DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

noaa / NATIONAL OCEANIC AND

ATMOSPHERIC ADMINISTRATION

National Environmental Satellite,

Data, and Information Service

NOAA Technical Memorandum NESDIS NGDC-6

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA :

PROCEDURES, DATA SOURCES AND ANALYSIS 

L.A.Taylor

B.W. Eakins

K.S. Carignan

R.R. Warnken

T. Sazonova

D.C. Schoolcraft

G.F. Sharman

National Geophysical Data Center

Marine Geology and Geophysics Division

Boulder, Colorado

January 2008


DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

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-6

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA:

PROCEDURES, DATA SOURCES AND ANALYSIS

Lisa A. Taylor1

Barry W. Eakins2

Kelly S. Carignan2

Robin R. Warnken1

Tatiana Sazonova2

David C. Schoolcraft1

George F. Sharman1

1NOAA, National Geophysical Data Center, Boulder, Colorado

2Cooperative 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)
iii

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

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 ............................................................................................................8

3.1.3 Topography..........................................................................................................15

3.1.4 Topography–Bathymetry.....................................................................................19

3.2 Establishing Common Datums .................................................................................................20

3.2.1 Vertical datum transformations ...........................................................................20

3.2.2 Horizontal datum transformations.......................................................................20

3.3 Digital Elevation Model Development .....................................................................................21

3.3.1 Verifying consistency between datasets..............................................................21

3.3.2 Averaging of Beaufort County LiDAR data........................................................21

3.3.3 Interpolation of USACE bathymetric data ..........................................................21

3.3.4 Smoothing of bathymetric data ...........................................................................21

3.3.3 Gridding the data with MB-System.....................................................................22

3.4 Quality Assessment of the DEM...............................................................................................22

3.4.1 Horizontal accuracy.............................................................................................22

3.4.2 Vertical accuracy .................................................................................................23

3.4.3 Slope maps and 3-D perspectives........................................................................23

3.4.4	 Comparison with source data files.......................................................................25

3.4.5 Comparison with NOAA tidal stations................................................................25

3.4.6 Comparison with NGS geodetic monuments......................................................25

4. Summary and Conclusions...............................................................................................................26

5. Acknowledgments............................................................................................................................27

6. References........................................................................................................................................27

7. Data Processing Software ................................................................................................................28

List of Figures

Figure 1. Shaded-relief image of the Savannah, Georgia region ...............................................................1

Figure 2. Satellite image of the mouth of the Savannah River from DigitalGlobe....................................2

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

Figure 4. Coastlines in vicinity of McQueen Inlet, GA..............................................................................5

Figure 5. Coastlines in vicinity of Hilton Head, SC...................................................................................6

Figure 6. Digital coastline segments combined for use in the Savannah DEM.........................................7

Figure 7. Digital NOS hydrographic survey coverage in the Savannah region .........................................8

Figure 8. Nautical Chart #11517 showing non-existent obstruction in Fripp Inlet..................................11

Figure 9. Hydrographic survey coverage for H11502, which was not used in the Savannah DEM........12

Figure 10. Location of USACE survey data within dredged shipping channels and the Atlantic 

Intracoastal Waterway........................................................................................................12

Figure 11. Coverage of ENC datasets in the Savannah region ..................................................................14

Figure 12. Non-digital depths in Beaufort River........................................................................................14

Figure 13. Color image of part of the Chatham County DEM...................................................................15

Figure 14. Color image of part of the 1/3 arc-second surface generated from the Beaufort County 

LiDAR data........................................................................................................................16

Figure 15. Color image of the NED DEM in the vicinity of St. Catherine’s Island ..................................17

Figure 16. Coverage of CSC topographic coastal LiDAR data .................................................................18

Figure 17. Spatial coverage of JALBTCX high-resolution (5-meter point spacing) coastal bathymetric–

topographic LiDAR surveys in the vicinity of Savannah that were utilized in DEM 

development.......................................................................................................................19
iv

Taylor et al., 2008

Figure 18. Histogram of the difference between NOS hydrographic survey H10620 and 

 the 1 arc-second pre-surfaced bathymetric grid ................................................................22

Figure 19. Slope map of the 1/3 arc-second Savannah DEM ....................................................................23

Figure 20. Perspective view from the east of the 1/3 arc-second Savannah DEM ....................................24

Figure 21. Color image of the Savannah DEM..........................................................................................24

Figure 22.	 Histogram of the difference between one file of the JALBTCX coastal bathymetric–

topographic LiDAR survey and the 1/3 arc-second Savannah DEM................................25

Figure 23. Location of NGS monuments and NOAA tidal benchmark used for evaluating the 

Savannah DEM..................................................................................................................26

Figure 24. Histogram of the differences between NGS geodetic monument elevations and 

the 1/3 arc-second Savannah DEM....................................................................................26

List of Tables

Table 1.	 PMEL specifications for the Savannah DEM .............................................................................2

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

Table 3. NOAA nautical charts in the Savannah, Georgia region ............................................................4

Table 4. Bathymetric datasets used in compiling the Savannah DEM.....................................................8

Table 5. Digital NOS hydrographic surveys used in compiling the Savannah DEM...............................9

Table 6. USACE survey data within dredged channels and the Atlantic Intracoastal Waterway...........13

Table 7. Topographic datasets used in compiling the Savannah DEM...................................................15

Table 8. Combined topographic–bathymetric datasets used in compiling the Savannah DEM.............19

Table 9. Relationship between Mean High Water and other vertical datums in the 

 Savannah region ................................................................................................................20

Table 10. Data hierarchy used to assign gridding weight in MB-System.................................................22

Table 11. Comparison of NOAA tidal benchmark elevation, in meters above MHW, with the 

 1/3 arc-second Savannah DEM .........................................................................................25


DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

Digital Elevation Model of Savannah, Georgia:

Procedures, Data Sources and Analysis

1. Introduction

In December 2006, 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 

Savannah, Georgia (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 Method of 

Splitting Tsunami (MOST) 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 Savannah DEM. 

. The Savannah 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 Savannah, Georgia (32°05′ N, 81°06′ W) 

1/3 arc-second of latitude is equivalent to 10.27 meters; 1/3 arc-second of longitude equals 8.75 meters.

Figure 1. Shaded-relief image of 

the Savannah, Georgia region. 

Contour interval (referenced to 

Mean High Water): 10 meters.


Taylor et al., 2008

2. Study Area

The Savannah DEM covers the coastal area surrounding the Savannah River and includes the southern tip 

of South Carolina and easternmost Georgia. The region is characterized by barrier islands, tidal inlets, extensive sand 

shoals, and wide tidal marshlands. Barrier islands were formed by river deposition and by sea level fluctuation in the

Pleistocene. The islands are generally level but include recently formed dunes, visible in LiDAR data and satellite 

imagery that can reach up to 50 feet above mean sea level (MSL). River inlets are characterized by sandy shoals 

formed as large sediment loads are deposited at the coast. Sediment deposition, alongshore currents, and wave action 

modify the shoreline seasonally. 

Highly influenced by the tides, inland marshlands form a network of creeks, streams, and estuaries that are

prone to seasonal and tidal flooding (Fig. 2). The marshlands have been influenced by deposition of sediment during

periods of high sea level, and erosion during periods of lower sea level.

Figure 2. Satellite image of the mouth of the Savannah River from DigitalGlobe.

3. Methodology

The Savannah 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 Savannah DEM.

Grid Area Savannah, Georgia

Coverage Area 81.35 o to 80.35o W; 31.5o to 32.45o 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 SAVANNAH, GEORGIA

3.1 Data Sources and Processing

Shoreline, bathymetric, topographic and combined topographic–bathymetric digital datasets (Fig. 3) were 

obtained from several U.S. federal and state agencies, including: NOAA’s National Ocean Service (NOS), Office

of Coast Survey (OCS), Coastal Services Center (CSC), National Geodetic Survey (NGS), and NGDC; the U.S. 

Geological Survey (USGS); the U.S Army Corps of Engineers (USACE); Chatham County, Georgia; and Beaufort 

County, South Carolina. 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 the NOAA Savannah tidal station, 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 Savannah DEM.
Taylor et al., 2008

3.1.1 Shoreline

Three digital coastline datasets of the Savannah region were analyzed for inclusion in the Savannah DEM: 

Office of Coast Survey electronic navigational charts, Coastal Services Center vector shoreline, and Beaufort County,

South Carolina digital coastline (Table 2).

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

Source Year Data Type Spatial Resolution

Original Horizontal 

Datum/Coordinate 

System

Original 

Vertical 

Datum

URL

OCS Electronic 

Navigational 

Charts

2006 MHW 

coastline

Digitized from 1:20,000 and 

1:80,000 scale charts WGS84 geographic MHW http://chartmaker.ncd.noaa.gov/

CSC 1992 MHW 

coastline Various NAD83 geographic MHW

http://www.

csc.noaa.gov/

shoreline/data_

central.html

Beaufort Co. 2002

LiDARdefined

coastline

1 meter

NAD83 State Plane 

South Carolina, int’l 

feet

NAVD88

1) OCS electronic navigational charts

Four electronic navigational charts (ENC) were available for the Savannah region (Table 3) and were 

downloaded from NOAA’s Office of Coast Survey (OCS) website (http://chartmaker.ncd.noaa.gov/); the 

ENCs are digital versions of NOAA’s published nautical charts. The NOAA Coastal Services Center’s 

‘Electronic Navigational Chart Data Handler for ArcView’ extension (http://www.csc.noaa.gov/products/

enc/) was used to import the data into ArcGIS. The chart data include coastline data files (MHW), which were

compared with the other coastline datasets, high-resolution coastal LiDAR data, topographic data, and NOS 

hydrographic soundings. The ENCs also include soundings (extracted from NOS hydrographic surveys) and 

land elevations.

The ENC coastline for Charts #11505, 11512, and 11514 generally corresponded well with the highresolution coastal LiDAR data (near-shore soundings and topography). Manual editing in ESRI ArcMap was 

required to eliminate piers and docks, and to fit ENC #11505 and #11512 to the JALBCTX Georgia bare

earth DEM. The coastline extracted from ENC #11513 was at a lower resolution and did not match other data 

sets well. It was used only where no other coastline data was available. The ENCs did not provide complete 

coverage of the Savannah region, and so were used in conjunction with other datasets to build a ‘combined 

coastline’ (Fig. 4).

Other NOAA nautical charts in the Savannah area (Table 3) were only available in raster format and were 

used to evaluate the accuracy and completeness of the coastline datasets. 

Table 3. NOAA nautical charts in the Savannah, Georgia region.

RNC 

# Scale Title Edition Edition date ENC available

11 505 1:40,000 SAVANNAH RIVER APPROACH 3rd 2006-08-01 yes

11 507 1:40,000 BEAUFORT RIVER TO ST SIMONS SOUND SIDE 32nd 2004-12-01 no

11 509 1:80,000 TYBEE ISLAND TO DOBOY SOUND 29th 2005-08-01 no

11 510 1:40,000 SAPELO AND DOBOY SOUNDS 19th 2004-05-01 no

11 511 1:40,000 OSSABAW AND ST CATHERINES SOUNDS 17th 2004-06-01 no

11 512 1:40,000 SAVANNAH RIVER AND WASSAW SOUND 61st 2006-10-01 yes

11 513 1:80,000 ST HELENA SOUND TO SAVANNAH RIVER 25th 2006-04-01 yes

11 514 1:20,000 SAVANNAH RIVER SAVANNAH TO BRIER CREEK 28th 2005-11-01 yes

11 516 1:40,000 PORT ROYAL SOUND AND INLAND PASSAGES 31st 2006-08-01 no

11 517 1:40,000 ST HELENA SOUND 17th 2001-08-25 no

11 518 1:40,000 INTRACOASTAL WATERWAY CASINO CREEK TO BEAUFORT 

RIVER 35th 2006-05-01 no

11 519 1:40,000 PARTS OF COOSAW AND BROAD RIVERS 12th 2003-04-01 no

11 521 1:80,000 CHARLESTON HARBOR AND APPROACHES 28th 2006-02-01 no
DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

2) CSC vector shoreline

NOAA’s National Ocean Service (NOS) and National Geodetic Survey (NGS) have developed a highresolution vector shoreline for parts of the U.S. East Coast. The shoreline is complied from NOS shoreline 

maps (T-sheets) and CAD-based Standard Digital Data Exchange Format (SDDEF) data. 

This shoreline dataset covers both South Carolina and Georgia. It is the primary dataset used in the 

southwestern portion of the Savannah DEM, as no other high-resolution coastline data was available for this 

area. Shapefiles were downloaded from the CSC web site and were edited inArcMap to remove data coverage

boundaries. The dataset was consistent with the NOAA raster nautical charts (RNCs), but not recent, highresolution LiDAR surveys along the coast (e.g., Fig 4). It was therefore edited to match the LiDAR data on 

the barrier islands in Georgia. Inland areas were edited to match the RNC coastline. 

Figure 4. Coastlines in vicinity of McQueen Inlet, GA. CSC vector shoreline in aqua matches the RNC #11509 depicted 

coastline. Red-brown is 2006 coastal LiDAR data; purple-blue is 1999 coastal LiDAR data. The CSC coastline was 

modified to be consistent with the coastal LiDAR data.
Taylor et al., 2008

3) Beaufort County shoreline

Beaufort County, South Carolina has produced a topographic dataset using LiDAR data and aerial 

photography, which was provided to NGDC by Jason Flake of the Beaufort County, South Carolina GIS 

Department. Within this dataset, a coastline dataset was developed to ensure accurate contouring of point 

elevation data. This dataset was used in the Savannah DEM as the primary coastline for the northeast portion 

of the DEM, as the point elevation data was used in that region as well (see Fig. 3). Some editing was 

necessary to remove extraneous features such as docks and piers, as well as smaller inlets and streams that 

contained no digital bathymetric data to constrain their depths. The ocean-facing shoreline was edited to 

match more recent coastal LiDAR data (Fig. 5).

Figure 5. Coastlines in vicinity of Hilton Head, SC. ENC coastlines and Beaufort County coastline were compared with 

coastal LiDAR data and NOS hydrographic survey data. Both coastlines differ from the LiDAR by approximately 50m and 

were shifted to be consistent with the LiDAR data.
DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

To obtain the best digital MHW coastline, NGDC combined the ENC, CSC and Beaufort County coastlines. 

Where overlap occurred, this ‘combined coastline’ (Fig. 6) was manually adjusted in many places, using ArcGIS, 

to match the high-resolution coastal LiDAR data (e.g., Fig. 5). The combined coastline was converted to point data 

for use as a coastal buffer for the bathymetric pre-surfacing algorithm (see Section 3.3.4) to ensure that interpolated 

bathymetric values reached “zero” at the coast. It was also used to clip topographic DEMs, which contained elevation 

values, typically zero, over rivers and the open ocean (see Section 3.1.3). 

Figure 6. Digital coastline segments combined for use in the Savannah DEM.
Taylor et al., 2008

3.1.2 Bathymetry

Bathymetric datasets used in the compilation of the Savannah DEM include 105 NOS hydrographic surveys, 

22 USACE surveys of dredged shipping channels, extracted soundings from one ENC, and NGDC-digitized soundings 

from RNC #11516 (Table 4). 

Table 4. Bathymetric datasets used in compiling the Savannah DEM.

Source Year Data Type Spatial Resolution

Original 

Horizontal Datum/

Coordinate System

Original 

Vertical 

Datum

URL

NOS 1925 to 

2005

Hydrographic 

survey 

soundings

Ranges from 4 to 400 meters 

(varies with scale of survey, 

depth, traffic and probability

of obstructions)

NAD27, NAD83

MLW or 

MLLW

(meters)

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

mgg/bathymetry/hydro.html

USACE 1960s 

to 2002

Bathymetric 

surveys Ranges from .3 to 15 meters

NAD83 State 

Plane (GA and 

SC)

MLW or 

MLLW

(meters)

OCS 

ENC 

#11514

2006 Extracted ENC 

sounding data 1:20,000 WGS84 MLLW(meters)

http://chartmaker.ncd.noaa.

gov/

RNC 

#11516 2006

Digitized 

sounding data 

points

1:40,000 WGS84

soundings 

in MLLW

(feet)

http://chartmaker.ncd.noaa.

gov/

1) NOS hydrographic survey data

A total of 105 NOS hydrographic surveys conducted between 1925 and 2005 were utilized in the Savannah 

DEM development (Fig. 7; Table 5). The hydrographic survey data were originally vertically referenced to 

either Mean Lower Low Water (MLLW) or Mean Low Water (MLW) and horizontally referenced to either 

NAD27 or NAD83 datums.

Figure 7. Digital NOS hydrographic survey coverage in the Savannah region. Red denotes boundary of Savannah DEM.
DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

Table 5. Digital NOS hydrographic surveys used in compiling the Savannah DEM.

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

D00069 1982/83 40,000 mean lower low water NAD27

D00090* 1982/83 20,000 mean lower low water NAD27

F00414 1995 10,000 mean lower low water NAD83

F00417 1995 10,000 mean lower low water NAD83

F00431 1997 10,000 mean lower low water NAD83

F00501 2005 10,000 mean lower low water NAD83

H04470 1925 20,000 mean low water NAD1913

H04472 1925 20,000 mean low water NAD1913

H04475 1925 20,000 mean lower low water NAD27

H05117 1931 10,000 mean low water NAD27

H05119 1931 20,000 mean low water NAD27

H05130 1931 10,000 mean low water NAD27

H05134 1931 40,000 mean low water NAD27

H05517 1934 10,000 mean low water NAD27

H05518 1933/34 10,000 mean low water NAD27

H05519 1933 10,000 mean low water NAD27

H05520 1934 10,000 mean low water NAD27

H05525 1934 10,000 mean low water NAD27

H05526 1934 10,000 mean low water NAD27

H05527 1934 10,000 mean low water NAD27

H05528 1934 10,000 mean low water NAD27

H05529 1934 10,000 mean low water NAD27

H05530 1934 10,000 mean low water NAD27

H05549 1934 10,000 mean low water NAD27

H05550 1934 10,000 mean low water NAD27

H05551 1934 10,000 mean low water NAD27

H05552 1934 10,000 mean low water NAD27

H05560 1934 10,000 mean low water NAD27

H05561 1934 10,000 mean low water NAD27

H05562 1934 10,000 mean low water NAD27

H05563 1934 10,000 mean low water NAD27

H05564 1934 10,000 mean low water NAD27

H05565 1934 10,000 mean low water NAD27

H05568 1934 10,000 mean low water NAD27

H05569 1934 10,000 mean low water NAD27

H05570 1934 10,000 mean low water NAD27

H05571 1934 10,000 mean low water NAD27

H05572 1934 10,000 mean low water NAD27

H05573 1934 10,000 mean low water NAD27

H05574 1934 10,000 mean low water NAD27

H05575 1934 10,000 mean low water NAD27

H05580 1934 10,000 mean low water NAD27

H05582 1934 10,000 mean low water NAD27

H05583 1934 10,000 mean low water NAD27

H05584 1934 10,000 mean low water NAD27

H05585 1934 10,000 mean low water NAD27

H05586 1934 10,000 mean low water NAD27

H05592 1934 10,000 mean low water NAD27

H05593 1934 10,000 mean low water NAD27

H05596 1934 10,000 mean low water NAD27

H05597 1934 10,000 mean low water NAD27

H05598 1934 10,000 mean low water NAD27

H05599 1934 20,000 mean low water NAD27
10

Taylor et al., 2008

H05632 1934 10,000 mean low water NAD27

H05633 1934 10,000 mean low water NAD27

H05650 1934 10,000 mean low water NAD27

H05654 1934 20,000 mean low water NAD27

H05717 1934 10,000 mean low water NAD27

H05718 1934 10,000 mean low water NAD27

H05719 1934 10,000 mean low water NAD27

H05721 1934 10,000 mean low water NAD27

H06025 1934 10,000 mean low water NAD27

H08364 1956 10,000 mean low water NAD27

H08365 1957 12,500 mean low water NAD27

H08477 1957 10,000 mean low water NAD27

H09144 1973/74 40,000 mean low water NAD27

H09145 1972/73 40,000 mean low water NAD27

H09197 1971/73 20,000 mean low water NAD27

H09198 1971/72 40,000 mean low water NAD27

H09211 1973 20,000 mean low water NAD27

H09299 1972 80,000 mean low water NAD27

H09314 1973 20,000 mean low water NAD27

H09360 1974 10,000 mean low water NAD27

H09363 1973 20,000 mean low water NAD27

H09364 1973 20,000 mean low water NAD27

H09375 1974 80,000 mean low water NAD27

H09429 1974 40,000 mean low water NAD27

H09459 1974 10,000 mean low water NAD27

H09460 1974 20,000 mean low water NAD27

H09461 1974 20,000 mean low water NAD27

H09462 1974 20,000 mean low water NAD27

H09472 1974 20,000 mean low water NAD27

H09865 1980 20,000 mean lower low water NAD27

H10576 1994 10,000 mean lower low water NAD83

H10577 1994 10,000 mean lower low water NAD83

H10581 1994/95 10,000 mean lower low water NAD83

H10582 1994/95 10,000 mean lower low water NAD83

H10591 1995 10,000 mean lower low water NAD83

H10597 1995 10,000 mean lower low water NAD83

H10600 1995 10,000 mean lower low water NAD83

H10609 1995 10,000 mean lower low water NAD83

H10613 1995 10,000 mean lower low water NAD83

H10620 1995 10,000 mean lower low water NAD83

H10624 1995 10,000 mean lower low water NAD83

H10627 1995 10,000 mean lower low water NAD83

H10629 1995 10,000 mean lower low water NAD83

H10630 1995 10,000 mean lower low water NAD83

H10631 1995 10,000 mean lower low water NAD83

H10642 1995 10,000 mean lower low water NAD83

H10643 1995 10,000 mean lower low water NAD83

H10656 1995 10,000 mean lower low water NAD83

H11140 2002 10,000 mean lower low water NAD83

H11145 2002 10,000 mean lower low water NAD83

H11466 2005 10,000 mean lower low water NAD83

* Survey D00090 was not used as the point data were inconsistent with RNC #11514. ENC soundings were 

used in place of this survey.
11

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

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 database (http://

www.ngdc.noaa.gov/mgg/bathymetry/hydro.html) in their original datums (Table 5). The data were then 

converted to WGS84 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 (~5%) larger than the 1/3 arc-second gridding 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 

the USACE multibeam and coastal LiDAR data, NED topographic data, the combined coastline, RNCs, and 

Google Earth satellite imagery. All NOS surveys were manually checked for digitizing errors or erroneous 

data points using ArcMap. Because the coastline has changed considerably in the past century, the position 

of many of the inland NOS survey data points had to be adjusted manually to be consistent with the modern 

‘river’ coastline.

Analysis of surfaced NOS data showed two discrepancies between survey data and NOAA nautical 

chart data. First, in Fripp Inlet, SC older NOS survey data (H05717) did not correspond to more recent raster 

chart data: a depression in the survey data did not appear on the chart #11517 (Fig. 8), which instead noted 

an obstruction. In researching an associated depth for the “obstruction fish haven” the feature was found to

be non-existent. This information was provided by Robert Martore of the Office of Fisheries Management,

Marine Resource Division, South Carolina Department of Natural Resources. 

Figure 8. Nautical Chart #11517 showing non-existent obstruction in Fripp Inlet.

Secondly, one recent NOS hydrographic survey, H11502, contained soundings that were up to 10 meters 

shallower than other survey soundings in the same region. The metadata for the survey identified the units

as feet and a vertical datum of NAVD88; NOS surveys are always reported in either MLW or MLLW. The 

metadata was assumed to be incorrect: taking the units to be meters instead of feet produced more consistent 

soundings. As other survey data covered the specific region completely (Fig. 9), and the metadata was

determined to be incorrect, survey #H11502 was not used in the DEM.
12

Taylor et al., 2008

Figure 9. Hydrographic survey coverage for H11502 (yellow), which was not used in the Savannah DEM.

2) USACE surveys of dredged shipping channels and the Intracoastal Waterway

The USACE Hydrographic Surveys Division of the Savannah and Charleston Districts provided NGDC 

with recent survey data in dredged shipping channels (Savannah River and Port Royal Sound) and the Atlantic 

Intracoastal Waterway (Fig. 10). All data were originally in NAD83 State Plane coordinates (Georgia or 

South Carolina), and in either MLW or MLLW vertical datum (Table 6).

Figure 10. Location of USACE survey data within dredged shipping channels and the Atlantic Intracoastal Waterway.
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DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

Table 6. USACE survey data within dredged channels and the Atlantic Intracoastal Waterway.

Region File name Original horizontal datum 

Original 

vertical 

datum

Spatial Resolution 

Port Royal 

Sound 2690926 NAD83 South Carolina State Plane MLW

4 parallel survey lines spaced 

~40m apart with < 1m point 

spacing along track

2700927 NAD83 South Carolina State Plane MLW

3 parallel survey lines spaced 30m 

and 50m apart at the northern end 

and continuing south 4 parallel 

survey lines spaced ~30m to 

~50m at southern most end; point 

spacing along track <1m

2710928 NAD83 South Carolina State Plane MLW

4 parallel survey lines ~50m 

spacing at northern most end and 

~25m continuing southeast ending 

in single track; all in track point 

spacing averaging <1m 

r690926 NAD83 South Carolina State Plane MLW single survey line with ~1m point 

spacing

r690927 NAD83 South Carolina State Plane MLW

3 parallel survey lines spaced 40m 

and 60m apart with < 1m point 

spacing in track

Intracoastal 

Waterway aiww_savh_brun_2006 NAD83 Georgia State Plane, 

eastern zone

MLLW single along channel survey line < 

1m spacing

aiww_savh_portroyal_

2006

NAD83 Georgia State Plane, 

eastern zone

MLLW

3 parallel survey lines along 

channel ~20m spacing with < 10m 

point spacing in track

2410829 NAD83 South Carolina State Plane MLW

2 parallel survey lines ~25m 

spacing with <.5m point spacing 

in track

Savannah River

savh_1_dump, savh_2_

dump, savh_3_dump, 

savh_4_dump, savh_5_

dump, and savh_6_dump

NAD83 Georgia State Plane, 

eastern zone

MLLW

~450m by 975m block of 9 

parallel track lines ~50m spacing 

and < 1m point spacing in track

savh_7_dump NAD83 Georgia State Plane, 

eastern zone

MLLW

2 blocks ~450m by ~975m one 

of 14 parallel track lines and 

the other of 15 track lines ~30m 

spacing with < 1m point spacing 

in track

savh_8_dump NAD83 Georgia State Plane, 

eastern zone

MLLW

1 block ~450m by ~975m of 15 

parallel track lines ~30m spacing 

with < 1m point spacing in track

savh_exam_63Bto85B_

may1997

NAD83 Georgia State Plane, 

eastern zone

MLW

set of channel profiles ~450m

wide and spaced ~150m apart with 

~5m point spacing

savh_exam_bar_aug2006 NAD83 Georgia State Plane, 

eastern zone

MLLW

set of channel profiles ~450m

wide and spaced ~150m apart with 

< 1m point spacing

savh_osd NAD83 Georgia State Plane, 

eastern zone

MLLW

1 block ~4150m by ~3800m of 

parallel track lines ~150m spacing 

with ~ 10m point spacing in track

Tybee Island tybee_borrow_21dec05 NAD83 Georgia State Plane, 

eastern zone

MLLW

1 block ~850m by ~1650m of 12

parallel track lines spaced ~80m 

apart with < 1m point spacing in 

track

tybee_feb2005 NAD83 Georgia State Plane, 

eastern zone

MLLW

profile track lines surrounding

Tybee I. spacing from 35m to 

275m apart with < 1m point 

spacing in track

savh_offshore_

tybeedisposal

NAD83 Georgia State Plane, 

eastern zone

MLLW grouping of tracklines ~ 30m apart 

with ~10 point spacing in track 
14

Taylor et al., 2008

3) OCS Nautical Chart Soundings

Digital soundings from ENC #11514 (Fig. 11) were used to augment the NOS hydrographic survey data 

in the upper reaches of the Savannah River, as NOS survey D00090 was inconsistent with the RNC version 

of the chart and the modern coastline; D00090 was not utilized in developing the Savannah DEM. There 

were also no digital NOS hydrographic data available for part of the Beaufort River (Fig. 12). NGDC hand 

digitized soundings in this region from RNC #11516 to fill the gap between NOS surveys.

Figure 11. Coverage of ENC datasets in the Savannah region. ENC #11514 was used in the Savannah DEM, as were some 

hand digitized soundings from RNC #111516.

Figure 12. Non-digital depths in Beaufort River. RNC #11516 (background image) with NOS hydrographic survey data shown in pink and green, 

illustrate the gap in bathymetric data within Beaufort River. The gap in digital sounding data was filled by hand digitizing soundings on chart 

#11516.
15

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

3.1.3 Topography

Topographic datasets in the Savannah region were obtained from Chatham County, Georgia, Beaufort County, 

South Carolina, the U.S. Geological Survey, and NOAA Coastal Services Center (Table 7).

Table 7. Topographic datasets used in compiling the Savannah DEM.

Source Year Data Type Spatial Resolution

Original Horizontal 

Datum/Coordinate 

System

Original 

Vertical Datum URL

Beaufort County, 

SC 2002 LiDAR ~1.25 meter South Carolina State 

Plane (intl. feet)

NAVD88

(feet)

USGS NED 2006 Topographic 

DEM 1 arc-second DEM NAD83 geographic NGVD29(meters) http://ned.usgs.gov/

CSC 1997–

2000 LiDAR 5-meter point spacing NAD83 geographic NAVD88 (meters)

http://maps.csc.

noaa.gov/TCM/

1) Chatham County topographic DEM

Chatham County, Georgia has developed a ‘hydrologically-correct’ topographic DEM of the entire 

county and surrounding areas, combining LiDAR data and USGS NED topography (for areas not covered 

by LiDAR). An airborne LiDAR survey was conducted in 1999 to generate countywide 1-foot contours. The 

data was then used to generate a DEM with 15-foot cell size, which was modified to be consistent with known

hydrologic flow in Chatham County. The Chatham County DEM—Georgia State Plane (feet) and NAVD88

(feet) datums—was provided to NGDC by William Brooks of NOAA’s Coastal Services Center.

The Chatham County DEM was clipped to the county line, and then to the combined coastline. NGDC’s 

analysis of the clipped DEM revealed many north–south and east­–west artifacts that appear to have been 

introduced during the development of the initial DEM (Fig. 13). The artifacts are expressed as meter-high 

offsets, and are interpreted as mismatches between the LiDAR and NED topographic data. NGDC could not 

eliminate these offsets, and as the offsets would significantly affect modeling of coastal flooding, this dataset

was not used in building the Savannah DEM.

Figure 13. Color image of part of the Chatham County DEM. The north–south and east–west artifacts are meter-high offsets within 

the DEM, and are inferred to represent mismatches between the LiDAR and NED topographic data used by the county to build the 

DEM. This dataset was ultimately deemed inappropriate for coastal inundation modeling.
16

Taylor et al., 2008

2) Beaufort County LiDAR topography

In 2002, Beaufort County, South Carolina funded a LiDAR survey, at 1-foot spacing, of the entire county 

for storm-water management purposes. Data from the survey were provided to NGDC by Jason Flake 

of the Beaufort County GIS Department. Data were in South Carolina State Plane coordinates (NAD83, 

international feet), and NAVD88 vertical datum (feet) and were provided as 245 separate coverage tiles, each 

containing up to 5 million elevation points—for a total of 742 million points in the Savannah DEM area.

The data were processed to “bare earth”, and reduced to ~1.25-meter point spacing (4 feet), though there are 

numerous gaps on the order of 5 to 10 meters throughout the dataset. The dataset also contains values from 

the surface of water bodies. 

NGDC transformed this massive dataset to WGS84 and MHW datums, and to ArcGIS shapefiles, which

were subsequently clipped to a boundary 5% larger than the Savannah DEM. The remaining point data were 

then ‘surfaced’ to a 1/3 arc-second (~10 m cell-size) raster (see Section 3.3.2). Surfacing permitted clipping 

of the dataset to the combined coastline, which excised water-surface returns from the open ocean and rivers 

where NOS hydrographic survey data was available. Noticeable in the original dataset, though subtler in 

the smoothed 1/3 arc-second surface, are northwest–southeast trending foot-high offsets between what are 

apparently LiDAR survey tracks (e.g., Fig 14). These artifacts could not be removed and, as this dataset is the 

best available topographic data for Beaufort County, are therefore present in the Savannah DEM. 

Figure 14. Color image of part of the 1/3 arc-second surface generated from the Beaufort County LiDAR data. The northwest–

southeast trending lineations (foot-high offsets) are inferred to represent the edges of LiDAR survey tracks. Note the “wave” pattern in 

the bottom portion of the image, caused by LiDAR returns from the surface of the Atlantic Ocean. The water returns were eliminated 

by clipping to the combined coastline.

2. With the inception of the Beaufort County Stormwater Utility, the County was tasked with developing detailed county-wide watershed management plans for the primary drainage system, hence the need for accurate 1 foot topography. In 2002, Beaufort County elected to acquire 1 foot 

county-wide topography derived from LiDAR. Airborne LiDAR mapping is an integration of technologies that enables the capture of accurate 

topographic data. The technology combines GPS (global positioning system), precision inertial aircraft guidance system, LiDAR (light detection and ranging laser) and computer processing. Basically, a high accuracy scanner sweeps the laser pulses across the flight path (approximately

33,000 pulses per second) and collects the reflected light. The laser range-finder measures the time between sending and receiving each laser pulse

to determine the elevation. All the topographic data sets were developed in South Carolina State Plane NAD83, International Feet, and NAVD88. 

The LiDAR data and the Aerial Photography were developed from a survey control network that was established for the LiDAR project. In order 

to achieve accurate and consistent results, any data utilized in conjunction with the LiDAR and Aerial Photography must utilize this same control 

network. The LiDAR coverage area is defined by the County boundary and the 3.75 foot contour for tidally affected areas of Beaufort County. The

bare earth points are the foundation data set for the LiDAR derived topographic data for Beaufort County. [Extracted from metadata]
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DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

3) USGS NED topography

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

complete 1 arc-second coverage of the contiguous lower 48 states3. Data are in NAD83 geographic coordinates 

and NAVD88 vertical datum (meters), and are available for download as raster DEMs. The extracted bareearth 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 quad maps and aerial photos based on surveys conducted in the 1970s and 1980s.

The NED data included “zero” elevation values over the open ocean (Fig. 15), which were removed from 

the dataset before gridding. Some anomalous values still remained over the open ocean, which were visually 

inspected and compared with NOAA nautical charts, the combined coastline, and Google Earth satellite 

imagery. These points were removed in ESRI ArcCatalog by clipping to the combined coastline.

Figure 15. Color image of the NED DEM in the vicinity of St. Catherine’s Island. A) NED DEM. Note mismatch between 

NED topography, derived from USGS topographic quadrangles, and the combined coastline (black), derived from modern 

topographic datasets. Data values over the open ocean (dark blue) had to be excised prior to gridding. B) Google Earth 

satellite image of same region.

3. 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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Taylor et al., 2008

4) CSC coastal LiDAR surveys

NOAA Coastal Services Center (CSC) provides online access to coastal topographic LiDAR surveys 

along the U.S. East Coast. Data in the Savannah region were collected in 1997, 1999, and 2000 with a LiDAR 

instrument that uses a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation 

and coastal topography4. Coastal LiDAR data in the Savannah region were downloaded from the CSC 

website (http://www.csc.noaa.gov/lidar/) in NAD83 geographic coordinates (meters) and NAVD88 (meters) 

at 5-meter point spacing. The LiDAR elevation points are horizontally accurate to +/- 0.8 meters at an aircraft 

altitude of 700 meters; raw elevation measurements are vertically accurate to within 15 cm. No processing 

was done by CSC to remove returns from water or vegetation. Thus, data values offshore primarily represent 

wave features on the ocean surface, not true topography. These data were not processed to bare earth, and thus 

include man-made structures and vegetation.

Examination of the near-shore data by NGDC indicated that a cutoff of 1 meter below MHW would 

effectively eliminate most of the open-ocean surface returns while retaining much of the beach-face 

morphology, as the surveys were generally flown near low tide. Visual inspection of each ESRI shape file

after clipping revealed some remaining offshore data points. These points were evaluated in conjunction with 

NOAA nautical charts and GoogleEarth satellite imagery. Many were sea-surface returns and navigation 

buoys, which were excised. 

Figure 16. Coverage of CSC topographic coastal LiDAR data. Data were collected in 1997, 1999, and 2000.

4. Laser beach mapping uses a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation and coastal topography. The 

laser emits laser beams at high frequency and is directed downward at the earth’s surface through a port opening in the bottom of the aircraft’s fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft.

The aircraft travels over the beach at approximately 60 meters per second while surveying from the low water line to the landward base of the sand 

dunes. This data set was collected with a LIDAR (LIght Detection And Ranging) instrument designed and developed by the Observational Sciences 

Branch (OSB) of NASA at the Wallops Flight Facility in Virginia. The instrument, originally designed for mapping ice sheets in Greenland, is called 

the Airborne Topographic Mapper or ATM. The ATM II (the latest version), operates with a Spectra Physics laser transmitter, which provides a 7 

nanoseconds long, 250 microjoules pulse at a frequency-doubled wavelength of 523 nanometers in the blue-green spectral region. The laser transmitter can function at pulse rates from 2 to 10 kilohertz (kHz). The laser system with a separate cooling unit weighs approximately 45 kilograms 

(kg) and requires approximately 15 amperes of power at 115 volts. The transmitted laser pulse is reflected to the surface of the earth with the aid of

a small folding mirror mounted on the back of a secondary mirror of a rotating scan mirror assembly mounted directly in front of the telescope. The 

scan mirror, which is rotated at 20 hertz, is comprised of a section of round aluminum stock, machined to a specific off-nadir angle. A scan mirror

with the off-nadir angle of 15 degrees was utilized, producing an elliptical scan pattern with a swath width equal to 50 percent of the approximately 

700-meter aircraft altitude. The reflected laser pulse is transmitted to a photo-multiplier assembly that consists of a lens, a narrow bandpass filter,

and a single photomultiplier tube. [Extracted from metadata]
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DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

3.1.4 Topography–Bathymetry

Combined topographic–bathymetric surveys of coastal Georgia and South Carolina (Fig. 17) were performed 

in 2006 by the Joint Airborne LiDAR Bathymetry Technical Center of Expertise (JALBTCX; Table 8). The data were 

collected using the CHARTS (Compact Hydrographic Airborne Rapid Total Survey) system to depict elevations above 

and below water along the immediate coastal zone5. The surveys generally extend 750 meters inland and up to 1500 

meters over the water. Data points are spaced approximately every 2 meters, and have an accuracy better than 3.0 

meters horizontally and 0.3 meters vertically. These data were not processed to bare earth.

Table 8. Combined topographic–bathymetric datasets used in compiling the Savannah DEM.

Source Year Data Type Spatial Resolution

Original Horizontal 

Datum/Coordinate 

System

Original Vertical 

Datum

JALBTCX 2006 Coastal topography 

and bathymetry 5-meter point data NAD83 geographic NAVD88(meters)

Figure 17. Spatial coverage of JALBTCX high-resolution (5-meter point spacing) coastal bathymetric–topographic LiDAR 

surveys in the vicinity of Savannah that were utilized in DEM development.

5. These data were collected using a SHOALS-1000T system. It is owned and operated by Fugro Pelagos performing contract survey services for 

the US Army Corps of Engineers. The system collects topographic lidar data at 10kHz and hydrographic data at 1kHz. The system also collects 

RGB imagery at 1Hz. Aircraft position, velocity and acceleration information are collected through a combination of Novatel and POS A/V equipment. Raw data are collected and transferred to the office for downloading and processing in SHOALS GCS software. GPS data are processed

using POSPac software and the results are combined with the lidar data to produce 3-D positions for each lidar shot. These data are edited using 

Fledermaus software to remove anomalous data from the dataset. The edited data are unloaded from SHOALS GCS, converted from ellipsoid to 

orthometric heights, based on the GEOID03 model, and split into geographic tiles covering approximately 5km each. [Extracted from metadata]
20

Taylor et al., 2008

3.2 Establishing Common Datums

3.2.1 Vertical datum transformations

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

of vertical datums including Mean Lower Low Water (MLLW), Mean Low Water (MLW), National Geodetic Vertical 

Datum of 1929 (NGVD29) and North American Vertical Datum of 1988 (NAVD88). All datasets were transformed 

to MHW to provide the worst-case scenario for inundation modeling. Units were converted from feet to meters as 

appropriate.

1) Bathymetric data

The NOS hydrographic surveys, USACE surveys, and NOAA nautical charts soundings were transformed 

from MLLW and MLW to MHW, using FME software, by adding a constant offset measured at the NOAA 

Savannah tidal station (see Table 9). 

2) Topographic data

The USGS NED, CSC coastal LiDAR and Beaufort County LiDAR data were originally referenced to 

NAVD88. Conversion to MHW, using FME software, was accomplished by adding constant offsets per Table 

9. 

3) Topographic–bathymetric data

Combined topographic–bathymetric coastal LiDAR survey data were transformed from NAVD88 to 

MHW (Table 9) using FME. 

Table 9. Relationship between Mean High Water and other vertical datums in the Savannah region.*

Vertical datum Difference to MHW

NGVD29 -0.660

NAVD88a -0.939

MSL -1.009

MLW -2.108

MLLW -2.174

* Datum relationships determined by tidal station #8670870 at Fort Pulaski, Savannah, Georgia.

3.2.2 Horizontal datum transformations

Datasets used to compile the Savannah DEM were originally referenced to UTM Zone 17, State Plane, 

NAD83, or WGS84 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.
21

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

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:

•	 Data values over the open ocean and rivers in the NED DEM and Beaufort County LiDAR data. Each dataset 

required automated clipping to the combined coastline.

•	 Presence of buildings and other man-made structures, as well as trees, in the coastal LiDAR datasets from 

CSC and JALBTCX. As these datasets were not bare earth, NGDC eliminated elevations greater than 3 

meters above MHW to crudely remove such features while retaining coastal morphology.

•	 Digital, measured bathymetric values from NOS surveys date back over 70 years. More recent data, such as 

USACE surveys in dredged shipping channels, differed from older, pre-dredging NOS data by as much as 10 

meters. The older NOS survey data were excised where more recent bathymetric data exists. 

3.3.2 Averaging of Beaufort County LiDAR data

The massive volume of point data (742 million) in the Beaufort County, South Carolina LiDAR data, as well 

as their small point-spacing (~1.25 meters) and the fact that the dataset contained returns from the surface of water 

bodies, necessitated averaging the data to a more manageable 1/3 arc-second spacing. This was accomplished by 

generating a ‘pre-surface’ or grid using GMT, an NSF-funded share-ware software application designed to manipulate 

data for mapping purposes (http://gmt.soest.hawaii.edu/).

The individual point data were median-averaged using the GMT tool ‘blockmedian’ onto a 1/3 arc-second 

grid 0.05 degrees (~5%) larger than Beaufort County, such that the median value of all of the points lying within 

each 1/3 arc-second cell (~10 by 10 meters) was calculated and output. The GMT tool ‘surface’ then created a grid 

or ‘surface’ of the median-averaged point data. This grid was converted into an ESRI Arc ASCII grid file using the

MB-System tool ‘mbm_grd2arc’. Conversion of this Arc ASCII grid file into an Arc raster permitted clipping of the

grid by the combined coastline (to eliminate data interpolation into areas outside the initial LiDAR data coverage and 

to remove water returns). The resulting surface was compared with the original soundings to ensure grid accuracy, 

converted to a shape file, and then exported as an xyz file for use in the final gridding process (see Table 9).

3.3.3 Interpolation of USACE bathymetric data

The USACE hydrographic surveys are more recent than most of the NOS hydrographic surveys that they 

overlap with, and are considered to be more accurate as they reflect dredging of modern shipping channels and the

Atlantic Intracoastal Waterway. Offshore of the Savannah River, the USACE survey data are sparse enough in some 

places that they were first pre-surfaced with GMT (See Section 3.3.2) to 1 arc-second spacing to fully infill the dredged

channel with interpolated depths. This surface was closely cropped to the extents of the USACE surveys, compared 

with the original survey values, and then used in creating an overall bathymetric ‘pre-surface’ (see Section 3.3.4). 

3.3.4 Smoothing of bathymetric data

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

water, the NOS survey data have point spacings up to 400 meters apart. In order to reduce the effect of artifacts in 

the form of lines of “pimples” in the 1/3 arc-second 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 (see Section 

3.3.2). 

The NOS hydrographic point data, in xyz format, were combined with the interpolated USACE pre-surface, 

and ENC and NGDC-digitized RNC soundings into a single file, along with points extracted from the combined

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 (~5%) larger than the Savannah DEM gridding 
22

Taylor et al., 2008

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 combined coastline (to

eliminate data interpolation into land areas). The resulting surface was compared with the original soundings to ensure 

grid accuracy (e.g., Fig. 18), converted to a shape file, and then exported as an xyz file for use in the final gridding

process (see Table 10). 

Figure 18. Histogram of the difference between NOS hydrographic survey H10620 (relatively dense survey in deeper 

water) and the 1 arc-second pre-surfaced bathymetric grid. Pre-surface cell values are highly consistent with the original 

hydrographic survey soundings.

3.3.5 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 

Savannah DEM. MB-System is an NSF-funded share-ware software application specifically designed to manipulate

submarine multibeam sonar data, though it can utilize a wide variety of data types, including generic xyz data. 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 10. Greatest 

weight was given to the high-resolution NOS multibeam and coastal LiDAR survey data. Least weight was given 

to the pre-surfaced 1 arc-second NOS bathymetric grid. Gridding was performed in quadrants, each with a 5% data 

overlap buffer. The resulting Arc ASCII grids were seamlessly merged in ArcCatalog to create the final 1/3 arc-second

Savannah DEM.

Table 10. Data hierarchy used to assign gridding weight in MB-System.

Dataset Relative Gridding Weight

USACE bathymetry 100

JALBTCX coastal lidar bathymetry–topography 100

Beaufort County pre-surfaced LiDAR grid 100

CSC coastal lidar topography 10

NOS hydrographic surveys: bathymetric soundings 1

NOAA nautical chart soundings 1

USGS NED topographic DEM 0.01

Pre-surfaced bathymetric grid 0.01

3.4 Quality Assessment of the DEM

3.4.1. Horizontal accuracy

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

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

10 to 15 meters: Beaufort County and coastal LiDAR 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 deepwater areas, in the southeast corner of the DEM. Shallow, near-coastal regions, rivers, and dredged shipping channels 

have an accuracy approaching that of subaerial topographic features. Positional accuracy is limited by: the sparseness 

of deep-water and inland river soundings; potentially large positional uncertainty of pre-satellite navigated (e.g., GPS) 
23

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

NOS hydrographic surveys; and by natural and artificial morphologic change that has occurred since the hydrographic

surveys were conducted. 

3.4.2 Vertical accuracy

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

contributing to grid cell values. Topographic areas have an estimated vertical accuracy between 0.15 (for Beaufort 

County and coastal LiDAR data) and up to 7 meters (for NED topography). Bathymetric areas have an estimated 

accuracy of between 0.1 meters and 5% of water depth (~2 meters in the southeast corner of the DEM). Those values 

were derived from the wide range of input data sounding measurements from the early 20th century to recent, GPSnavigated sonar surveys. Gridding interpolation to determine values between sparse, poorly-located NOS soundings 

degrades the vertical accuracy of elevations in deep-water. Also suspect are the accuracy of values within inland rivers, 

as substantial morphologic change has occurred in some areas since the NOS hydrographic surveys of the 1930s to 

1970s.

3.4.3 Slope maps and 3-D perspectives

ESRI ArcCatalog was used to generate a slope grid from the 1/3 arc-second Savannah DEM to allow for 

visual inspection and identification of artificial slopes along boundaries between datasets (e.g., Fig. 19). The DEM

was transformed to UTM Zone 17 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. 20) was accomplished using ESRI ArcScene. Analysis of preliminary grids 

revealed suspect data points, which were corrected before recompiling the DEM. Figure 21 shows a color image of 

the 1/3 arc-second Savannah DEM in its final version

Figure 19. Slope map of the 1/3 arc-second Savannah DEM. Flat-lying slopes are white; dark 

shading denotes steep slopes; combined coastline in red.
24

Taylor et al., 2008

Figure 20. Perspective view from the east of the 1/3 arc-second Savannah DEM. 

Combined coastline in black; vertical exaggeration–times 100.

Figure 21. Color image of the Savannah DEM.
25

DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

3.4.4	 Comparison with source data files

To ensure grid accuracy, the Savannah 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 a JALBTCX

coastal bathymetric–topographic LiDAR survey file and the Savannah DEM is shown in Fig. 22.

Figure 22. Histogram of the difference between one file of the JALBTCX coastal bathymetric–topographic LiDAR survey 

(87,311 points) and the 1/3 arc-second Savannah DEM.

3.4.5 Comparison with NOAA tidal stations

The National Geodetic Survey (NGS) data sheets for U.S. tidal stations (http://tidesandcurrents.noaa.gov/) 

document benchmark elevations, in meters above MHW, allowing for direct comparison with DEM values at those 

locations. There is only one tidal station within the Savannah study area (Fort Pulaksi, Savannah River, Georgia, 

#8670870), which was compared with the value taken at the same locale from the 1/3 arc-second Savannah DEM 

(see Fig. 23 and Table 11 for station location). The 1/3 arc-second DEM value of 2.477 meters for that location (Table 

11) derives from the 1 arc-second USGS NED topographic DEM and the summer of 2000 CSC coastal topographic 

LiDAR survey, which was not processed to bare earth. The area has significant vegetation and buildings, which the

tide-station bench mark is close to, likely contributing to the observed offset with the DEM.

Table 11. Comparison of NOAA tidal benchmark elevation, in meters above MHW, with the 1/3 arc-second Savannah DEM.

Station 

number Station name Year Longitude Latitude Bench mark DEM Difference

8670870 Fort Pulaski 1978 80.8947222° W 32.0286111° N 0.723 2.477 1.754

3.4.6 Comparison with NGS geodetic monuments

The elevations of 1169 NOAA NGS geodetic monuments were extracted from online shapefiles of monument

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

accuracy) and elevations in NAVD88 (in meters). Elevations were shifted to MHW vertical datum (see Table 9) for 

comparison with the Savannah DEM (see Fig. 23 for monument locations). Differences between the Savannah DEM 

and the NGS geodetic monument elevations range from -17 to 7 meters, with a negative value indicating that the DEM 

is less than the monument elevation (e.g., Fig. 24). Examination of the monuments with the largest positive offsets 

from the DEM revealed that they are mounted on bridges spanning a river. Those with the largest negative offsets are 

close to topographic highs that are poorly resolved within the 1 arc-second NED topographic DEM.
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Taylor et al., 2008

Figure 23. Location of NGS monuments and NOAA tidal benchmark used for evaluating the Savannah DEM.

Figure 24. Histogram of the differences between NGS geodetic monument elevations and the 1/3 arc-second Savannah 

DEM. 

4. Summary and Conclusions

A topographic–bathymetric digital elevation model of the Savannah, Georgia 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 Savannah DEM, based on NGDC’s research and analysis, are listed below:

•	 Process coastal LiDAR data to bare earth.

•	 Obtain digital versions of several NOAA nautical charts (#11507, 11509, 11510, 11511, 11516, 11517, 11518, 

11519, and 11521) that have not yet been digitized.

•	 Improve topography in the regions currently covered by NED 1 arc-second data (in the central and western 

parts of the DEM). This may be accomplished in part by acquiring the original Chatham County LiDAR data, 

which was unavailable for this project.
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DIGITAL ELEVATION MODEL OF SAVANNAH, GEORGIA

•	 NOS mapping of inland waterways where significant morphologic change has occurred since the original

surveys utilized in this study were conducted.

5. Acknowledgments

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

The authors thank Chris Chamberlin and Vasily Titov (PMEL), Jason Flake (Beaufort County, South Carolina GIS 

Department), Robert Martore (Office of Fisheries Management, Marine Resource Division, South Carolina Department

of Natural Resources), Ned Durden, Jr. (USACE Savannah District), Doug Holmes (USACE Charleston District) and 

William Brooks (NOAA Coastal Services Center)

6. References

Nautical Chart #11505, 3rd Edition, 2006. Savannah River Approach. Scale 1:40,000. U.S. Department of Commerce, 

NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11507, 32th Edition, 2004. Beaufort River to St. Simons Sound Side. Scale 1:40,000. U.S. Department 

of Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11509, 29th Edition, 2005. Tybee Island to Dobay Sound. Scale 1:80,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11510, 19th Edition, 2004. Sapelo and Doboy Sounds. Scale 1:40,000. U.S. Department of Commerce, 

NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11511, 17th Edition, 2004. Ossabaw and St. Catherines Sounds. Scale 1:40,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11512, 61st Edition, 2006. Savannah River and Wassaw Sound. Scale 1:40,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11513, 25th Edition, 2006. St. Helena Sound to Savannah River. Scale 1:80,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11514, 28th Edition, 2005. Savannah River Savannah to Brier Creek. Scale 1:20,000. U.S. Department 

of Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11516, 31st Edition, 2006. Port Royal Sound and Inland Passages. Scale 1:40,000. U.S. Department 

of Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11517, 17th Edition, 2001. St. Helena Sound. Scale 1:40,000. U.S. Department of Commerce, NOAA, 

National Ocean Service, Coast Survey.

Nautical Chart #11518, 35th Edition, 2006. Intracoastal Waterway Casino Creek to Beaufort River. Scale 1:40,000. 

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

Nautical Chart #11519, 12th Edition, 2003. Parts of Coosaw and Broad Rivers. Scale 1:40,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11521, 28th Edition, 2006. Charleston Harbor and Approaches. Scale 1:80,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.
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Taylor et al., 2008

7. Data Processing Software

ArcGIS v. 9.1, 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. 4.1.1 – 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. 5.0.9, 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/