DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

noaa / NATIONAL OCEANIC AND

ATMOSPHERIC ADMINISTRATION

National Environmental Satellite,

Data, and Information Service

NOAA Technical Memorandum NESDIS NGDC-8

DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA:

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 PANAMA CITY, FLORIDA

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-8

DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA:

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

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)
iii

DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

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 ............................................................................................................9

3.1.3 Topography..........................................................................................................14

3.1.4 Topography–Bathymetry.....................................................................................17

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

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

3.2.2 Horizontal datum transformations.......................................................................21

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

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

3.3.2 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.......................................................................24

3.4.5 Comparison with NGS geodetic monuments......................................................25

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

5. Acknowledgments............................................................................................................................26

6. References........................................................................................................................................26

7. Data Processing Software ................................................................................................................27

List of Figures

Figure 1. Color image of the Panama City, Florida region ........................................................................1

Figure 2. An example of coastal erosion at Carillon Beach post-Hurricane Dennis..................................2

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

Figure 4. NOAA Electronic Navigational Charts available in the Panama City region ............................5

Figure 5A. Detail of coastline datasets for Upper Goose Bayou ..................................................................6

Figure 5B. Image of RNC #11390 showing Upper Goose Bayou................................................................6

Figure 6. Digital coastline segments used to create a ‘combined coastline’ for the Panama City 

region ...................................................................................................................................7

Figure 7. Example of the difference in coastal morphology around Indian Pass between 2004 and 

 2005 LiDAR surveys...........................................................................................................8

Figure 8. Digital NOS hydrographic survey coverage in the Panama City region ..................................11

Figure 9. Location of USACE survey data within dredged shipping channels in the Panama City 

region .................................................................................................................................12

Figure 10. NGDC’s digitized representation of the Intracoastal Waterway...............................................13

Figure 11. Source and coverage of topographic datasets used in building the Panama City DEM...........14

Figure 12. FDEP topographic LiDAR data before (left) and after (right) NGDC processing ...................15

Figure 13. Color image of the NED DEM in the vicinity of Cape San Blas .............................................16

Figure 14. Spatial coverage of JALBTCX high-resolution coastal bathymetric–topographic 

LiDAR surveys utilized in DEM development .................................................................17

Figure 15. Post-Hurricane Katrina JALBTCX data before and after NGDC processing to 

simulate bare earth.............................................................................................................18

Figure 16. Indistinct MHW coastline in post-Hurricane Dennis JALBTCX survey .................................19

Figure 17. Beach replenishment areas offshore Laguna Beach .................................................................20
iv

Taylor et al., 2008

Figure 18. Histogram of the difference between NOS hydrographic survey H10236 and the 

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

Figure 19. Slope map of the Panama City DEM........................................................................................23

Figure 20. Perspective view from the south of the Panama City DEM .....................................................24

Figure 21.	 Histogram of the difference between one file of the post-Katrina JALBTCX coastal

bathymetric–topographic LiDAR survey and the Panama City DEM. .............................24

Figure 22. Histogram of the differences between NGS geodetic monument elevations and the 

Panama City DEM.............................................................................................................25

Figure 23. Location of NGS monuments and NOAA tide stations in the Panama City region .................25

List of Tables

Table 1.	 PMEL specifications for the Panama City, Florida DEM...........................................................3

Table 2. Shoreline datasets used in compiling the Panama City DEM.....................................................4

Table 3. NOAA nautical charts in the Panama City, Florida region.........................................................4

Table 4. Bathymetric datasets used in compiling the Panama City DEM................................................9

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

Table 6. USACE bathymetric surveys used in compiling the Panama City DEM.................................12

Table 7. Topographic datasets used in compiling the Panama City DEM..............................................14

Table 8. Combined topographic–bathymetric datasets used in compiling the Panama City DEM........17

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

region .................................................................................................................................20

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


DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

Digital Elevation Model of Panama City, Florida:

Procedures, Data Sources and Analysis

1. Introduction

In January 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 

Panama City, Florida (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 Panama City DEM. 

. The Panama City 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 Panama City, Florida (30°10′ N, 85°40′

W) 1/3 arc-second of latitude is equivalent to 10.26 meters; 1/3 arc-second of longitude equals 8.92 meters.

Figure 1. Color image of the 

Panama City, Florida region. 

Coastline in red.


Taylor et al., 2008

2. Study Area

The Panama City DEM covers the coastal region centered on Panama City, Florida including the communities 

of Laguna Beach, Panama City Beach, Tyndall Air Force Base, Mexico Beach, and Port St. Joe (Fig. 1). Geologically, 

the region is located where the Gulf Coastal Plain meets the Florida Platform. Siliclastic sediments overlay the 

carbonate sediments that dominate the Florida peninsula. These are, in turn, covered by young, unconsolidated sand 

deposits that form barrier islands (http://pubs.usgs.gov/of/2004/1044/setting.html).

The beaches and barrier islands in the region are severely impacted by seasonal storms and coastal erosion 

processes. Recent hurricane seasons have had a dramatic effect on the shape and geomorphology of the coastline. 

Beach restoration projects are part of the continuing effort to maintain the tourist-based economy by mitigating 

the kind of hurricane damage caused during the 2005 hurricane season. The Florida Department of Environmental 

Protection (FDEP), Division of Water Resource Management, Bureau of Beaches and Coastal System has published 

a comprehensive report on the impacts of the 2005 hurricane season on Northwest Florida (http://bcs.dep.state.fl.us/

reports/2005/2005hur1.pdf). 

According to the FDEP Bureau of Coastal Studies: “At Stump Hole, between Cape San Blas and St. Joseph 

Peninsula, storm tide flooding occurred during both Tropical Storm Arlene and Hurricane Dennis. Waves from both

storms battered the revetment causing rock displacement and damage. Storm tides from both storms flooded the

road and additional road damage was caused by Dennis. Cape San Blas erodes at about 40 feet per year. With every 

passing storm severe erosion is experienced. On June 11, Tropical Storm Arlene inflicted another approximately 25

feet of bluff recession at the Cape San Blas Lighthouse. With Hurricane Dennis, another 100 feet or so of erosion was 

sustained. This area is the most severely eroding area in Florida.” (http://bcs.dep.state.fl.us/reports/dennis.pdf)

Figure 2. An example of coastal erosion at Carillon Beach post-Hurricane Dennis (http://bcs.dep.

state.fl.us/reports/2005/2005hur1.pdf). 

3. Methodology

The Panama City 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.
DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

Table 1: PMEL specifications for the Panama City, Florida DEM.

Grid Area Panama City, Florida

Coverage Area 85.2o to 86.1o W; 29.55o to 30.5o 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

3.1 Data Sources and Processing

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

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

Coastal Services Center (CSC); the U.S. Geological Survey (USGS); the U.S Army Corps of Engineers (USACE); the 

Florida Department of Environmental Protection (FDEP); and the Bay County, Florida GIS Office. 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 local NOAA Panama City tidal stations, 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 Panama City DEM.
Taylor et al., 2008

3.1.1 Shoreline

Three digital coastline datasets of the Panama City region were analyzed for inclusion in the Panama 

City DEM: OCS Electronic Navigational Charts, FDEP digital shoreline, and the USGS High Resolution National 

Hydrography Dataset shoreline (Table 2).

Table 2: Shoreline datasets used in compiling the Panama City DEM.

Source Year Data Type Spatial Resolution

Original Horizontal 

Datum/Coordinate 

System

Original 

Vertical 

Datum

URL

OCS Electronic 

Navigational 

Charts

2001 to 

2004

MHW 

coastline

Digitized from 1:40,000 to 

1:456,394 scale charts WGS84 geographic MHW http://chartmaker.ncd.noaa.gov/

Florida 

Department of 

Environmental 

Protection 

(FDEP) BIS/GIS 

Section

1999 MHW 

coastline 1:40,000 NAD83 geographic MHW

http://www.dep.

state.fl.us/gis/

datadir.htm

USGS High 

Resolution 

National 

Hydrography 

Dataset

2002 to 

2004 shoreline 1:100,000 NAD83 geographic NGVD29 http://nhd.usgs.gov/index.html

1) OCS electronic navigational charts

Eleven NOAA nautical charts were available for the Panama City region (Table 3) and were downloaded 

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

charts are available in raster nautical chart (RNC) format—georeferenced map imagery, which are frequently 

updated—with some also available as Electronic Navigational Charts (ENCs)—digital GIS chart components 

(Fig. 4). 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 ENCs into ArcGIS. The ENCs 

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.

Five of the ENCs (#11360, #11385, #11388, #11393, and #11400) were used in conjunction with other 

coastline datasets to build a ‘combined coastline’ (Fig. 9). The coastline files extracted from ENCs #11400

and #11360 were at a lower resolution and were used only where no other higher resolution coastline data 

was available. ENCs #11385, #11388, and #11393 were at a higher resolution, but provided only limited 

coverage in the gridding area. Editing all of the ENC coastline data was necessary to provide more detail in 

areas where recent bathymetric survey data existed. Those nautical charts that exist only as RNCs were used 

to evaluate other coastline, bathymetric and topographic datasets and for digitization of coastal features not 

represented in any digital coastline dataset (e.g., Fig 5).

Table 3: NOAA nautical charts in the Panama City, Florida region.

Chart Number Title Edition Date Scale Available 

Format

Used in 

Combined 

Coastline

11 360 Cape St. George to Mississippi Passes 7 06/2006 1:456,394 ENC yes

11 385 West Bay to Santa Rosa Sound 7 11 /2006 1:40,000 ENC yes

11 388 Choctawhatchee Bay 2 12/2006 1:80,000 ENC yes

11 389 St. Joseph and St. Andrews Bay 3 05/2006 1:80,000 ENC no

11 390 East Bay to West Bay Florida Side A 23 02/2004 1:40,000 RNC no

11 391 St. Andrew Bay 24 12/2005 1:25,000 RNC no

11 392 St. Andrew Bay – Bear Point to Sulpher Point 7 05/2006 1:5,000 ENC no

11 393 Lake Wimico to East Bay Side A & B 7 11 /2006 1:40,000 ENC yes

11 400 Tampa Bay to Cape San Blas 5 09/2006 1:456,394 ENC yes

11 401 Apalachicola Bay to Cape San Blas 4 11 /2006 1:80,000 ENC no

11 402 Apalachicola Bay to Lake Wimico 6 07/2006 1:40,000 ENC no
DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

Figure 4. NOAA Electronic Navigational Charts available in the Panama City region.

2) Florida Department of Environmental Protection 

The Florida Department of Environmental Protection (FDEP) has developed a dataset merging extracted 

Florida county lines from USGS DLG boundary layers with the FLSHORE/FMRI Florida 1:40,000 shoreline 

(http://www.dep.state.fl.us/gis/datadir.htm). This shoreline coverage was originally digitized from 1:40,000 

NOAA nautical charts and edited to the coverage by FDEP using 1:24,000 USGS quadrangles.

In order to match the FDEP shoreline to recent NOS bathymetric surveys, NGDC manually edited the 

dataset using ArcMap to fit the coastline to RNCs. Figure 5 illustrates the lack of detail in available digital

coastline datasets for Upper Goose Bayou, along the North Bay of St Andrew. Both the 1:456,394-scale ENC 

#11360 and the FDEP coastline in the area fail to capture the intricate details of the bayou (Fig 5A). The 

larger scale RNC #11390 (1:40,000; Fig. 5B) provided enough detail to enable NGDC to digitize the bayou’s 

coastline, specifically to enclose soundings from NOS survey H10236. Google Earth satellite imagery was 

used to check shoreline accuracy throughout the coastline editing process (Fig. 5B). 
Taylor et al., 2008

Figure 5A. Detail of coastline datasets for Upper Goose Bayou. 1987 NOS survey H10236, in red, extended into upper reaches of the bayou. 

Neither the FDEP coastline (green) nor coastline from ENC #11360 (blue, scale 1:456,394) captured the intricate details of the bayou. The 

combined coastline (gray) was built by digitizing the coastline from RNC #11390 (scale 1:40,000; see Fig 5B).

Figure 5B. Image of RNC #11390, on left, showing Upper Goose Bayou. Google Earth satellite 

image of same area on right.
DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

3) USGS National Hydrography Dataset

The USGS National Hydrography Dataset (NHD) provides information on both naturally occurring and 

developed bodies of water, rivers, streams, and water related features (http://nhd.usgs.gov/index.html). The 

shoreline for this dataset was extracted from 1:100,000 USGS quads in DLG format. NGDC downloaded, 

re-projected, and clipped the data for the north-western corner of the DEM, to improve the accuracy of the 

East River Island area (Fig. 1). This dataset was subsequently edited in the southern part of East River Island 

to be consistent with NOS hydrographic soundings from survey H06452.

To obtain the best digital MHW coastline, NGDC combined the ENC, FDEP, and NHD coastlines into a 

‘combined coastline’ (Fig. 6). Where overlap occurred between coastline datasets, the one with the most detail and 

consistency with topographic, bathymetric, and topographic–bathymetric datasets was used. This combined coastline 

was also manually adjusted along the Gulf coast, in ESRI ArcMAP, to match the JALBTCX high-resolution coastal 

LiDAR data, particularly the late 2005 post-Hurricane Katrina survey. Piers, docks, and other manmade structures 

were also deleted. The combined 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).

Figure 6. Digital coastline segments used to create a ‘combined coastline’ for the Panama City region. Areas in yellow 

highlight coastline segments that were manually adjusted to match recent bathymetric–topographic LiDAR surveys.
Taylor et al., 2008

The Gulf coast in the Panama City region is subject to rapid morphologic change, particularly by hurricanes. 

The 2005 hurricane season had a dramatic impact along the coastline here, as exemplified by Figure 7—Indian Pass,

in the southeast corner of the DEM—with Hurricanes Dennis and Katrina significantly modifying the coastline.

Figure 7. Example of the difference in coastal morphology around Indian Pass between 2004 and 2005 LiDAR surveys. 

Green–blue transition represents the MHW coastline in the 2004 JALBTCX LiDAR survey. Yellow–purple transition 

represents the MHS coastline in the 2005 post-Dennis JALBTCX LiDAR survey. The FDEP shoreline is shown in red.
DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

3.1.2 Bathymetry

Bathymetric datasets used in the compilation of the Panama City DEM include 50 NOS hydrographic surveys, 

25 USACE surveys of dredged shipping channels, and NGDC-digitized soundings within the Intracoastal Waterway 

(Table 4). 

Table 4: Bathymetric datasets used in compiling the Panama City DEM.

Source Year Data Type Spatial Resolution

Original 

Horizontal Datum/

Coordinate System

Original 

Vertical Datum URL

USACE

2005 

to 

2006

Bathymetric 

surveys

Profiles 60 to 500

m long, 60 to 150 m 

apart with .5 to 20 m 

point spacing

NAD83 State 

Plane Florida 

North (feet)

MLLW 

(meters)

 NOS 

1930 

to 

1993

Hydrographic 

survey 

soundings

Ranges from 10 

m to 1 km (varies 

with scale of survey, 

depth, traffic, and

probability of 

obstructions)

NAD27, NAD83 

geographic

MLLW, MLW, 

and Gulf Coast 

Low Water 

(meters)

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

bathymetry/hydro.html

NGDC 2006

Digitized 

Intracoastal 

Waterway 

soundings

2 parallel tracks 10 

to 20 m apart with 

<10 m point spacing

WGS84 

geographic MHW (feet)

1) NOS hydrographic survey data

A total of 50 NOS hydrographic surveys conducted between 1930 and 1993 were utilized in developing 

the Panama City DEM (Table 5; Fig. 8). The hydrographic survey data were originally vertically referenced 

to Mean Lower Low Water (MLLW), Mean Low Water (MLW), or Gulf Coast Low Water (GCLW) and 

horizontally referenced to either NAD27 or NAD83 geographic datums. Gulf Coast Low Water datum 

is equivalent to MLLW (National Tidal Datum Convention of 1980, http://tidesandcurrents.noaa.gov/

publications/glossary2.pdf). 

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 datums (Table 

5). 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 (~5%) larger than the Panama City 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 

the USACE bathymetric surveys and coastal LiDAR data, NED topographic data, the combined coastline, 

RNCs, and Google Earth satellite imagery.

Table 5: Digital NOS hydrographic surveys used in compiling the Panama City DEM.

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

H05024 1930 10,000 mean low water NAD27

H05780 1935 10,000 mean low water NAD27

H05781 1935 10,000 mean low water NAD27

H05782 1935 10,000 mean low water NAD27

H05783 1935 10,000 mean low water NAD27

H05791 1935 10,000 mean low water NAD27

H05793 1935 10,000 mean low water NAD27

H05796 1935 10,000 mean low water NAD27

H05812 1935 20,000 mean low water NAD27
10

Taylor et al., 2008

H06449 1939 10,000 mean low water NAD27

H06450 1939 10,000 mean low water NAD27

H06451 1939 10,000 mean lower low water NAD27

H06452 1939 10,000 mean low water NAD27

H06689 1941 40,000 mean low water NAD27

H06691 1941 80,000 mean low water NAD27

H06694 1941/47 20,000 mean low water NAD27

H06784 1942/43 40,000 mean low water NAD27

H06785 1942/43 40,000 mean low water NAD27

H06786 1942/43 20,000 mean low water NAD27

H6787 1942/43 20,000 mean low water NAD27

H07173 1947 10,000 mean lower low water NAD27

H07603 1947/48 200,000 mean low water NAD27

H07631 1947 40,000 mean low water NAD27

H07632 1947 40,000 mean low water NAD27

H07633 1947 40,000 mean low water NAD27

H07723 1948/50 100,000 mean low water NAD27

H09734 1977/78 20,000 mean low water NAD27

H09735 1977/78 20,000 Gulf Coast low water NAD27

H09755 1978 20,000 Gulf Coast low water NAD27

H09761 1978 20,000 mean low water NAD27

H09786 1978 40,000 mean low water NAD27

H09846 1979/80 40,000 mean lower low water NAD27

H09883 1980 40,000 Gulf Coast low water NAD27

H09915 1980 20,000 Gulf Coast low water NAD27

H09924 1980/81 10,000 mean lower low water NAD27

H09925 1980/81 10,000 mean lower low water NAD27

H09989 1981/82 10,000 mean low water NAD27

H09996 1982 10,000 mean low water NAD27

H10069 1982/83 10,000 mean lower low water NAD27

H10122 1983/84 10,000 mean low water NAD27

H10166 1984/85 10,000 mean lower low water NAD27

H10170 1985 10,000 mean low water NAD27

H10235 1986/88 10,000 mean lower low water NAD27

H10236 1987 10,000 mean lower low water NAD27

H10237 1986/87 10,000 mean lower low water NAD27

H10259 1987/89 10,000 mean lower low water NAD27

H10260 1987/88 10,000 mean lower low water NAD27

H10266 1988/89 10,000 mean lower low water NAD27

H10267 1988 10,000 mean lower low water NAD27

H10452 1993 10,000 mean lower low water NAD83
11

DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

Figure 8. Digital NOS hydrographic survey coverage in the Panama City region. DEM boundary in red, combined coastline in gray.

2) USACE surveys of dredged shipping channels

USACE bathymetric surveys of dredged shipping channels in St. Andrew Bay, East Bay, and West Bay 

(Fig. 9) were provided to NGDC by Victoria Ann Anderson, USACE Mobile Dist., Panama City Site Office.

All data were originally in NAD83 Florida State Plane North coordinates, and MLLW vertical datum (Table 

6). Surveys consist of numerous, parallel, across-channel profiles, spaced 60 to 150 meters apart, with point

soundings 0.5–20 meters apart.
12

Taylor et al., 2008

Figure 9. Location of USACE survey data within dredged shipping channels in the Panama City region.

Table 6: USACE bathymetric surveys used in compiling the Panama City DEM.

Region Original horizontal 

datum

Original vertical 

datum Spatial Resolution

Grand Lagoon NAD83 State Plane 

Florida North (feet) MLLW Profiles ~125 m long, spaced 60 m apart, with <10 m

point spacing

Watson Bayou NAD83 State Plane 

Florida North (feet) MLLW Profiles ~150 m long, spaced 60 m apart, with <0.5 m

point spacing

St. Andrew Bay NAD83 State Plane 

Florida North (feet) MLLW Profiles ~350 to 500 m long, spaced 60 m apart, with

<20 m point spacing

East Bay NAD83 State Plane 

Florida North (feet) MLLW Profiles ~250 m long, spaced 100 m apart, with <10 m

point spacing

St. Andrew Bay 

to West Bay

NAD83 State Plane 

Florida North (feet) MLLW Profiles ~250 m long, spaced 100 to 150 m apart, with

~1 m point spacing

St. Andrew Bay 

– Sulpher Pt. to 

Long Pt.

NAD83 State Plane 

Florida North (feet) MLLW Profiles ~250 m long, ~spaced 100 to 150 m apart, with

~1 m point spacing
13

DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

3) NGDC Digitized Intracoastal Waterway

The Intracoastal Waterway (ICW) in the Panama City region was digitized by NGDC, as no digital 

bathymetric survey data were available (Fig. 10). Digitization was performed in ArcMAP, referencing RNCs 

#11385 and #11393, and Coast Pilot 5. Two parallel lines along the ICW, 25 meters apart, were created, with 

points spaced every 10 meters along each line. An elevation value of -4.05 meters at MHW was assigned 

to the points, derived from the project depth of 12 feet at MLLW, as listed in Coast Pilot 5 and the NOAA 

nautical charts. 

Figure 10. NGDC’s digitized representation of the Intracoastal Waterway (green). DEM boundary in red.
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Taylor et al., 2008

3.1.3 Topography

Topographic datasets in the Panama City region were obtained from the Florida Department of Environmental 

Protection and the U.S. Geological Survey (Table 7; Fig. 11). NASA 1 arc-second SRTM data, Bay County Florida 

data and a NOAA CSC LiDAR survey from 1998 were not utilized in developing the Panama City DEM as they were 

superceded by higher-resolution, or more recent, datasets.

Table 7: Topographic datasets used in compiling the Panama City DEM.

Source Year Data Type Spatial 

Resolution

Original Horizontal 

Datum/Coordinate System

Original 

Vertical Datum URL

Florida Dept. of 

Environmental 

Protection

2004 LiDAR ~1 m NAD83 State Plane 

Florida North

NAVD88

(feet)

http://www.dep.state.

fl.us/

USGS 1999 to 

2004

NED 1/3 arcsecond ~10 m NAD83 geographic NAVD88

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

Figure 11. Source and coverage of topographic datasets used in building the Panama City DEM.
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DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

1) Florida Department of Environmental Protection

The Florida Department of Environmental Protection (FDEP) provided NGDC with 68 files of high

resolution topographic LiDAR data averaging 1500 meters in length and 500 meters wide, generally covering 

beach topography up to 300 meters inland. Coverage extends the length of the Gulf coast within the Panama 

City region, except for the entrance to St. Joseph Bay. The data were originally in Florida State Plane North 

coordinates and in NAVD88 vertical datum. They were converted to WGS84 and MHW using FME software, 

then visually displayed and edited using ArcGIS to eliminate elevation values below zero and those points 

located over water, by clipping to the combined coastline.

As the LiDAR data had not been processed to bare earth, NGDC simulated bare-earth by eliminating 

elevation values greater than 8 meters above MHW. This “clipping” elevation value of 8 meters was selected 

to remove any elevations associated with man-made structures such as buildings, while retaining most of the 

natural topographic variability along the coast. Numerous piers and other coastal structures were also excised 

from the dataset using ArcMap. Figure 12 illustrates the results of NGDC’s processing efforts on one data 

file.

Figure 12. FDEP topographic LiDAR data before (left) and after (right) NGDC processing.
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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 Panama City region. Data are in NAD83 geographic coordinates 

and NGVD88 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 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. 13), 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. ESRI Arc Catalog was used to clip the data to the combined coastline.

Figure 13. Color image of the NED DEM in the vicinity of Cape San Blas. Blue represents “zero” values in NED DEM 

over the open ocean. Combined coastline, derived from post-Dennis LiDAR survey, in red illustrates the magnitude of 

coastal change that has occurred in this area.

. 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 PANAMA CITY, FLORIDA

3.1.4 Topography–Bathymetry

Combined topographic–bathymetric surveys of coastal Florida (Fig. 14) were performed in 2004 and 

2005—post-Hurricanes Dennis and Katrina—by the Joint Airborne LiDAR Bathymetry Technical Center of Expertise 

(JALBTCX; Table 8; Fig. 14). 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 zone3. The surveys 

generally extend 750 meters inland and up to 1500 meters over the water. Data points are spaced approximately every 

5 meters, and have an accuracy better than 3.0 meters horizontally and 0.3 meters vertically. These data were not 

processed to bare earth, therefore NGDC deleted all values greater than 8 meters above MHW to remove the effect of 

buildings in the datasets.

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

Source Year Data Type Spatial 

Resolution

Original Horizontal Datum/Coordinate 

System

Original Vertical 

Datum

JALBTCX 2004 2004 LiDAR 5 m NAD83 geographic NAVD88 (meters)

JALBTCX post-Dennis 2005 LiDAR 5 m NAD83 geographic NAVD88 (meters)

JALBTCX post-Katrina 2005 LiDAR 5 m NAD83 geographic NAVD88 (meters)

Figure 14. Spatial coverage of JALBTCX high-resolution (5-meter point spacing) 

coastal bathymetric–topographic LiDAR surveys utilized in DEM development.

3. 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]
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Taylor et al., 2008

1) Post-Hurricane Katrina 2005 JALBTCX LiDAR survey 

This dataset consists of a bathymetric–topographic coastal LiDAR survey covering 60 kilometers of the 

coastal region from Greyton Beach to St. Andrew Sound. Post-Hurricane Katrina elevations were collected 

above and below water along the immediate coastal zone.

The survey has a spatial resolution of 5 meters and straddles the shoreline from 1,000 to 1,500 meters in 

width. NGDC removed elevations greater than 8 meters using FME, roughly approximating ‘bare earth’ by 

removing buildings, tall structures and trees. Other features such as piers, docks, and anomalous returns were 

also edited out using ArcMap (e.g., Fig. 15).

Figure 15. Post-Hurricane Katrina JALBTCX data before (left) and after (right) NGDC processing to simulate bare earth. 

Note pier and beach-front structures present before processing.

2) Post-Hurricane Dennis 2005 JALBTCX LiDAR survey

This dataset consists of a bathymetric–topographic coastal LiDAR survey covering the entire Gulf Coast 

shoreline within the DEM area, with the exception of St. Joseph Bay. The survey has a spatial resolution of 5 

meters and straddles the shoreline from 500 to 2200 meters. The “zero” elevation line representing MHW is 

less sharply defined in this dataset than in the post-Katrina dataset (e.g., Fig. 16). NGDC removed elevations

greater than 8 meters using FME software, roughly approximating ‘bare earth’ by removing buildings, tall 

structures and trees. Other features such as piers, docks, and anomalous returns were also edited out using 

ArcMap. The coastal area of the St. Joseph Peninsula was particularly impacted by Hurricane Dennis in 

2005, making this data set critical in defining the current shoreline.
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DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

Figure 16. Indistinct MHW coastline in post-Hurricane Dennis JALBTCX survey (left). Clearly defined MHW coastline in 

post-Hurricane Katrina JALBTCX survey (right). 

3) 2004 JALBTCX LiDAR survey

This dataset consists of a bathymetric–topographic coastal LiDAR survey covering the entire Gulf Coast 

shoreline within the DEM area, with the exception of St. Joseph Bay. The survey has a spatial resolution of 

5 meters and straddles the coastline from 1500 to 2200 meters. NGDC used this dataset for the coastal areas 

not covered by either the post-Hurricane Katrina or post-Hurricane Dennis datasets, specifically the offshore

area on and to the north of St. Joseph Peninsula. NGDC removed elevations greater than 8 meters using FME, 

roughly approximating ‘bare-earth’ by removing buildings, tall structures and trees. Other features such as 

piers, docks, and anomalous returns were also edited out using ArcMap. This dataset was used to modify the 

St. Andrew Bay East Pass Inlet coastline to reflect inlet closure information provided by Terry Jangula at the

USACE Panama City Field office.

Analysis of the data revealed anomalous elevations near shore not present in the post-Dennis and postKatrina datasets (Fig. 17). Jeff Lillycrop, USACE, confirmed that these features are dredged areas used for

local beach restoration projects.
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Taylor et al., 2008

Figure 17. Beach replenishment areas offshore Laguna Beach. JALBTCX 2004 survey data, on left, reveals numerous geometric shapes of deeper 

than expected elevations (arrows), which are dredged source areas for beach restoration and replenishment projects in the Panama City region. 

Right panel shows the 2005 post-Hurricane Katrina dataset in the same area, which also reveals these pits.

3.2 Establishing Common Datums

3.2.1 Vertical datum transformations

Datasets used in the compilation and evaluation of the Panama City DEM were originally referenced to a 

number of vertical datums including Mean Lower Low Water (MLLW), Gulf Coast Low Water (GCLW), Mean Low 

Water (MLW), 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 and the USACE surveys were transformed from MLLW, MLW, and 

GCLW to MHW, using FME software, by adding a constant offset determined by averaging two Panama City 

NOAA tidal stations (Table 9; Fig. 23). 

2) Topographic data

The USGS NED 1/3 arc-second DEM and the Florida Department of Environmental Protection LiDAR 

data were originally referenced to NAVD88. Conversion to MHW, using FME software, was accomplished 

by adding tide-station derived constant offsets (Table 9). 

3) Topographic–bathymetric data

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

MHW using FME software (Table 9). 

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

Vertical datum Difference to MHW

NAVD88 -0.224

MLW -0.337

Gulf Coast Low Water+ -0.394

MLLW -0.394

* Datum relationships determined by averaging values from tide stations #8729108, Panama City/St. Andrew Bay 

and #8729210, Panama City Beach.

+ Equivalent to MLLW.
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DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

3.2.2 Horizontal datum transformations

Datasets used to compile the Panama City DEM were originally referenced to State Plane Florida North, 

NAD27, NAD83 geographic, 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 most coastline datasets, which had to be removed.

•	 Inconsistencies between various coastline datasets and bathymetric, topographic and bathymetric–

topographic datasets. These inconsistencies are partly the result of differing resolution between datasets and 

of morphologic change in the highly dynamic coastal zone.

•	 Data values over the open ocean and rivers in the NED DEMs and FDEP 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 bathymetric–topographic 

LiDAR datasets from JALBTCX. As these datasets were not bare-earth, NGDC eliminated elevations greater 

than 8 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 Smoothing of bathymetric data

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

in deep water, the NOS survey data have point spacings up to 2 km 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 USACE and ICW soundings, and 

JALBTCX bathymetric–topographic survey data 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 Panama City 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 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). 
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Taylor et al., 2008

Figure 18. Histogram of the difference between NOS hydrographic survey H10236 (relatively dense survey in North Bay) 

and the 1 arc-second pre-surfaced bathymetric grid. Discrepencies between survey soundings and the pre-surface grid 

result from the averaging of several closely spaced soundings.

3.3.3 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 

Panama City 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 post-Katrina coastal LiDAR survey. Least weight was given to the 

pre-surfaced 1 arc-second 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 Panama City

DEM.

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

Dataset Relative Gridding Weight

JALBTCX coastal lidar bathymetry–topography: post-Katrina 10000

JALBTCX coastal lidar bathymetry–topography: post-Dennis 1000

JALBTCX coastal lidar bathymetry–topography: 2004 100

USACE bathymetry 100

NGDC-digitized Intracoastal Waterway 100

FDEP coastal lidar topography 10

USGS NED topographic DEM 1

NOS hydrographic surveys: bathymetric soundings 1

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 Panama City DEM is dependent upon 

the datasets used to determine corresponding DEM cell values. Topographic features have an estimated accuracy of 10 

to 15 meters: JALBTCX and FDEP 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 hundred meters in 

deep-water areas (i.e., the southwest 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 soundings; potentially large positional uncertainty of pre-satellite navigated (e.g., GPS) NOS 

hydrographic surveys; and by the rapid morphologic change that occurs in this dynamic region. 
23

DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

3.4.2 Vertical accuracy

Vertical accuracy of elevation values for the Panama City DEM is also highly dependent upon the source 

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

JALBTCX and FDEP 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 (~4 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 Panama City 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 16 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 UTMtransformed 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 1 shows a color image of the 1/3 arcsecond Panama City DEM in its final version.

Figure 19. Slope map of the Panama City DEM. Flat-lying slopes are white; dark shading denotes 

steep slopes; combined coastline in red.
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Taylor et al., 2008

Figure 20. Perspective view from the south of the Panama City DEM. Combined 

coastline in red; vertical exaggeration–times 10.

3.4.4	 Comparison with source data files

To ensure grid accuracy, the Panama City 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 post-Hurricane

Katrina JALBTCX coastal bathymetric–topographic LiDAR survey file and the Panama City DEM is shown in Figure

21.

Figure 21. Histogram of the difference between one file of the post-Katrina JALBTCX coastal bathymetric–topographic 

LiDAR survey (438,007 points) and the Panama City DEM.
25

DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

3.4.5 Comparison with NGS geodetic monuments

The elevations of 101 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 NAVD88 (in meters). Elevations were shifted to MHW vertical datum (see Table 9) for 

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

DEM and the NGS geodetic monument elevations range from -2.3 to 5.2 meters, with a negative value indicating 

that the monument elevation is less than the DEM (Fig. 22). Examination of the monuments with the largest positive 

offsets from the DEM revealed that they lie within the East River Island region, alongside a highway, or atop a small 

hill that is poorly resolved within the NED topographic DEM. 

Figure 22. Histogram of the differences between NGS geodetic monument elevations and the Panama City DEM. 

Figure 23. Location of NGS monuments and NOAA tide stations in the Panama City region. Tide stations used to convert 

between vertical datums; NGS monument elevations used to evaluate the DEM.
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Taylor et al., 2008

4. Summary and Conclusions

A topographic–bathymetric digital elevation model of the Panama City, Florida 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 Panama City 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 (#11390 and 11391) that have not yet been 

digitized.

•	 NGDC digitized the Intracoastal Waterway in the vicinity of Panama City, based upon minimum depths 

reported in Coast Pilot 5, as no digital data existed for these channels. The channels are frequently deeper 

along much of their lengths than their representation in the DEM, which could be remedied with new survey 

work.

5. Acknowledgments

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

The authors thank Chris Chamberlin and Vasily Titov (PMEL), Jeff Lillycrop (USACE), Terry Jangula and Victoria 

Ann Anderson (USACE Panama City Field Office), Janet Bogere (Bay County GIS Office), and Gary Cook, (Florida

Department of Environmental Protection).

6. References

Coast Pilot 5, 34th Edition, 2006. Atlantic Coast: Gulf of Mexico, Puerto Rico, and Virgin Islands. U.S. Department of 

Commerce, NOAA, National Ocean Service.

Nautical Chart #11360, 7th Edition, 2006. Panama City River Approach. Scale 1:456,394. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11385, 7th Edition, 2006. West Bay to Santa Rosa Sound. Scale 1:40,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11388, 2nd Edition, 2006. Choctawhatchee Bay. Scale 1:80,000. U.S. Department of Commerce, 

NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11389, 3rd Edition, 2006. St. Joseph and St. Andrews Bay. Scale 1:80,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11390, 23rd Edition, 2004. East Bay to West Bay Florida Side A. Scale 1:40,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11391, 24th Edition, 2005. St. Andrew Bay. Scale 1:25,000. U.S. Department of Commerce, NOAA, 

National Ocean Service, Coast Survey.

Nautical Chart #11392, 7th Edition, 2006. St. Andrew Bay – Bear Point to Sulphur Point. Scale 1:5,000. U.S. 

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

Nautical Chart #11393, 7th Edition, 2006. Lake Wimico to East Bay Side A & B. Scale 1:40,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11400, 5th Edition, 2006. Tampa Bay to Cape San Blas. Scale 1:456,394. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.
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DIGITAL ELEVATION MODEL OF PANAMA CITY, FLORIDA

Nautical Chart #11401, 4th Edition, 2006. Apalachicola Bay to Cape San Blas. Scale 1:80,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

Nautical Chart #11402, 6th Edition, 2006. Apalachicola Bay to Lake Wimico. Scale 1:40,000. U.S. Department of 

Commerce, NOAA, National Ocean Service, Coast Survey.

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. 4.1.4 – 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/