DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

noaa / NATIONAL OCEANIC AND

ATMOSPHERIC ADMINISTRATION

National Environmental Satellite,

Data, and Information Service

NOAA Technical Memorandum NESDIS NGDC- 10

DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII:

PROCEDURES, DATA SOURCES AND ANALYSIS 

L.A.Taylor

B.W. Eakins

K.S. Carignan

R.R. Warnken

T. Sazonova

D.C. Schoolcraft

National Geophysical Data Center

Marine Geology and Geophysics Division

Boulder, Colorado

January 2008


DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

UNITED STATES

DEPARTMENT OF COMMERCE

Carlos M. Gutierrez

Secretary

NATIONAL OCEANIC AND

ATMOSPHERIC ADMINISTRATION

VADM Conrad C. Lautenbacher, Jr.

Under Secretary for Oceans

and Atmosphere/Administrator

National Environmental Satellite,

Data, and Information Service

Mary E. Kicza

Assistant Administrator

NOAA Technical Memorandum NESDIS NGDC-10

DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII:

PROCEDURES, DATA SOURCES AND ANALYSIS 

Lisa A. Taylor1

Barry W. Eakins2

Kelly S. Carignan2

Robin R. Warnken1

Tatiana Sazonova2

David C. Schoolcraft1

1

NOAA, National Geophysical Data Center, Boulder, Colorado

2

Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder 

National Geophysical Data Center

Marine Geology and Geophysics Division 

Boulder, Colorado

January 2008
ii

Taylor et al., 2008

NOTICE

Menton of a commercal company or product does not consttute an endorsement by the 

NOAA Natonal Envronmental Satellte, Data, and Informaton Servce. Use of nformaton 

from ths publcaton concernng propretary products or the test of such products for publcty

or advertsng purposes s not authorzed. 

Corresponding author contact:

Lsa A. Taylor

NOAA, Natonal Geophyscal Data Center

Marne Geology and Geophyscs Dvson

35 Broadway, E/GC 3

Boulder, Colorado 80305

Phone: 303-497-6767

Fax: 303-497-653

E-mal: Lsa.A.Taylor@noaa.gov

http://www.ngdc.noaa.gov/mgg/nundaton/

Also avalable from the Natonal Techncal Informaton Servce (NTIS)

(http://www.nts.gov)
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DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

Contents

1. Introduction........................................................................................................................................1

2. Study Area..........................................................................................................................................2

3. Methodology ......................................................................................................................................2

3.1 Data Sources and Processing ......................................................................................................3

3.1.1 Shoreline................................................................................................................4

3.1.2 Bathymetry ............................................................................................................5

3.1.3 Topography..........................................................................................................10

3.2 Establishing Common Datums .................................................................................................13

3.2.1 Vertical datum transformations ...........................................................................13

3.2.2 Horizontal datum transformations.......................................................................13

3.3 Digital Elevation Model Development .....................................................................................13

3.3.1 Verifying consistency between datasets..............................................................13

3.3.2 Gridding of raw USGS multibeam bathymetric data ..........................................14

3.3.3 Smoothing of bathymetric data ...........................................................................14

3.3.4 Gridding the data with MB-System.....................................................................14

3.4 Quality Assessment of the DEM...............................................................................................15

3.4.1 Horizontal accuracy.............................................................................................15

3.4.2 Vertical accuracy .................................................................................................15

3.4.3 Slope maps and 3-D perspectives........................................................................15

3.4.4	 Comparison with source data files.......................................................................17

3.4.5 Comparison with NGS geodetic monuments......................................................17

4. Summary and Conclusions...............................................................................................................19

5. Acknowledgments............................................................................................................................19

6. References........................................................................................................................................19

7. Data Processing Software ................................................................................................................19

List of Figures

Figure 1. Color image of the Lahaina, Hawaii region................................................................................1

Figure 2. Aerial image of Lahaina Harbor .................................................................................................2

Figure 3. Source and coverage of datasets used to compile the Lahaina DEM .........................................3

Figure 4. Source and coverage of bathymetric datasets used to compile the Lahaina DEM.....................5

Figure 5. Digital NOS hydrographic survey coverage in the Lahaina region............................................7

Figure 6.	 Oblique view of the seafloor between the islands of Kahoolawe, Molokai, Maui and

Lanai ....................................................................................................................................8

Figure 7. Spatial coverage of JALBTCX SHOALS bathymetric LiDAR surveys in the Lahaina 

region ...................................................................................................................................9

Figure 8. Source and coverage of topographic datasets used to compile the Lahaina DEM...................10

Figure 9. Color image of the CSC bare-earth DEM in the vicinity of Lahaina Harbor...........................11

Figure 10. Color image of the NED DEM in the vicinity of Lahaina........................................................12

Figure 11. Histogram of the differences between NOS hydrographic survey H08522 and the 

 1 arc-second pre-surfaced bathymetric grid ......................................................................14

Figure 12. Slope map of the Lahaina DEM................................................................................................16

Figure 13. Perspective view from the south of the Lahaina DEM.............................................................16

Figure 14.	 Histogram of the differences between one file of the CSC coastal topographic LiDAR

survey and the Lahaina DEM. ...........................................................................................17

Figure 15.	 Histogram of the differences between one file of the JALBTCX coastal topographic

LiDAR survey and the Lahaina DEM ...............................................................................17

Figure 16. Histogram of the differences between NGS geodetic monument elevations and the 

Lahaina DEM.....................................................................................................................18

Figure 17. Location of NGS monuments and NOAA tide stations in the Lahaina region.........................18
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Taylor et al., 2008

List of Tables

Table 1.	 PMEL specifications for the Lahaina, Hawaii DEM ..................................................................2

Table 2. Shoreline datasets used in compiling the Lahaina DEM ............................................................4

Table 3. Bathymetric datasets used in compiling the Lahaina DEM........................................................5

Table 4. Digital NOS hydrographic surveys used in compiling the Lahaina DEM..................................6

Table 5. Topographic datasets used in compiling the Lahaina DEM .....................................................10

Table 6. Relationship between Mean High Water and other vertical datums in the Lahaina region......13

Table 7. Data hierarchy used to assign gridding weight in MB-System.................................................15


DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

Digital Elevation Model of Lahaina, Hawaii:

Procedures, Data Sources and Analysis

1. Introduction

In March 2007, the National Geophysical Data Center (NGDC), an office of the National Oceanic and

Atmospheric Administration (NOAA), developed a bathymetric–topographic digital elevation model (DEM) of 

Lahaina, Hawaii (Fig. 1) for the Pacific Marine Environmental Laboratory (PMEL) NOAA Center for Tsunami

Research (http://nctr.pmel.noaa.gov/). The 1/3 arc-second coastal DEM will be used as input for the MOST (Method 

of Splitting Tsunami) model developed by PMEL to simulate tsunami generation, propagation and inundation. The 

DEM was generated from diverse digital datasets in the region (grid boundary and sources shown in Fig. 3) and will be 

used for tsunami inundation modeling, as part of the tsunami forecast system SIFT (Short-term Inundation Forecasting 

for Tsunamis) currently being developed by PMEL for the NOAA Tsunami Warning Centers. This report provides a 

summary of the data sources and methodology used in developing the Lahaina DEM. 

. The Lahaina DEM is built upon a grid of cells that are square in geographic coordinates (latitude and longitude), however, the cells are not square 

when converted to projected coordinate systems, such as UTM zones (in meters). At the latitude of Lahaina, Hawaii (20°52′ N, 156°41′ W) 1/3 

arc-second of latitude is equivalent to 10.25 meters; 1/3 arc-second of longitude equals 9.63 meters.

Figure 1. Color image of 

the Lahaina, Hawaii region. 

Coastline in black.


Taylor et al., 2008

2. Study Area

The Lahaina DEM covers the coastal region centered on the western coast of the island of Maui, Hawaii, and 

the marine channels between Maui, Lanai and Molokai, including the communities of Lahaina and Kapalua, Maui,

Lopa, Lanai, and Kaluaaha, Molokai (Fig. 1). Development in the coastal zone in these popular tourist destinations

has modified local morphology, especially in boat harbors (e.g., Fig 2).

The islands of Hawaii have been created by shield-building volcanoes, whose low-viscosity lava flows often

reach the coast. The marine channels between the islands exhibit significant morphologic relief (Fig. 1), reflecting

alternation between living and drowned coral reefs built atop submarine volcanic material (see http://geopubs.wr.usgs.

gov/i-map/i2809/ for further information).

Figure 2. Aerial image of Lahaina Harbor (http://www.soest.hawaii.edu/coasts/data/maui/obliquephoto.html).

3. Methodology

The Lahaina DEM was developed to meet PMEL specifications (Table 1), based on input requirements

for the MOST inundation model. The best available digital data were obtained by NGDC and shifted to common 

horizontal and vertical datums: World Geodetic System 1984 (WGS84) and Mean High Water (MHW), for modeling 

of “worst-case scenario” flooding, respectively. Data processing and evaluation, and DEM assembly and assessment

are described in the following subsections.

Table 1. PMEL specifications for the Lahaina, Hawaii DEM.

Grid Area Lahaina, Hawaii

Coverage Area 156.55o to 156.9o W; 20.7o to 21.1o N

Coordinate System Geographic decimal degrees

Horizontal Datum World Geodetic System 1984 (WGS84)

Vertical Datum Mean High Water (MHW)

Vertical Units Meters

Grid Spacing 1/3 arc-second

Grid Format ESRI ASCII raster grid
DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

3.1 Data Sources and Processing

Shoreline, bathymetric and topographic digital datasets (Fig. 3) were obtained from several U.S. federal 

agencies, including: NOAA’s National Ocean Service (NOS) and Coastal Services Center (CSC); the U.S. Geological 

Survey (USGS); the Joint Airborne LiDAR Bathymetry Technical Center of Expertise (JALBTCX); and the National 

Geospatial-Intelligence Agency (NGA). The data were collected by numerous methods, in different terrestrial 

environments, and at various scales and resolutions. Datasets were assessed for quality and accuracy both within 

each dataset, and between datasets to ensure consistency and gradual topographic transitioning along the edges of 

datasets. Safe Software’s (http://www.safe.com/) FME data translation tool package was used to shift datasets to 

WGS84 horizontal datum and to convert into ESRI (http://www.esri.com/) ArcGIS shape files. The shape files were

then displayed with ArcGIS to assess data quality and manually edit datasets; NGDC’s GEODAS software (http://

www.ngdc.noaa.gov/mgg/geodas/) was used to manually edit large xyz datasets. Vertical datum transformations to 

MHW were also accomplished using FME, based upon data from a NOAA tide station on Maui, as no VDatum model 

software (http://nauticalcharts.noaa.gov/csdl/vdatum.htm) was available for this area.

Figure 3. Source and coverage of datasets used to compile the Lahaina DEM.
Taylor et al., 2008

3.1.1 Shoreline

One digital coastline dataset of the Lahaina region was used in building the Lahaina DEM: the National 

Geospatial-Intelligence Agency (NGA; Table 2). 

Table 2. Shoreline datasets used in compiling the Lahaina DEM.

Source Year Data Type Spatial Resolution Original Horizontal Datum/

Coordinate System

Original Vertical 

Datum

NGA 1998 to 2002 MHW shoreline 50 meters WGS84 MHW

1) NGA Global Imagery-Derived Shoreline 

The NGAGlobal Imagery-Derived Shoreline is an unclassified vector dataset generated by Earth Satellite

Corporation (EarthSat) of Rockville, Maryland for NGA, under contract to Boeing in 2004. The shoreline is 

referenced to MHWand constructed from consistently orthorectified LandsatTM satellite imagery (GeoCover

Ortho), acquired between 1998-2002 for NASA under the Global Land Mapping Program (GLMP). NDVI 

and SWIR models were used to define the landward extent of inundation (i.e., MHW). Independently verified

positional accuracy for the source product (GeoCover Ortho) is consistently better than 50m root mean 

square (RMS) error. 

The NGA coastline was mostly consistent with coastal topographic and bathymetric LiDAR surveys, 

though it was modified in places to match those datasets. Piers, docks, and other manmade structures were

also present in the coastline, which had to be deleted. The NGA coastline was converted to point data for use 

as a coastal buffer for the bathymetric pre-surfacing algorithm (see Section 3.3.2) to ensure that interpolated 

bathymetric values reached “zero” at the coast. It was also used to clip USGS NED topographic DEMs, 

which contain elevation values, typically zero, over the open ocean (Section 3.1.3). 
DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

3.1.2 Bathymetry

Bathymetric datasets used in the compilation of the Lahaina DEM include 38 NOS hydrographic surveys, a 

USGS multibeam survey of the channels between the islands, and JALBTCX SHOALS bathymetric LiDAR surveys 

along the coasts (Table 3; Fig. 4). 

Table 3. Bathymetric datasets used in compiling the Lahaina DEM.

Source Year Data Type Spatial Resolution

Original Horizontal 

Datum/Coordinate 

System

Original 

Vertical 

Datum

URL

 NOS 1931 to 

1984

Hydrographic 

survey 

soundings

Ranges from 10 

m to 1 km (varies 

with scale of survey, 

depth, traffic, and

probability of 

obstructions)

Early Hawaiian Island 

or Old Hawaiian MLLW http://www.ngdc.noaa.gov/mgg/bathymetry/hydro.html

USGS 1998 DEM 20 meters NAD83, UTM Zone 4 MSL http://walrus.wr.usgs.gov/

pacmaps/mi_index.html

USGS 1998 multibeam ~1 meter WGS84 geographic MSL

JALBTCX 1999 to 

2000

SHOALS 

LiDAR

averages 5 to 10 

meters WGS84 geographic MLLW

http://shoals.sam.usace.army.

mil/hawaii/pages/Hawaii_

Data.htm

Figure 4. Source and coverage of bathymetric datasets used to compile the Lahaina DEM.
Taylor et al., 2008

1) NOS hydrographic survey data

A total of 38 NOS hydrographic surveys conducted between 1931 and 1984 were utilized in developing 

the Lahaina DEM (Table 4; Fig. 5). The hydrographic survey data were originally vertically referenced 

to Mean Lower Low Water (MLLW) and horizontally referenced to either Early Hawaiian Island or Old 

Hawaiian datums.

Data point spacing for the NOS surveys varied by collection date. In general, earlier surveys had greater 

point spacing than more recent surveys. All surveys were extracted from NGDC’s online NOS hydrographic 

database (http://www.ngdc.noaa.gov/mgg/bathymetry/hydro.html) in their original, digitized vertical datum 

and NAD83 horizontal datum (Table 4). The data were then converted to WGS84 and MHW using FME 

software, an integrated collection of spatial extract, transform, and load tools for data transformation (http://

www.safe.com). The surveys were subsequently clipped to a polygon 0.05 degrees (~10%) larger than the 

Lahaina DEM area to support data interpolation along grid edges. 

After converting all NOS survey data to MHW (see Section 3.2.1), the data were displayed in ESRI 

ArcMap and reviewed for digitizing errors against scanned original survey smooth sheets and compared to 

coastal topographic LiDAR and NED data, JALBTCX coastal bathymetric LiDAR data, the NGA coastline, 

NOAA nautical charts, and Google Earth satellite imagery.

Table 4. Digital NOS hydrographic surveys used in compiling the Lahaina DEM.

NOS Survey ID Year of Survey Survey Scale Original Vertical Datum Original Horizontal Datum

H05290 1931 20,000 mean lower low water early Hawaiian Island 

H05297 1931/32 40,000 mean lower low water early Hawaiian Island 

H05298 1932 5,000 mean lower low water early Hawaiian Island 

H05310 1931 20,000 mean lower low water early Hawaiian Island 

H05311 1931 20,000 mean lower low water early Hawaiian Island 

H05337 1931 20,000 mean lower low water early Hawaiian Island 

H05338 1931 5,000 mean lower low water early Hawaiian Island 

H05339 1932 100,000 mean lower low water early Hawaiian Island 

H08576 1961 10,000 mean lower low water old Hawaiian 

H08577 1961 10,000 mean lower low water early Hawaiian Island 

H08578 1961 10,000 mean lower low water early Hawaiian Island 

H08579 1961 10,000 mean lower low water early Hawaiian Island 

H08580 1961 10,000 mean lower low water old Hawaiian 

H08581 1961 5,000 mean lower low water early Hawaiian Island 

H08582 1961 5,000 mean lower low water old Hawaiian 

H08583 1961/62 40,000 mean lower low water old Hawaiian 

H08677 1962 40,000 mean lower low water early Hawaiian Island 

H08678 1962 20,000 mean lower low water old Hawaiian 

H08679 1962 20,000 mean lower low water old Hawaiian 

H08680 1962 10,000 mean lower low water old Hawaiian 

H08683 1962 10,000 mean lower low water early Hawaiian Island 

H08685 1962 5,000 mean lower low water early Hawaiian Island 

H08828 1965 5,000 mean lower low water old Hawaiian 

H08831 1965 10,000 mean lower low water old Hawaiian 

H08832 1965 10,000 mean lower low water old Hawaiian 

H08833 1965 40,000 mean lower low water early Hawaiian Island 

H08834 1965 20,000 mean lower low water old Hawaiian 

H08835 1965 10,000 mean lower low water old Hawaiian 

H08881 1965 5,000 mean lower low water old Hawaiian 

H08882 1965 10,000 mean lower low water old Hawaiian 

H08886 1966 10,000 mean lower low water old Hawaiian 

H08889 1966 10,000 mean lower low water early Hawaiian Island 

H08919 1966/67 10,000 mean lower low water early Hawaiian Island 
DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

H08998 1968 10,000 mean lower low water early Hawaiian Island 

H09130 1971/72 40,000 mean lower low water early Hawaiian Island 

H09611 1976 20,000 mean lower low water early Hawaiian Island 

H10126 1984 2,500 mean lower low water early Hawaiian Island 

H10169 1984 2,500 mean lower low water old Hawaiian 

Figure 5. Digital NOS hydrographic survey coverage in the Lahaina region. DEM boundary in red, NGA coastline in gray.
Taylor et al., 2008

2) USGS multibeam surveys

The USGS conducted high-resolution multibeam swath sonar surveys around the Hawaiian Islands in 

1998. These data were processed by USGS, with bathymetric DEMs posted online for public access. The 

DEM of the Maui survey (see Fig. 6), in the channels between Maui, Lanai, Kahoolawe, and Molokai was

downloaded from the USGS web site (http://walrus.wr.usgs.gov/pacmaps/mi_index.html). It has a 20-meter 

cell size and is in NAD83, UTM Zone 4 coordinates. NGDC also obtained the raw multibeam sonar files—

~1-meter resolution—for most of the USGS Hawaii surveys, with the exception of the Pailolo Channel

between Maui and Molokai, which are presumed lost.

Comparison of a bathymetric grid of the multibeam data with the USGS DEM revealed that seafloor

features were offset roughly 100 meters to the south in the DEM. Further comparison with coastal JALBTCX 

LiDAR data showed that the grid derived from the raw multibeam sonar data to be consistent with the 

coastal LiDAR data where the two datasets overlap to the southwest of Lahaina. NGDC chose to use the raw 

multibeam sonar data within ‘Au‘au Channel, and the USGS Maui DEM only in the northern region (Pailolo 

Channel) where the raw multibeam is not available.

 

Figure 6. Oblique view of the seafloor between the islands of Kahoolawe (foreground), Molokai, Lanai, and Maui. Image is derived 

from a DEM built from the USGS multibeam survey around Maui. The vertical exaggeration is 5 times. Image obtained from http://

walrus.wr.usgs.gov/pacmaps/mi-fig1.html.2

. Oblique overview of the seafloor between Kahoolawe (foreground), Molokai (background), Lanai (left side), and Maui (right side). Distance

between Lanai and Maui about 20 km. The sparse red regions between Lanai and Maui (A) are the present living reefs in water depths of less than 40 

m, dark orange areas (B) are drown reef platforms and pinnacles in water depths between 50 and 85 m. Large basin in middle of view (C) is shown 

in more detail in Figs. 2 and 3. Maui is known to be subsiding about 2 mm/y under the load of the volcano, a rate that must have slowed with time. 

In addition, long-term sea level rises and falls at about 2 mm/y. The area between Lanai and Maui has filled with lava flows as the islands subsided

and vertical growth of coral reefs kept pace with sea level fluctuations and island subsidence. Coral growth in the area between Lanai, Kahoolawe,

and Maui has not kept pace with fluctuations in sea level, island subsidence, and lava-flow buildup, and is now drowned. The scale across the bottom

of the image is10 km. The vertical exaggeration is 5x. [Extracted from web site.]
DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

3) JALBTCX LiDAR surveys

High-resolution bathymetric LiDAR surveys of coastal Hawaii have been performed by Joint Airborne 

LiDAR Bathymetry Technical Center of Expertise (JALBTCX; Fig. 7). The data were collected using the 

SHOALS3 (Scanning Hydrographic Operational Airborne Lidar Survey) system along the Maui coastline 

and parts of the Lanai and Molokai coasts. The LiDAR data have a horizontal accuracy of 3 meters, and a 

vertical accuracy of 15 cm. The surveys have point spacings of between 2 and 10 meters, and measure the 

seafloor down to about 40 meters depth.

Positive elevation values were present in the data, reflecting subaerial returns, and were excised by

NGDC prior to building the Lahaina DEM. Some anomalous values were also present in bathymetric regions, 

which were also deleted.

Figure 7. Spatial coverage of JALBTCX SHOALS bathymetric LiDAR surveys in the Lahaina region.

3. These data were collected by the SHOALS (Scanning Hydrographic Operational Airborne Lidar Survey) system, which consists of an airborne 

laser transmitter/receiver capable of measuring 400 soundings per second. The system operates from a deHavilland DHC-6 Twin Otter flying at

altitudes between 200 and 400 meters with a ground speed of about 100 knots. The SHOALS system also includes a ground-based data processing 

system for calculating acurate horizontal position and water depth. Lidar is an acronym for LIght Detection And Ranging. The system operates 

by emitting a pulse of light that travels from an airborne platform to the water surface where a small portion of the laser energy is backscattered to 

the airborne receiver. The remaining energy at the water’s surface propogates through the water column and reflects off the sea bottom and back

to the airborne detector. The time difference between the surface return and the bottom return corresponds to water depth. The maximum depth 

the system is able to sense is related to the complex interaction of radiance of bottom material, incident sun angle and intensity, and the type and 

quantity of organics or sediments in the water column. As a rule-of-thumb, the SHOALS system should be capable of sensing bottom to depths 

equal to two or three times the Secchi depth. [Extracted from metadata.]
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Taylor et al., 2008

 3.1.3 Topography

Topographic datasets in the Lahaina region were obtained from NOAA’s Coastal Services Center and the 

U.S. Geological Survey (Table 5; Fig. 8). 

Table 5. Topographic datasets used in compiling the Lahaina DEM.

Source Year Data Type Spatial 

Resolution

Original Horizontal 

Datum/Coordinate System

Original 

Vertical Datum URL

CSC Oahu/

Maui Mapping 

Project

2005 topographic 

LiDAR DEM ~ 2 meters NAD83, UTM Zone 4 Local Tidal 

Datum

USGS 2001 NED 1/3 arcsecond DEM ~10 m NAD83 geographic NAVD88

(meters) http://ned.usgs.gov/

Figure 8. Source and coverage of topographic datasets used in building the Lahaina DEM.
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DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

1) CSC Topographic Mapping Project

NOAA’s Coastal Services Center’s (CSC) Coastal Remote Sensing Program funded coastal topographic 

LiDAR surveys on the Hawaiian Islands of Oahu and Maui. The Maui survey data were collected4 in 2005 

and processed to bare earth5 by EarthData Aviation. CSC provided bare earth DEMs of the LiDAR data—2-

meter cell size—to NGDC for use in building the Lahaina DEM. Evaluation of the DEMs revealed that

buildings and other man-made features had been removed, though anomalous values within Lahaina Harbor 

appear to result from LiDAR returns from the ocean surface and moored vessels (Fig. 9). These values were 

removed by NGDC before building the Lahaina DEM. 

Figure 9. Color image of the CSC bare-earth DEM in the vicinity of Lahaina Harbor. The DEM shows anomalous 

elevation values within the harbor that presumably result from moored vessels, as well as the ocean surface (blue).

4. EarthData Aviation was contracted by EarthData International to collect ALS-40 Lidar data over the west coast of Maui, Hawaii. The project site 

was flown on March 16th and 24th of 2005, using aircraft N806CP. Lidar data was captured using an ALS-40 Lidarsystem, including an inertial

measuring unit (IMU) and a dual frequency GPS receiver. Lidar was obtained at an altitude of 762 meters (2,500 feet) above mean terrain, at an 

average airspeed of 130 knots. Sensor pulse rate was set at 20,000 Hz with a field of view of 25 degrees and a scan rate of 17 Hz. Average swath

width of the collected raw lines is 337 meters. Lidar data was recorded in conjunction with airborne GPS and IMU; the stationary GPS receiver 

was positioned over a control point located at the airport. Recorded digital data was shipped via external hard drive to the production facility for 

processing. During airborne data collection, an additional GPS receiver was in constant operation over a published National Geodetic Survey (NGS) 

control point at Kahului Airport. The control point with designation OGG ARP 2 and PID AA3608, is “A” Order horizontal with Third Order Class

II ellipsoid height. During the data acquisition, the receivers collected phase data at an epoch rate of 1 Hz. All GPS phase data was post processed 

with continuous kinematic survey techniques using “On the Fly” (OTF) integer ambiguity resolution. The GPS data was processed with forward 

and reverse processing algorithms. An adjustment was made to the ellipsoid height of the published point by Terrasurv to reflect Local Tidal Elevation. The results from each process, using the data collected at the airport, were combined to yield a single fixed integer phase differential solution

of the aircraft trajectory. [Extracted from metadata.]

5. 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 data set 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 clientspecified 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. (7) The final DEM was written to an ESRI grid format (.flt). [Extracted from metadata.]
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Taylor et al., 2008

2) USGS NED topography

The U.S. Geological Survey (USGS) National Elevation Dataset (NED; http://ned.usgs.gov/) provided 

complete 1/3 arc-second coverage of the Lahaina region6. Data are in NAD83 geographic coordinates and 

NGVD88 vertical datum (meters), and are available for download as raster DEMs. The extracted bare-earth 

elevations have a vertical accuracy of +/- 7 to 15 meters depending on source data resolution. See the USGS 

Seamless web site for specific source information (http://seamless.usgs.gov/). The dataset was derived from 

USGS quadrangle maps and aerial photographs based on topographic surveys; it has been revised using data 

collected in 1999 and 2004.

The NED data included “zero” elevation values over the open ocean (Fig. 10), which were removed 

from the dataset before gridding. Non-zero values still remained over the open ocean, which were visually 

inspected and compared with NOAA nautical charts, the NGA coastline, and Google Earth satellite imagery. 

ESRI Arc Catalog was used to clip the data to the NGA coastline. 

The NAVD88 vertical datum is established only for the North American mainland and has not been 

surveyed for Hawaii. The NED DEMs are therefore inferred to represent elevations relative to Mean Sea 

Level, not NAVD88.

Figure 10. Color image of the NED DEM in the vicinity of Lahaina. Blue represents “zero” values in the NED DEM over 

the open ocean. NGA coastline is shown in black.

6. The USGS National Elevation Dataset (NED) has been developed by merging the highest-resolution, best quality elevation data available across 

the United States into a seamless raster format. NED is the result of the maturation of the USGS effort to provide 1:24,000-scale Digital Elevation 

Model (DEM) data for the conterminous U.S. and 1:63,360-scale DEM data for Georgia. The dataset provides seamless coverage of the United 

States, HI, AK, and the island territories. NED has a consistent projection (Geographic), resolution (1 arc second), and elevation units (meters). The

horizontal datum is NAD83, except for AK, which is NAD27. The vertical datum is NAVD88, except for AK, which is NGVD29. NED is a living

dataset that is updated bimonthly to incorporate the “best available” DEM data. As more 1/3 arc second (10 m) data covers the U.S., then this will 

also be a seamless dataset. [Extracted from USGS NED website]
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DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

3.2 Establishing Common Datums

3.2.1 Vertical datum transformations

Datasets used in the compilation and evaluation of the Lahaina DEM were originally referenced to a number 

of vertical datums including Mean Lower Low Water (MLLW), Mean Low Water (MLW), Mean Sea Level (MSL), 

Local Tidal datum, and North American Vertical Datum of 1988 (NAVD88). All datasets were transformed to MHW to 

provide the worst-case scenario for inundation modeling, using values measured at the NOAA tidal station at Kahului,

Maui (#1615680; Table 6).

1) Bathymetric data

The NOS hydrographic and JALBTCX LiDAR surveys were transformed from MLLW to MHW, using 

FME software, by adding a constant offset of -0.577 m. The USGS raw multibeam data and Maui DEM are 

inferred to be referenced to MSL and were shifted by adding a constant offset of -0.238 m. 

2) Topographic data

The USGS NED 1/3 arc-second DEMs were originally referenced to NAVD88, which is not defined

in Hawaii: this dataset was inferred to be referenced to MSL. The CSC coastal LiDAR bare-earth DEMs 

were referenced to “Local Tidal” datum, which is undefined. They too are inferred to be referenced to MSL.

Conversion to MHW, using FME software, was accomplished by adding tide-station derived constant offsets 

(Table 6). 

Table 6. Relationship between Mean High Water and other vertical datums in the Lahaina region.*

Vertical datum Difference to MHW

MSL+ -0.238

MLW -0.478

MLLW -0.577

* Datum relationships measured at tide station #1615680, Kahului, Maui.

+ Topographic data referenced to Local Tidal datum or NAVD88 inferred to be equivalent to MSL.

3.2.2 Horizontal datum transformations

Datasets used to compile the Lahaina DEM were originally referenced to NAD83 geographic, NAD83 

UTM Zone 4, or WGS84 geographic horizontal datums. The relationships and transformational equations between 

these horizontal datums are well established. All data were converted to a horizontal datum of WGS84 using FME 

software.

3.3 Digital Elevation Model Development

3.3.1 Verifying consistency between datasets

After horizontal and vertical transformations were applied, the resulting ESRI shape files were checked in

ESRI ArcMap for inter-dataset consistency. Problems and errors were identified and resolved before proceeding with

subsequent gridding steps. The evaluated and edited ESRI shape files were then converted to xyz files in preparation

for gridding. Problems included:

•	 Presence of man-made structures and river banks in the NGA coastline dataset, which had to be removed.

•	 Inconsistencies between the NGA coastline dataset and bathymetric and topographic datasets. These 

inconsistencies are partly the result of lower resolution of the NGA coastline.

•	 Data values over the open ocean and rivers in the NED and CSC bare-earth DEMs. The DEMs required 

automated clipping to the NGA coastline.

•	 Offset of bathymetric features between the USGS raw multibeam data and the corresponding DEM built by 

USGS. The raw multibeam data were more consistent with overlapping JALBTCX LiDAR bathymetry along 

coastal Maui.
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Taylor et al., 2008

3.3.2 Gridding of raw USGS multibeam bathymetric data

MB-System (http://www.ldeo.columbia.edu/res/pi/MB-System/) was used to grid the raw multibeam 

sonar files from the USGS survey of the channel between Maui and Lanai. MB-System is an NSF-funded shareware software application specifically designed to manipulate submarine multibeam sonar data. The MB-System

tool ‘mbgrid’ applied a tight spline tension to the swath sonar data, and interpolated values for nearby cells without 

data. The resulting 1/3 arc-second ASCII grid was brought into ArcGIS for evaluation and conversion to MHW, and 

exported as xyz data for surfacing of all of the bathymetric data.

3.3.3 Smoothing of bathymetric data

The NOS hydrographic surveys are generally sparse at the resolution of the 1/3 arc-second Lahaina DEM: in 

deep water, the NOS survey data have point spacings up to 900 m apart. In order to reduce the effect of artifacts in the 

form of lines of “pimples” in the DEM due to this low resolution dataset, and to provide effective interpolation into 

the coastal zone, a 1 arc-second-spacing ‘pre-surface’ or grid was generated using GMT, an NSF-funded share-ware 

software application designed to manipulate data for mapping purposes (http://gmt.soest.hawaii.edu/).

The NOS hydrographic point data, in xyz format, were combined with the USGS and JALBTCX survey data 

into a single file, along with points extracted from the NGA coastline—to provide a “zero” buffer along the entire

coastline. These point data were then median-averaged using the GMT tool ‘blockmedian’ to create a 1 arc-second 

grid 0.05 degrees (~10%) larger than the Lahaina DEM gridding region. The GMT tool ‘surface’ then applied a tight 

spline tension to interpolate cells without data values. The GMT grid created by ‘surface’ was converted into an ESRI 

Arc ASCII grid file, and clipped to the coastline (to eliminate data interpolation into land areas). The resulting surface

was compared with the original soundings to ensure grid accuracy (e.g., Fig. 11), converted to a shape file, and then

exported as an xyz file for use in the final gridding process (see Table 7).

Figure 11. Histogram of the differences between NOS hydrographic survey H08522 (3,056 points) and the 1 arc-second 

pre-surfaced bathymetric grid. Discrepancies between survey soundings and the pre-surface grid result from the averaging 

of several closely spaced soundings.

3.3.4 Gridding the data with MB-System

MB-System (http://www.ldeo.columbia.edu/res/pi/MB-System/) was used to create the 1/3 arc-second 

Lahaina DEM. The MB-System tool ‘mbgrid’ applied a tight spline tension to the xyz data, and interpolated values for 

cells without data. The data hierarchy used in the ‘mbgrid’ gridding algorithm, as relative gridding weights, is listed in 

Table 7. Greatest weight was given to the high-resolution coastal bathymetric and topographic LiDAR surveys. Least 

weight was given to the pre-surfaced 1 arc-second bathymetric grid. The resulting Arc ASCII grids were seamlessly 

merged in ArcCatalog to create the final 1/3 arc-second Lahaina DEM.
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DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

Table 7. Data hierarchy used to assign gridding weight in MB-System.

Dataset Relative Gridding Weight

CSC coastal topographic LiDAR 10000

JALBTCX SHOALS coastal bathymetric LiDAR 10000

USGS multibeam sonar data 1000

USGS multibeam bathymetric DEM 100

USGS NED topographic DEM 100

NOS hydrographic surveys: bathymetric soundings 100

Pre-surfaced bathymetric 1 arc-second grid 1

3.4 Quality Assessment of the DEM

3.4.1. Horizontal accuracy

The horizontal accuracy of topographic and bathymetric features in the Lahaina DEM is dependent upon 

the datasets used to determine corresponding DEM cell values. Topographic features have an estimated accuracy 

of 10 to 15 meters: CSC coastal LiDAR data have an accuracy of between 1 and 3 meters, NED topography is 

accurate to within about 15 meters. Bathymetric features are resolved only to within a few tens of meters in deep-water 

areas (i.e., the southwest corner of the DEM). Shallow, near-coastal regions have an accuracy approaching that of 

subaerial topographic features. Positional accuracy is limited by: the sparseness of deep-water soundings; potentially 

large positional uncertainty of pre-satellite navigated (e.g., GPS) NOS hydrographic surveys; and the observed offset 

between the USGS raw multibeam data and the USGS bathymetric DEM derived from that multibeam data. 

3.4.2 Vertical accuracy

Vertical accuracy of elevation values for the Lahaina DEM is also highly dependent upon the source datasets 

contributing to DEM cell values. Topographic areas have an estimated vertical accuracy of 0.15 (for CSC coastal 

LiDAR data) to 7 meters (for NED topography). Bathymetric areas have an estimated accuracy of between 0.1 meters 

and 5% of water depth (~10 meters in the southwest corner of the DEM). Those values were derived from the wide 

range of input data sounding measurements from the early 20th century to recent, GPS-navigated sonar surveys. 

Gridding interpolation to determine values between sparse, poorly-located NOS soundings degrades the vertical 

accuracy of elevations in deep water. 

3.4.3 Slope maps and 3-D perspectives

ESRI ArcCatalog was used to generate a slope grid from the Lahaina DEM to allow for visual inspection and 

identification of artificial slopes along boundaries between datasets (e.g., Fig. 12). The DEM was transformed to UTM

Zone 4 coordinates (horizontal units in meters) in ArcCatalog for derivation of the slope grid; equivalent horizontal 

and vertical units are required for effective slope analysis. Three-dimensional viewing of the UTM-transformed DEM 

(e.g., Fig. 13) was accomplished using ESRI ArcScene. Analysis of preliminary grids revealed suspect data points, 

which were corrected before recompiling the DEM. Figure 1 shows a color image of the 1/3 arc-second Lahaina DEM 

in its final version
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Taylor et al., 2008

Figure 12. Slope map of the Lahaina DEM. Flat-lying slopes are white; dark shading denotes steep 

slopes; NGA coastline in red.

Figure 13. Perspective view from the south of the Lahaina DEM. NGA coastline in red; 

vertical exaggeration–times 3.
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DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

3.4.4	 Comparison with source data files

To ensure grid accuracy, the Lahaina DEM was compared to select source data files. Files were chosen on

the basis of their contribution to the grid-cell values in their coverage areas (i.e., had the greatest weight and did not 

significantly overlap other data files with comparable weight). A histogram of the difference between one CSC coastal

topographic LiDAR survey file—covering the town of Lahaina—and the Lahaina DEM is shown in Figure 14. Figure

15 shows a comparison between one JALBTCX coastal bathymetric survey—covering the marine region offshore

Lahaina—and the Lahaina DEM. Both show close agreement with the DEM, with the exception of areas where closely

spaced values contribute to one elevation in the DEM. Significant discrepancies between some data values and the

DEM resulted in reevaluation of the source data, further data editing and building of a revised DEM.

Figure 14. Histogram of the differences between one file of the CSC coastal topographic LiDAR survey (1,043,557 points) 

and the Lahaina DEM. The largest discrepancies result from the averaging of many closely spaced elevation values in 

regions of steep terrain.

Figure 15. Histogram of the differences between one file of the JALBTCX coastal bathymetric LiDAR survey (105,822 points) and the Lahaina 

DEM. The largest discrepancies result from the averaging of several closely spaced elevation values.

3.4.5 Comparison with NGS geodetic monuments

The elevations of 69 NOAA NGS geodetic monuments were extracted from online shape files of monument

datasheets (http://www.ngs.noaa.gov/cgi-bin/datasheet.prl), which give monument positions in NAD83 (sub-mm 

accuracy) and elevations in Local Tidal datums, which is assumed to be equivalent to MSL. Elevations were shifted 

to MHW vertical datum (see Table 6) for comparison with the Lahaina DEM (see Fig. 17 for monument locations). 
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Taylor et al., 2008

Differences between the Lahaina DEM and the NGS geodetic monument elevations range from -26 to 15 meters, 

with a positive value indicating that the DEM elevation value is greater than the monument elevation (Fig. 16). 

Examination of the monuments with the largest positive offsets from the DEM revealed that the corresponding DEM 

elevations derive from the USGS NED topographic DEMs. This is especially notable along the southeast coast of 

Molokai, where NED values of approximately 15 m extend some 30 meters offshore. The largest negative offset 

occurs where the position and/or elevation of an NGS monument (TU3194, on the southern coast of Lanai) appears 

to be incorrect.

Figure 16. Histogram of the differences between NGS geodetic monument elevations and the Lahaina DEM. 

Figure 17. Location of NGS monuments and NOAA tide stations in the Lahaina region. Blue circle locates tide station used 

to convert between vertical datums; NGS monument elevations were used to evaluate the Lahaina DEM.
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DIGITAL ELEVATION MODEL OF LAHAINA, HAWAII

4. Summary and Conclusions

A topographic–bathymetric digital elevation model of the Lahaina, Hawaii region, with cell spacing of 1/3 

arc-second, was developed for the Pacific Marine Environmental Laboratory (PMEL) NOAA Center for Tsunami

Research. The best available digital data from U.S. federal agencies were obtained by NGDC, shifted to common 

horizontal and vertical datums, and evaluated and edited before DEM generation. The data were quality checked, 

processed and gridded using ESRI ArcGIS, FME, GMT, and MB-System software. 

Recommendations to improve the Lahaina DEM, based on NGDC’s research and analysis, are listed below:

•	 Conduct topographic LiDAR surveys along the coasts of Molokai and Lanai.

•	 Obtain all of the raw multibeam files from the USGS bathymetric survey around Maui or rectify the

discrepancies between the USGS raw multibeam and the derived USGS bathymetric DEM.

5. Acknowledgments

The creation of the Lahaina DEM was funded by the NOAA, Pacific Marine Environmental Laboratory. The

authors thank Chris Chamberlin and Vasily Titov (PMEL), Darcee Killpack (NOAA Pacific Services Center), and

Jeff Lillycrop (USACE). The USGS raw multibeam files had been previously shared with B. Eakins by Jim Gardner

(USGS), also much appreciated.

6. References

Nautical Chart #19347, 18th Edition, 2005. Channels between Molokai, Maui, Lanai and Kahoolawe. Scale 1:80,000.

U.S. Department of Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #19348, 8th Edition, 2003. Approaches to Lahaina. Scale 1:15,000. U.S. Department of Commerce, 

NOAA, National Ocean Service, Coast Survey.

7. Data Processing Software

ArcGIS v. 9.2, developed and licensed by ESRI, Redlands, California, http://www.esri.com/

Electronic Navigational Chart Data Handler for ArcView, developed by NOAA Coastal Services Center, http://www.

csc.noaa.gov/products/enc/

FME 2006 GB – Feature Manipulation Engine, developed and licensed by Safe Software, Vancouver, BC, Canada, 

http://www.safe.com/

GEODAS v. 5 – Geophysical Data System, shareware developed and maintained by Dan Metzger, NOAA National 

Geophysical Data Center, http://www.ngdc.noaa.gov/mgg/geodas/

GMT v. 4.1.4 – Generic Mapping Tools, shareware developed and maintained by Paul Wessel and Walter Smith, 

funded by the National Science Foundation, http://gmt.soest.hawaii.edu/

MB-System v. 5.1.0, shareware developed and maintained by David W. Caress and Dale N. Chayes, funded by the 

National Science Foundation, http://www.ldeo.columbia.edu/res/pi/MB-System/