sections from the “vegetation-removed” DEM’ (see figure 16).

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Heavy rains associated with Hurricane Mitch caused three majorlandslides in Tegucigalpa. The most devastating slide occurred onthe Cerro Berrinche in northwest Tegucigalpa. The El Berrinchelandslide destroyed an entire hillside community and dammed theRio Grande O Choluteca causing significant flooding in the citycenter. Figure 17 shows the topography of the El Berrinchelandslide after mitigation. The toe of the landslide has been cut

into a series of steps and stabilized with gabions.

Figure 17. Shaded relief image of the El Berrinche landslide inTegucigalpa.

5 DISCUSSION

Erosion along the Texas coast caused by the recent tropicalstorms in the Gulf of Mexico has intensified efforts to saveproperty and houses. ALSM can provide the topographic modelsneeded for geomorphic analysis and the delineation of areasparticularly susceptible to storm damage. Post-storm ALSMsurveys allow rapid and quantitative assessment of the amount oferosion and vulnerability of the coast to subsequent storms. In thepast, coastal geologists and engineers have either conductedregional studies with sparse data or local studies with detaileddata. With ALSM, however, it is possible to acquire detailed andaccurate topographic data over a broad coastal region allowinggeomorphic analysis across the continuum of spatial ndslide and flooding risks are strongly dependent ontopography. With ALSM it is possible to characterize topographyover large areas with sufficient resolution and accuracy to modelhydrologic and geomorphic processes with unprecedented detail.New, quantitative models for hydrologic and surficial processescan be developed and tested using high-resolution topographicdata.

6 REFERENCES

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Burman, H., 2000, Adjustment of laser scanner data forcorrection of orientation errors, International Archives of

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Krabill, W.B., R.H. Thomas, C.F. Martin, R.N. Swift, and E.B.Frederick, 1995; Accuracy of Airborne Laser Altimetry Over theGreenland Ice Sheet, International Journal Remote Sensing, Vol.16, No. 7, pp. 1211-1222.

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Petzold, B., P. Reiss, and W. Stössel, 1999, Laser scanning –surveying and mapping agencies are using a new techniques forthe derivation of digital terrain models, ISPRS Journal ofPhotogrammetry and Remote Sensing, vol. 54, no.2-3, pp.95-104.Rabine, D. L., J. L. Bufton, and C. R. Vaughn, 1996,Development and test of a raster scanning laser altimeter forhigh-resolution airborne measurements of topography,IGARSS96.

Smith, D.A., and D.R. Roman, 2001, GEOID99 and G99SSS:One arc-minute models for the United States, Journal of Geodesy,in press.

Wehr, A. and U. Lohr, 1999, Airborne laser scanning - anintroduction and overview, ISPRS Journal of Photogrammetryand Remote Sensing, vol. 54, no.2-3, pp.68-82.

U.S. Corps of Engineers, 1998, HEC-RAS River AnalysisSystem, Hydraulic Reference Manual version 2.2, HydraulicEngineering Center, Davis, California, 237p.

U.S. Corps of Engineers, 2000, HEC-GeoRAS, An extension forsupport of HEC-RAS using ArcView, User’s Manual version 2.2,Hydraulic Engineering Center, Davis, California, 96p.

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