GUIDANCE FOR BENTHIC HABITAT MAPPING:

AN AERIAL PHOTOGRAPHIC APPROACH

by

Mark Finkbeiner

National Oceanic and Atmospheric Administration

Coastal Services Center

Bill Stevenson and Renee Seaman 

Technology Planning and Management Corporation

March 2001

ACKNOWLEDGMENTS

This document is a product of the experience, wisdom, and applied research of the

National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center. 

Many individuals at the federal, state, and local level have contributed to this document. 

In particular the authors would like to acknowledge Dr. Randolph Ferguson and Lisa

Wood at the NOAA Center for Coastal Fisheries and Habitat Research in Beaufort,

North Carolina, for their efforts in developing the original NOAA Coastal Change

Analysis Program: Guidance for Regional Implementation document and for their

continuing support of benthic mapping. Frank Sargent of the Florida Fish and Wildlife

Commission, Florida Marine Research Institute and Charles Costello of the

Massachusetts Department of Environmental Protection have been consistent

supporters of NOAA’s benthic mapping efforts at the Coastal Services Center. Their

long-term perspective and pragmatic approach to coastal environmental issues have

benefited this document significantly. Dr. Robert Virnstein and Becky Robbins of the

St. Johns River and South Florida Water Management Districts respectively have been

instrumental in helping shape these methods through collaborative project work. The

authors also would like to acknowledge the staff of the NOAA Coastal Services Center,

in particular Dr. Dorsey Worthy and Steve Raber for their leadership and for making this

document possible.

U.S. NOAA Coastal Services Center. 2001. Guidance for Benthic Habitat Mapping: An Aerial

Photographic Approach by Mark Finkbeiner [and by] Bill Stevenson and Renee Seaman, Technology

Planning and Management Corporation, Charleston, SC. (NOAA/CSC/20117-PUB). Available on: U.S.

National Oceanic and Atmospheric Administration. Coastal Services Center. Submerged Aquatic

Vegetation: Data Development and Applied Uses. (CD-ROM). (NOAA/CSC/20116-CD). Charleston,

SC. 2001. 

NOAA/CSC/20117-PUB
CONTENTS

Acknowledgments ...................................................... i

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

• Objectives of This Document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

• What Can Be Mapped Using These Methods .......................... 2

• Document Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Image Acquisition ..................................................... 6

• Mission Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

• Environmental Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Collection of Ground Control Points for Image Rectification ....... ............ 15

• Ground Control Point Selection and Measurement with GPS .... ........ 15

• Alternative Sources of Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Photointerpretation and Image Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

• Recommended Interpretation Decision Rules . . . . . . . . . . . . . . . . . . . . . . . . . 22

Data Development Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

• Analytical Photogrammetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

• Soft-Copy Photogrammetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

• Analog Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Editing and Attributing Polygonal Habitat Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

• Building and Cleaning Polygon Topology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

• Reviewing Edited Polygon Coverages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Field Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

• Field Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

• Signature Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Data Validation Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

• Spatial Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

• Thematic Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

• Temporal Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Supplemental Mapping Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

• Videography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

• Single-Beam Acoustics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Data Quality Reporting and Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

• Spatial Accuracy Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

• Thematic Accuracy Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

• Other Data Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

• Metadata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Appendix 1: Sample Project Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Appendix 2: Brief Overview of Alternative Mapping Technologies . . . . . . . . . . . . . . . 70

Appendix 3: Flight Planning Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Appendix 4: Scanned Aerial Photo Worksheet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Appendix 5: Ground Control Point Collection Sheet . . . . . . . . . . . . . . . . . . . . . . . . . . 75
1

INTRODUCTION

This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic

Approach, describes proven technology that can be applied in an operational manner

by state-level scientists and resource managers. This information is based on the

experience gained by NOAA Coastal Services Center staff and state-level cooperators

in the production of a series of benthic habitat data sets in Delaware, Florida, Maine,

Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well

as during Center-sponsored workshops on coral remote sensing and seagrass and

aquatic habitat assessment. 

The original benthic habitat document, NOAA Coastal Change Analysis Program

(C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the

Department of Commerce in 1995. That document summarized procedures that were

to be used by scientists throughout the United States to develop consistent and reliable

coastal land cover and benthic habitat information. Advances in technology and new

methodologies for generating these data created the need for this updated report,

which builds upon the foundation of its predecessor. 

 

Objectives of This Document 

The goal of this document is to provide technical guidance to data developers working

to produce digital spatial data on benthic habitat. Using these methods, developers will

be able to produce consistent benthic data suitable for regional comparison and

application to various coastal management issues. 

All mapping efforts are designed to answer specific questions about the environment

and meet objectives specific to a given project. The techniques used in generating a

map determine its utility for meeting those objectives. The methods described in this

document are designed to meet the following general objectives:

• Produce digital baseline data on the spatial extent and characteristics of

benthic habitats. 

• Produce synoptic data over estuary-sized study areas. 

• Provide data that optimize the efficiency of further in-situ sampling. 

• Provide data at a resolution that can contribute to environmental

permitting processes (such as Clean Water Act Section 404 fill

determinations).

• Produce data that support change detection over extensive areas.

The technical recommendations are designed to allow some flexibility in the choices of

classification scheme, remote sensor data source, analysis procedures, and other key

elements that vary regionally; however, all have been applied in various regions of the
2

country and should be usable with minor modifications in the majority of geographic

settings. 

The primary audience of this document is the spatial data analyst tasked with

developing baseline benthic habitat data. The methods that follow rely strongly on

aerial photointerpretation and photogrammetry. Effective implementation of these

technologies requires a specialized set of skills and experience. Project analysts ideally

should have a background in remote sensing and photogrammetry. A familiarity with

the physical and biological components of the study area is also very important and a

working knowledge of geographic information system (GIS) technology is essential to

producing the digital data and conducting further spatial analysis of the results. 

A secondary audience is the coastal resource manager. Managers can use the major

components of this document as guidance for preparing technical statements for grants

or contracts, and for project planning. One element that is usually of particular interest

to managers is the expected cost of a mapping project. The actual cost of a project is

determined by many project variables and objectives. Therefore, specific information

on costs is not provided in this document. Cost information is best obtained on a

project-by-project basis in consultation with commercial data and service providers and

other professionals working in the field. 

What Can Be Mapped Using These Methods

The methods in the sections that follow rely strongly on aerial photography, in either

analog or scanned digital format, as the primary data source. Aerial photography is a

powerful tool for identifying habitats within the photic zone. In the nearshore estuarine

and marine environment this zone can range from as shallow as 2 meters to as deep as

30 meters. These methods are well suited to deriving certain types of information about

benthic habitats and are less suited to others. Some of the characteristics that can be

determined using this approach are spatial extent and distribution, habitat

fragmentation (expressed as a percent bottom-cover value), and qualitative measures

of biomass (in the case of submerged aquatic vegetation). Characteristics that are

more difficult to assess using aerial photography are condition or health, species

composition, and sediment texture. In order to capture this more detailed information,

as well as map in deep or turbid areas where the photography is ineffective, the Center

routinely employs submersed videography and single-beam acoustics as supplemental

technologies. These systems capture more specific information about benthic habitats

and also detect certain habitats that cannot be effectively mapped from the air. 

However, these systems are limited by the scale at which they collect data and usually

require some level of statistical interpolation to produce a comprehensive map. 

An explicit habitat classification system is not included with this document. Currently

the Center is developing a comprehensive benthic classification system based strongly

on the best available systems in use by the National Ocean Service (FMRI 1998), the
3

U.S. Fish and Wildlife Service (Cowardin et al. 1979), and various state natural

resource agencies. Nevertheless, some discussion about what habitats can be

mapped using these methods is needed. The following habitats can be reliably

mapped using aerial photography:

• Seagrass meadows, both patchy and continuous cover

• Coral reefs

• Unconsolidated sediments

• Shellfish beds, oyster and mussel

• Hard bottom areas, soft corals, sponges, etc. on consolidated substrate

• Macro algal beds and drift algal accumulations

The following are examples of some of the habitats that are more difficult to map using

aerial imagery. These may require use of alternative technologies to map.

• Low biomass submerged aquatic vegetation (SAV), such as species in the

genus halophila (videography)

• Clam beds (videography)

• Bacterial mats (videography)

• Worm tubes (videography and single-beam acoustics)

• Shrimp burrows (videography and single-beam acoustics)

An example of a digital benthic habitat map of the Buck Island area in the U.S. Virgin

Islands produced using the methods described in this document follows in figure 1. 

This map illustrates a high-resolution multiclass map derived from conventional color

analog aerial photography and compiled using analytical photogrammetry. In this

situation no existing source of ground control was available and points had to be

measured in the field. Depths in the map area range from 0 to -20 meters. The

mapping was supported by two field verification visits to the study area. The

classification incorporates some geomorphological or structural components that give

context to the biologically oriented habitat classes. Some unique features in this area

also were captured in this map, specifically the haystack coral structures. 
4

Figure 1. Benthic habitat map of the Buck Island area, U.S. Virgin Islands.

Document Structure

This document provides specific practical advice and guidance without prescribing a

particular instrument or software. The structure of this report is loosely intended to

follow typical project data development processes, specifically:

• Image Acquisition: collecting imagery under the best conditions.

• Ground Control Point Collection: obtaining spatial control points for image

rectification.

• Image Analysis/Interpretation: guidance and suggested rules for habitat

delineation.

• Data Development: methods for producing digital data.

• Digital Data Editing and Attribution: assigning values and topology to

digital data.

• Field Surveys: methods and approaches for calibrating and verifying the

remotely sensed data.
5

• Supplemental Technologies: guidance for applying two technologies to

complement the remotely-derived data. 

• Data Validation and Metadata: documenting the data for future use.

A sample project plan is included as Appendix 1 that also outlines some of the major

topics that should be considered during the project planning step. The Center

recognizes that there are a variety of technologies and approaches to benthic habitat

mapping. Several of these have great promise for meeting the mapping objectives

previously listed. A brief discussion of some of these technologies is presented in

Appendix 2. Additional appendices include tables that can assist with flight planning,

scanning and ground control point documentation. 

Just as the 1995 implementation document required updates due to changes in

technology, these methods will be supplemented and revised based on technological

advances, emerging environmental issues, and the needs and capabilities of the

coastal management community. Users of this document are strongly encouraged to

consult with the Center’s benthic habitat mapping project Web page

(www.csc.noaa.gov/crs/bhm) for the latest updates and technical guidance. 
6

IMAGE ACQUISITION

No element of a benthic mapping effort is more critical to project success than

collecting source photography at the proper specifications and under the optimal

environmental conditions. Following these procedures and carefully addressing the

environmental variables will have a profound effect on the quality of any mapping. 

Failure to consider them can make mapping impossible. The following sections have

been drawn from the 1995 report (Dobson et al. 1995) and were developed based on

change detection pilot work by Dr. Randolph Ferguson and Lisa Wood of the NOAA

Center for Coastal Fisheries and Habitat Research at Beaufort North Carolina. These

guidelines have proven themselves in every subsequent Center project. They remain

essential for successful benthic mapping. As discussed in the 1995 report, benthic

habitat mapping is primarily a photogrammetric task relying on aerial photography as

the primary data source. Aerial photography has been successfully used for benthic

mapping of diverse habitats (Sheppard et al. 1995; Hopley 1978) and it has the

following advantages for mapping aquatic habitat:

• It provides wide area synoptic coverage amenable to mapping. 

Depending on the scale, a typical aerial photograph provides a planimetric

(map-based) view of several square kilometers of the ground at consistent

resolution.

• It is readily obtainable throughout the nation through either federal, state

or private sources. A strong commercial aerial survey industry exists that

can collect new imagery, and several national archives contain historical

imagery that is available to the public.

• It is easily integrated into the coastal management process. Photography

is already commonly used to address other coastal management issues

such as shoreline and coastal development. This data source is familiar

to the coastal management community and has been accepted into the

legal process.

• It can be obtained when environmental conditions are optimal. Sufficient

aircraft/camera services are available so that a mission can be held on

standby until conditions are right.

• It provides sufficient spectral and superior spatial resolution for detecting

subtle submerged features. Depending on scale, this imagery produces

an image that the human eye can easily interpret and resolves features

smaller than 1 meter.

The image acquisition process consists of two components: 1) setting project

acquisition specifications, and 2) addressing environmental considerations. 

Discussions of both follow.
7

Mission Specifications

Film

The recommended film has been Aerocolor 2445 color negative film. However, Kodak

is now producing Aerocolor film 2444. This film has been applied in a Center benthic

mapping project in coastal Massachusetts and initial results indicate a slight

improvement over 2445. Another good choice is Aerochrome 2448 color reversal film. 

This film has a slower effective aerial film speed that reduces its ability to image darker

submerged features but since it is a reversal film it provides a first generation product

for interpretation. 

Aerographic 2405 black and white negative film has a sufficient spectral range to be

useful for benthic mapping as well, although the loss of color hampers the ability to

discriminate between certain bottom types and between dark bottoms and deeper

water. Anti-vignetting filters are recommended on all these films. Haze filters (Wratten

HF-3 or 2B) are also strongly encouraged to minimize the degrading effect of haze on

photographic images. These filters can be used with 2445 and 2448 films. Aerocolor

2444 has an integral ultraviolet filter and normally does not require additional filtering.

Polarizing filters subdue reflections from the water surface. However, their

effectiveness is influenced by sun angle, and the use of polarizing filters also affects

color saturation of the film. It should be noted that comparable medium- to high-speed

aerial films are available from other sources as well.

Infrared film is generally not recommended for delineating benthic habitats. In a North

Carolina pilot project, with tandem cameras, Aerochrome 2443 false color infrared film

was much less effective than color film at recording benthic features in shallow,

moderately turbid water. Near-infrared light is absorbed in only a few decimeters of the

water surface, and red wavelengths only penetrate to depths of a few meters (Lillesand

and Keifer 2000). Conventional color film gives more information than either black-andwhite or infrared film, and can be critical for initial mapping attempts in new or unfamiliar

areas. This film may permit identification of species in some tropical, clear water areas. 

Color negative film also appears to be better than color reversal or black-and-white film

for identification of habitat under moderately turbid or hazy conditions. Color

transparencies (diapositives) are dimensionally stable and are most amenable to

illumination of dark areas of the photograph for viewing under magnification. Paper

prints are not as dimensionally stable as transparencies (i.e., they are subject to

stretching and shrinking) and typically have lower spatial resolution than diapositives

due to a lower density of silver halide grains. However, paper prints don’t require

backlighting, which makes them more useful in the field.

Flight Line Orientation and Overlap/Sidelap

Flight lines can be planned using U.S. Geological Survey (USGS) 7.5-minute quads,

which at 1:24,000 provide good detail for developing a flight map. NOAA nautical

charts should also be consulted in setting up a flight plan since they depict bathymetry
8

and can indicate areas where submerged aquatic vegetation (SAV) or other important

benthic habitats may be located. 

Occasionally, airspace is restricted for military or other use. These restrictions are

usually indicated on aeronautical charts, which will likely be used by the flight crew

during the actual mission. Reconnaissance flights can provide valuable perspective on

habitat distribution if timed to optimize visualization of shallow bottoms. Ideally, each

photograph in a flight line records sufficient cultural and shoreline features to register

the image to a base map, or support a digital rectification process, about one-third of

the exposure. This permits correction of photographic scale and orientation to the

external reference system. At a scale of 1:24,000 (1 inch = 2,000 feet), a standard 9

inch by 9 inch aerial photograph has a coverage of 18,000 feet by 18,000 feet. Large

areas of open water require parallel flight lines. These should be oriented such that

they support bridging of control points if aerotriangulation is planned, or to maximize the

amount of land features that will assist in image rectification. 

Overlap of photographs includes endlap of adjacent photographs along a flight line and

sidelap of photographs along parallel flight lines. Sixty percent endlap allows

stereoscopic interpretation, facilitates interpretation from the most central region of the

photographs, and usually compensates for loss of coverage due to sun glint in the

photographs. In certain instances where sun glint is expected to be a problem endlap

can be increased to 80 percent to ensure that glint does not prevent interpretation of

certain areas. Sidelap of 30 percent ensures contiguous coverage of adjacent flight

lines and produces a block of aerial photographs that may be subjected to

photogrammetric bundle adjustment if necessary. It also supports the use of pass

points for those using photogrammetric data development methods.

Scale

Photography should be obtained at a scale appropriate to the areal extent of habitat,

local water conditions, type of habitat being studied, and resolution requirements for the

resultant data. Determining a mission scale requires a compromise between resolution

sufficient to detect small features, coverage of habitat with land features sufficient for

horizontal control, and cost. Photographic scale for benthic mapping normally ranges

from 1:12,000 to 1:48,000. For most estuaries, a scale of 1:24,000 represents a good

balance between area coverage and small-feature detection. This scale also matches

the USGS 7.5-minute topographic quad maps. For chronically turbid estuarine or

brackish water areas, 1:12,000 or larger scale photographs obtained at times of

minimal turbidity may be required for acceptable visualization of submerged features. 

Small-scale (higher altitude) photography may be necessary to bridge habitat

delineated in larger-scale (low altitude) photographs to local horizontal control points on

adjacent land feature that are not included in the larger-scale photos. Global

Positioning System (GPS) instruments on board the airplane to position photographic

centers during exposure may be used to reduce this limitation of larger-scale

photography. For extensive areas of relatively clear water such as the Florida Keys, a

scale of 1:48,000 may be sufficient and cost-effective.
9

Metric Cameras

The Center recommends the use of USGS-calibrated metric aerial framing cameras as

a primary sensor for benthic mapping. These cameras have the highest quality optic

lenses and are specially designed to strict tolerances to produce finely detailed

photographs. The exact camera geometry is also recorded in the camera calibration

report. These reports are available from the U.S. Geological Survey and provide a

measure of the distortion and specifications for each camera/lens system. This

information is critical to all photogrammetric applications, where the objective is to

remove radial distortion inherent in the image, topographic displacement, and the

effects of aircraft tilt from the image before compiling a map. These effects are

accounted for in the photogrammetric orientation process and are recorded directly

when the aircraft employs a GPS and an Inertial Motion Unit. Normal aerial survey

mission specifications require that tilt be less than 4 degrees, crab be less than 3

degrees, and both together not exceed 5 degrees (American Society of

Photogrammetry and Remote Sensing - Draft Standards for Aerial Photography, 1995). 

Distortions greater than these can cause offsets in the apparent horizontal locations of

features both above and below the water surface. 

Environmental Considerations

Knowledge of the study area is important to a successful project. This information

includes the following:

• The benthic communities likely to be present 

• The general bottom characteristics in the area

• The plant species comprising any SAV 

• The morphology and phenology of these plants

• The depth ranges and location of known habitats

• Locations with water depth potentially suitable for habitat

• The types and locations of features that may confuse photointerpretation 

• The seasonality of turbidity, weather, and haze 

• Daily patterns in wind speed and direction, and progression of sun angle

through the day 

• Daily and seasonal tidal regimes

Primary and secondary seasonal windows and the day and time of conducting

photography should be selected to optimize the visibility of habitat in the photography.

Water bodies in different locations and at different times of the year will be more or less

sensitive to surface waves, turbidity from local runoff, plankton blooms, and local

resuspension of sediment. Tidal currents and temperature gradients can also result in

material being suspended in the water column. Seasonal and daily trends for haze,

cloud cover, and wind direction, duration and velocity should be included in planning for

photography. The decisions of when to have the aircraft arrive at the study area (within

the seasonal window) and when to collect photography should be based on NOAA
10

National Ocean Service tide tables, local knowledge of factors affecting water clarity

and depth, observation of recent weather patterns (precipitation and wind direction and

speed), and water clarity. The decision to photograph should be based on ground

observations of conditions on the day of the mission and finally on observations by the

flight crew while in the air. It is critical to a project’s success that specific individuals be

charged with making these determinations (one ground crew and one flight crew), and

that these individuals remain in close contact. In most instances the ground-crew

member will be the mapping project leader. The flight-crew member will often be part

of an aerial survey company. Both individuals must have a common appreciation of the

importance of proper environmental conditions to mission success.

Project plans should allow two or three months for primary and secondary photographic

windows to assure the occurrence of optimal conditions for photography. For singleday missions it may be possible to have the plane and flight crew fly to the study area

on the day of photography. In the North Carolina pilot project, staging of the plane and

flight crews to the study area several times for periods of several days was required to

complete missions involving more than one day of actual photography.

In tropical clear-water areas these windows can probably be greatly reduced, while in

the Pacific northwest they may have to be doubled. 

The decision to fly should be driven primarily by atmospheric conditions (clouds), water

clarity, and tidal stage. Other conditions should be optimized as much as possible once

these variables have been addressed.

Phenology

All other conditions being acceptable, the best time of year to acquire photography is

during the season of maximum biomass or flowering of dominant species. Considering

the phenologic overlap, that is the season when most plants or communities are at their

peak, for the entire community. This peak is June for the SAV of the Pacific Northwest

and Atlantic Northeast, April and May for the southeastern U.S., and September for

most of the other species of SAV in the eastern U.S. While biomass may be high

during the summer months, in many areas the strong potential for runoff from

convective storms and haze during this season limits the ability to acquire adequate

photography.

Figure 2, on the following page, illustrates the apparent differences in habitat that can

result from changes due to phenological stage of seagrass. The frame on the left was

acquired in the spring while manatee grass was in full foliage. The frame to the right

was acquired later in the season when above-ground biomass had acquiesced (died

back). There is no real loss of seagrass between the two dates. 
11

Figure 2. Differences in Jupiter Sound, Florida, seagrass biomass. Left photo was acquired in

May 1988 and the right photo in August 1996.

Turbidity

Aerial photography should be conducted when turbidity is low. Care should be

exercised in areas adjacent to sources of suspended sediment and nutrients. Data

collection should be avoided during seasonal phytoplankton blooms. These blooms

may also occur several days after rain events. Data acquisition also should be avoided

immediately following heavy rains or persistent strong winds, which can deliver

sediment loads into nearshore waters or resuspend sediment on the bottom. Potential

days for photography are those during the photographic window for which high-water

clarity is expected, based on local experience, recent weather patterns, and surfacelevel observation. The ground and flight crews should confirm water clarity on the day

of photography. The subtle effects of turbidity on image interpretability can be seen in

figure 3. In the left frame (1988) the edge of a mixed SAV bed in the lower left is clearly

defined, while an algal bloom has obscured this same edge in the frame at right (1996). 
12

Figure 3. Effect of increased turbidity on ability to resolve SAV bed edges. The right photo was

acquired during an algal bloom.

Tidal Stage

Generally, aerial photography should be collected within approximately 2 hours of the

lowest tide as predicted by the NOAA National Ocean Service tide tables, although

factors affecting water depth and water clarity should be considered simultaneously. In

general, extreme low tide, which may be -0.5 to -1.0 or more meters lower than mean

low water around the coast of the U.S., is preferred, if other constraints have been met. 

In some estuaries there is a significant lag in tidal stage, which should be considered for

data acquisition. There are instances, however, where low or falling tide may not be

optimal. This can occur in estuaries where tannic or turbid water is draining out through

an inlet during falling tides. A rising tide in these cases can cause an inflow of clear

marine water that improves the ability to see bottom features. In certain areas, strong

tidal flow can resuspend sediments and degrade water clarity. Missions should be

timed to avoid these events in these locations.

Wind and Surface Waves

For aerial photography, the absence of wind and waves is the ideal condition. Winds of

0 - 5 miles per hour (mph) are generally not a problem and winds from 5 -10 mph may

be acceptable. The direction, persistence, fetch (the distance that wind can blow

unobstructed over water), and recent wind events should be taken into account. Winds

blowing offshore typically pose less of a problem than winds coming in from open water. 

Breaking waves and associated turbidity, whitecaps, wrack lines, and/or floating debris

should not be visible from the air or in the photographs. For some areas, ocean swell

can be an important consideration and should not exceed 3 feet.
13

Figure 4. St. Croix, March 1999. Figure 5. Northeastern Maine, May 1997.

Sun Angle

Sun angle affects the illumination of benthic features, shadows from tall shoreline

features, and the amount of glint in aerial imagery. Sun glint can preclude visualization

of benthic features where it occurs in the photograph. As sun angle increases, glint

also increases and moves from the edge toward the center of the photograph. Using a

typical mapping camera equipped with a six-inch focal length lens mounted in a

standard vertical camera mount, the maximum angular field of view is approximately 94

degrees, or 47 degrees off-nadir (into the corners of the photograph). Sun elevations of

43 degrees would just begin to create glint under these conditions. As sun angle

increases, sun glint also increases and moves from the edge toward the center of the

photograph. 

Sun angles ranging between 30 degrees and 45 degrees are recommended. Sun

angles above 30 degrees illuminate the bottom sufficiently for photographic purposes

while angles above 45 degrees tend to produce glint. Sun glint can be partially

compensated for by acquiring imagery with endlap of 60 percent. This endlap has the

additional benefit of facilitating stereo analysis of the imagery. Increasing the endlap to

80 percent will improve coverage when higher sun angles cannot be avoided. Sun glint

can also be minimized when the sun and land are on the same side of the plane

because sun glint is not as detrimental to the imagery when it occurs on land. Shadows

from tall objects on shore such as trees, however, can preclude visualization of benthic

features and may be a factor when the land and sun are on the same side of the plane.

Figures 4 and 5 show the southeastern quarters of two typical 23 square centimeter (9

inch x 9 inch) metric photographs. Figure 4 was acquired during poor glint conditions. 

Despite clear water conditions, large parts of this photo are uninterpretable due to

excessive glint. Figure 5 shows a similar portion of a photograph as figure 4, but in this

case the timing of the mission was calculated to avoid flying during poor sun angles. 
14

Figure 6. Clouds and shadows over St. Lucie River,

Florida.

Clouds and Haze

It is best to have no clouds or haze in benthic photography. Haze will reduce the

contrast in any aerial photography and hinder the ability to distinguish benthic features

and habitats. Clouds pose a problem

not only when they occur over water,

but also when they occur over

surrounding shoreline areas, thus

reducing the potential source of

features for use as control or pass

points to support image rectification

and photogrammetry. Cloud shadows

have almost as serious an impact on

water features as clouds. The

maximum amount of cloud cover

recommended is 5 percent.

Figure 6 shows how cloud shadows on

water can be confused with SAV beds

or make interpretation impossible. In

many regions of the country, cumulus

clouds tend to form during warm,

summer months in the early afternoon. 

Photography acquired in the morning

generally has a better chance of

avoiding interference from these

convective clouds; however, in certain

regions, convective clouds can even be

a problem during this time of day. 
15

COLLECTION OF GROUND CONTROL POINTS 

FOR IMAGE RECTIFICATION

Rectification of aerial imagery over extensive water bodies poses the greatest challenge

to benthic mapping. Even in areas where habitat can be successfully imaged and

mapped, the lack of usable ground control data to bring the data into a spatial reference

plane can severely hamper the mapping effort. Typically, project leaders will address

this issue by either obtaining spatial location information (x, y, z coordinates) from

another image or map source or by measuring image features on the ground with

surveying instruments or GPS receivers. With the improvement in the coastal

Continuously Operating Reference Stations (CORS) and radio beacons operated by the

U.S. Coast Guard and other agencies, Global Positioning System (GPS) technology

has been established as a powerful way of making direct ground control point

measurements. The following sections outline guidance for this type of measurement

as well as recommendations for using other sources of control.

Ground Control Point Selection and Measurement with GPS

In cases where no acceptable raster or existing point source of ground control points

(GCPs) exists for photorectification, it will be necessary for the project to collect its own. 

If the resources permit, it is often worthwhile to collect at least some independent GCPs

as a cross-reference to a raster control source that may provide the bulk of GCPs. It is

recommended that GCPs be selected after the imagery has been received and

screened. In this way, points can be selected with the best possible distribution

throughout the study area and for the individual photo frames. Collecting GCPs is a

field-intensive process, so all effort should be made to be efficient in selecting the

points.

Point Selection Criteria

Choosing the right features for GCPs will make the measurement process easier and

also facilitate the later image rectification. Good GCPs should meet the following

criteria:

• They should be fixed cultural features that are unlikely to shift position

with time.

• They should be easily visible on the photographs. This will help when the

time comes to measure the point during the rectification process.

• They should be easily accessible, preferably by vehicle. If a point can be

measured without walking a long distance then more points can be

measured in a given time. 

• They should be on public land or rights-of-way to minimize access

restriction by fences and trespass laws.

• They should be located away from tall buildings, large metal objects, and

power lines that may cause multipath effects in the signal.
16

Figure 7. An optimal 

 distribution of full control points

 (yellow labels). Supplemental

 control points are shown in blue. 

 All four quadrants of the photo

 contain a point, and they are 

 distributed on either side of the

 lagoon, which is the focus of this

 mapping effort.

• They should be located in open areas away from heavy tree cover to

minimize the potential loss of satellite signals.

Examples of good GCPs are sidewalk corners and intersections, the corners of paved

parking lots, railroad crossings (in cases where it is safe), and piers and pier abutments. 

Less desirable GCPs are trees or bushes, curves or banks of streams, corners of

buildings, and areas of heavy vegetation cover or sheer terrain.

Point Distribution

GCPs should be selected after a review of the photography and should be well

distributed throughout the photo. Photogrammetric orientation solutions require a

minimum of three points to establish a model. However, it is advisable to collect at

least several additional points (five or six) to allow rejection of points that don’t

contribute to an acceptable solution. In cases where multiple flight lines converge,

more points should be collected to ensure that polygons delineated on adjacent frames

are not out of position with each other. Another case where additional points are

recommended occurs when a flight line begins to extend into remote areas where no

control is available, as in an area where triangulation or bridging is required. In this

case, errors occurring along the triangulated strip are minimized to the greatest extent

possible by a robust rectification at the beginning. Linear arrangements of points or

points clustered in small portions of the photographs will typically not produce the most
17

accurate rectifications. If full aerotriangulation is anticipated for the mapping project, a

greatly reduced number of points is required. In these instances GCPs should be

collected primarily at the beginning and ends of flight lines and around the edges of

parallel lines in a block. 

Point Measurement and Documentation

As GCPs are chosen during a review of the photography, it is recommended that the

points be annotated in some way on a set of working prints. This assists in later

measurement of the points during the rectification process. In addition to documenting

the points on the photos, a data sheet describing each point should be completed. The

most important component of this sheet is a detailed sketch of the actual feature being

mapped. In many cases the scale of the working print will not allow this to be

adequately annotated. The detailed drawing on the data sheet will be valuable later

during the rectification process when the photos can be observed under high

magnification. The sheets also form a cross record for ensuring that all points were

measured. A sample sheet is included at the end of this document in Appendix 5.

The actual measurement or recording of Global Positioning System signals while on

site should normally follow common GPS practices. The goal of this process is to

produce a positional record for the feature that is accurate to less than 1 meter. Using

either real-time differential correction from a radio beacon, or post-processing, the field

data should produce data that meet this requirement, provided the GPS receiver is of

sufficient quality. GPS receivers that are capable of tracking 12 satellites (12-channel)

are more than adequate for this task and are commonly available on the commercial

market. 

Typical settings for GPS data collection are:

• Elevation mask set to 15 to avoid degraded signals from satellites close to

the horizon.

• Positional Dilution of Precision (PDOP) threshold of 6

• Data logging at 1-second intervals

• Collection of data should be conducted for between one and three

minutes to allow a sufficient number of records for statistical analysis such

as t-tests.

• Data should only be logged when a 3-D solution is possible (four or more

satellites) This is usually not a problem given the number of satellites in

the current GPS constellation.
18

Figure 8. Continuously Operating Reference Stations throughout

the U.S.

Sources of Differential Correction Radio Signals

With the recent deactivation of Selective Availability (SA) by the U.S. Department of

Defense, the performance of uncorrected GPS receivers was greatly enhanced. 

Previously, uncorrected signals could produce errors on the scale of hundreds of

meters. Without SA, expected positional errors are on the scale of tens of meters. 

While this has improved general navigation, this accuracy is still usually too low for use

in GCP measurement. In order to produce data of acceptable spatial accuracy, GCPs

should be measured using differential GPS. Both real-time corrections and correction

through post-processing are acceptable. In coastal regions of the U.S. the Coast

Guard operates a series of Continuously Operating Reference Stations (CORS) that

broadcast correction signals. Many GPS receivers can integrate this signal to perform

real-time differential corrections. 

Figure 8 shows the network of

CORS stations current through

May 2000. For recent changes

to this network the user is

encouraged to check the

National Geodetic Survey Web

site at www.ngs.noaa.gov.

Alternative Sources of Control

Although taking measurements at GCPs specifically selected for a project ensures that

the quality and distribution of measurements are sufficient for project needs, there are

several reasons why it would be worth exploring alternate sources of control. The

reasons for this might be as follows:

• The study area is remote and would require extensive travel to visit.

• Access to large parts of the study area is limited and might require boat

travel or overland hiking.

• Suitable GPS receivers are not available.

In these instances it is worthwhile to obtain ancillary sources of control. A variety of
19

Figure 9. Example of digital orthophotograph from Apalachicola Bay

area, Florida. Color infrared film.

sources exist that provide this type of information. These sources vary in quality and

have their own advantages and disadvantages. In addition, some are more universally

available than others. Ancillary control source data, like any other spatial data fall into

either vector or raster format. Examples of a vector source would be a precision

shoreline coverage with physiographic features that could be used to rectify a photo. A

common raster source is a digital orthophotoquad. Orthophotoquads were used

successfully as ancillary control sources in three Center benthic mapping projects

(Coastal Massachusetts; Florida Bay, Florida; and Apalachicola Bay, Florida). These

data are available in many coastal areas through the U.S. Geological Survey or state

governments. They are most often compiled from National Aerial Photography

Program (NAPP) aerial photographs acquired at a scale of 1:40,000 and typically

contain sufficient detail to allow features common to the orthophotoquad and the

mission photography to serve as GCPs. The spatial resolution of these products is

usually less than 2 meters, and they are often stored in a compressed image format

(MrSid) that greatly reduces their size. A potential weakness of these images as source

material is the lack of any elevational value for control features. However, in flat coastal

areas this has not resulted in excessive loss of horizontal accuracy. 

Besides digital raster and vector data as a source of features for rectifying other

images, it is sometimes possible to obtain the original GCPs used to generate such

data. Great caution should be exercised when using these points to rectify project

imagery. In most cases these points will have been collected for purposes other than

benthic mapping. 

Therefore, their distribution

across the landscape may

not be optimal for producing

a solution over water areas. 

Significant data

documentation (metadata)

should also accompany

points to be used from other

sources to allow the user to

determine whether the data

logging thresholds are

compatible with the current

project and to assist in

finding the points on the

image reliably. Figure 9

shows a typical

orthophotoquad. The detail

in this imagery provides

numerous features suitable

for control points. 
20

PHOTOINTERPRETATION AND IMAGE ANALYSIS

The following section draws on Chapter 4 of Dobson et al. 1995; however, since 1995

mapping efforts using these methods have been applied to many other habitats besides

SAV. Other habitats that have been successfully mapped include algae, corals, and

hardbottom habitats. Habitats such as sand flats, mud areas, and rubble bottoms have

also occasionally been mapped. All of these habitats can be identified in aerial photos

within the photic zone. Specific guidance on actual polygon delineation is provided in

the following discussion based on experiences in Indian River Lagoon, Florida, and

other project areas around the country.

Benthic habitats can be interpreted from metric-quality aerial photographs acquired as

recommended in the previous sections. The accurate identification of these habitats in

aerial photographs requires visual evaluation of the fundamental elements of image

interpretation (tone, color, contrast, texture, shadow, etc.). This type of mapping also

requires experience at ground level in the study area since the photographic images of

habitat features vary in ways that cannot readily be modeled, described, or

communicated. Training for a habitat change analysis effort includes literature

research, discussions with local ecologists and biologists, site visits, overflights in small

aircraft, and examination of historical aerial photographs of the area (Maragos and

Cook 1995). Training of photointerpreters is active throughout the life of the project.

Photointerpretation of shallow-water benthic habitats is best accomplished using stereo

pairs of photographs and high quality stereoscopic instruments (e.g. Wild, AVIOPRET,

APT2, stereoscopes). Polygons can then be annotated on overlays fixed to each

photograph or digitally delineated through a screen display or stereoplotter view. To be

delineated as a particular habitat, recognizable and verified signatures associated with

that habitat must be present in the photographs (Hopley 1978). These habitat

signatures will often vary depending upon species composition, bottom sediment,

depth, season, haze, clouds, water clarity and surface disturbances, and sun angle at

the time of photography. The analyst will need to account for this variability in habitat

signature and aggregate them into one habitat class where appropriate or discriminate

between habitat classes during the mapping interpretation process.

The designation of a given area as a particular habitat is a function of minimum

detection unit, minimum mapping unit (mmu), the resolving power/resolution of the

image data, and the area’s proximity to other similar habitats. The minimum detection

unit is the smallest feature that can be discerned in the imagery. Assuming a

photographic scale of 1:24,000, high-quality optics, high-resolution film, and ideal

conditions, it is usually possible to have a minimum detection unit of approximately 1

meter. In pilot work at Buck Island, Virgin Islands, with clear marine water, features of

this size could be seen at depths of over 25 meters (80 feet). All detected habitat types

that appear to be in a continuum with the same adjacent habitat types in an area that

exceeds 0.03 hectares will be mapped as a single polygon. The minimum mapping unit

is the smallest area to be mapped as habitat. At a map scale of 1:24,000, the minimum
21

mapping unit is 0.03 hectares (0.25 acres) for benthic habitats (i.e., a diameter of about

0.8 millimeters on the map represents a diameter of about 20 meters or an area of

about 0.03 hectares on the ground). Therefore, isolated groups of shoots with a

diameter of less than 20 meters may be detected but not mapped as habitat. The

presence of a representative bottom signature in the photograph defines habitat if the

following conditions are met:

• The total area exceeds 0.03 hectares.

• No discontinuities such as land areas, or dredged or natural channels

partition the distribution into spatial units less than 0.03 hectares. 

• Small micro-habitat areas within a polygon are not large relative to the

minimum mapping unit. 

In any effort to map benthic habitats using remote sensing, it is likely that some habitat

areas will be missed due to small size, sparse cover, or poor conditions (turbidity

plumes, depth, etc.). Due to the constraint of the minimum mapping unit and the

possibility of suboptimal photography, delineations of benthic habitat will tend to be

conservative. The degree of underestimation depends upon the atmospheric and

hydrographic conditions at the time of photography, the experience of the

photointerpreter, and the nature of the subject area.

Optimizing conditions for photography will minimize habitat underestimation and other

errors, particularly in areas that are intrinsically more difficult to interpret. Where habitat

edges are clearly distinct in superior quality photography, they may also be detected in

inferior quality photography (e.g., high biomass of SAV along a clear water channel with

a steep bank of light-colored sediment). In other cases where the edges are not clearly

distinct in superior quality photography they are likely to remain undetected in inferior

photography (e.g., low biomass of SAV growing on a shallow depth gradient of deep,

turbid water over dark-colored sediment). The deep-water edge of habitat may be

difficult to delineate. This edge may also be at high risk for loss due to degradation in

water quality that limits the illumination of the bottom with photosynthetically active

radiation. Bottom types with unrecognized signatures due to poor photographic

conditions cannot be mapped as habitat unless the area is rephotographed or

additional sources of data are incorporated into the database. When

photointerpretation is difficult or not possible, the preferred option is to rephotograph the

area under better conditions. Although desirable, this may not be possible. Even under

the best photographic conditions, delineation of all or part of some habitat polygons

may require additional effort in the form of surface level verification or direct inclusion of

surface level data. Polygon borders derived from surface-level data must be so

designated in the project metadata to meet truth in labeling requirements. Suitable

surface level positioning techniques include GPS or more traditional survey positioning

techniques that can be demonstrated to provide high levels of the positional accuracy.

In the case of an SAV polygon, the extent of coverage of the bottom by shoots of SAV

and the pattern of distribution of the shoots or bed form (e.g. circular, doughnut-shaped,
22

irregular patches and/or continuous cover of SAV), reflects the interaction of biotic,

physical, and anthropogenic factors. 

An example of an index of coverage is an adaptation of the crown density scale

originally developed to categorize percent cover by the crowns of trees in forests (Orth

et al. 1991). The Center and USGS are currently discriminating between continuous

beds of SAV and patchy beds. These two habitats have different functional values and

the disintegration of continuous SAV cover into a patchy bed structure can be a sign of

habitat stress. Patchy beds may also be a sign of new colonization. For these reasons

identification of patchy habitat areas is important to habitat monitoring and trend or

change analysis. 

The Center is applying a percent cover system that has been employed successfully for

several years by the St. Johns River and South Florida Water Management Districts for

mapping SAV. This system defines continuous SAV polygons as areas where 51-100

percent of the bottom is covered by that . Areas where coverage is 50 percent or less

are defined as patchy SAV as long as none of the patches exceed the MMU. 

It should be noted that percent cover and bed form identifications are affected by

factors such as water depth, species composition, and brightness of bottom sediments.

The degree of contrast between shoots and exposed sediment, and clarity of the

photographic image determine the minimum detection unit of features within SAV.

Analysis of change over time at a given location therefore requires that different 

photographic conditions be considered. Field verification will be especially important in

evaluating habitat change. Changes in coverage or bed form over time in a given

location may indicate changing conditions in that habitat polygon or disturbances such

as scarring by boat propellers. Figure x shows a sample delineation between

continuous seagrass beds and patchy beds. Consideration of the minimum mapping

unit and individual patch size was essential to this determination

Some data including species, biomass, productivity, functional status, and health of

various habitats may not be interpretable from the aerial photographs. Species

identification is not possible from aerial photography in temperate areas such as North

Carolina, many portions of the Gulf of Mexico, and the Chesapeake Bay. However, in

some tropical areas photographic signatures may be sufficiently distinct to discriminate

between genus, such as high-biomass turtle grass and lower bio-mass shoal grass

beds.

Recommended Interpretation Decision Rules

The following guidelines/strategies for interpretation are presented as general

guidelines to help standardize interpretation. These recommendations are based on

technical guidance used by the St. Johns River and South Florida Water Management

Districts for their ongoing SAV monitoring/mapping project. These recommendations
23

Figure 10. This example shows

 a sample delineation derived using

 the interpretation decision rules listed 

 above. Small patches of SAV in this 

 area have been aggregated where the 

 patches are closer than the minimum 

 mapping unit (mmu) and the aggregated

 area of patchiness is larger than

 the mmu.

are based on the need to conduct change analysis over large areas with as much

consistency as possible. Local needs and project scope may require some modification

of these decision rules.

• Outer boundaries of beds are more important than internal structure

(patchiness, shapes or sand patches within) of beds.

• Outer boundaries of beds are more important than density categorizations

within beds.

• One of the most difficult decisions to make is whether areas with patches

of SAV are one polygon of patchy SAV or individual SAV polygons. In this

case, the minimum mapping unit of 0.03 hectares should be used to make

the determination. 

• Erring on the side of lumping is preferred except in areas where small

patches are the only vegetation. In deciding whether to exclude or include

an area with only a few patches (all less than 0.03 hectares), include the

polygon of patchy SAV if the total area is greater than 0.03 hectares. Err

on the side of including these areas rather than excluding them. 

• A cutoff should be approximately 10 percent cover. Areas with less than

10 percent cover are unlikely to be reliably delineated and may better be

classified as whatever the remaining 90 percent cover type is.
24

In summary, the habitat delineation process should be carried out to preserve the

maximum detail obtainable from the photography. Because a focus of these methods

is on supporting habitat change detection, small movements of an SAV edge due to

increased turbidity or other factors are important to capture. Generalized habitat

delineations will be unlikely to capture these small changes. 
25

DATA DEVELOPMENT METHODS

The Center recommends three methods for creating digital habitat data from aerial

photography and other supplemental data streams. These methods are designed to

maximize the capture of thematically and spatially accurate data on benthic habitat. 

Three methods are presented to provide guidance to agencies with varying levels of

technical capacity. They are also intended to be applicable by state and private-sector

scientists and environmental technicians working in a variety of environmental settings. 

All the methods assume a certain level of expertise in remote sensing and

photointerpretation. The objective in each case is to identify all living benthic habitat

despite the interference presented by the water column. An additional objective is to

produce spatially precise baseline data that minimizes positional offsets that can detract

from the accuracy of subsequent change detection efforts. Three methods listed in

order of preference are recommended for producing benthic data:

• Analytical Photogrammetry

• Soft-Copy Photogrammetry

• Analog Interpretation

Analytical Photogrammetry

This method is the preferred technique for generating digital benthic data. The method

has been applied successfully by several of the water management districts in the state

of Florida. This method employs a stereoplotter to delineate and simultaneously rectify

and digitize habitat polygons. The three-dimensional stereo model of the aerial

photographs is leveled and scaled in the analytical plotter (AP), and the interpreter

views a three-dimensional landscape during photointerpretation. All polygonal

interpretations are automatically stored in digital x, y, and z coordinates in their proper

planimetric position during photointerpretation (Welch et al. 1992), avoiding any error

which might arise during information transfer using a zoom transfer scope or hand

digitization where base map inaccuracies may be a factor.

The analytical photogrammetric process employs either original or duplicate film

diapositives. This is the optimal interpretation medium for photomapping. Analytical

stereoplotters typically have system resolutions on the order of 1 to 2 microns. 

Therefore, to reduce the effects of film shrinkage and distortion that could affect the

orientation process, it is recommended that film be processed to a 7mil estar base for

dimensional stability. In addition to stable diapositives, this method requires ground

control points with elevational values to correct for terrain displacement, radial

distortion, and aircraft positional aberrations (roll, pitch and yaw). These ground control

points can be obtained from a variety of sources, as well as created through GPS as

part of the project activities as previously discussed. Detailed information on the

camera specifications is also needed for this method. This is available through the

camera calibration report. The USGS maintains a calibration report archive for many of
26

the metric cameras used by government and aerial survey firms in the U.S. This can be

obtained through formal request or by accessing the camera calibration database

maintained by the USGS Optical Science Lab. A typical calibration report contains

highly accurate measurements of a camera’s lens distortion, film plane geometry, and

focal length. 

The analytical method consists of three orientation processes (interior, relative, and

absolute). An aerotriangulation step is then required to adjust a block or strip of photo

frames. Once these corrections are complete, the interpretation/digitization of habitat

polygons is accomplished in one step with great spatial precision. 

Orientation Process

The interior orientation consists of specifying camera parameters that will set up the

image on the stage of the instrument. It also will guide the setup of all subsequent

photos in a project. The interior orientation process is accomplished by measuring all

camera fiducials. The Center recommends very strict tolerances for this process since

all error in the orientation process will propagate throughout the rest of the compilation

process. Typical thresholds for this orientation are less than 5 microns.

The relative orientation process follows and involves setting up a stereo model that

allows three-dimensional viewing through two overlapping photos. This is

accomplished by selecting scheme points common to the two photos and measuring

them in three dimensions. The Center recommends a set of 12 paired scheme points

that are well distributed through the overlap area between the two photos, although a

minimum of 6 can be used to produce a solution. The large open-water areas typical to

benthic mapping make this difficult, since bottom features may be required to serve as

scheme points. It is important that scheme point features be clearly visible on both

photos and not obscured by glint, turbidity, or poor exposure on one frame. In areas

with large water expanses the Center recommends that additional scheme points on

land areas be added to the normal 12.

Once the stereo model has been set up through the relative orientation process, an

absolute orientation is needed to introduce the image coordinate system into a

geographic reference plane. It is necessary that the reference plane be cartesian;

therefore the Center recommends that a Universal Transverse Mercator or State Plane

coordinate system be used. During the absolute orientation, ground control point

features are measured in the photography. The x, y, and z coordinate values for each

point are input into a table/database prior to the measuring process, either manually or

by importing existing tabular data. In cases where the aircraft has GPS/IMU data

available, these data can be imported into the orientation process, thus greatly reducing

the need for measured Ground Control Points (GCPs). At the end of this process, each

image coordinate will have a corresponding real-world reference coordinate and

compilation (delineation of habitat boundaries) can begin. The interpretation rules

described in the following sections serve as a guideline during this process. 
27

Aerotriangulation

In cases where multiple strips of photography are required for the project, or in areas

where GCPs are not available, an aerotriangulation process will be required. In fact, it

is recommended that this procedure be used whenever possible, as it reduces the

number of GCPs that have to be measured. This process will rely on tie points

common to exterior oriented photos to rectify photos without any actual GCPs within

them. If GPS/IMU information on photo centers is available, these data will also greatly

facilitate the aerotriangulation process, especially over open-water areas. A

triangulation algorithm will typically employ an iterative least-squares approach to

adjusting the block or strip of photography. The convergence value at which this

process ceases should be in ground units. It is especially important in the

aerotriangulation process to measure tie points accurately and have a minimal

convergence value. 

At the conclusion of the triangulation and compilation process, a set of spatially precise

positionally registered habitat polygons will be exported from the photogrammetric

environment. A subsequent effort to build polygon topology, perform Quality

Assurance/Quality Control (QA/QC), and attribute the polygon data will still be needed.

Recommendations

Analytical stereoplotters are very expensive and require special training. Some

additional expense to locate x, y, and z control points may be necessary to successfully

level the block of aerial photography. This technology may be outside the capability of

many Center partners. For this reason it is recommended that this technique be

employed in the following cases:

• When there is a need for a spatially precise baseline to support future

change detection projects. These often require high levels of positional

accuracy to reduce change caused by positional shifts between data sets.

• When the data are likely to be critical to local permitting activities.

• When the number of photographs in the project is very large and storage

of scanned digital photographs might be problematic.

• When the environmental conditions are challenging and interpretation off

of the original or first generation film media is critical.

• When existing base maps for analog interpretation and zoom transfer are

clearly outdated or inaccurate.
28

Soft-Copy Photogrammetry

Recent advances in soft-copy photogrammetry allow analytical stereoplotter functions

to be accomplished using computer workstations and image processing software (e.g.

ERDAS OrthoBase, Socet Set, Softplotter, and Intergraph). Therefore, this alternative

will become more affordable and attractive in the future. Fundamental to the soft-copy

approach is the fact that the analysis relies on a native digital or scanned analog aerial

photograph. In order to preserve image geometry and the spectral balance in the

native imagery, photogrammetric scanners are recommended to produce the scans. 

The scan resolution (pixels per inch) will vary based on the scale of the original

imagery, but should be sufficient to capture small features that allow identification of

different habitats. Since texture plays such a primary role in this habitat determination,

preserving a high spatial resolution is important to this process. A minimum resolution

that has proven satisfactory for soft-copy interpretation is 1 meter, although higher

resolutions are desirable if file size and computational capacity do not become limiting

factors. In cases where the original film diapositives remain available to the analyst,

lower resolutions can be used. In areas where making an interpretation from the

screen is difficult, the analyst can then fall back on the film data.

Orientation Process and Aerotriangulation

The orientation steps required to build stereo models and register them to a ground

reference plane are the same in soft-copy photogrammetry as in analytical. One

advantage of some soft-copy systems is the ability to automatically generate large

numbers of pass points based on similar image signatures between stereopairs. The

analyst can then choose the best of these points when conducting the relative and

absolute orientations. These points are also then useful in the aerotriangulation

process. Because the images are stored in digital format, large numbers of images can

be called up quickly when doing the block adjustment, unlike analytical instruments,

which require the analyst to reload film diapositives and redo the interior orientation to

accomplish the same step. If a digital elevation model (DEM) exists for the region, the

scanned photography can be orthorectified to this digital data set. As in analytical

photogrammetry, aircraft kinematic GPS and IMU data provide detailed information on

aircraft position and camera nadir location. These data are stored digitally and assist in

rectification of imagery over open water with no GCPs. 

Image Manipulation

In cases where the analyst is interpreting directly from a scanned photograph, there are

a variety of image processing techniques that can assist in delineating habitat. These

include histogram manipulation and stretches to highlight dark areas and increase

contrast, and also spatial filters to emphasize certain spatial patterns in the data. Two

useful techniques are histogram matching and low-pass filtering (Hale and Frazer

1997). These tools can assist an analyst during the mapping process but should be

used carefully to avoid misinterpretation of image artifacts and noise. 

Spectral clustering of aerial photography has been employed in certain studies to
29

produce a quick initial organization of the photo data. These routines can highlight

certain features, especially sand bottoms, but they are extremely vulnerable to

misclassification from spectrally similar features on land or from image artifacts such as

glint or sea state. This approach is not recommended as a mapping method. The level

of effort needed to extract meaningful habitat information from clustered aerial

photography is usually significantly greater than that required of a skilled analyst using

the spectral and spatial data inherent in the photo to perform a manual interpretation. 

However, in certain localized areas of a study area image manipulation may be useful

as an ancillary interpretation tool. When directly interpreting/compiling from scanned

rectified aerial photos it is recommended that, in areas of overlapping coverage,

interpretation be done in the center portion of the photo. Flight plans that incorporate at

least 30 percent sidelap and 60 percent endlap will facilitate this approach. 

The soft-copy photogrammetric method can produce spatially precise habitat polygonal

data of comparable quality to that produced in an analytical environment. However,

there are some advantages and disadvantages to this method that should be

considered when there is a choice of whether to use either the analytical or soft-copy

approach. 

• Skill requirements and computer hardware necessary to conduct this type

of mapping are not as high as for analytical photogrammetry but are

substantial nevertheless. 

• This method has the advantage of allowing multiple analysts to work

simultaneously on a project in a networked environment. 

• Working with a digital image allows the user to employ several image

enhancement processes. Some of the most useful are histogram

stretching and spatial filtering. These can assist in mapping certain

selected areas; however, they must be used with great caution since they

may highlight image artifacts that do not represent actual habitats. 

• The loss of resolution associated with the scanning process does

potentially hinder the interpretation process. The scanning process

produces a spectral record of the raw image that is based on a systematic

x, y array of pixels of a given size. Narrow image features that are not

oriented along the same axis as the scan array can be captured poorly by

the scanning process. In addition, the native resolution of most film

emulsions is on the order of multiple line-pairs per millimeter. Most scan

resolutions are unable to capture images at this resolution.

• Larger projects can raise issues associated with file storage and data

retrieval. A typical color 23 centimeter x 23 centimeter (9 inch x 9 inch)

frame at a scale of 1:24,000, scanned to produce a 1 meter pixel

(acceptable for interpretation), can result in a raw file size of 100

megabytes. 
30

Recommendations

Based on the characteristics of soft-copy photogrammetry, the Center recommends its

use in the following situations:

• Where environmental conditions are especially favorable and

interpretation is less challenging due to the reduced image detail.

• Where data storage is not a limiting factor.

• Where existing hardware supports this method as opposed to the

analytical method.

• Where time can be saved by splitting the workload between skilled

interpreters working on separate computers from a strict set of commonly

agreed-upon guidelines

• In study areas with large expanses of open water without features for

GCPs or terrain points.

Analog Interpretation

Analog interpretation is the traditional method for generating data from aerial

photography. This method involves visually interpreting original or duplicate film and

delineating habitat polygons on transparent or semi-transparent overlays attached to

the photos. The Center recommends that film diapositives be viewed on a light table to

accomplish the interpretation. Original film materials (reversal films) are preferable due

to the loss of detail that occurs during the duplication or printing process. Transparent

polyfilm is the recommended overlay material since it is structurally stable and doesn’t

hinder the interpretation process. Each overlay should be registered to the photo by

annotating the fiducial marks and some portion of the film titling (usually the frame, roll,

date, and mission identification) to allow the overlay to be removed and reattached

correctly. Stereopairs with overlays attached (adjacent photographs with overlap) are

best interpreted using high quality stereoscopic instruments (e.g. Leica SD3000, Wild

AVIOPRET, APT2, B&L stereoscopes, etc.). If overlap is 60 percent or greater, only

every other frame need be annotated. The alternate frame can then be devoted to

fieldwork. High-quality drafting pens are recommended for the annotation process. 

Pen sizes of 4x0 or 3x0 produce a fine continuous line that can be easily digitized at a

scale of 1:24,000; these pens produce lines of 4.3 and 6.0 meters width on the ground.

Once the film has been interpreted and overlays completed, it is then necessary to

bring the interpreted habitat polygons into a corrected reference frame and capture the

information digitally. The reference process usually involves using a zoom transfer

scope to transfer the photo overlay annotations to a hard-copy planimetric base map of

some type. USGS 7.5-minute quadrangles are the usual choice for this process,

although printed orthoquads and NOAA nautical charts are also commonly used. A

second acetate or mylar overlay is often attached to the base map. The zoom transfer

scope allows rubber sheeting of the photo overlay and superimposes the view on a

simultaneous view of the base map using multiple optical lenses. In this manner the
31

distortion and displacement inherent in all aerial photography is removed. Habitat

delineations from the aerial photo are then traced onto the base map overlay using

technical drafting pens.

Recommendations

This method is the simplest and easiest to implement by the greatest number of Center

cooperators. It requires the least capital investment of any of the methods. In the

hands of experienced and diligent photointerpreters, it can produce benthic habitat data

suitable for detailed analysis and for change detection. While this document prefers

photogrammetric methods over analog interpretation, it is useful under the following

conditions:

• When the experience and skill level of the photointerpreters is high but the

technical resources available to support the work are low.

• When project areas are relatively small with extensive land areas for

reference points.

All of these methods, if used by experienced analysts, will produce acceptable benthic

habitat data. The choice of which method or which suite of methods to use is

determined by the project partner. The Center typically works in partnership with statelevel cooperators and private-sector vendors to accomplish a project and can provide

technical guidance and in-kind assistance to partners/firms in completing a project

according to any of these methods, as well as in selecting an approach for developing

benthic habitat data.

Table Digitization

Following transfer of all polygonal annotations to the base map mylars, the linework is

digitized through manual table digitization; alternatively, vector polygon data can be

generated after scanning the overlay and running an automated digitization routine

(ArcTrace, R2V). Although an analyst is still required to assist in the automated

decision process, these vectorization routines have the potential to greatly reduce the

labor associated with the digitization/vectorization process. For these routines to work

smoothly, the linework should be heavy enough and contain enough contrast from the

background mylar to be easily captured during the scanning process and thus

recognized by the vectorization algorithm.

For projects employing the analog method and a zoom transfer rectification process, it

will be necessary to bring line work that has been transferred from the photography to a

hard-copy base map into a digital environment. In table digitizing, a copy of the base

map is attached to a digitizing table and registered on the table using a GIS software

such as ArcInfo. Digitization normally is accomplished by first measuring a set of

graticule tic marks on the map and, once the results show an acceptable spatial error

(expressed as root mean square error or RMSE), then tracing the line work with the

digitizing puck. Because the process relies on hard-copy maps, it is recommended that

stable media such as mylar be used for the base maps whenever possible to minimize
32

the spatial error introduced by shrinkage of the map media. Some simple steps to

successful table digitizing include the following:

• Use the highest quality maps. This includes the best material, the most

appropriate scale, and the most recent publication dates.

• Establish a procedure for the digitizing. This typically involves digitizing

one feature at a time, using a fixed naming convention, etc.

• Prepare the line work. This involves manually indicating start/stop nodes

on polygonal boundaries, assigning easily identifiable names to the

measured tics and clarifying any line-work uncertainties prior to digitizing.

Screen Digitization of Manually Delineated Habitat Polygons

An alternative approach to zoom transfer and table digitization is the screen digitization

approach. In this method the aerial photo, with interpreted overlay attached, will be

scanned and rectified using control derived from GCPs or other rectified images. In the

Center’s Florida Bay project, interpreted source diapositives at a scale of 1:48,000 were

scanned at 600 ppi (pixels per inch). This resulted in a digital image with a resolution of

2 meters. This image provided enough detail to conduct an image-to-image

rectification with digital orthophotoquads provided by the state and adequately captured

the line work on the overlay. Once the photos/overlays have been scanned and

rectified the line work will then be digitized to create the digital polygonal data set. 

There are several software packages that allow digitization and attribution of the line

work. The analyst will manually trace the scanned line work or will employ a vectorizing

software that will automatically create a preliminary vector line coverage. When

manually digitizing the scanned line work, it is important that the analyst trace the line

consistently. Most linework on acetate is annotated using high-quality drafting pens. 

Depending on the gauge of pen used, the delineated lines can be fairly thick. The

analyst should track either the center of the line so that small manual errors during the

digitization process do not alter the delineated polygon boundaries. Automated

digitizing software (R2V, ArcTrace, etc.) exists that can greatly facilitate the process. 

Some of these routines capture a digital line coverage in one pass that then requires an

analyst to edit to close polygons, connect arcs, or remove artifacts. Others require

iterative decision making by the analyst to assist the routine in capturing the appropriate

lines during breaks or intersections. 

At the conclusion of the initial line work generation process, additional processes will be

required to produce a polygon vector coverage with all appropriate habitat attributes. 

These include editing, building, cleaning, and labeling the polygonal line work.

Once these preparatory steps are completed, the line work is ready for digitization. A

general rule is to avoid working near the edge of the table where inaccuracies are

sometimes introduced. The process should start with tic measurements to check

RMSE values. RMSE values at this stage of the process are expressed in terms of

digitizer inches. General values of 0.003 to 0.004 are good for paper maps at 1:24,000. 

The actual RMSE values for a project should reflect the spatial accuracy requirements

of the data in ground units. During the digitizing process it is recommended that only
33

one feature at a time be digitized, such as shoreline, then one class of polygons, etc. It

is also recommended that line work should be traced to overshoot intersection points. 

These can be removed later in the editing process. At the conclusion of either the

screen process (digitizing or interpretation/digitizing) or the table process, the topology

building and editing process will follow.
34

EDITING AND ATTRIBUTING POLYGONAL HABITAT DATA

A final component of benthic mapping from aerial photography is bringing delineated

habitat polygons into a digital format with polygon topology and attributes. Due to its

widespread availability and relative ease of manipulation, preferred formats for this

digital line work are Environmental Systems Research Institute (ESRI) polygon

coverages or shapefiles. The editing and attribution process will be needed after the

following two data development processes:

• After exporting photogrammetrically derived line work into either Arc

generate, auto-cad (.dxf), or design (.dgn) files (analytical or soft-copy

methods).

• After manual or semiautomatic generation of line work from a screen

display (analog method).

A vector is a digital element with a defined structure that represents physical forms

(elements) such as points, lines, and polygons. These terms are defined below as

used in referring to ESRI format data.

• Points represent the locations of a specific geographic feature or object

that has no area, such as a mountain peak, or navigation buoy.

• Lines consist of unclosed segments and represent linear geographic

features, such as rivers, roads, or utility lines.

• Polygons are closed sets of line segments defining homogeneous areas,

such as a particular soil type, land use, or water body. The label point

links each polygon to its attributes This creates a vector layer that

consists of both vector features and the attribute information.

Vector data are expressed as a series of vertex coordinates. The vertices that define

each element are referenced with x, y values (longitude, latitude or easting, northing). 

Although it is possible to have points, lines and polygons in a single layer, a layer

typically consists of one type of feature. 

Building and Cleaning Polygon Topology

Once line work has been digitized, it is necessary to establish the delineated areas as

discrete polygon units recognizable in a GIS software environment. Two ESRI Arc

commands accomplish this, Build and Clean. The Clean command generates a

coverage with correct polygon or arc-node topology. Clean edits and corrects

geometric coordinate errors, assembles arcs into polygons and creates feature attribute

information for each polygon or arc; that is, it creates a polygon attribute table (PAT) or

arc attribute table (AAT). Clean can be used to process line coverages in which

intersecting arcs must be split, or to re-create arc-node topology after editing. This tool

will assist in the prevention of dangles and unclosed polygons. 
35

Figure 11. Graphic representation of the node snap

process.

It is critical that attention be given to setting the tolerances for the clean process. 

Applying the clean process with inappropriate settings can severely damage a

coverage. The choice of a fuzzy tolerance is especially important. No two coordinates

(vertices along an arc) in the output coverage will be within this distance of each other. 

In this respect the fuzzy tolerance determines the detail of the output coverage and

strongly influences its resolution. A fuzzy tolerance that is too small may prevent the

clean process from resolving congruent arc segments, that is, parallel arc segments

that are within the fuzzy tolerance of one another. Existing slivers or undershoots may

not be successfully cleaned. Conversely, a fuzzy tolerance that is too large may

collapse polygons or merge arcs that should not merge. Specific parameters that must

be set for both the Clean and digitizing process include setting arc and node snap

tolerances, weeding and grain tolerance.

Build with the Poly option creates polygon topology and a PAT that contains

information about that polygon. Build with the Line option will create an AAT or rebuild

one if it exists. Build does not perform coordinate editing as does Clean. For

example, it cannot split arcs where they intersect with other arcs. Build does not create

polygon labels. When using Build with the Poly option on an already attributed

coverage, polygons must have label points to retain their attributes. This is important if

some arcs in a previously attributed

coverage were moved during an edit

session and it is necessary to

rebuild polygon topology. As a

general rule it is always preferable to

use the Build command to create

topology as this does not change

nodes, nor does it change vertices

as does the more powerful Clean

command.

Node Snap When the node snap

option is enabled, new and edited

lines that do not terminate at existing

nodes will be automatically snapped

to the nearest node, if there is a

node within the set snap distance.
36

Figure 12. Graphic representation of the arcsnap

process.

Arcsnap. When the arcsnap option

is enabled, new and edited lines that

do not terminate at existing nodes

will be automatically snapped to the

nearest line if there is a line within

the set snap distance. A node will be

created at this new intersection.

Figure 12 illustrates how arcsnap

affects dangling lines and nodes.

Weed. If Weed is enabled, vertices must be at least the weed distance apart to be

retained.

Grain tolerance. Specify the distance between adjacent vertices in lines. This

parameter is used when lines are splined or densified.

When using Clean with the Poly option, polygon label points are recommended but not

required. Do not run Clean on a geographic coverage. Geographic coverages have

units in decimal degrees, decimal seconds, radians, etc. These units are designed to

measure angles. They do not measure distances. They represent a spherical

coordinate system and should not be confused with a two-dimensional rectilinear

coordinate system. Users must first project a geographic coverage to a suitable

projection to convert angles of latitude/longitude to a Cartesian coordinate system using

distance units such as feet, meters, or kilometers. As a general practice, when editing

ESRI vector coverages it is advisable to follow a sequential naming convention that

increases with each editing session. This ensures that data can be reconstructed if a

mistake is made and ensures that the Info file associated with the coverage is always

up-to-date. 

Once a clean polygon coverage has been constructed, the polygons must be attributed

according to their habitat class by assigning polygon labels. This can be a meticulous

process, and it is often helpful to have the source photography and sometimes a hardcopy printout of the digital line work to assist in this process. 
37

Reviewing Edited Polygon Coverages

The Quality Assurance and Quality Control process for reviewing vector data in detailed

habitat maps is especially important. There are two processes involved in reviewing the

line work digitized from the rectified images. Both rely on visual inspection by a

technician.

The first process utilizes a digital display of the scanned and rectified imagery. The

polygonal vector data are overlaid onto the imagery and reviewed to assure all lines

have been successfully captured from the overlay. This is readily accomplished by

examining each frame of photography with the line work assigned an easily viewable

color such as yellow, magenta or red. All line work shared by adjacent photos must be

edge matched (this also serves as a check of the relative quality of the image

rectification). Once the analyst is assured that all the line work has been captured and

all polygons closed, especially where line work extends over adjacent photos, the next

step is to check for attribute accuracy and completeness. 

All polygons should have label points and polygonal topology (see discussion of

cleaning and building topology). Each habitat class should be expressed as an ASCII

string and also as a numeric value. This allows a user to examine the table for habitat

type, and the numeric value allows statistical examination and manipulation of the

habitat data by class. This becomes important when generating random samples for

accuracy assessment. Each class should also be assigned a unique color, and the

coverage should be checked for obvious errors, i.e., inclusion polygons that are most

likely non-SAV and adjacent polygons of the same class. Another check should be

made with only the centroids, assigned a unique habitat class color or habitat attribute,

displayed. This allows the line work and any identification code on the imagery to be

viewed through the polygonal data. 

It is often helpful to conduct both these reviews with hard-copy printouts. Test plots of

the line work should be printed out at the same scale as the photography and

compared to the photos on a light table. Both line work and attributes can then be

assessed and any unacceptable data flagged for further editing in the digital

environment. In complicated coverages over larger areas, it is helpful to work with the

assistance of a grid laid over the printed linework to reduce the chances of missing an 

item or rechecking areas that have already been reviewed. Queries of the polygon

attribute table are also recommended to check for naming consistency and other

issues. 
38

FIELD SURVEYS

Field surveys are critical to any successful remote sensing project. Due to the

difficulties of mapping submerged habitat imposed by the intervening water column,

field surveys are even more critical to creating accurate benthic data. The Center has

traditionally employed extensive field surveys in all of its benthic mapping projects, and

this component will continue to be an important element of future project work. Field

surveys provide critical opportunities for educating image analysts, verifying the

accuracy of data, deploying ancillary technologies to assist in the mapping, and

documenting more detailed habitat character and conditions. However, field surveys

are often one of the more costly components of a project. For this reason, efficiency in

conducting field operations is especially important. Field activities typically fall into one

of two general categories, signature development and accuracy assessment, the former

occurring primarily at the beginning or during a project and the latter at the end.

Regardless of whether field verification is for signature development or final accuracy

assessment, many of the methods for recording site information and the logistics

associated with fieldwork will be the same. Because benthic field verification can

occasionally involve operation of electronic equipment from small craft, planning for

environmental, and other conditions is especially important. The following sections

present some of the issues to be considered for field visit planning, logistics, and

equipment.

Planning

Successful fieldwork is contingent upon good planning. Project leaders need to

consider many factors before leading a team onto the water. During the initial planning

of a field trip, it is important to identify the goals and desired results of the fieldwork. 

The goal will determine the types of data that need to be collected and the amount of

preparation time. Other questions must be considered as well:

• Is this fieldwork for signature development or accuracy assessment? 

• Considering the goal, what are the minimum amounts of sites that need to

be visited?

For most fieldwork, a boat will be necessary to access sites. It is important to consider

the size of the team and the amount of equipment that can fit comfortably on the boat. 

The boat must be suitable for the type of fieldwork to be conducted; a dingy would not

be suitable for offshore fieldwork, while a large deep-draft boat would not be suitable for

getting into shallow marshes. Once the goals are clearly identified, a determination of

what equipment is necessary to conduct the fieldwork must be made. Two very

important considerations must be taken prior to beginning the fieldwork:

• Most computer and GPS equipment is not waterproof, particularly against

saltwater, unless explicitly stated. The equipment will be vulnerable to

humidity, spray and rain. In addition, equipment will be sensitive to direct

sunlight and heat. 
39

• What will be the source of power? Batteries may be short-lived and take

up a lot of space on a boat. A generator produces a lot of noise, fumes,

and heat and needs to be protected from salt water and direct sunlight. 

Connecting to the boat's battery may be a feasible option; however, the

equipment may possibly drain the boat's battery. The best option for a

field team is to use a variety of power sources rather than rely upon one

option.

Weather

Check the local weather forecast and conditions the day of fieldwork. A boat with

"housing" can extend the amount of fieldwork and the life of the equipment, as the

housing provides protection from harsh weather, direct sunlight, or humidity. In

addition, it is important to determine the desired navigational track for the fieldwork. 

The conditions offshore may be extremely different from conditions within a protected

bay. Unfortunately, the team can only plan to do fieldwork during times when the

weather is traditionally calm. It is extremely important to recognize that conditions may

change daily and that fieldwork may be canceled or postponed. 

Tides

Using bathymetry maps or local expertise, determine if areas to be visited are only

accessible during high or low tide. This will reduce the number of boat strandings and

decrease the amount of time at each study site. A nautical chart and/or sound local

knowledge is highly recommended. 

Turbidity

Many observations can be made by swimming, snorkeling, scuba diving and with the

assistance of a towed video camera. The field team may find it advantageous to

conduct verification activities when phytoplankton blooms are not in season, or after

periods of heavy wind or rain, in order to decrease the amount of time required to

adequately characterize the site.

Phenology

Field observations are best made as close as possible to the date of photo acquisition

to facilitate comparison between data recorded in the field and signatures observed on

the imagery. If this is not possible, the field team may find it advantageous to conduct

fieldwork during the same month that the photography was acquired to reduce the error

from observations made during the growing and nongrowing season of SAV. Thus, if

the photography was acquired in June, when SAV has the highest biomass, and the

fieldwork were to be conducted in January when biomass is at its lowest, the

differences in observation would likely be due to the differences in the phenology.

 
40

Field Equipment

The Center has developed field methods that rely on various hardware and software

components to conduct the signature development and accuracy assessment field

verifications. The following section describes the equipment commonly used by project

technicians. This information is included to provide guidance to other researchers in

conducting their own field work. Below are lists of minimal and additional equipment for

field verification. The primary concern in obtaining field information, regardless of the

equipment used, is to record observations with locational certainty. 

Minimum Equipment

• Differential GPS and aerial photographs

• Equipment for observation, which varies depending on depth, weather,

and clarity of water (may range from wading, to scuba, to underwater tow

video systems) 

• Method for recording location and observations

• 8-magnification Lupe lens

• Clipboard (for holding photos or maps)

Additional Equipment

• Laptop computer (weatherized and/or protected from elements) to record

field observations

• Fieldwork software package that collects and displays GPS points while

storing collected field information in a functional and query able database

• GPS hookup to computer for real-time observation of navigational track

and collected data points

• Relevant ancillary data sets (bathymetric data, historic coverage, current

coverage)

• Scanned and rectified aerial photographs

• Snorkel equipment

• Scuba equipment

• Underwater video or still camera with display monitor to view deep or

highly turbid habitats and/or to use during foul weather

• Depth finder

• Viewing tube/bucket for surface observations

• Source of electrical power to support the equipment. The Center has had

much success with small portable generators (1000 Watts). In certain

cases, much equipment can be run from the boat battery. Care must be

taken, however, to avoid drawing down batteries required for starting the

boat engines.
41

Signature Development

Signature development is the process of visiting areas visible on the imagery and

determining the actual habitat present in the field. This process serves primarily as a

training tool to support the subsequent mapping effort. Signature development begins

as the aerial imagery is being screened for quality and acceptability. During this review,

certain portions of the study area will be easily interpreted, while others will be more

difficult. This could be due to isolated problems with turbidity or depth, or unique

habitats either not previously encountered by the analyst or unique to a particular study

area. A signature development visit should be designed around these initial areas of 

confusion. It is recommended that signature development field surveys address the

following themes.

Areas of Confusion/Uncertainty

These sites will be the higher priority sites during any field visit. Typical confusion sites

are caused by factors such as turbidity, depth, glint, sediment color that is confused

with living habitat, unfamiliar habitats, and subtle gradients between identifiable

habitats. There are often a number of these confusion sites within the study area. 

When prioritizing confusion sites for field examination, the emphasis should be placed

on clearly discernable signatures that cannot easily be assigned to a category. Areas

of confusion caused by deep or turbid water should be the next priority. As many of

these sites should be visited as possible. 

Areas of Initial Confidence

In addition to visiting the priority confusion sites, it is also important to visit and verify

areas that initially seemed easily categorized or mapped. This is important to test the

assumptions about the habitat as observed in the preliminary photointerpretation. 

Occasionally, this visit reveals that the initial assumptions were not correct and that

what had been a simple site may now be a confusion site. These types of adjustments

often happen during signature development trips, and some amount of flexibility is

necessary. 
42

DATA VALIDATION METHODS

For every completed data set it is necessary to test the quality and correctness of the

data prior to use and distribution. This final stage is the accuracy assessment. 

Accuracy assessment falls into two categories, spatial and thematic. Spatial accuracy

is the evaluation of the positional correctness of the data, while thematic accuracy is a

measure of whether a habitat or resource is correctly labeled in the final data. Both are

of critical importance since errors in baseline data can be propagated through the

change detection process resulting in false estimates of habitat gain or loss. Portions

of the following discussions on spatial and thematic accuracy are drawn from Chapter 5

of the 1995 report. Recommendations on how to assess the spatial and thematic

accuracy of benthic data are also included. In addition, a short discussion of the

timeliness of the assessment and possible approaches to address this issue are

presented in a section on temporal accuracy.

Spatial Accuracy

Spatial or positional accuracy is a measure of the accuracy of the geometric placement

of points, lines, and polygon boundaries. Positional accuracy of photographic

delineations of submersed habitat is increasingly of concern to resource managers;

however, it has not often been a subject of independent verification. This is

compounded by the fact that positional errors may be difficult to detect even when

verifying a specific polygon in the field. For a single time period, positional errors may

not greatly affect the aggregate area of each cover type. For change detection,

however, positional accuracy is a crucial concern (Ferguson et al. 1992, 1993). 

Change data, especially data produced by post-classification comparison, will

conspicuously record positional errors in excess of about 10 meters between data sets.

This compounds the problem of recognizing real changes in the extent of habitat, which

also tend to occur at polygon edges and class boundaries.

Registration of benthic habitat polygon edges is a function of a combination of factors,

including the metric quality of photographs, the methods used to transfer the

information to a planimetric map base, the spatial accuracy of that base map, the

photorectification process (including the quality of the source control points), and the

quality of the digitization performed. In every case the spatial accuracy of the final

digital data set is only as high as the least accurate source of control. The spatial

accuracy of delineations derived using table methods will only be as accurate as the

base map. In many cases, the most commonly available base maps are USGS 7.5-

minute quads. These have spatial accuracies that meet National Map Accuracy

Standards, which at a scale of 1:24,000 amounts to 13.3 meters on the ground. This is

the minimum spatial accuracy for Center data. 

With the increased availability of higher sources of control, such as differential GPS

units and digital orthoquads, and as image rectification software becomes more
43

common and easy to apply, the need to depend on base maps at National Map

Accuracy Standards is diminishing. Soft-copy and analytical photogrammetric methods

should produce data with spatial accuracies on the order of 1 or 2 meters. While the

recent deactivation of Selective Availability by the U.S. Department of Defense has

greatly increased the spatial accuracy of GPS units without a real-time differential

correction beacon, the accuracies of uncorrected GPS readings remain on the order of

tens of meters and is still not recommended for determining spatial accuracy of Center

digital data.

Recommended Approach

The Center’s benthic habitat mapping project has implemented two tests of spatial

accuracy based on project work in Indian River Lagoon, Florida, and coastal

Massachusetts. In the first test, the benthic habitat polygons are spatially buffered to

produce a zone following the delineated lines. The width of the zone should be

determined by the expected accuracy of the weakest source of control. In the Center’s

experience, using differential GPS as the primary source of control, a buffer of 5 meters

on either side of the line is recommended. This buffer allows for real-time differential

GPS readings that produce values less than 1 meter, but that occasionally produce

readings greater than 1 meter. It also allows for boat motion and addresses the

difficulty of precisely positioning a vessel on the water. This buffer should be

determined by the scale of the imagery and by the sources of control that were used to

bring the data into a reference plane. The maximum buffer width should be 13 meters

on either side of the polygon boundary to be consistent with National Map Accuracy

Standards. This buffered vector data set then becomes a source of randomly selected

spatial accuracy points that are verified in the field by video observation or diving. 

In multidensity habitat classes only the boundaries of high-density (continuous cover)

polygons should be examined to reduce potential subjectivity associated with patchy

polygon boundaries (Bruce et al.1998). At each sample point, a video or diver transect

can be run across the buffer zone, and if the edge of a habitat is detected within the

zone, then the polygon boundary can be considered to have met the spatial accuracy

requirements. This test is most needed in large open-water areas and is also

recommended in more enclosed environmental settings to check the accuracy of the

benthic polygon data. When performing this test, consideration should be given to any

seasonal differences between the date of the imagery and the date of the field

verification. Changes in phenology may affect the apparent edge of certain habitats

such as seagrass meadows and algal beds. 

A second test of spatial accuracy is also recommended to further address the

challenges of precisely positioning a small vessel on the water for more than a few

moments, and the occasional difficulty of determining a habitat edge during low visibility

diving or in a patchy environment. In this test, a fixed terrestrial linear feature, such as

a road or reinforced shoreline is delineated periodically during the mapping process. 

The closer this feature is to the center of the image and the water the better. A
44

Figure 13. Buffered line work for spatial accuracy testing.

differential GPS field measurement is then made on this linear feature (on land) where

it is possible to be more certain of the measurement. 

In cases where Aids to Navigation (ATONs) are present and visible in the imagery, they

can also be used to assess spatial accuracy. The NOAA Office of Coast Survey has

coordinate information for many of these ATONs that can be compared to imagederived coordinates. If no existing coordinate data are available for ATONs in a

particular area, they can be measured using GPS. Day marks on fixed pilings are

preferred for this type of measurement, while anchored buoys are less useful because

their position may shift depending on tidal currents, wind, etc. Great caution should be

exercised if ATONs are to be measured. They are typically located along channels,

and the field crew must avoid posing a hazard to navigation during the measurement

process. Both tests should be done at several locations throughout the data set to

determine overall spatial accuracy. If possible, fixed spatial accuracy points should be

measured on at least every flight line. In cases of long flight lines with many frames, a

measurement from every tenth frame may be needed. Habitat polygon boundary points

may be measured in conjunction with the thematic accuracy assessment.

At the conclusion of the spatial accuracy assessment, the results should be reported as

either correctly located within the buffer or located outside the buffer. For those

samples falling outside the buffered line work, the distance and azimuth of the

boundary should be reported. This information can then be used to improve the

rectification or to edit the line work appropriately. 

Figure 13 shows a graphic

representation of the buffer

approach and how samples

are drawn from within the

buffered area. During field

verification, the points are

visited and any habitat

boundaries within the buffer

indicate that the data are

within the tolerances for

spatial accuracy.
45

Thematic Accuracy

Thematic or attribute accuracy is a measure of the probability that the cover type for

any given polygon is properly identified according to the classification scheme. The

remote sensing literature contains a variety of procedures for measuring attribute

accuracy (Congalton 1991). Generally, these procedures serve well for single time

periods and for relatively small study areas. Historical data, however, cannot be field

verified and conventional procedures also are difficult to apply to large (hundreds of

square kilometers) open-water areas, especially when operating out of small boats.

Thematic accuracy of remotely derived spatial data is influenced by a number of

factors. The most critical is the quality of the source imagery. Others are the

complexity of the benthic environment, the experience of the analyst, the amount of

signature development that has been done to support the mapping, temporal

differences between image date/season and verification data/season, the spatial

precision of the field verification data, and the logical integrity of the classification

system (Congalton et al. 1983; Congalton 1988; and Felix and Binney 1989). The

reported thematic accuracy of a digital map may also be negatively influenced by errors

in making an accurate field determination of habitat type. This can occur when poor

visibility hinders direct observation of habitat in a site or when the boundary between

habitat classes occurs across a transition zone of patchy or fragmented habitat.

Recommended Approach

Currently the approach for thematic accuracy assessment of submersed habitat is

similar to that for emergent and upland habitat, but it should be noted that data for

submersed habitat are intrinsically vector, not raster. Since Center benthic habitat data

are typically in a vector data structure, the actual units of the data are the polygons

themselves, which constitute the thematic accuracy assessment sample units (Elliot

and Bruce 1998).

Habitat polygons (samples) should be selected by random sample stratified by class. 

Other stratification criteria that are useful are region (water body) and bathymetry. 

Vector water body and bathymetric contours can be merged with the habitat data

through the Arc Union process to produce a stratified source for sample units.

Additional sample locations from potential habitat sites (for example, areas of suitable

depth but devoid of mapped habitat) should also be selected. By converting the vector

habitat data to a raster format such as an Arc grid, automated sample generating

routines within commercial image processing softwares such as ERDAS Imagine can

be used. The resulting sample set can be stored in a database format that is

compatible with pen-based field softwares or ESRI’s ArcView. 

An ongoing area of research within the remote sensing community is the appropriate

sample size for a classified remotely derived data set. This sample size should be

based on the expected variance of the cover classification. To date, little research has

been done in the area of benthic habitat. Congalton and Green (1999) recommend as
46

a rule of thumb a sample size of 50 samples (polygons) per class. This was also the

sample size for land cover classification accuracy assessment recommended by Hay

(1979). In every thematic accuracy assessment effort a balance must be reached

between the need to collect a statistically valid sample size and the challenges of

visiting a large number of sites in small boats over project areas on the scale of major

estuaries. While the 50 points per class number was derived based on experience with

terrestrial land cover data, this approach was successfully implemented in the Willapa

Bay, Washington benthic mapping project. Over a period of several days it was

possible to sample this many points from a 4-class map with a reasonable effort. 

When visiting the sample points (polygons) it is important to examine the polygon for

both internal attribute integrity as well as the accuracy of its delineated edge. In large

polygons this can be an intensive process involving multiple video tows or dives. 

Observations can be made starting with circular tows or dives in the interior of polygons. 

The National Ocean Service uses a 7-meter radius for this type of observation in coral

reef mapping. This should be the minimum area surveyed to assess the internal

attributes of a polygon. Video or dive tracks should then be made across the polygon

to determine how well it has been delineated. In many cases at least two tracks normal

to each other are needed to fully assess the polygon. During field verification, the

following minimum number of items should be recorded:

• Latitude or northing of center of polygon

• Longitude or easting of center of polygon

• Depth

• Date

• Map classification

• Observed field classification

• Time

• Observation method (either snorkeling, boat, or video). In the case of

video it is helpful to record what tape the site is captured on.

When making field observations for comparison to aerial synoptic data, the issue of

scale becomes an important factor. Diver or video observation typically takes place on

a scale of meters, while remote observations are made at the kilometer scale. 

Individuals making the field verification should bear in mind that they will see small

habitat changes within an area likely to have been given a single habitat attribute by the

mapper. Small openings and bare areas are often seen within a continuous SAV bed

and do not necessarily indicate an inaccuracy. Likewise, individual plants or coral

heads do not necessarily constitute SAV or coral habitats. A limited study comparing

video transects to aerial photography in Core Sound, North Carolina, highlighted

significant challenges to integrating these two data streams due to scale issues

(Fonseca et al., in publication).
47

At the conclusion of the field visit, the accuracy assessment database containing the

field observations should be used to construct an error matrix. This matrix should be

used to calculate overall and category-specific accuracies as well as a kappa coefficient

and conditional kappa for each class. The kappa coefficient is a statistical measure of

the actual agreement minus chance agreement and measures how well the

categorization sample reflects the actual data. A kappa value of 0.0 is obtained when

agreement between the reference data and a categorization result is the same as the

agreement that would occur from chance alone. The upper limit of kappa is 1.0, which

occurs only when there is perfect agreement (Rosenfeld and Fitzpatrick-Lins 1986). 

Kappa values below 0.5 may suggest that the results of the accuracy assessment do

not actually reflect the validity of the data. The results of the error analysis should meet

an overall accuracy of 85 percent.

Temporal Accuracy

An important issue to be considered when planning the accuracy assessment of a

benthic habitat data set is timeliness. Many benthic habitats, especially seagrass

meadows, are dynamic resources that colonize new areas and die back from existing

areas from season to season. Many are also subject to significant impacts from

catastrophic events such as hurricanes. Unfortunately, it is not unusual for the

accuracy assessment stage of a mapping project to occur months or years after the

original imagery and source data were collected. The changes that can occur in a

habitat over that time can hinder the ability to assess both the spatial and thematic

accuracy of a data set. 

To the extent feasible, the Center recommends that during the initial signature

development stage, a selected set of field observations be collected that will later serve

as accuracy assessment samples more concurrent with the imagery. Collecting this

initial field information as close as possible to the date of the aerial mission increases

the utility of these points for a true accuracy assessment. These samples should then

be separated from the signature development data and not examined until the final

accuracy assessment stage.

If a previous data set is available, the polygons in this data may be a source of initial

sample points that can be visited during the overflight, before the analyst has imagery in

hand. These points can then serve as a set of concurrent accuracy assessment

samples.
48

SUPPLEMENTAL MAPPING TECHNOLOGIES

Although aerial imagery such as photography can provide a wealth of information on

submerged habitat, inevitably there will be areas that are difficult to characterize from

an aerial platform. These areas might be localized turbidity plumes, glint or sea-state

obscured areas, or deeper water locations. In these instances, technologies that are in

more direct contact with the habitat can assist in the mapping effort and also provide a

verification tool for the photographic mapping. Two technologies, underwater

videography and single-beam acoustic sensing, are commonly employed for habitats

found in shallow nearshore estuarine and marine areas. The Center recommends that

these technologies be employed as supplements to the aerial photography rather than

as the primary data source for benthic mapping unless conditions preclude aerial

imaging.

Videography

Submersed videography is a powerful tool for characterizing the benthic environment

and complements. Videography has been used successfully in a variety of

environmental settings, including both clear and turbid water estuaries (Aronson et al.

1995; Norris et al.1997) This technology has the following advantages for benthic

characterization:

• Videography reduces the need for direct diver observation. This is

especially important in colder water, in hazardous areas, and in deeper

environments. The ability to reduce diving for field verification also

lengthens the season in which these operations can be conducted in

northern project areas. Deploying certain video systems is also faster

than using direct dive observation, increasing efficiency and cost

effectiveness. 

• Videography produces a permanent record of observations that are

objective and not as vulnerable to interpretation as diver notes.

• Videography allows detailed observation and characterization of the

habitat. This view allows an analyst to identify individual plant and animal

species. It also facilitates discrimination between a pure seagrass

meadow and one in which algae are growing or have been blown into the

canopy. This may not be detectable through aerial imaging. This close

view can also allow an analyst to distinguish live coral in a reef from dead

rubble that is still standing in place. The level of encrusting algae present

in the environment can be determined from videography, which may give

an indirect measure of the amount of nutrient loading.

• Videography is a powerful tool when used to confirm habitat presence or

clarify causes of uncertain signatures in the imagery.
49

Figure 14. Amphibico - Sony

DVC1000 housing and camera unit.

• Videography allows supplemental delineations in areas that are not

interpretable in the imagery.

While videography is a valuable tool in characterizing benthic habitats, there are a

number of issues that need to be considered when incorporating this type of data into a

comprehensive mapping strategy. Most pressing of these is the difficulty of relating

micro-scale features visible in a video camera to macro-scale features commonly

observed on aerial imagery. For example, the video record will often reveal small open

areas within polygons that are mapped as continuous SAV beds. A continual

consideration of minimum mapping unit and the different scales of information provided

by the two data sets is needed to incorporate video information properly. In addition,

detailed interpretation methods for visually categorizing habitat on video images are

necessary to ensure consistency.

System Types

The Center has employed videography in routine project work since 1995, and this work

has been successful in a variety of geographic settings. Several types of videographic

sensors are commonly used in shallow benthic habitat mapping. These are handheld,

towed, and fixed. 

Handheld video systems are carried by a diver. 

These systems are best used to provide reference

images of different habitat types, or to film sampling

or analysis activities underwater. Because they are

hand held, there is inherently a lack of spatial

reference to the resulting data; therefore, it is best

deployed in situations where spatial location is not as

critical or spatial reference can be determined by

documenting vessel position information and

measuring the distance and direction between the

diver and the vessel. Handheld units have the

advantage of requiring minimal power, being

portable, and easy to use. They do, however,

require a person in the water to collect imagery,

which can increase data collection time and cost. 

They are also not well suited to hazardous

conditions. 

Towed video systems are deployed from both small boats and larger vessels. These

units involve pulling a camera on either a controlled umbilical or freehand. The platform

can either be a sled that rides the bottom or a more free-flying unit. While there is

some positional offset due to the length of the cable, a GPS track recorded on the

survey boat will represent the trail of any tows. In fixed tow arrangements, the offset

and depth can later be calculated to determine the actual position of the unit at a given

time.
50

Figure 15. Fishers TOV-1 unit in a small boat.

Figure 15 shows the Fishers TOV-1

towed video camera unit. This unit

features a low-lux pan camera in a

rugged hydrodynamic housing. It is

designed to skip over the bottom

on weighted runners. 

Fixed units are usually deployed on a davit or pole attached to the survey boat. 

Because these units are mounted on the boat, a GPS record of the track is directly

correlated to the location of the video view. The disadvantages of these systems,

however, are that they require fixed structures on the survey boat and are not easily

portable. They are less useful in deeper waters where the pole may not be long

enough to ensure that the bottom is in view or in waters with varied bathymetry where

sharp rises in the bottom may cause the mount to ground or the bottom to fade out of

view. 

All of these units have their utility and can be included in the development of benthic

habitat data sets. The choice is up to the cooperator and determined by the local study

area character and logistical capabilities. Both towed and fixed video systems can be

set up to allow real-time viewing by analysts in the boat. This allows a field party to stop

the video survey should something unusual appear and then deploy divers for direct

observation. 

By recording the video data onto magnetic tape the data can be reviewed later. This

will assist with the photointerpretation process and will form a permanent record of

conditions at the site. VHS video is also a widely available medium for sharing data. 
51

Figure 16. Frame-grabbed analog panchromatic S-VHS

video image

Figure 16 shows a typical analog

video frame captured through digital

frame-grabbing software. Blades of

manatee grass are clearly visible in

this image. In addition, information on

substrate type, leaf health,

epiphytization, and macrofauna can

be obtained from this imagery. The

field of view in this image is less than

one square meter. When comparing

this type of imagery to aerial

photography, the vast scale

differences between the two must be

considered.

Recommendations on Deployment

The Center employs videography as a supplement and verification tool to aerial

photography. Videography is deployed in selected areas to confirm assumptions and

resolve confusion in the imagery. It also serves as a record for long-term transect

monitoring and more detailed characterization of the benthic environment.

The Center recommends a towed unit for collecting video imagery over more extensive

areas. These units allow sampling in deeper waters as well as very shallow

environments. They also are more responsive to changes in underwater topography

and are simpler to deploy on small boats. The Center recommends that the video unit

be towed across habitat gradients to identify breakpoints. Two cases where this is most

important follow: 

• Where gradual changes are occurring between habitats, such as between

continuous and patchy SAV or between seagrass and algae, etc.

• Where there are optical limitations to delineating habitat, such as those

presented by deep water or turbidity. 

Videography is a powerful tool for making quick identifications for thematic accuracy in

spot drops and for creating images of representative habitat types. Any of the above

units is suitable for this. In order to relate the video to other imagery, the Center

recommends that a GPS track be established for any transect work or waypoints be

marked for point observations. If possible, the GPS coordinate data stream should be

encoded directly onto the video tape so that the data are self referencing. There are a

number of units that will accomplish this. 

Videography is typically used in both the signature development stage and the final

accuracy assessment stage of a benthic habitat mapping project. During signature
52

development, the video is used to assist the analyst in mapping habitat from the aerial

imagery. The GPS track of the video should be overlaid onto the imagery, and the

habitat delineation guided by changes along the track in the video. Videography is also

used as part of the accuracy assessment process. Habitat edges detected in the video

should be compared to line work in the draft data for spatial coincidence and accuracy. 

Single-Beam Acoustics

Single-beam acoustic sensors are increasingly being applied to seabed

characterizations. These sensors are excellent tools for deriving detailed information

about habitat, providing a textural component to imagery, and acquiring bathymetry in

shallow estuaries. Single-beam sensors range in complexity from simple echosounders with strip paper output or LCD display to more sophisticated signal

processors that extract additional information from specific components of the return

waveform or from secondary echoes.

Echo-Sounders

Echo-sounders produce a visual display of bottom texture by showing rough areas of

vegetation or rocks. They also have demonstrated utility for detecting SAV (Maceina

and Shireman 1990; Miner 1993). A qualitative measure of bottom hardness can

sometimes be obtained by examining subsurface echoes. The wavelengths employed

by these echo-sounders vary depending on the model. In general, shorter wavelengths

(higher frequencies) produce more detailed bottom information, but these signals are

more vulnerable to attenuation by the water column. Longer wavelength (lower

frequencies) produce less detail but penetrate to greater depths and thus have a larger

footprint. Echo-sounders have the following advantages and disadvantages as tools for

benthic habitat mapping: 

Advantages

• Echo-sounders are commonly available at relatively low cost.

• They are typically designed for rugged outdoor use.

• They are often integrated into the hulls of many working boats.

• Portable units can be deployed on boats of opportunity.

• They can collect data at higher speeds.

Disadvantages

• There is usually no logging of data other than a real-time display. 

However, some new softwares have been written that capture the

acoustic record.

• They may or may not have positional data integrated into the data stream.
53

Acoustic Signal Processors

Signal processing instruments build on the basic technology of the echo-sounder. In

these more sophisticated instruments, more technology is devoted to producing a

precisely formed wave front on the initial pulse. This is because the altered shape of

the returning first pulse is analyzed as part of the processing. The altered shape of the

return wave produces a record of the bottom roughness component. Signal processing

devices use additional analyses to extract further bottom information from the initial

acoustic pulse. Two units that are commercially available are the QTC View sensor

manufactured by Questar-Tangent and the RoxAnn sensor manufactured by Marine

Microsystems Ltd. 

The QTC unit examines shape of specific regions of the returning wave front and builds

an acoustic signature based on the signal response at these regions (Prager et al.

1995). This approach supports a three-dimensional analysis of acoustic signals that

corresponds to different bottom types. Software for the system allows statistical

analysis of the acoustic returns similar to spectral clustering algorithms used in optical

remote sensing.

The RoxAnn system expands on the traditional use of the first backscatter return for

measuring water depth and limited seafloor sediment information by collecting the

second backscatter return (Burns et al. 1989). The first backscatter returns, E1 values

in the Roxann vernacular, provide a measure of the roughness of the bottom by

isolating the oblique back reflection. The isolation is necessary in order to eliminate the

element of hardness, sub-bottom reverberation, that is already calculated within the

second echo calculation. The second backscatter return, E2, indicates hardness. This

is inferred from signals that have reflected from the seabed and back to the sea surface

before reaching the transducer head. The reflections of these signals provide a

measure of the acoustic impedance of the seabed relative to the seawater above. This

is derived from a combination of both amplitude and length of the second echo

(Rukavina et al. 1997). Combining the information from both returns allows the

operator to discriminate between bottom types.

Because these signal processing units focus on the subtle characteristics of returning

waves, there is little subsurface information captured by the software. Sediment

penetration for the RoxAnn at 220 kilohertz can be 5 to10 centimeters while penetration

at 30 kilohertz may reach 1 to 2 meters depending on the sediment type.

All signal processing acoustic sensor units incorporate a live GPS signal to provide

spatial locational data. Usually the total system consists of the signal processing

device, an echo-sounder, a GPS unit, and a field PC running a data logging/analysis

software. These systems tend to be portable and can be deployed with minimal power

requirements. 
54

Figure 17. An arrangement of survey lines in a typical

project, where an interpolated bottom grid is desired.

Data Acquisition 

When planning an acoustic survey, areas of known habitat type should be visited to

collect signature data. There are two approaches to conducting an acoustic survey of

an area. If possible, a predetermined survey grid pattern can be set up and loaded into

a navigation software package. Then, using live GPS data, the tracks can be followed

by the survey boat. In the experience of Center staff on small open boats, it is difficult

to maintain this type of predetermined grid. Changes in tidal depth can render certain

parts of the study area inaccessible during parts of the day. In addition, wind and

currents can make following the grid tracks almost impossible. In these situations the

Center recommends a strategy that collects data on tracks that increase in proximity as

the survey progresses. The initial set of tracks follows the perimeter of the study area

(usually the shallowest portions of an enclosed water body). Then a set of tracks

crossing the area from west to east are alternated with tracks running north to south (or

along length/width axes). In each subsequent pass, the track bisects the remaining unsurveyed area. This approach thus starts with an initial grid that increases in spatial

resolution as the survey continues. Should weather curtail operations, at least a gross

survey of the entire area can be accomplished. The survey pattern shown in figure 17

is an example of this latter strategy in an enclosed water body. Assuming the end

product will be a grid interpolated from the point data, the desired resolution of the final

data and the spatial variability of the bottom habitats should determine the spacing of

the lines.

Data acquisition in both QTC View

and RoxAnn sensors is limited by

two factors. The first factor is

depth. There must be at least 1.4

meters of water between the

transducer head and bottom in the

RoxAnn unit and 7.0 meters for the

QTC View. Depths shallower than

this cause the first echo to come

back too soon to be captured by

the transducer. Both units typically

contain the LCD display of the

main echo-sounder. As depths

approach the minimum, the analyst

should cross-reference the depth

displays recorded in the data

logging software with the echosounder display. Water that is too shallow can cause the softwares to lock up and

repeat the last good depth, bottom class, and echo values, or it can cause no response

at all. 

The second limiting factor for data acquisition is speed. In practice, using a portable

over-the-side transducer mount for the RoxAnn unit, speeds of approximately 5 knots
55

were optimal for data collection and efficient boat operation. Regardless of the speed,

a consistent speed is recommended to avoid changes in the density of the sample

points and to optimize continual capture of the second echo (Schlagenweit 1993). In

addition, attention must be paid to the location of the transducer. The transducer

should be below the hull, as vertical as possible, and situated away from the propellor

wash to minimize signal distortion. The footprint of the high-frequency (220 kilohertz)

RoxAnn on the bottom is one-tenth of the water depth. 

Calibration/Classification

An initial calibration of the acoustic sensor may be required for each unique study

location. This may be an automated process or may require gathering returns from the

hardest/softest and roughest/smoothest bottom to set the parameters of expected

return values. 

In normal practice, data are classified while the surveying is under way. During the

survey, the analyst assigns classification values to the acoustic data and thus

subsequent data are assigned to these classes. This process of “training” the system

with field observations is called calibration. As new signals are received, a camera or

diver can be deployed to determine the bottom type.

There are two approaches to organizing the initial acoustic data. The first is to rely on

previous classifications or the factory calibration. This approach approximates a

supervised training method where existing values help determine the assignment of

new data. A second approach is to begin with no previous calibration (a blank “box” in

the case of RoxAnn) and observe the signal. When a signal repeatedly clusters around

certain echo values, then a camera, grab sample, or diver is deployed to identify that

particular bottom type. The Center recommends this approach or a combination of the

two for initial surveying. Starting without a calibration reduces the initial bias in a

classification. In starting with the blank box, it is necessary to collect signals from the

softest/smoothest and hardest/roughest bottoms in the study. This will allow an intuitive

arrangement of subsequent bottom types by the analyst. Local experts should be

consulted to locate these initial target bottom types. If necessary, notations on nautical

charts may be used. In figure 17, clearly defined signatures were collected for

continuous seagrass and sand. The other categories, sparse grass, fine sand and mud

were developed partly by their relationship to the initial classes.
56

Figure 18. RoxMap calibration “box” and initial classes.

Figure 18 shows initial acoustic

bottom classes in a calibration box

within the RoxMap software

environment. Greens represent SAV

and browns and yellows represent

unvegetated bottoms. These colored

boxes are organized around

consistent acoustic signals plotted

along the Y (E1- roughness) and X

(E2- hardness) axes.

Data Post Processing

The acoustic data can be exported from most single-beam sensors as a delimited

ASCII text file with a numeric attribute equivalent to the classification, x and y

coordinates, depth, first and second echo values, time, and date fields. An initial

filtering of the data to clean out repetitive records (the RoxMap acquisition software

defaults to the last known good value if speed is too great or depth is too shallow)

results in a point data set ready for importation into a GIS such as ArcView or Imagine. 

The data can then be interpolated or otherwise analyzed depending on the desired

outcome. 

The Center has been using an Inverse Distance Weighting interpolation method with a

nearest neighbor classifier, which can be accomplished in an ArcView Spatial Analyst

environment. This has produced satisfactory results although the output grid cell size is

a variable that is often specific to each project. Several factors influence the success of

the interpolation:

• Diversity of bottom types in an area. Areas of very diverse bottom classes

with high spatial variability should be interpolated with caution to avoid

overgeneralization.

• The orientation of the track lines. Nonsystematic track line layouts tend to

bias the results along certain axes.

• The density of the survey grid. Lines that are closer together better

support interpolation across the entire study area.
57

Figure 19. Preliminary classification of West Florida Shelf station 7. 

Shades of brown correspond to sands and muds in this 1 km2

 area.

• It is useful to produce several grids when evaluating the results of a

survey. These grids are based on the raw echo returns, the bottom

classification, and the bathymetry. This allows a visual check of the logic

of the interpolated bottom classification. 

The Center currently employs the RoxAnn sensor to characterize areas not easily

discernable from the aerial imagery or in sensitive or hazardous environments such as

in inlets, near rocky outcrops, and in areas with rocky high-relief bottoms. This type of

single-beam sensor has been most useful in the shallow water estuaries where Center

projects most commonly occur. However, in deeper water areas other acoustic sensors

can be just as useful.

Advantages of single-beam sensors

• Useful in turbid estuaries where aerial photos cannot image the bottom

• Useful in deepwater environments

• Units are generally portable 

• Multiple classification schemes can be created and stored for later use

• They collect detailed bathymetry

• Data can be exported easily in a simple format for a variety of other

analyses

• Data storage requirements are minimal

Disadvantages of single-beam sensors

• Unknown variance of signal due to sea state, relative orientation of

transducer, salinity gradients, and range of vessel speeds.

• Temperature affects overall signal strength

• Small footprint relative to depth

• Systems are limited to specific depth ranges 

Figure 19 shows a filled 3D

output from the RoxAnn

system. The track line data

are interpolated to produce

a comprehensive colorcoded wire mesh diagram

of the bottom. This figure

was generated from

deepwater seagrass

surveys off the west Florida

continental shelf. A

bathymetric spike on the

left side of the figure may

be due to a fish strike or a

missed return. 
58

Figure 20. Buffered transect lines in a wide area RoxAnn survey.

Figure 20 shows another output processed through ESRI’s ArcView software. In this

example, a 200-meter cell size grid has been created for the study area. The grids

have been assigned a

class based on the

majority class of points

within the 200-meter

grid. The validity of the

interpolation between

measured transect

lines will depend on the

spatial variability of the

bottom and the

required accuracy of

the interpolated data

set. The survey grid in

this instance was more

systematic to take

advantage of additional

benthic sampling, which

assisted in the acoustic

calibration and also

supported the final map

generation.

Recommendations on Deployment

As with videography, the Center generally recommends single-beam acoustics as a

supplement to synoptic data derived from raster remote sensing. Experience in

Rehoboth Bay, Delaware; Apalachicola Bay, Florida; and the West Florida Continental

Shelf suggests that this technology is best applied in medium scale (tens of square

kilometers) projects. Similar work by the U.S. Army Corps of Engineers Waterways

Experiment Station supports this (Sabol et al. 1996). Certain single-beam sensors are

vulnerable to noise produced by rough seas, so missions should be scheduled to avoid

this problem. Transect spacing is a variable that should ideally address the variability of

the bottom and the logistics of the field effort. In Sabol’s work in St. Andrew’s Bay,

Florida, a spacing of 50 meters was adequate. A possible test of the adequacy of a

proposed transect spacing is to sub-survey a small area at a higher transect density

and compare raw and interpolated results.
59

DATA QUALITY REPORTING AND DOCUMENTATION

As described in the 1995 document, Quality Assurance and Quality Control from data

acquisition through final database compilation are the responsibility of each project

team. Acceptance of the final data is contingent upon demonstration that the project

meets the following standards. The Center’s standards of data quality are based on

authoritative references (Goodchild et al. 1990; Chrisman 1991; Lunetta et al. 1991;

and Congalton 1991).

Spatial Accuracy Requirements

Change data between two vector data sets require a high level of spatial accuracy in

order to reduce the amount of change produced by simple offsets. Although early data

sets were restricted in their accuracy by the quality of their base maps, the recent

increases in spatial accuracy provided by differential GPS and photogrammetric

methods for data compilation have made it possible to achieve spatial accuracy on the

order of a few meters. In order to be most useful for subsequent change analysis, it is

expected that spatial accuracy be correct to within 13 meters. This is based on analog

data development methods that rely on USGS topographic maps as a source of control. 

Thematic Accuracy Requirements

Reference data for accuracy assessment must have a resolution and reliability that

meet or exceed those of the remotely sensed data. Occasionally in satellite remote

sensing efforts aerial photographs are used as reference data. However, since aerial

photography forms the primary source data for these benthic mapping methods, only

field observations will suffice to test the thematic accuracy of benthic habitat data. 

These surface-level observations must be evaluated in accordance with the imagery’s

minimum detection unit and minimum mapping unit for the remote data and with the

classification system used to categorize the habitat. The simple presence of an

individual species or natural feature may not, in itself, establish an area as a particular

type of habitat. A number of questions need to be answered to draw a conclusion

about the appropriate cover category to assign based on the reference data: does a

characteristic species or feature meet the minimum detection unit of the remote

sensor? What other characteristic species or features also are present within the

minimum mapping unit?

Due to the subjectivity associated with any photointerpretation process, it is critical that

the thematic accuracy of delineated habitat be as high as possible. The Center

emphasizes the importance of field observation and verification in any remote

sensing/mapping study. Using positionally registered field observation methods,

thematic accuracies over 85 percent should be obtainable by regional scientists. In
60

order to be accepted into the NOAA archive, benthic habitat data should meet or

exceed this overall accuracy. 

Other Data Parameters

In order to facilitate fieldwork, integration with ancillary data, and incorporation with

other project data, the Center requires that benthic habitat data be projected into a

Universal Transverse Mercator projection with a North American Datum of 1983 as a

horizontal datum. Units of measure should be meters and the GRS 1980 spheroid

should be used. This is a Cartesian system that is amenable to photogrammetry and

that also integrates well with other Center coastal spatial data.

Metadata

As part of a federal agency dealing with spatial data, the Center is required to

document its data in a format that is compliant with the Federal Geographic Data

Committee (FGDC) guidelines. Many state agencies are required to produce metadata

in formats unique to their states. These formats may be more or less compliant with the

FGDC guidelines. The Center recommends that producers of data include the following

information at a minimum: 

• Lineage: A record of the type of data sources and the operations involved

in the creation of a database. This includes not only the primary data

source (usually aerial photography) but also supplemental sources of

information such as videography, existing maps, in-situ measurements,

etc.

• Thematic Accuracy and Precision: The closeness of attribute values to

their true values. Expressed as overall accuracy in an error matrix that

illustrates errors of omission and commission.

• Spatial Accuracy and Precision: The positional certainty associated with

polygon, line, and point data in the project, expressed in x, y, z, units.

• Logical Consistency: The adherence of internal data structures to

established conventions or stated rules.

• Temporal Accuracy and Precision: The time over which source materials

were acquired and observations made. 

• Fitness for Use: The degree to which the data quality characteristics of

each database and its components collectively suit an intended

application. Any prohibitions or warnings against inappropriate or

unsanctioned use should be documented.

• Minimum Mapping Unit: This is the smallest unit discretely identified in the

data set. Objects smaller than this will have been aggregated into larger

units.
61

• Projection Information: Documentation of the spatial reference plane into

which the data have been projected, including projection, datum,

spheroid, zones, units, etc.

Information on these characteristics of a data set are sufficient to allow a user to

intelligently analyze it, incorporate it with other geospatial information, and apply it to

environmental decision making in an appropriate manner. However, as part of the goal

of producing a nationally standard data set for coastal benthic habitat, the Center will

require the production of the FGDC metadata record. The Center encourages

cooperators to produce this record themselves as they are best suited to document

their own processes. The Center has produced several tools for generating FGDC

metadata from ESRI vector coverages in an ArcView environment

(www.csc.noaa.gov/metadata/text/download.html). These tools greatly reduce the

effort needed to produce the FGDC record. NOAA Coastal Services Center staff are

also available to assist with the production of this record.
62

CONCLUSION

This document is intended to provide technical guidance to benthic habitat data

developers working with the NOAA Coastal Services Center and for state and national

level mapping efforts. An effort has been made to provide general guidance that is not

limited by specific hardware or software whenever possible. These methods reflect

technologies that have been proven efficient and effective for generating benthic habitat

data in nearshore marine and tidal estuary environment. However, as existing

technologies improve and as new technologies emerge, new technical guidance will be

required. The following principles will be used to update this guidance document:

• Seek a balance between the latest technologies and proven methods

applicable by state-level natural resource scientists on a broad scale.

• Evaluate new technologies and facilitate their adoption by Center partners

through methods development.

• Emphasize comprehensive, raster format data as the preferred source

data structure for habitat mapping. 

• Provide data that facilitate trend analysis and capture ecologically

significant changes in the distribution and spatial arrangement of benthic

habitats.

• Provide data that integrate seamlessly with other spatial data for

comprehensive environmental analysis.

Users of this document are encouraged to consult directly with Center staff and to visit

the Center’s benthic habitat mapping project Web site for updates on methods, Center

activities, and technical resources. It is also recommended that users contact other

Center partners for recommendations in their region. Through this continuing dialogue,

interested scientists will fill the existing data gaps in the nation’s nearshore habitat

database.
63

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68

APPENDIX 1

SAMPLE PROJECT DESIGN

General steps required to conduct a NOAA Coastal Services Center benthic habitat

baseline mapping project.

Project Scoping

• Identify the regional data gap or change detection problem

• Consult with local and regional scientific and management community to

shape specific project goals, objectives, and partners

• Define the study area

• Determine minimum feature of interest size (minimum mapping unit)

• Select data development method

• Refine classification system

Mission Planning/Acquisition

• Identify aerial image sources

• Select sensor and scale

• Flight planning, including points-of-contact (POCs) for go/no-go decision

• Address environmental variables (POC)

• Collect and process aerial imagery

Analysis

• Review imagery and conduct initial field visit, Ground Control Point (GCP)

collection or signature development (employ any needed supplemental

technologies, such as videography or acoustics)

• Interpret aerial photography to extract water and benthic habitat

information (Compilation of initial digital data may be concurrent with this

step when using the photogrammetric or soft-copy data development

methods)

• Second field visit for mid-project verification (employ supplemental

technologies)

Digitization/Vectorization

• Transfer analog polygon data to planimetric map base (if using the analog

method)

• Digitize transferred polygons (if using the analog method)

• Edit and attribute digitized information (needed in all data development

methods)

_____________________________________________________________________
69

APPENDIX 1

SAMPLE PROJECT DESIGN (CONTINUED)

_____________________________________________________________________

Data Validation

• Final field visit to determine spatial (positional) and thematic accuracy

(employ supplemental technologies)

Data Production and Dissemination

• Correct any final inaccuracies in the data

• Generate FGDC compliant metadata

• Distribute via Internet or hard-copy media

• Meet with user community to facilitate integration of the data into coastal

management process

___________________________________________________________________

 
70

APPENDIX 2

BRIEF OVERVIEW OF ALTERNATIVE MAPPING TECHNOLOGIES 

The methods in this document rely strongly on optical remote sensing, specifically

metric aerial photography, and are focused on production of high-resolution data. For

this reason, they are most applicable in moderately clear to clear water systems where

the habitats of interest occur in the photic zone, typically close to coastal land masses. 

A variety of alternative approaches are available for capturing information on the extent

and characteristics of benthic habitats in these areas and elsewhere. 

The following sections briefly describe some of the other major methods for developing

benthic habitat data. Some of these have promise to supplement or even replace some

of the methods recommended in this document. 

Satellite Image Analysis 

Satellite imagery, has been used successfully in tropical ecosystems for coral mapping

(Luczkovich et al. 1993 and de Vel and Bour 1990). Satellite systems have the

advantage of being able to capture images in remote areas or over very extensive

geographies where an aircraft mission could prove difficult. They are typically affected

by the same environmental variables that affect all imaging of submerged features

(clouds, sea state, tidal stage, etc.). Because of their fixed orbital paths acquisition of

satellite imagery under optimal environmental conditions is strictly coincidental,

although off-nadir viewing systems can mitigate this somewhat. Dark bottoms, deep

water and turbid areas tend to introduce confusion into satellite image mapping (Zainal

et al. 1993), nevertheless, this type of remote sensing has a role in remote areas or as

part of an initial reconnaissance. A new generation of high-resolution satellite sensors

such as the IKONOS system have the potential to produce information comparable to

aerial photography when images are collected during optimal conditions. 

Hyperspectral Imaging

Hyperspectral imaging has been a tool for terrestrial remote sensing since the 1970s

and has also been applied to benthic mapping, especially in clear-water systems

(Sciliano et al. 2000). Hyperspectral mapping from airborne platforms allows the

mission to be flown when environmental conditions are favorable. Many hyperspectral

instruments can be calibrated to collect information in the most promising parts of the

spectrum for benthic mapping (usually the blue and green wavelengths) and can have

up to 224 discrete spectral bands (channels). These sensors can be flown such that

they produce high spatial resolution data, but they are vulnerable to difficulties in the

georectification process. Spectral image processing of these data can sometimes

generate useful information on habitat type and condition, but extracting this information

is hampered by the other environmental conditions that affect the spectral response of

a particular bottom feature, such as water chemistry/clarity, glint, sea-state, and

variations in solar illumination. In addition, the skill level required to process this type of

imagery is very high and may be difficult to obtain. 
71

Several technologies are currently in an operational phase of their development and

have great promise for producing data that meet the objectives for which the following

methods were designed. They include both optical and acoustic sensors.

Digital Aerial Photography

This type of imagery has the mission flexibility advantage of other airborne sensors. In

addition, in certain systems aircraft positional information is collected concurrent with

the imagery through Inertial Motion Units (IMUs) and Global Positioning System (GPS)

receivers in the aircraft. This information can greatly facilitate rectification of the

imagery over extensive open-water areas or in remote locations. The imagery can be

collected to produce whatever pixel size is needed to meet project requirements. Most

digital cameras have a limited number of spectral bands (3-5) that adequately represent

most benthic habitats without collecting numerous additional bands that contribute only

limited information to a mapping effort. Digital aerial photography is also smoothly

integrated into most soft-copy photogrammetric analysis environments. A prime

advantage of this type of imagery is the lack of chemical processing needed to produce

a working image. This can save time and allow reflights on short notice if conditions

warrant. A potential disadvantage of these systems is that some systems do not

employ metric cameras. This can slightly hinder the rectification process. 

The NOAA Coastal Services Center is currently exploring the utility of this technology

for operational benthic habitat mapping and expects to produce technical guidance on

the collection and analysis of this data stream. 

Side-Scan Sonar

This swath acoustic sensing technology has been operational for many years for

mapping and surveying deepwater environments. They are active sensors that pulse

the bottom at an oblique angle and record the returning acoustic echoes. Many units

record this information directly onto analog paper, although digital systems allow the

data to be analyzed at a later date. Different wavelengths are available depending on

the unit, and the wavelength determines the size of the feature (spatial resolution) that

will be imaged. 

Multi-Beam Sonar

Multi-beam sonars usually integrated with side-scan sonar to produce an image of the

bottom that also has bottom topography combined with the acoustic backscatter

response. Multi-beam systems usually incorporate Inertial Motion Unit (IMU) data to

assist with registering the bathymetric and backscatter data (rectification). These units

allow vessel position (heave, roll, pitch, and yaw) to be compensated for to reduce

distorting the final bathymetric bottom profile. Both side-scan and multi-beam sonar

units have most often been deployed in deeper water environments (well beyond the

photic zone). However, new shallow-water units are becoming available that can be

deployed from small boats. These systems have great promise as an additional

benthic mapping tool, not only for deep water areas, but also for shallow turbid

estuaries. Both side-scan and multi-beam sonars have demonstrated utility for
72

identifying certain sediments and consolidated bottoms. The Center is investigating this

technology for mapping other habitat areas, such as seagrass meadows and algal flats.

All of the above methods are forms of remote sensing applicable over extensive

geographic areas. There are also point sampling methods for identifying and

characterizing benthic habitats. These methods can be used to produce a map through

statistical interpolation methods and have the primary advantage of producing highly

detailed information on bottom type, condition, and often biological and chemical

processes that are occurring there.

Benthic Grab and Core Sampling

These methods have traditionally been used to develop information on bottom types. 

They rely on direct collection of a portion of the bottom and are deployed from both

small and large vessels. They have the advantage of allowing direct observation and

quantitative measurement of such characteristics as sediment type, organic content,

and in-faunal presence. They are limited by their inability to capture samples in hard

substrate areas, and they require an understanding of the spatial diversity of the bottom

for accurate interpolation over distances. This type of sampling is often made more

efficient and useful when used in conjunction with other spatial data such as that

derived from remote sensing.

Sediment Profiling Imagery

A powerful tool for characterizing the benthic environment is the sediment profiling

camera. These instruments penetrate the substrate and photograph the sediment

profile. They can be deployed from small boats but often require fixed davits for

effective deployment. This type of data provides a context for grab and core sampling

and also captures structural information (layering, worm tubes, etc.) that more invasive

grabbing and coring techniques might not preserve. Some of the advantages of this

technology are the permanent record provided by the photography, and the information

about the water-sediment interface. Some potential disadvantages are the size and

complexity of the units, and the narrow field of view. Both this technology and the

grab/core techniques are more powerful when applied in the context of other spatial

habitat data.
73

APPENDIX 3

FLIGHT PLANNING CHART FOR 153mm (6") LENS AND 23cm (9") FILM

Scale

Altitude

 (m)

Lateral

Coverage

(m)

Frames 

per Kilometer

(60% FOL)

 Frame 

Coverage 

(km2

)

Altitude 

(ft)

Lateral 

Coverage 

(ft)

Frames

per Mile

(60% FOL)

Frame 

Coverage 

(mi2

)

1:2,000 305 458 5.46 0.21 1,000 1500 8.80 0.08

1:3,000 457 686 3.64 0.47 1,500 2250 5.87 0.18

1:4,000 610 915 2.73 0.84 2,000 3000 4.40 0.32

1:5,000 762 1,143 2.19 1.31 2,500 3750 3.52 0.50

1:6,000 914 1,371 1.82 1.88 3,000 4500 2.93 0.73

1:7,000 1,067 1,601 1.56 2.56 3,500 5250 2.51 0.99

1:8,000 1,219 1,829 1.37 3.34 4,000 6000 2.20 1.29

1:9,000 1,372 2,058 1.21 4.24 4,500 6750 1.95 1.63

1:10,000 1,524 2,286 1.09 5.23 5,000 7500 1.76 2.02

1:11,000 1,676 2,514 0.99 6.32 5,500 8250 1.60 2.44

1:12,000 1,829 2,744 0.91 7.53 6,000 9000 1.47 2.91

1:13,000 1,981 2,972 0.84 8.83 6,500 9750 1.35 3.41

1:14,000 2,134 3,201 0.78 10.25 7,000 10500 1.26 3.95

1:15,000 2,286 3,429 0.73 11.76 7,500 11250 1.17 4.54

1:16,000 2,438 3,657 0.68 13.37 8,000 12000 1.10 5.17

1:17,000 2,591 3,887 0.64 15.10 8,500 12750 1.03 5.83

1:18,000 2,743 4,115 0.61 16.93 9,000 13500 0.98 6.54

1:19,000 2,896 4,344 0.58 18.87 9,500 14250 0.93 7.28

1:20,000 3,048 4,572 0.55 20.90 10,000 15000 0.88 8.07

1:21,000 3,200 4,800 0.52 23.04 10,500 15750 0.84 8.90

1:22,000 3,352 5,028 0.49 25.28 11,000 16500 0.80 9.77

1:23,000 3,505 5,258 0.48 27.64 11,500 17250 0.77 10.67

1:24,000 3,658 5,487 0.45 30.11 12,000 18000 0.74 11.62

1:25,000 3,810 5,715 0.44 32.66 12,500 18750 0.70 12.61

1:30,000 4,572 6,858 0.36 47.03 15,000 22500 0.59 18.16

1:40,000 6,096 9,144 0.27 83.61 20,000 30000 0.44 32.28

1:48,000 7,315 10,973 0.23 120.40 24,000 36000 0.37 46.49

1:50,000 7,620 11,430 0.22 130.64 25,000 37500 0.35 50.44

1:58,000 8,839 13,259 0.19 175.79 29,000 43500 0.30 67.88

1:60,000 9,144 13,716 0.18 188.13 30,000 45000 0.29 72.64

Common U.S. Government Scales:

1:20,000 USDA ACSC panchromatic 1:48,000 USDOC NOS conventional color

1:40,000 USGS NAPP panchromatic and CIR 1:58,000 USGS NHAP panchromatic and CIR
74

APPENDIX 4

SCANNED AERIAL PHOTO WORKSHEET

Pixel Ground Resolution (meters)

ppi m 1:10,000 1:12,000 1:20,000 1:24,000 1:40,000 1:48,000 1:58,000

100 254.00 2.54 3.05 5.08 6.10 10.16 12.19 14.73

200 127.00 1.27 1.52 2.54 3.05 5.08 6.10 7.37

300 84.67 0.85 1.02 1.69 2.03 3.39 4.06 4.91

400 63.50 0.64 0.76 1.27 1.52 2.54 3.05 3.68

500 50.80 0.51 0.61 1.02 1.22 2.03 2.44 2.95

600 42.34 0.42 0.51 0.85 1.02 1.69 2.03 2.46

700 36.29 0.36 0.44 0.73 0.87 1.45 1.74 2.10

800 31.75 0.32 0.38 0.64 0.76 1.27 1.52 1.84

900 28.23 0.28 0.34 0.56 0.68 1.13 1.35 1.64

1000 25.40 0.25 0.30 0.51 0.61 1.02 1.22 1.47

1200 21.17 0.21 0.25 0.42 0.51 0.85 1.02 1.23

1500 16.94 0.17 0.20 0.34 0.41 0.67 0.81 0.98

2000 12.70 0.13 0.15 0.25 0.30 0.51 0.61 0.74

3000 8.47 0.08 0.10 0.17 0.20 0.33 0.41 0.49

4000 6.35 0.06 0.08 0.13 0.15 0.25 0.30 0.37

Common Variables

ppi = Pixels (dots) per inch M = Meters

m = Microns I = Inches

S = Photo scale F = File size

PM = Pixel size in meters PF = Pixel size in feet

A = Array size of image in pixels In = Size of image in

inches

C = Size of image in centimeters B = Number of bands in a file

Conversions

PPI to Microns: Microns to PPI

m = (2.54/ppi)*10,000 PPI = (2.54/m)*10,000

Inches to Meters Meters to Inches

M = I x 0.00254 I = M x 39.37

Determining Pixel Ground Resolution

Using PPI Using Microns

PM = (S/ppi)/39.37 PM = (S x m)* 0.000001

PF = (S/ppi)/12 PF = (S x m)* 39.37

Determining File Size of Scanned Images*

* Assuming no header in file. Header information can add as much as 30% to a file’s size.

Using PPI Using Microns

A = (I x ppi)2 x B A = ((C x 0.01)/(m x 0.000001))2 x B
75

APPENDIX 5

GROUND CONTROL POINT IDENTIFICATION

Project Control Point ID 

Date Measured Measured By

State County Other Legal

Location

Map Name Map Type 

Map Number Map Scale 

Map Date Map Accuracy 

GPS

Time Instrument 

Real-Time Differential Post-Processed Differential 

PDOP Base Station 

HRMS File Name 

VRMS Satellite Visibility Mask 

Survey

Instrument Station Azimuth Station

To Station Distance

Control Data Reference Chief of Party

Description of Station Sketch of Station

Image ID #

Ground Control Point Attributes

X = Projection 

Y = Zone 

Z = Datum