Identification and Extraction of the Seaward Edge of 

Terrestrial Vegetation using Digital Aerial Photography

U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2006–1092
Identification and Extraction of the Seaward Edge of 

Terrestrial Vegetation using Digital Aerial Photography

Melanie Harris1 and John C. Brock1

with contributions from A. Nayegandhi1

, M. Duffy2 and C.W. Wright3

1

U.S. Geological Survey, Center for Coastal and Watershed Studies, St. Petersburg, FL 33701

2

National Park Service, Assateague Island National Seashore, Berlin, MD 21811

3

National Aeronautics and Space Administration, Wallops Flight Facility, Wallops Island, VA 23337

Open-File Report 2006-1092 

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

Gale A. Norton, Secretary

U.S. Geological Survey

P. Patrick Leahy, Acting Director 

U.S. Geological Survey, Reston, Virginia 2006

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

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resources, natural hazards, and the environment:

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This report is preliminary and has not been reviewed for conformity with U.S. Geological Survey editorial 

standards. Any use of trade names is for descriptive purposes only and does not imply endorsement by the 

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Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted material contained within this report.
i

Contents

SECTION ONE ......................................................................................................................................................................1

Project Overview .......................................................................................................................................................1

1.1 Introduction ................................................................................................................................................. 1

1.2 Study Area ................................................................................................................................................... 1

1.3 Scientific Significance and Rationale for Project ................................................................................ 2

1.4 Aims and Objectives of Project ................................................................................................................ 2

1.5 Methodology Overview .............................................................................................................................. 3

1.6 Metadata Creation ...................................................................................................................................... 4

SECTION TWO .....................................................................................................................................................................6

Detailed Methods for Extracting Edge of Vegetation Line ..................................................................................6

Detailed Steps using ArcGIS 8.3 ................................................................................................................... 6

2.1 Classify Image ............................................................................................................................................. 6

2.2 Create Signature File .................................................................................................................................. 7

2.3 Perform Image Classification ................................................................................................................... 8

2.4 Load Classified Image ................................................................................................................................ 8

2.5 Aggregate Classes ................................................................................................................................... 10

2.7 Convert Raster to Polygon ....................................................................................................................... 11

2.8 Convert Polygon Layer to Polyline ......................................................................................................... 11

2.9 Extract Vegetation Line ............................................................................................................................ 12

Appendix I ..........................................................................................................................................................................14

Obtaining Aerial Photography ...............................................................................................................................14

Appendix II .........................................................................................................................................................................14

List of Acronyms ......................................................................................................................................................14

Appendix III ........................................................................................................................................................................15

Example Metadata for Digital Camera Image .....................................................................................................15

ASIS Digital Camera Mosaic 2001 ............................................................................................................... 15

Metadata .................................................................................................................................................15

Example Metadata for Edge of Vegetation Line .................................................................................................20

Edge of Vegetation - ASIS 2001 .................................................................................................................... 20

Metadata .................................................................................................................................................20

References .........................................................................................................................................................................25

Notes ................................................................................................................................................................................26
ii

Figures

Figure 1. Assateague Island National Seashore .......................................................................................................1

Figure 2. Coastal barrier island showing seaward edge of terrestrial vegetation ..............................................3

Figure 3. Figure 3. False-color aerial photo of a portion of Assateague Island National Seashore; 

vegetation shows in shades of red; sand/nonvegetated is white; water is blue ................................4

Figure 4. Extracted seaward edge of vegetation line overlaid on digital photo (left) 

and classified image (right). .........................................................................................................................5

Figure 5. Add raster image to ArcMap dataframe ....................................................................................................6

Figure 6. Convert raster to image using the Classification Analysis tool ..............................................................7

Figure 7. Dialog box used when creating signature file for image classification. ...............................................7

Figure 8. Use Classification Analysis Tool to perform classification; 

classification dialog box show at right ......................................................................................................8

Figure 9. Resulting classified aerial photo (15 classes) ...........................................................................................9

Figure 10. Aggregate existing classes into a smaller number of classes using Spatial Analyst. 

Reclassify dialog box shown above .........................................................................................................10

Figure 11. Final two classes resulting from reclassification are shown above ...................................................10

Figure 12. Using Spatial Analyst, convert raster layer to feature (polygon) layer; 

Raster to Feature dialog box shown above .............................................................................................11

Figure 13. Using the XTools extension to convert a polygon to a polyline ............................................................11

Figure 14. Section of polyline/polygon zoomed in to show detail. ..........................................................................12

Figure 15. Begin Editing menu ......................................................................................................................................12

Figure 16. Resulting edge of vegetation line shown in red ......................................................................................13

Plate 1. (A) Digital aerial photograph of a portion of Assateague Island National Seashore. 

(B) Classified image. (C) Classified image aggregated into six classes. ..............................................5
1

SECTION ONE

Project Overview

1.1 Introduction

This report is created as part of the Aerial Data Collection and Creation of Products for Park Vital Signs 

Monitoring within the Northeast Region Coastal and Barrier Network project, which is a joint project between the 

National Park Service Inventory and Monitoring Program 

(NPS-IM), the National Aeronautics and Space Administration (NASA) Observational Sciences Branch, and 

the U.S. Geological Survey (USGS) Center for Coastal 

and Watershed Studies (CCWS). This report is one of a 

series that discusses methods for extracting topographic 

features from aerial survey data. It details step-by-step 

methods used to extract a spatially referenced digital line 

from aerial photography that represents the seaward edge 

of terrestrial vegetation along the coast of Assateague 

Island National Seashore (ASIS). One component of the 

NPS-IM/USGS/NASA project includes the collection of 

NASA aerial surveys over various NPS barrier islands 

and coastal parks throughout the National Park Serviceís 

Northeast Region. These aerial surveys consist of collecting optical remote sensing data from a variety of sensors, 

including the NASA Airborne Topographic Mapper 

(ATM), the NASA Experimental Advanced Airborne 

Research Lidar (EAARL), and down-looking digital 

mapping cameras. 

Information is presented in two main sections. Section 

One describes the study area and discusses the scientific 

rationale behind the project with a brief description of the 

sensors used and initial data-processing techniques. References for papers providing detailed discussions of the 

topics mentioned are included. Section Two presents detailed step-by-step instructions for extracting the seaward 

edge of vegetation from aerial photography, as performed 

with ESRI ArcGIS 8.3 software. Although ESRI software 

was utilized for this project, similar techniques may be 

applied with other GIS or image-processing software. Imagery is spatially referenced to the Universal Transverse 

Mercator (UTM) coordinate system, Zone 18, referenced 

to the North American Datum 1983. 

1.2 Study Area

Assateague Island National Seashore (ASIS) is located 

on the eastern seaboard along the coasts of Maryland 

and Virginia (Figure 1). Park boundaries encompass the 

entire island; management of the island is a partnership 

between the National Park Service, Assateague State 

Park, and Chincoteague National Wildlife Refuge. 

Given its proximity to the NASA Wallops Flight Facility as well as NPS interest in using the resulting datasets 

for ongoing resource management activities, Assateague 

Island has been a focus of data collection and applications-development activity. NASA Wallops Flight Facility, located on Wallops Island, Va, has been collecting 

aerial survey data over ASIS since 1995, beginning with 

topographic lidar (light detection and ranging) surveys 

(Krabill and others, 2000; Brock and Sallenger, 2001) 

and expanding to include digital aerial photography 

Figure 1. Assateague Island National Seashore.
2

acquisition and additional development of innovative 

lidar sensors that integrate bathymetric and topographic 

surveys (Nayegandhi and others, 2005). Lidar surveys 

provide point ground elevations that are used to construct 

a three dimensional representation of the island landscape 

(Brock and others, 1999; Brock and others, 2003). At 

ASIS, pilot efforts to use NASA aerial survey data in resource management and monitoring have already resulted 

in significant practical contributions to park resource 

management (Nayegandhi, 2002; Nayegandhi and others, 

2005). 

1.3 Scientific Significance and Rationale for 

Project 

 Tracking changes in terrain along barrier island beaches 

has long been problematic because of a lack of accurate 

high-resolution topographic data. Traditional products, 

such as available contour maps or low-resolution digital 

elevation models (DEMs), could not provide the level 

of detail or the update frequency necessary to monitor 

barrier island parks. To address this need, the NPS and 

NASA initiated an experimental beach-mapping program 

using topographic lidar surveys at ASIS (Brock and others, 1999; Brock and others, 2001). 

NASA began collecting airborne laser surveys over Assateague Island in 1995 using the NASA ATM sensor. 

Initially, the ATM carried a single-return green wavelength lidar; a down-looking camera was added in 2001 

(Brock and Sallenger, 2001). Further enhanced sensor 

development resulted in a new waveform-resolving 

red-wavelength lidar (NASA EAARL). The EAARL is 

a cross-environment sensor, capable of surveying both 

terrestrial and aquatic environments (Brock and Wright, 

2002). As a result, sensor survey data provides a wide 

range of information, including but not limited to: (1) 

bare earth digital elevation models, (2) first return DEMs, 

and (3) vegetation canopy height and distribution. Currently, both sensors incorporate down-looking cameras 

for collecting digital photography in concordance with 

the lidar survey data. 

Data collected by the sensors are referenced to the ground 

using kinematic differential global positioning system 

(GPS) methods, providing vertical accuracy to within 20 

cm. In addition, orientation of the aircraft is measured 

using Inertial Navigation Systems (INS). Small laser spot 

size and high-pulse frequency result in DEM products being produced at a 1 m resolution (Nayegandhi and Brock, 

2002). The ATM and EAARL sensors are mounted on 

small aircraft and can be commissioned as needed. Typical flight time required to complete surveys within the 

NPS Northeast Coastal and Barrier Island network have 

varied between 1 to 5 days. As a result, lidar surveys not 

only provide accurate, high-resolution datasets, but can 

be acquired frequently in order to meet resource-management and monitoring needs. 

Over time, and with major cooperation from the USGS, 

the project has developed to the point where survey data 

is being used in a number of park programs, including 

change detection for shorelines and mapping high-resolution topography and bathymetry. Topographic lidar 

data and aerial photography acquired during NASA 

overflights of ASIS are being used in the Threatened and 

Endangered Species Recover Program1: Piping Plover 

and Sea Beach Amaranth, the Geomorphologic Monitoring Program1

 (elevation models, topographic profiles, and 

beach renourishment), and within the Wildlife Management Program1

: Horse grazing effects on vegetation and 

natural dune evolution (DeStoppelaire and others, 2001). 

The project has also revealed the importance of the 

USGS role in converting raw NASA remote-sensing 

datasets into GIS-compatible information layers of high 

relevance to the management needs of national seashores 

and parks. Lidar surveys result in very large datasets, 

which in their raw format are not compatible with most 

GIS software. The USGS has taken the lead role in developing methods for processing these data to a level that 

can be imported into widely used GIS software packages 

(Brock and others, 2001; Nayegandhi, 2001; Nayegandhi 

and Brock, 2002). Data is presented to the NPS in ESRI 

compatible formats. As a result, the NPS has been able to 

directly access these data for use in park natural resource 

management activities.

1.4 Aims and Objectives of Project

Over time, the seaward edge of barrier islands along 

the northeast U.S. coast has eroded. Periodically, major 

storms wash sand over the barrier island. Coastal erosion 

resulting from both natural and anthropogenic sources 

is one of the primary problems facing park management. Change in shoreline position, either through loss 
3

or accretion, can alter natural habitats. Shoreline retreat 

may destroy cultural resources, facilities, and other infrastructure. Upland resources can be adversely affected 

by coastal erosion because they are not mobile. Another 

basic concern on barrier islands is geomorphologic change. 

Changes in geomorphology drive change in other NPS 

natural resource areas of interest, including: water quality 

in ground and in estuaries, species and habitats of concern, 

recreational visitor use, and resource extraction.

The initial NPS/USGS/NASA cooperative project at ASIS 

has clearly demonstrated the value of NASA aerial surveys 

in meeting “on the ground” NPS resource management 

needs. Presently, lidar surveys are being incorporated in 

Vital Signs and Monitoring methods related to ocean beach 

features within the Northeast Barrier Island Park Network.1

The NPS has identified shoreline, dune, and vegetation 

features as critical indicators of geomorphic change. 

Over time, sand is transported inland onto dunes where it 

is trapped by vegetation and remains there until removed 

by storms. This movement of sand dissipates onshore 

wave energy and works to build dunes, which protect back 

island environments. During large storms, both the shoreline and dunes can erode, sometimes causing the base of 

the dune to collapse, sometimes completely destroying the 

dune. Dunes are also susceptible to wind erosion and depend upon beach grass for their protection. On the surface 

of the dunes, beach grass traps windblown sand. Under 

the surface, grass roots help to stabilize dunes. Changes 

in both shoreline and dunes may affect the location of the 

seaward edge of vegetation, hence its use as one of the indicators of change monitored by park resource managers at 

Assateague Island National Seashore. Using aerial surveys 

to periodically monitor changes in the seaward edge of 

vegetation enables park managers to assess management 

needs in a reasonable time frame and cost in the dynamic 

coastal environment. One component of the project is to 

develop a method for the detection and extraction of the 

seaward edge of terrestrial vegetation, or “vegetation line”. 

The vegetation line is defined here as the first line of stable 

natural vegetation along the ocean beach side of the barrier island. This line represents the boundary between the 

normal dry-sand beach, which is subject to constant flux 

due to waves, tides, storms and wind, and the more stable 

upland areas. It is generally located at, or immediately 

oceanward of, the seaward toe of the frontal dune or erosion escarpment (Figure 2).

1.5 Methodology Overview

The vegetation line was determined from digital aerial 

photography by using the ESRI software package. Photographs provide a qualitative, and potentially quantitative, record of the barrier island conditions (Figure 3). 

They can be used to document general conditions, storm 

events, development, or to assess resource conditions 

over time. Image-processing software allows for quantitative studies using various methods, such as classifying the image to create a thematic layer in which areal 

extents of classes may be calculated. 

The aerial photography used for this project was collected coincident with the NASA topographic lidar 

surveys using a camera mounted on the sensor platform. 

The photography is true color with an image resolution 

of 1-meter. For the purpose of the vital signs monitoring project, digital photography collected with the lidar 

surveys is preferable to other aerial photography because 

it provides coincident data with the other critical indicators (dune and shoreline) derived from the lidar data. 

Additional types of aerial photography are available from 

Federal agencies; these are listed in Appendix I.

The methodology incorporated the use of ESRI ArcGIS 

8.3 software. ArcMap extensions used included Spatial 

Analyst, XTools, and XClassif (downloaded from the 

ESRI website). The photography is classified using unsupervised classification. The classes are then aggregated 

into six classes. Afterward, the classified raster image is 

Figure 2. Coastal barrier island showing seaward edge of terrestrial vegetation.
4

converted to a feature (polygon) layer. An example showing the digital camera image and the two classifications is 

shown in Plate 1. Finally, the polygon representing sand 

is converted to a polyline layer. This polyline is edited 

in ArcMap to clip out the line that eventually represents 

the edge of vegetation (Figure 4). Detailed step-by-step 

instructions are presented in Section Two of this report.

1.6 Metadata Creation

Federal Geographic Data Committee (FGDC)-compliant metadata records are created for each “final” product. 

Examples of metadata included with products are shown 

in Appendix III.

Figure 3. False-color aerial photo of a portion of Assateague Island 

National Seashore; vegetation shows in shades of red; sand/nonvegetated is white; water is blue. Image courtesy of National Park 

Service.
5

Figure 4. Extracted seaward edge of vegetation line overlaid on digital photo (left) and classified image (right).

Plate 1. (A) Digital aerial photograph of a portion of Assateague Island National Seashore. (B) Classified image. (C) Classified image 

aggregated into six classes.
6

SECTION TWO

Detailed Methods for Extracting Edge of 

Vegetation Line

Detailed Steps using ArcGIS 8.3 

ESRI ArcGIS 8.3 software is used for the extraction of 

the edge of the vegetation line from digital aerial photography. Computer software requirements include: ArcGIS 

8.2 or higher and a Spatial Analyst Extension License. 

To extract a digital line from the imagery without manual 

digitization, the raster image was classified to create a 

thematic layer. The resulting thematic layer was then 

converted from a raster to polygon layer. The polygon 

layer was further converted to polylines, from which 

the vegetation line was extracted. In order to perform 

the classification, a Classification Analysis Tool script 

written for ESRI ArcGIS software was downloaded from 

the ESRI website. Follow the link to the ESRI arcscript 

download page to obtain the tool [URL:http://arcscripts.

esri.com/details.asp?dbid=13784]. All the instructions 

for downloading and other pertinent information can be 

found there. Once the tool has been installed, proceed 

to the step-by-step procedure detailing the methodology 

used to extract the edge of vegetation line from the digital 

imagery as follows:

• Classify image

• Create signature file

• Perform image classification

• Load classified image

• Aggregate classes

• Final classes from aggregation

• Convert raster to polygon

• Convert polygon layer to polyline

• Extract vegetation line

2.1 Classify Image

Open ArcMap and Load image to classify. An example 

using a mosaic of digital camera images captured during 

a 2001 ATM survey is shown in Figure 5. The digital 

camera image is in Geotiff format (assateague.tif).

The Classification Analysis Tool requires the raster to 

be an image format. Use the following steps to perform 

image conversion. If the file is already in image format, 

proceed to step 2.

Click on the Classification Analysis Tool (Figure 6). 

Select Utilities. 

Select Convert Raster to Image.

Select image file name from dropdown list.

Click OK.

Figure 5. Add raster image to ArcMap dataframe.
7

The new image will automatically load into the map 

dataframe. For this example, the new file is named assateague.img.

2.2 Create Signature File

The next step to perform is the image classification using 

the Classification Analysis Tool. First, a signature file 

must be created.

From the dropdown menu of the Classification Analysis 

Tool, select Signature Creator (Figure 7). Options for 

supervised or unsupervised classification are listed. Unsupervised classification was determined to be satisfactory 

for distinguishing between vegetation and sand, which is 

chiefly the edge of vegetation line on Assateague Island. 

A maximum of 25 classes was chosen, but this can be 

adjusted.

Figure 6. Convert raster to image using the Classification Analysis 

tool.

Figure 7. Dialog box used when creating signature file for image 

classification.
8

Select the Unsupervised Classification tab.

Select the Image File to be classified.

Input the Number of Classes. 

Input the Number of Iterations.

Input the Minimum Number of Cells in Valid Class. 

Input the Interval of Sampling.

Provide an output Signature File name (for this example: 

assateague_class.gsg).

Click OK.

2.3 Perform Image Classification

Once the signature file has been created from the image, 

perform the classification on the image (Figure 8).

Select Classification from the Classification Analysis 

Tool menu.

Select the Image to be Analyzed.

Select the Signature File that was just created.

Select new location of Output File and provide a new 

name (assateague_class25.img).

Next, load new image into dataframe; see step 2.4.

2.4 Load Classified Image

The classified image will automatically load into the map 

dataframe. Note that only 15 of the maximum 25 classes 

for this image were created (Figure 9). Note, name 

changed to asis_class25.img)

The classes will be aggregated (reclassified) to create 

fewer classes using Spatial Analyst during the next step.

Figure 8. Use Classification Analysis Tool to perform classification; classification dialog box shown at right.
9

Figure 9. Resulting classified aerial photo (15 classes).
10

2.5 Aggregate Classes

Using Spatial Analyst, reclassify the image until the fewest number of classes necessary to allow for the capture 

of the seaward edge of vegetation have been created 

(Figure 10).

Select Reclass from the Spatial Analyst menu.

Select Input Raster and Reclass Field. 

Provide New Values in order to aggregate the old classes 

into fewer new classes.

Select Output Raster location and enter name (asis_reclass.img).

2.6 Final Classes from Aggregation

For this example, the original 15 classes were aggregated 

until only two new classes remained (Figure 11). The two 

classes are:

sand (value 2), and 

other (value1).

Next the raster is converted to a feature layer (polygons).

Figure 10. Aggregate existing classes into a smaller number of 

classes using Spatial Analyst. Reclassify dialog box shown above.

Figure 11. Final two classes resulting from reclassification are 

shown.
11

2.7 Convert Raster to Polygon

To extract the edge of vegetation Line, convert the raster 

to a feature (polygon) using Spatial Analyst (Figure 12).

Select Convert from the Spatial Analyst menu.

Select Raster to Feature.

From the Raster to Feature dialog, select Input Raster, 

Field, Output Geometry Type (Polygon).

Deselect Generalize Lines if selected.

Select Output Feature location and provide name for 

polygon layer.

Click OK.

2.8 Convert Polygon Layer to Polyline

To extract the edge of vegetation line, the polygon must 

be converted to a polyline. This can be accomplished 

using XTools Pro2.2, an extension for ArcGIS 8.x and 

9.x downloaded from the ESRI webpage. The program 

was written by Maxim Chikinev and Igor Popov. The 

URL used to locate the download is: http://arcscripts.esri.

com/details.asp?dbid=11731 

First, select the polygon that will be edited to create the 

edge of vegetation line. Export to a new file and load into 

the dataframe.

From the ArcMap menu bar, click on Tools (Figure 13).

Figure 12. Using Spatial Analyst, convert raster layer to feature 

(polygon) layer; Raster to Features dialog box shown above.

Figure 13. Using the XTools extension to convert a polygon to a polyline.
12

From the drop-down menu, select XTools.

Select Feature Conversions.

Select Convert Polygons to Polylines.

A pop-up will direct you to select the polygon layer to 

convert and select the directory to which the new file will 

be written with a new file name.

The new polyline will automatically be added to the 

dataframe in ArcMap (Figure 14).

Next, the polyline will be edited to extract the edge of 

vegetation line. 

2.9 Extract Vegetation Line

Edit the polyline to extract the vegetation line. Clip out 

line that runs between seaward edge of terrestrial vegetation and sand using the Editor tool in ArcGIS (Figure 15). 

In areas where there is no stable natural vegetation 

present, this line shall be established by connecting or 

extending the lines from the nearest adjacent vegetation 

on either side of the site and by extrapolating (by either 

on-ground observation or by aerial photographic interpretation) to establish the line. 

Click the Editor menu on the ArcMap toolbar.

From the drop-down menu, select Start Editing.

From the pop-up GUI, select the folder that contains the 

file to be edited.

Select the polyline to edit using the selection tool; this 

will activate the editing tools. Ensure that the file name is 

listed in the Target dialog box on the Editor toolbar.

From the Tasks menu, select Modify Feature.

To edit, the polyline may be clipped; open sections are 

closed by digitizing using the sketch tool, or if the gap is 

small enough, simply drag vertices together.

As edits are made, save using the Save Edits selection on 

the Editor drop-down menu.

Figure 14. Section of polyline/polygon zoomed in to show detail.

Figure 15. Begin Editing menu.
13

When editing is complete, select Save Edits and Stop 

Editing from the Editor drop-down menu.

The resulting line is the edge of vegetation line 

(Figure 16).

Figure 16. Resulting edge of vegetation line shown in red.
14

Appendix I

Obtaining Aerial Photography

Aerial photography may be obtained from the following agencies:

USGS Earth Science 

Information Center

507 National Center

12201 Sunrise Valley Dr.

Reston, VA 22092

800-USA-MAPS

USDA Consolidated Farm 

Service Agencies 

Aerial Photography Field Office

222 West 2300 South

Salt Lake City, UT 84103-0010

801-524-5856

Cartographic and Architectural Branch

National Archives and Records Admin.

8601 Adelphi Road

College Park, MD 20740-6001

301-713-7040

Appendix II

List of Acronyms and Abbreviations

ASIS – Assateague Island National Seashore

ATM – Airborne Topographic Mapper

CCSW – Center for Coastal and Watershed Studies

DEM – Digital Elevation Model

EAARL – Experimental Advanced Airborne Research Lidar

ESRI – Environmental Systems Research Institute

FGDC – Federal Geographic Data Committee

GIS – Geographic Information System

GPS – Global Positioning System

IM – Inventory and Monitoring

INS – Inertial Navigation System

LIDAR – Light Detection and Ranging

NASA – National Aeronautic and Space Administration
15

NCBN – Northeast Coastal and Barrier Network

NPS – National Park Service

USDA – United States Department of Agriculture

USGS – United States Geological Survey

UTM – Universal Transverse Mercator

cm – centimeter

m – meter

Appendix III

Example Metadata for Digital Camera Image

ASIS Digital Camera Mosaic 2001

Metadata:

• Identification_Information

• Data_Quality_Information

• Spatial_Data_Organization_Information

• Spatial_Reference_Information

• Distribution_Information

• Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator: U.S. Geological Survey Center for Coastal and Watershed Studies 600 4th 

Street South St. Petersburg, FL 33701 

Publication_Date: 2001 

Title: ASIS Digital Camera Mosaic 2001 

Edition: First 

Geospatial_Data_Presentation_Form: raster digital data 

Other_Citation_Details: The USGS, in cooperation with the National Park Service (NPS) 

and the National Aeronautics and Space Administration (NASA), is to provide the coastal 

management community with usable, useful digital elevation products. The USGS processes 

aircraft lidar data (provided by NASA), develops software tools and algorithms to use 

and analyze the data and make products available to the coastal management community 

through a variety of media, including the internet, CD-ROMs and data reports. 

Online_Linkage: none 

Description:

Abstract: Dataset contains mosaiced georeferenced digital camera images. These data were 

collected during the September 5, 2001, NASA ATM3 survey mission over Assateague Island 

National Seashore. 
16

Purpose: The digital camera imagery is collected in conjunction with lidar elevation data in 

order to provide a more complete dataset to be used in resource management for National 

Seashores. 

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 20010905 

Currentness_Reference: 20010905 

Status:

Progress: Complete 

Maintenance_and_Update_Frequency: Unknown 

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -81.163032 

East_Bounding_Coordinate: -81.140150 

North_Bounding_Coordinate: 38.216397 

South_Bounding_Coordinate: 38.198342 

Keywords:

Theme:

Theme_Keyword: Airborne Topographic Mapper 

Theme_Keyword: coastal management 

Theme_Keyword: elevation change 

Theme_Keyword: Digital Camera 

Theme_Keyword: resource management 

Place:

Place_Keyword: Assateague Island National Seashore 

Place_Keyword: Atlantic Coast 

Place_Keyword: Maryland 

Place_Keyword: United States East Coast 

Place_Keyword: Virginia 

Access_Constraints: Any use of these data signifies a user’s agreement to comprehension and 

compliance of the USGS Standard Disclaimer. Ensure all portions of metadata are read and clearly 

understood before using these data in order to protect both user and USGS interests. See section 6.3 

Distribution Liability. 

Use_Constraints: Although the USGS is making these datasets available to others who may find 

them valuable, USGS does not warrant, endorse, or recommend the use of these data for any given 

purpose. The user assumes the entire risk related to the use of these data. These datasets are not 

for navigational purposes. USGS is providing these data “as is,” and USGS disclaims any and all 

warranties, whether expressed or implied, including (without limitation) any implied warranties of 

merchantability or fitness for a particular purpose. In no event will USGS be liable to you or to any 

third party for any direct, indirect, incidental, consequential, special, or exemplary damages or lost 

profits resulting from any use or misuse of these data. 

Acknowledgement of the U.S. Geological Survey Center for Coastal and Watershed Studies as a 

data source would be appreciated in products developed from these data, and such acknowledgement 

as is standard for citation and legal practices for data source is expected by users of this data. 

Sharing new data layers developed directly from these data would also be appreciated by USGS 

staff. Users should be aware that comparisons with other datasets for the same area from other time 

periods may be inaccurate due to inconsistencies resulting from changes in photo interpretation, 

mapping conventions, and digital processes over time. These data are not legal documents and are 

not to be used as such. 
17

Point_of_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: U.S. Geological Survey, Center for Coastal and Watershed 

Studies 

Contact_Person: Dr. John C. Brock 

Contact_Address:

Address_Type: mailing and physical address 

Address: 600 4th Street South 

City: St. Petersburg 

State_or_Province: FL 

Postal_Code: 33701 

Country: USA 

Contact_Voice_Telephone: (727)803-8747 

Contact_Electronic_Mail_Address: jbrock@usgs.gov 

Hours_of_Service: Monday-Friday, 8-5, EST 

Data_Set_Credit:

The USGS Center for Coastal and Watershed Studies would like to acknowledge NASA 

Wallops Flight Facility for their cooperation and assistance in the development of the data. 

Native_Data_Set_Environment:

Microsoft Windows 2000 Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 8.3.0.800 

Cross_Reference:

Citation_Information:

Originator: John Brock and Asbury Sallenger, U.S. Geological Survey 

Publication_Date: 2001 

Title: Airborne Topographic Lidar Mapping for Coastal Science and Resource Management 

Geospatial_Data_Presentation_Form: USGS Open-File Report 

Publication_Information:

Publication_Place: St. Petersburg, FL 

Publisher: U.S. Geological Survey 

Citation_Information:

Originator: Brock, J.C.; Wright, C.W.; Sallenger, A.H.; Krabill, W.B.; and Swift, R.N. 

Publication_Date: 2003 

Title: Basis and Methods of NASA Airborne Topographic Mapper Lidar Surveys for 

Coastal Studies 

Geospatial_Data_Presentation_Form: journal article 

Publication_Information:

Publication_Place: West Palm Beach, FL 

Publisher: Journal of Coastal Research 

Spatial_Data_Organization_Information:

Direct_Spatial_Reference_Method: Raster 

Raster_Object_Type: Pixel 

Row_Count: 4000 

Column_Count: 4000 

Vertical_Count: 1 
18

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Grid_Coordinate_System:

Grid_Coordinate_System_Name: Universal Transverse Mercator 

Universal_Transverse_Mercator:

UTM_Zone_Number: 17 

Transverse_Mercator:

Scale_Factor_at_Central_Meridian: 0.999600 

Longitude_of_Central_Meridian: -81.000000 

Latitude_of_Projection_Origin: 0.000000 

False_Easting: 500000.000000 

False_Northing: 0.000000 

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: row and column 

Coordinate_Representation:

Abscissa_Resolution: 0.500000 

Ordinate_Resolution: 0.500000 

Planar_Distance_Units: meters 

Geodetic_Model:

Horizontal_Datum_Name: D_WGS_1984 

Ellipsoid_Name: WGS_1984 

Semi-major_Axis: 6378137.000000 

Denominator_of_Flattening_Ratio: 298.257224

Distribution_Information:

Distributor:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: U.S. Geological Survey 

Contact_Position: GIS Specialist 

Contact_Address:

Address_Type: Mailing Address 

Address: 600 4th Street South 

City: St. Petersburg 

State_or_Province: FL 

Postal_Code: 33701 

Country: USA 

Contact_Voice_Telephone: 727-803-8747 

Contact_Instructions: Call Office for Details 

Resource_Description: Call Office for Details

Distribution_Liability:

The United States Geological Survey shall not be held liable for improper or incorrect use 

of the data described and/or contained herein. These data and related graphics are not legal 

documents and are not intended to be used as such. 
19

The information contained in these data is dynamic and may change over time. The data are 

not better than the original sources from which they were derived. It is the responsibility of 

the data user to use the data appropriately and consistent within the limitations of geospatial 

data in general and these data in particular. The related graphics are intended to aid the data 

user in acquiring relevant data; it is not appropriate to use the related graphics as data. 

The U.S. Geological Survey gives no warranty, expressed or implied, as to the accuracy, 

reliability, or completeness of these data. It is strongly recommended that these data be 

directly acquired from a USGS server and not indirectly through other sources which may 

have changed the data in some way. Although these data have been processed successfully 

on a computer system at the U.S. Geological Survey, no warranty expressed or implied is 

made regarding the utility of the data on another system or for general or scientific purposes, 

nor shall the act of distribution constitute any such warranty. This disclaimer applies both to 

individual use of the data and aggregate use with other data. 

Standard_Order_Process:

Custom_Order_Process: Call USGS for Details

Metadata_Reference_Information:

Metadata_Date: 20050629 

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: U.S. Geological Survey 

Contact_Person: Melanie Harris

Contact_Position: GIS Specialist 

Contact_Address:

Address_Type: Mailing 

Address: 600 4th Street South 

City: St. Petersburg 

State_or_Province: FL 

Postal_Code: 33701 

Country: USA 

Contact_Voice_Telephone: 727-803-8747 

Contact_Instructions: Call Survey for Details 

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

Metadata_Standard_Version: FGDC-STD-001-1998 

Metadata_Time_Convention: local time 

Metadata_Extensions:

Profile_Name: ESRI Metadata Profile 
20

Example Metadata for Edge of Vegetation Line

Edge of Vegetation - ASIS 2001

Metadata:

• Identification_Information

• Data_Quality_Information

• Spatial_Data_Organization_Information

• Spatial_Reference_Information

• Entity_and_Attribute_Information

• Distribution_Information

• Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator:

U.S. Geological Survey Center for Coastal and Watershed Studies 600 4th Street South 

St. Petersburg, FL 33701 

Publication_Date: 2004 

Title: Edge of Vegetation - ASIS 2001 

Edition: First 

Geospatial_Data_Presentation_Form: vector digital data 

Other_Citation_Details:

The USGS, in cooperation with the National Park Service (NPS) and the National 

Aeronautics and Space Administration (NASA), is to provide the coastal management 

community with usable, useful digital elevation products. The USGS processes aircraft 

lidar data (provided by NASA), develops software tools and algorithms to use and 

analyze the data and make products available to the coastal management community 

through a variety of media, including the internet, CD-ROMs and data reports. 

Online_Linkage: none 

Description:

Abstract:

Dataset contains edge of vegetation line derived from mosaiced georeferenced digital 

camera images. These data were collected during the September 5, 2001, NASA ATM3 

survey mission over Assateague Island National Seashore. 

Purpose:

The digital camera imagery is collected in conjunction with lidar elevation data in order to 

provide a more complete dataset to be used in resource management for National Seashores. 

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 20010905 

Currentness_Reference: 20010905 
21

Status:

Progress: Complete 

Maintenance_and_Update_Frequency: Unknown 

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -81.154681 

East_Bounding_Coordinate: -81.147511 

North_Bounding_Coordinate: 38.213517 

South_Bounding_Coordinate: 38.199864 

Keywords:

Theme:

Theme_Keyword: Airborne Topographic Mapper 

Theme_Keyword: coastal management 

Theme_Keyword: edge of vegetation 

Theme_Keyword: digital camera 

Theme_Keyword: resource management 

Place:

Place_Keyword: Assateague Island National Seashore 

Place_Keyword: Atlantic Coast 

Place_Keyword: Maryland 

Place_Keyword: United States East Coast 

Place_Keyword: Virginia 

Access_Constraints:

Any use of these data signifies a user’s agreement to comprehension and compliance of the 

USGS Standard Disclaimer. Ensure all portions of metadata are read and clearly understood 

before using these data in order to protect both user and USGS interests. See section 6.3 

Distribution Liability. 

Use_Constraints:

Although the USGS is making these datasets available to others who may find the data of value, 

USGS does not warrant, endorse, or recommend the use of these data for any given purpose. 

The user assumes the entire risk related to the use of these data. These datasets are not for 

navigational purposes. USGS is providing these data “as is,” and USGS disclaims any and all 

warranties, whether expressed or implied, including (without limitation) any implied warranties 

of merchantability or fitness for a particular purpose. In no event will USGS be liable to you 

or to any third party for any direct, indirect, incidental, consequential, special, or exemplary 

damages or lost profits resulting from any use or misuse of these data. 

Acknowledgement of the U.S. Geological Survey Center for Coastal and Watershed Studies 

as a data source would be appreciated in products developed from these data, and such 

acknowledgement as is standard for citation and legal practices for data source is expected by 

users of this data. Sharing new data layers developed directly from these data would also be 

appreciated by USGS staff. Users should be aware that comparisons with other datasets for 

the same area from other time periods may be inaccurate due to inconsistencies resulting from 

changes in photo interpretation, mapping conventions, and digital processes over time. These 

data are not legal documents and are not to be used as such. 

Point_of_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: U.S. Geological Survey, Center for Coastal and Watershed 

Studies 

Contact_Person: Dr. John C. Brock 

Contact_Position: National Coastal Assessment Project Chief 
22

Contact_Address:

Address_Type: mailing and physical address 

Address: 600 4th Street South 

City: St. Petersburg 

State_or_Province: FL 

Postal_Code: 33701 

Country: USA 

Contact_Voice_Telephone: (727)803-8747 

Contact_Electronic_Mail_Address: jbrock@usgs.gov 

Hours_of_Service: Monday-Friday, 8-5, EST 

Data_Set_Credit:

The USGS Center for Coastal and Watershed Studies would like to acknowledge NASA 

Wallops Flight Facility for their cooperation and assistance in the development of the data. 

Native_Data_Set_Environment:

Microsoft Windows 2000 Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 8.3.0.800 

Cross_Reference:

Citation_Information:

Originator: John Brock and Asbury Sallenger, U.S. Geological Survey 

Publication_Date: 2001 

Title:

Airborne Topographic Lidar Mapping for Coastal Science and Resource Management 

Geospatial_Data_Presentation_Form: USGS Open-File Report 

Publication_Information:

Publication_Place: St. Petersburg, FL 

Publisher: U.S. Geological Survey 

Citation_Information:

Originator:

Brock, J.C.; Wright, C.W.; Sallenger, A.H.; Krabill, W.B.; and Swift, R.N. 

Publication_Date: 2003 

Title:

Basis and Methods of NASA Airborne Topographic Mapper Lidar Surveys for Coastal 

Studies 

Geospatial_Data_Presentation_Form: journal article 

Publication_Information:

Publication_Place: West Palm Beach, FL 

Publisher: Journal of Coastal Research 

Spatial_Data_Organization_Information:

Direct_Spatial_Reference_Method: Vector 

Point_and_Vector_Object_Information:

SDTS_Terms_Description:

SDTS_Point_and_Vector_Object_Type: String 

Point_and_Vector_Object_Count: 83
23

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Grid_Coordinate_System:

Grid_Coordinate_System_Name: Universal Transverse Mercator 

Universal_Transverse_Mercator:

UTM_Zone_Number: 18 

Transverse_Mercator:

Scale_Factor_at_Central_Meridian: 0.999600 

Longitude_of_Central_Meridian: -75.000000 

Latitude_of_Projection_Origin: 0.000000 

False_Easting: 500000.000000 

False_Northing: 0.000000 

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: coordinate pair 

Coordinate_Representation:

Abscissa_Resolution: 0.000001 

Ordinate_Resolution: 0.000001 

Planar_Distance_Units: meters 

Geodetic_Model:

Horizontal_Datum_Name: North American Datum of 1983 

Ellipsoid_Name: Geodetic Reference System 80 

Semi-major_Axis: 6378137.000000 

Denominator_of_Flattening_Ratio: 298.257222 

Entity_and_Attribute_Information:

Detailed_Description:

Entity_Type:

Entity_Type_Label: asis2001_edgeveg 

Attribute:

Attribute_Label: FID 

Attribute_Definition: Internal feature number. 

Attribute_Definition_Source: ESRI 

Attribute_Domain_Values:

Unrepresentable_Domain: Sequential unique whole numbers that are automatically 

generated. 

Attribute:

Attribute_Label: Shape 

Attribute_Definition: Feature geometry. 

Attribute_Definition_Source: ESRI 

Attribute_Domain_Values:

Unrepresentable_Domain: Coordinates defining the features. 

Attribute:

Attribute_Label: ParkID 

Attribute:

Attribute_Label: Year 

Attribute:

Attribute_Label: Sensor 

Attribute:

Attribute_Label: Date_ 
24

Distribution_Information:

Distributor:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: U.S. Geological Survey 

Contact_Address:

Address_Type: Mailing Address 

Address: 600 4th Street South 

City: St. Petersburg 

State_or_Province: FL 

Postal_Code: 33701 

Country: USA 

Contact_Voice_Telephone: 727-803-8747 

Contact_Instructions: Call Office for Details 

Distribution_Liability:

The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data 

described and/or contained herein. These data and related graphics are not legal documents and 

are not intended to be used as such. 

The information contained in these data is dynamic and may change over time. The data are 

not better than the original sources from which they were derived. It is the responsibility of the 

data user to use the data appropriately and consistent within the limitations of geospatial data 

in general and these data in particular. The related graphics are intended to aid the data user in 

acquiring relevant data; it is not appropriate to use the related graphics as data. 

The U.S. Geological Survey gives no warranty, expressed or implied, as to the accuracy, 

reliability, or completeness of these data. It is strongly recommended that these data be directly 

acquired from a USGS server and not indirectly through other sources which may have changed 

the data in some way. Although these data have been processed successfully on a computer 

system at the United States Geological Survey, no warranty expressed or implied is made 

regarding the utility of the data on another system or for general or scientific purposes, nor shall 

the act of distribution constitute any such warranty. This disclaimer applies both to individual 

use of the data and aggregate use with other data. 

Standard_Order_Process:

Custom_Order_Process: Call USGS for Details

Metadata_Reference_Information:

Metadata_Date: 20050630 

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: U.S. Geological Survey 

Contact_Person: Melanie Harris 

Contact_Position: GIS Specialist 

Contact_Address:

Address_Type: Mailing 

Address: 600 4th Street South 

City: St. Petersburg 

State_or_Province: FL 

Postal_Code: 33701 

Country: USA 
25

Contact_Voice_Telephone: 727-803-8747 

Contact_Instructions: Call Survey for Details 

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata 

Metadata_Standard_Version: FGDC-STD-001-1998 

Metadata_Time_Convention: local time 

Profile_Name: ESRI Metadata Profile 

References

Brock, J.C., and Sallenger, A.H., 2001, Airborne topographic lidar mapping for coastal science and resource 

management: U.S. Geological Survey Open-File Report 01-46, 4 p.

Brock, J.C., Sallenger, A.H., Krabill, W.B., Swift, R.N., Manizade, S., Meredith, A., Jansen, M., and 

Eslinger, D., 1999, Aircraft laser altimetry for coastal process studies, in Proceedings of the 4th

International Symposium on Coastal Engineering and Science of Coastal Sediment Processes, 

Hauppauge, NY, June 21-23, 1999: v. 3, p. 2414-2428. 

Brock, J.C., Sallenger, A.H., Krabill, W.B., Swift, R.N., and Wright, C.W., 2001, Identification and mapping 

of barrier island vegetation with NASA Airborne Topographic Mapper lidar surveys, in Proceedings of the 

5th International Airborne Remote Sensing Conference, San Francisco, CA, September 17-20, 2001: 8 p.

Brock, J.C., and Wright, C.W., 2002, Initial results from a test of the NASA experimental advanced airborne 

research lidar (EAARL) for the study of coral reef ecosystems, in Proceedings for the 7th International 

Conference on Remote Sensing for Marine and Coastal Environments, Miami, FL, May 20-22, 2002.

Brock, J.C., Wright, C.W., Sallenger, A.H., Krabill, W.B., and Swift, R.N., 2003, Basis and methods of 

NASA Airborne Topographic Mapper lidar surveys for coastal studies: Journal of Coastal Research, v. 

18, no. 1, p. 1-13.

DeStoppelaire, G., Brock, J.C., Lea, C., Duffy, M., and Krabill, W.B., 2001, USGS, NPS, and NASA 

investigate horse-grazing impacts on Assateague Island dunes using airborne lidar surveys: U.S. 

Geological Survey Open-File Report 01-382, 4 p.

Krabill, W.B., Wright, C.W., Swift, R.N., Fredreck, E., Manizade, S., Yungel, J., Martin, C., Sonntag, J., 

Duffy, M., Hulslander, W., and Brock, J.C., 2000, Airborne laser mapping of Assateague National 

Seashore beach: Photogrammetric Engineering and Remote Sensing, v. 66, no. 1, p. 65-71.

Nayegandhi, A., 2001, LaserMap: Software system for processing topographic lidar imagery: Tampa, 

University of South Florida, Masters thesis, 88 p.

Nayegandhi A., 2002, Lidar mapping of vegetation at Assateague Island National Seashore: a first look: 

Sound Waves. [URL:http://soundwaves.usgs.gov]

Nayegandhi, A., and Brock, J.C., 2002, Gridding NASA ATM coastal LIDAR data, in Proceedings for 

the 7th International Conference on Remote Sensing for Marine and Coastal Environments, Miami, FL, 

May 20-22, 2002.

Nayegandhi, A., Brock, J.C., and Wright, C.W., 2005, Classifying vegetation using NASA’s Experimental 

Advanced Airborne Research Lidar (EAARL) at Assateague Island National Seashore, in Proceedings 

of the American Society of Photogrammetry and Remote Sensing Annual Conference (CDROM), 

Baltimore, MD, March 7-11, 2005: 15 p.
26

Notes

1

National Park Service Inventory and Monitoring Program: Northeast Coastal and Barrier Network Vital Signs 

Monitoring Plan Documents [URL:http://www1.nature.nps.gov/im/units/ncbn/m_plan.html]