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 EPA/600/R-07/062 

 August 2007

A Guide to Mapping Intertidal Eelgrass and Nonvegetated Habitats 

in Estuaries of the Pacific Northwest USA 

by 

Patrick J. Clinton, David R. Young, David T. Specht, and Henry Lee II 

Project Officer: Walter G. Nelson 

Western Ecology Division (WED)/Pacific Coastal Ecology Branch (PCEB) 

National Health and Environmental Effects Research Laboratory (NHEERL) 

Office of Research and Development (ORD) 

United States Environmental Protection Agency (US EPA) 

Newport, OR 97365 

Disclaimer: The information in this document has been funded wholly or in part by the US Environmental 

Protection Agency. It has been subjected to review by the National Health and Environmental Effects 

Research Laboratory and approved for publication. Approval does not signify that the contents reflect the 

views of the Agency, nor does mention of trade names or commercial products constitute endorsement or 

recommendation for use. 
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List of Acronyms

AML ArcInfo® Macro Language 

AWAR Area Weighted Average Resolution 

CAD Computer Aided Drawing 

CD-ROM Compact Disc Read-only Memory 

CIR Color Infrared 

CMT Corvallis MicroTechnology® 

DGPS Differentially-corrected Global Positioning System 

DN Digital Number 

DPI Dots Per Inch 

DTM Digital Terrain Model 

DVD Digital Versatile Disc 

EPA Environmental Protection Agency 

GCP Ground Control Point 

GIS Geographic Information System 

GPS Global Positioning System 

INS Inertial Navigation System 

IR Infrared 

LCGC Lincoln County Geodetic Control 

LL Lower Left 

MLLW Mean Lower Low Water 

NAD North American Datum 

NIR Near-infrared 

NOAA National Oceanic and Atmospheric Administration 

NVDI Normalized Vegetation Difference Index 

PCEB Pacific Coastal Ecology Branch 

PNW Pacific Northwest 

RGB Red, Green, Blue 

SAVI Soil Adjusted Vegetation Index 

SAV Submerged Aquatic Vegetation 

SE Standard Error of the Mean 

SOW Scope of Work 

TC True Color 

TIFF Tagged Image File Format 

UR Upper Right 

UTM Universal Transverse Mercator

UV Ultraviolet 

WED Western Ecology Division
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Table of Contents

Title Page ........................................................................................................................................ i 

Disclaimer ....................................................................................................................................... i 

Acronyms........................................................................................................................................ ii 

Table of Contents .......................................................................................................................... iii 

List of Figures ............................................................................................................ vi

List of Tables ............................................................................................................................... vii 

Abstract....................................................................................................................................... viii 

1.0 Introduction..........................................................................................................................1 

1.1 Objective..................................................................................................................1 

1.2 Background..............................................................................................................1 

1.2.1 Pacific Northwest Estuaries .........................................................................1 

1.2.2 Documenting SAV Distribution .................................................................1 

2.0 Approach..............................................................................................................................2 

2.1 Aerial Photography Acquisition Considerations .....................................................2 

2.1.1 Introduction..................................................................................................2 

2.1.2 Film Type.....................................................................................................2 

2.1.3 Film Format / Camera..................................................................................4 

2.1.4 Lens Size......................................................................................................4 

2.1.5 Filters and Exposure ....................................................................................4 

2.2 Mission Planning .....................................................................................................5 

2.2.1 Film Scale ....................................................................................................5 

2.2.2 Number of Photos ........................................................................................6 

2.2.3 Photo Angle .................................................................................................6 

2.2.4 Photo Centers...............................................................................................6 

2.2.5 Timing..........................................................................................................6 

2.3 Ancillary In situ Survey and Global Positioning Systems.......................................7 

2.4 PCEB_FlitePlannr.xls ..............................................................................................8 

2.5 Contracting for Aerial Surveys .............................................................................12 

2.6 Aerial Photography Analysis Considerations ........................................................12 

2.6.1 Photointerpretation.....................................................................................12 

2.6.2 Digitizing Aerial Photography...................................................................12 
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2.6.3 Digital Image Orthorectification................................................................13 

2.6.4 Digital Image Classification ......................................................................14 

2.7 Classification Accuracy .........................................................................................22 

2.7.1 Theory of Classification Accuracy ............................................................22 

2.7.2 Accuracy Assessment ................................................................................23 

3.0 Summary............................................................................................................................25 

4.0 Acknowledgements............................................................................................................26 

5.0 Literature Cited ..................................................................................................................26 

Appendix 1: Useful Links .............................................................................................................28 

Appendix II: Specifications for Aerial Photography used by WED/PCEB for Aerial 

Photomap/Classification Projects Between 1997 and 2006...............................................29 

Appendix III: Spatial Accuracy of Orthophotography ..................................................................30 

Appendix IV: Procedures for Conducting Ground Surveys of Intertidal Vegetation Percent 

 Cover in Support of Aerial Photography Habitat Mapping....................................31 

1.0 Introduction............................................................................................................31 

1.1 Planning .................................................................................................................31

1.2 Positioning .............................................................................................................32 

1.3 Ground Station Surveying......................................................................................32 

1.4 Moving a Station into a Target Habitat..................................................................34 

1.5 Margin Mapping ....................................................................................................35 

1.6 Data Archiving.......................................................................................................35 

1.7 Application of Ground Survey Data ......................................................................35 

1.8 Literature Cited ......................................................................................................36 

Appendix V: Example Scope of Work - Aerial Photography........................................................37 

1.1 Location of Work...................................................................................................37 

1.2 Definitions..............................................................................................................37

1.3 Aerial Photography Requirements.........................................................................38 

1.4 Flight Plan Data .....................................................................................................40 

2.1 Business Arrangements..........................................................................................41 

3.1 Minimum Qualification Requirements ..................................................................41 

Appendix VI: Example Scope of Work - Digital Orthorectification of Aerial Photographs.........45 

1.1 Definitions..............................................................................................................45

1.2 Photographic Hard Copy........................................................................................46 
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2.1 Photographic Diapositive Digitization...................................................................47 

2.2 Image Rectification ...............................................................................................47 

3.1 Digital File Naming Convention............................................................................48 

3.2 Documentation of Image Rectification..................................................................49 

3.3 Quality Assessment - Image Rectification.............................................................49 

4.1 Business Arrangements..........................................................................................49 

5.1 Technical Evaluation Criteria ................................................................................50 
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LIST OF FIGURES 

Figure 1 Typical spectral reflectance curves for vegetation and water..................................3 

Figure 2 An example of a flight map. Flight center coordinates, center points and photo 

overlap areas can be generated through the use of PCEB_FlitePlannr.xls............11 

Figure 3 Spectral response curve of exposed seagrass (Z. marina) and macroalgae (Ulva spp.) 

measured in situ on intertidal flats of Yaquina Bay estuary, Oregon ....................15 

Figure 4 Aerial photomosaic detail of Yaquina Bay estuary ...............................................16 

Figure 5 Detail of the SAVI and shoreline vector masked image of Yaquina Bay 

 estuary....................................................................................................................18 

Figure 6 Detail of an unsupervised seven-class isocluster classification of a SAVI masked 

image of Yaquina Bay estuary...............................................................................19 

Figure 7 Hybrid classification work flowchart.....................................................................21 

Figure 8 Seagrass classification grid and validation point cover .........................................24 

Attachment I: Required flight lines and precise locations of photo centers for Year 2006 color 

infrared aerial photography of Yaquina Bay estuary, Oregon...............................43 
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LIST OF TABLES 

Table 1 Dimensions and area captured in aerial photographs using a large format 

camera at differing scales ......................................................................................6 

Table 2a Sample PCEB_FlitePlannr.xls Input Parameters page ..........................................9 

Table 2b Sample PCEB_FlitePlannr.xls Output Parameters page......................................10 

Table 3 The ground resolution of a digitized aerial photo pixel is expressed in meters 

at varying scanning resolutions and photo scales ...............................................13 

Table 4 Example error matrix for four hypothetical land cover categories (A – D).........23 

Table III-1 Worksheet showing spatial accuracy of orthophotography based on the 

published location of geodetic survey points between U.S. 101 (Yaquina Bay 

Bridge) in the City of Newport and the City of Toledo, Oregon, compared to 

locations obtained from orthorectified photographs for the aerial photosurvey 

of Yaquina Bay estuary on July 23, 1997............................................................30 

Table IV-1 Example field data sheet for aerial photomapping ground surveys ....................33 

Attachment II: Time/tidal elevation (ft) windows for allowable photography of Yaquina Bay 

estuary, Oregon, April 29 – August 12, 2006 (initial page only) ........................44 
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ABSTRACT 

Seagrasses are a critical habitat component of Pacific Northwest (PNW) estuaries. Scientists and 

managers need cost-effective methods of determining seagrass distributions in different classes of 

PNW estuaries. Aerial photomapping is one such technique. A protocol for conducting aerial 

photography surveys of nearshore habitats using true color film, based on experience from the 

Atlantic and Gulf of Mexico coasts, already has been developed. However, there are substantial 

differences between estuaries in those regions and in the Pacific Northwest. This document 

presents an alternate approach to obtaining aerial photomaps of seagrass and macroalgae 

distributions to deal with the significant intertidal habitat areas exposed by the large intertidal range 

typical of PNW estuaries. This condition provides an opportunity to conduct aerial photography 

surveys using false color, near-infrared (color infrared) film during exposed conditions, when the 

high absorption of near-infrared radiation by water is not a limiting factor. Classification of the 

resulting images of intertidal vegetation (submerged aquatic vegetation) has been found to be 

superior to that obtained using true color film. Issues that need to be considered in planning an 

aerial photography survey are discussed, and a mission planning aid is provided. Example scopes 

of work for acquiring commercial aerial photography, and subsequent geocoding and 

orthorectification of the photographs to produce digital photomaps, also are provided. In addition, 

approaches used to obtain corroborative information on submerged aquatic vegetation intertidal 

distributions from ground surveys within one PNW estuary are described.
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A Guide to Mapping Intertidal Eelgrass and Nonvegetated Habitats 

in Estuaries of the Pacific Northwest USA 

1.0 INTRODUCTION

1.1 OBJECTIVES 

The objectives of this document are to provide guidance for mapping, via aerial photography, 

intertidal distributions of the eelgrass Zostera marina L. in estuaries with substantial tidal ranges, 

such as those found in the Pacific Northwest region (PNW) of the USA, and for assessing the 

accuracy of such photomap classifications. 

1.2 BACKGROUND 

1.2.1 Pacific Northwest Estuaries

The mean tidal range of PNW estuaries is often between 2 and 3 meters, so that a substantial 

proportion of the area of a given estuary is exposed when the tidal elevation is below 0.0 feet 

relative to Mean Lower Low Water (MLLW; in the USA, tidal height traditionally is measured in 

feet). These systems are characterized by extensive tideflats that support a variety of habitats, 

including perennial seagrass meadows and extensive beds of seasonal benthic macroalgae. Large 

tidal ranges and extensive intertidal flats distinguish estuaries in the PNW from those in 

Chesapeake Bay and other areas of the Atlantic and Gulf of Mexico coasts that have been the 

subject of seagrass studies for several decades (Orth 1977; Orth and Moore 1983; Valiela et al. 

1992; Short and Burdick 1996; Hauxwell et al. 2003). 

1.2.2 Documenting SAV Distribution

Submerged aquatic vegetation (SAV), such as the seagrasses and benthic macroalgae, constitutes a 

most important estuarine and shallow coastal habitat. This has stimulated efforts to develop costeffective methods of documenting its distribution. One successful approach is the use of traditional 

ground surveys in combination with the production of intertidal habitat maps from aerial 

photographs.
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2.0 APPROACH 

The approach used by the US Environmental Protection Agency (US EPA) Western Ecology 

Division/Pacific Coastal Ecology Branch (WED/PCEB) to map intertidal SAV in the estuaries of 

the PNW has been through the use of false color, near-infrared (color infrared, CIR) aerial 

photography augmented with in situ surveys using global positioning systems (GPS). Other 

mapping methodologies are appropriate depending on the physical environment to be mapped. For 

example, the National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center 

has published an excellent guide for benthic mapping that advocates the use of true color (TC) 

aerial photography (Finkbeiner et al. 2001). The approach described here responds to physical 

features of PNW estuaries that differ from those of the Atlantic or Gulf of Mexico coasts. 

2.1 AERIAL PHOTOGRAPHY ACQUISITION CONSIDERATIONS

2.1.1 Introduction

In planning an aerial photography survey of SAV, decisions on a number of interrelated factors 

regarding equipment and mission parameters need to be made. These decisions will directly affect 

the resolution of the data and cost of the survey. A number of excellent publications are available 

that provide much greater detail on the subject of aerial photographic mapping, including Avery 

and Berlin (1985), Warner et al. (1996), and Finkbeiner et al. (2001). In addition, Appendix I 

provides useful links to internet websites dealing with remote sensing issues. Specifications for the 

aerial photomapping projects conducted by WED/PCEB between 1997 and 2006 are listed in 

Appendix II. 

2.1.2 Film Type

Film type varies according to its overall range of spectral sensitivity and the number and spectral 

sensitivity range of emulsion layers. Panchromatic films (black and white) have a single emulsion 

layer with varying ranges of spectral sensitivity. Color films have three emulsion layers which also 

have varying ranges of spectral sensitivity. Normal black and white panchromatic film is sensitive 

to the light spectrum from the near-ultraviolet to the red wavelengths (~ 0.25 μm - 0.7 μm). Infrared 

(IR) panchromatic film has added sensitivity into the near-infrared (NIR) wavelengths (~ 0.25 μm - 

0.9 μm). Natural or TC film is sensitive to visible light in blue band (0.4 μm - 0.5 μm), green band 

(0.5 μm - 0.6 μm) and red band (0.6 μm - 0.7 μm) wavelengths. Color infrared film (when filtered 

to block blue band wavelengths) is sensitive to visible light in the green and red band wavelengths, 

as well as the non-visible NIR photographic band wavelengths (0.7 μm - 0.9 μm) (Avery and Berlin 

1985). The added discrimination between objects with different reflectance characteristics provided 

by the use of color films precludes the use of panchromatic films in any serious SAV mapping 

exercise except in the case where there is no alternative, as in mapping from historic photos. 
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The considerable differences in the reflectance characteristics of water and vegetation between the 

visible and IR bands will strongly influence the choice of film type for use in mapping SAV. 

Vegetation reflectance is maximized in the IR band. However, water is a strong absorber of IR 

radiance, with the potential to block SAV reflectance in the IR band, and thus subtidal features may 

not be detectable (Figure 1). In contrast, while visible light in the blue band can reflect from 

objects down to 25 m in clear water, the greatest average percent reflectance of vegetation in the 

visible bands (within the green photographic band) is approximately one-third the percent average 

reflectance of vegetation in the IR band (Avery and Berlin 1985). This suggests that immersed 

SAV may be more readily imaged by TC film while exposed vegetation may be more readily 

imaged by CIR film. 

In regions with little tidal amplitude, low turbidity and deep distributions of SAV, such as found in 

many southeastern estuaries, the use of TC rather than CIR film may be more appropriate for SAV 

mapping than CIR film (Dobson et al. 1995). However, because of the large tidal amplitudes in the 

PNW and the subsequent exposure of SAV during low tide events, CIR film can provide more 

benefits than TC film (Young et al. 1999). In a qualitative comparison of TC and CIR aerial 

photography nearly simultaneously acquired, taken during a low tide event within the Yaquina Bay 

estuary, Oregon, during the summer of 1997, PCEB researchers found little difference in the 

apparent subtidal distribution of inundated SAV while the detection of the intertidal distribution 

was more readily delineated using CIR. Turbidity may have limited the advantage of TC film in 

detecting SAV through the water column and thus we do not suggest that TC film is inappropriate 

for detecting subtidal SAV. Because significant levels of turbidity and large tidal amplitudes are 

common estuarine conditions in the PNW, the use of CIR film at extreme low tides is 

recommended for SAV photomapping in this region.

 

Figure 1. Typical spectral reflectance curves for vegetation and water (Canada Centre 

for Remote Sensing - Natural Resources Canada 2004). 
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2.1.3 Film Format / Camera

Another consideration is the size of the film and the associated camera, which can be divided into 

large format cameras (23 cm), medium format (12.5 cm to 6 cm), and small format camera (35 

mm). Large format aerial cameras offer a number of advantages but are bulky and expensive to 

own and operate, and therefore are usually found in the hands of aerial survey firms or government 

agencies. Modern large format cameras are often interfaced with GPS, are computer controlled 

and have forward motion compensating stabilized mounts (Warner et al. 1996). Modern large 

format cameras are photogrammetric or metric cameras for which the geometry of the lens and 

film surface has been precisely calibrated. Metric cameras enable precise measurements of object 

scenes through the accurate reconstruction of their optical geometry (Canada Centre for Remote 

Sensing - Natural Resources Canada 2004). The wide field of view of large format aerial 

photography has made it the conventional choice for aerial photomapping. Medium and small 

format camera systems offer an alternative to conventional large format systems. The cameras are 

much less expensive, lighter and metric versions are available. A larger variety of films are 

available, film processing is simple and inexpensive, and a wide variety of ultralight to light 

aircraft can be used as aerial platforms (Warner et al. 1996). While the smaller scene capture of 

these films may limit their utility in mapping large areas, they may be quite appropriate for site 

monitoring and other large scale (small area) applications. 

2.1.4 Lens Size

The choice of lens size in aerial photomapping affects the scale of the photography, the altitude of 

the aerial platform and the amount of radial distortion present in the photography. The scale of 

aerial photography is a function of the focal length, or lens size, of the camera system and the 

height of the focal plane of the camera. If the scale of the photography is pre-determined, the 

choice of camera lens will affect the altitude of the aerial platform, and vice versa. Shorter focal 

length lenses produce greater radial distortion in the imaged scene. This may be desirable if the 

purpose of the aerial photography includes the production of a Digital Terrain Model (DTM) from 

overlapping stereo photo pairs. Standard focal lengths for large format camera lenses are nominally 

6 and 12 inches. Given the same desired photo scale, 6 inch focal length lenses have a wider angle 

of view which increases the possibility of introducing glint into the imagery, while 12 inch focal 

length lenses would be flown at twice the altitude of a 6 inch lens, introducing greater atmospheric 

interference into the imagery. 

2.1.5 Filters and Exposure

Lens filters are designed to alter the properties of light entering a camera in order to enhance image 

quality. Anti-vignetting filters that help to compensate for darkening edges of aerial photos should 

be standard in any aerial photo survey. Blue haze and ultraviolet (UV) filters are desirable in TC 

photography. Special red or yellow filters to block the blue and UV spectrum are mandatory in CIR 

photography. Typical exposure settings should be increased by the filter factor of the filter used 

(Eastman Kodak Company 2000). CIR exposure settings for photographing SAV on exposed 
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tideflats and in very shallow water should be increased over typical exposure settings for 

photographing terrestrial vegetation (Mumford and Berry 2006). We recommend consultation with 

the areal image acquisition provider on exposure settings appropriate to the time of day, season and 

target vegetation. 

2.2 MISSION PLANNING

In addition to the hardware considerations discussed above, a number of operational decisions also 

have to be made in planning of an aerial photographic survey. The primary objectives of the survey 

play the critical role in mission planning decisions that ultimately determine the nature of survey 

product. 

2.2.1 Film Scale

Photo scale is the ratio of distance on a photo to the actual distance in the scene. Photo scale equals 

the focal length of the camera system divided by flying height of the aerial platform. Choice of 

scale will affect the level of detail visible in a scene, the areal extent of the scene and the number of 

photos in the survey. Photo scales up to 1:20,000 are considered large scale (small area), from 

1:20,000 to 1:100,000 is considered medium scale, and small scale (large area) is anything over 

1:100,000 (Canada Centre for Remote Sensing - Natural Resources Canada 2004). (Note the use of 

‘large’ versus ‘small’ scale in the context of mapping, with large scale referring to a small area with 

higher resolution and small scale referring to a large area with lower resolution.) Applications 

appropriate to these magnitudes of scale might be agricultural or municipal aerial surveys at a large 

scale, county-wide mapping at a medium scale, and state-wide surveys at the small scale. Table 1 

illustrates the aerial extent of large format (23 cm) aerial photos acquired at differing scales. The 

choice of photo scale is crucial to any SAV photomapping project as it will directly affect other 

factors in the project (e.g., the resources required to digitize and orthorectify the imagery). The 

choice of scale should be a balance between the size of the area to be mapped and the level of detail 

required. The choice of photo scale also will affect the level of detail that can be achieved in 

digitally scanning aerial photos and therefore determines the smallest mapping unit that can be 

used. Although a larger mapping unit may be employed, an array of 3 x 3 pixels is required to 

distinguish an isolated feature represented by a single pixel. PCEB recommends a photo scale of 

1:20,000 for estuary-wide mapping of SAV in the PNW. (For further discussion, see Section 2.6). 
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SCALE LENGTH / WIDTH (km) AREA (km5) 

1:10,000 2.3 5.29 

1:20,000 4.6 21.16 

1:40,000 9.2 84.64 

Table 1. Dimensions and area captured in aerial photographs using a large format camera at 

differing scales. 

2.2.2 Number of Photos

The number of photos in a given aerial photo survey is determined by the scale of the photography, 

the degree of photo overlap and the size of the study area. Photo surveys that include the purpose 

of stereo-compilation of a DTM typically are designed with a 60% photo overlap within each 

flightline and 30% photo sidelap with adjacent flightlines in order to enable stereo viewing of the 

entire study area. A minimum of 40% overlap and sidelap is recommended to ensure complete 

coverage if stereo-pairs (>50% overlapping photos) are not required. (For further discussion, see 

Section 2.4). 

2.2.3 Photo Angle

Aerial photography can be classed as vertical or oblique, depending on the angle at which a scene is 

captured. PCEB’s primary focus is on vertical aerial photography where the scene is captured from 

directly above. 

2.2.4 Photo Centers

The photo center or nadir of an aerial photo is that point on the ground vertically below the camera 

(Warner et al. 1996). Any aerial photographic mission plan must provide the geographic location 

of all the photo centers in order for photography to be acquired at those locations, whether plotted 

on a paper map or provided as a digital list of coordinates to be loaded into a GPS. The easting and 

northing coordinates of a particular photo mission can be calculated and/or plotted either in-house 

or by a contracting aerial survey entity (see Section 2.4). 

2.2.5 Timing

The timing of an aerial survey depends both upon the specific objectives of the survey as well as 

various practical considerations. A major consideration in the PNW is whether the objective is to 

capture only seagrasses, or both seagrasses and macroalgae, which will dictate the season in which 

the photography should be acquired. Another consideration is whether the objective is to evaluate 

only intertidal SAV or whether the objective is to evaluate shallow subtidal SAV as well. The 
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practical considerations include the sun angle (enough light, too much shadow?), the weather (is it 

likely to be cloudy, rainy?), the tide (when do the low tides occur?), the availability of the aerial 

platform, etc. 

Finding appropriate temporal windows at low tide with sufficient solar illumination for aerial 

photography in the often uncooperative maritime climate of the PNW can be challenging. The use 

of predictive tide height and solar angle software models can greatly aid in scheduling potential 

flight windows for CIR aerial photography of estuarine SAV. An example of an on-line tide 

prediction utility, >WWW Tide and Current Predictor=, can be found at: 

http://tbone.biol.sc.edu/tide/sitesel.html. 

PCEB determined that the general rule-of-thumb for summer large format photography is that the 

tide must be below MLLW after 9:00 a.m., that the weather should be free of cloud and fog or with 

a uniform high altitude haze, and that surface winds should be below 12 knots. 

2.3 ANCILLARY IN SITU SURVEY AND GLOBAL POSITIONING 

SYSTEMS 

While aerial photography provides a cost-effective alternative to extensive ground surveys, 

ancillary in situ field surveys are usually an important component of an aerial survey. There are 

three primary reasons for conducting in situ field studies in conjunction with aerial photo surveys: 

1) geographic control, 2) classification calibration, and 3) classification validation. 

Ground control points (GCP) are points that fall within a photo scene whose geographic coordinates 

are known. GCP are used to register digitized aerial photos in real-world geographic coordinates. 

The establishment of geographic >ground control= can be accomplished by the placement and 

precise geopositioning of aerial target ‘premarks’ prior to the photo mission or by establishing the 

precise geopositions of permanently fixed objects visible in the photo scene. Modern soft-copy 

photogrammetric methods combining the use of GPS and Inertial Navigation Systems (INS) have 

greatly reduced the need for ground control. However, while not always practical, an idealized ruleof-thumb is to establish two GCP at the ends of each flightline as well as four GCP within each 

flightline. 

Such established geodetic control points can be used to test the spatial accuracy of 

orthophotography provided the description and physical context of the point location is sufficient to 

visually locate the point in the imagery, or the point has been premarked for visibility prior to image 

capture. A geographic information system (GIS) point layer is generated from the published 

coordinates of the geodetic points and overlaid on the orthophotography. The minimum and 

maximum probable distances between the overlaid point and the apparent location based on the 

published description of the point location are listed. Accuracy is then expressed as the mean 

distance between apparent and published locations with an uncertainty based on the visibility and 

context of the apparent location. An accuracy summary based on the aerial photography of 

Yaquina Bay estuary taken on July 23, 1997 is presented in Appendix III. The geodetic control 
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points listed in the first column range in position from U.S. Highway 101 (Yaquina Bay Bridge) in 

the City of Newport to the City of Toledo, beyond the eastern border of most of the photo surveys 

of Yaquina Bay estuary made between 1998 and 2006. For the 11 photo visible control stations 

(without premarks) listed in Appendix III, the median difference was 0.50 m (range: 0.10 m – 

1.66 m), and the average difference (+ 1 SE) was 0.67 m + 0.14 m. 

Precisely geopositioned landscape measurements are used either as calibration sites or as validation 

sites for image classification of ground cover. Calibration data are used to train supervised 

classification of imagery or to assign classes to unsupervised image classification (see Section 

2.6.4). Validation or ‘ground truth’ data are used to assess the accuracy of classified imagery. 

These data should not be used interchangeably, that is, a specific photograph or location on a 

photograph should only be used in calibration (training) or in validation. Ideally, these 

classification and validation data should be collected concurrent with the photography. A delay in 

conducting the field survey could allow growth of seagrass extending the perimeter of the beds, 

which could confound the validation if a previously bare area was later covered with seagrass. A 

potentially greater source of error in the PNW is the seasonal bloom of macroalgae in the summer, 

which can cover major sections of certain intertidal areas, often commingling with seagrass. These 

sources of error need to be evaluated if the field survey is not concurrent with the aerial 

photographs. Again, ideally, at least one calibration site for each classification class should be 

established for each photo scene. 

A robust image classification validation scheme would include the collection of 30 to 50 randomly 

located validation sites for each classification class (Congalton 1991; Congalton and Green 1999). 

Note that with three classes (e.g., eelgrass, green macroalgae, and bare substrate), this results in 90 

to 150 sites to evaluate per estuary. In Yaquina Bay estuary PCEB found that,with the use of a 

differentially-corrected global positioning system (DGPS) in an intensive vegetation cover ground 

survey effort, more than 200 previously staked locations could be surveyed within one week of 

photo acquisition using 10 two-person teams. The DGPS used (Corvallis MicroTechnology®, CMT 

PC5-L) to position the numbered stake locations is rated at an average spatial accuracy of + 0.6 m. 

Data logging functions of GPS units also facilitate the importation of survey data directly into a 

GIS, and thus decrease both the time and potential errors of transcribing data from field notes to an 

electronic media. A detailed procedure is presented in Appendix IV for planning, executing, and 

evaluating results from a typical ground survey operation. 

2.4 PCEB_FLITEPLANNR.XLS 

Given the number of variable inputs, planning an aerial survey can be time consuming. To assist in 

this effort, we have developed an interactive spreadsheet that allows the user to explore ‘what if’ 

options in aerial photographic mission planning. For example, the user can adjust the desired scale 

of photography and observe changes in the number of photographs the mission will require, the size 

of the photographic >footprint= as well as a number of other variables (Tables 2a, 2b; Figure 2). The 

interactive spreadsheet also generates ArcInfo® macro language (AML) text for generating photo 

center points and photo footprint polygons using ArcInfo® geographic information systems. 
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Table 2a. Sample PCEB_FlitePlannr.xls Input Parameters page. 
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Table 2b. Sample PCEB_FlitePlannr.xls Output Parameters page. 
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Figure 2. An example of a flight map. Flight center coordinates, center points and photo overlap 

areas can be generated through the use of PCEB_FlitePlannr.xls. 
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2.5 CONTRACTING FOR AERIAL SURVEYS 

In nearly all cases, aerial surveys will be conducted either through an agreement with a federal (e.g., 

NOAA) or state agency or through a contract with a private firm. In either case, it is critical to 

clearly identify the objectives of the study and the requirements to achieve those objectives. 

Appendix V is an example of a scope of work (SOW) that the PCEB has used to contract for aerial 

surveys of Yaquina Bay estuary. This agreement can be modified to reflect specific project needs 

and/or contractual requirements.

2.6 AERIAL PHOTOGRAPHY ANALYSIS CONSIDERATIONS

2.6.1 Photointerpretation 

The traditional method of delineating features from aerial photography involves outlining features 

on transparent Mylar® overlays directly from the photograph. Such manual photointerpretation 

relies on the photointerpreter’s knowledge of the nature of the features in a photo scene, and their 

ability to differentiate features based on elements of photographs such as tone, color, contrast, 

texture, and context (Finkbeiner et al. 2001). If points with known geographic coordinates are also 

marked on the overlay, the delineations can be digitized and spatially referenced into a GIS using a 

digitizing tablet. Another method that uses the same knowledge and skill of the photointerpreter is 

known as >heads-up= digitizing. In this method, features are delineated using a computer mouse onscreen, with digitally scanned aerial photos as the computer screen background, using computer 

aided drawing (CAD) tools. If the digital aerial photo used in this process has been georeferenced 

to real-world coordinates and/or orthorectified, and the delineation is done within a GIS program, 

the delineation automatically will be spatially referenced. 

2.6.2 Digitizing Aerial Photography

Aerial photos can be scanned at varying resolutions, usually expressed in dots per inch (dpi) or in 

microns. Upon subsequent georectification of a photo, photo scale and scanning resolution will 

determine its ground resolution, the size of the area in a scene represented by a single pixel (Table

3). Aerial photography is typically digitized into the three additive color photographic bands (red, 

green, blue - RGB) using 256 intensity values coded on 8 bits (Kölbl et al. 1996). The color 

scanning process assigns digital numbers (DN) to each pixel in an image, ranging from 0 to 255, 

that correspond to the average intensity values of the RGB colors within that pixel. Imagery may 

be scanned directly from exposed film, or from diapositives or opaque prints developed from the 

film. We recommend that 1:20,000 scale aerial photography of PNW estuaries be scanned at 12 

microns, to ensure a nominal 0.25 m ground pixel in the final orthophotography. Although it is 

quite possible to scan aerial photo diapositives with an in-house large format transparency scanner, 

we recommend that aerial photo scanning be performed with a commercial grade photogrammetric 

scanner directly from the exposed film to ensure the highest radiometric fidelity to the scene. The 

practical limit for scanning film is about 8 microns due to film granularity. 
_______________________________________________________________________________ 

 Page 13 of 50 

 Pixel Ground Resolution (m) vs. Scanning Resolution 

 

 Photo Scale 5000 10000 12000 24000 40000 

Scanning Resolution 

dpi microns 

300 85 0.42 0.85 1.02 2.03 3.39 

600 42 0.21 0.42 0.51 1.02 1.69 

800 32 0.16 0.32 0.38 0.76 1.27 

1000 25 0.13 0.25 0.30 0.61 1.02 

1100 23 0.12 0.23 0.28 0.55 0.92 

1200 21 0.11 0.21 0.25 0.51 0.85 

1300 20 0.10 0.20 0.23 0.47 0.78 

1400 18 0.09 0.18 0.22 0.44 0.73 

1500 17 0.08 0.17 0.20 0.41 0.68 

2000 13 0.06 0.13 0.15 0.30 0.51 

2500 10 0.05 0.10 0.12 0.24 0.41 

Table 3. The ground resolution of a digitized aerial photo pixel is expressed in meters at varying 

scanning resolutions and photo scales. 

2.6.3 Digital Image Orthorectification 

A digitally orthorectified aerial photo is an aerial photo that has been digitally scanned and 

georeferenced to real-world coordinates in a process that compensates for the spatial distortion in 

the original photo caused by terrain variation and camera geometry. Distortion caused by terrain is 

corrected with the use of a DTM, and distortion caused by camera interior geometry is corrected 

with the use of parameters from a camera calibration report. Appendix VI is an example scope of 

work that the PCEB has used to contract for the digital orthorectification of aerial photographs of 

Yaquina Bay estuary. Desktop orthorectification software that corrects for camera and terrain 

distortion and uses pre-existing orthophotography for GCP selection can be a very cost- effective 

means of producing digital orthophotography in-house. Once individual photos are orthorectified, 

they are mosaiced together to form a complete scene. 

The photographs, as provided directly from the aerial surveys, can be used to qualitatively evaluate 

various landscape features. However, for accurate estimates of the locations of seagrass beds or 

quantitative estimates of their area, we recommend working with digitally scanned, orthorectified 

aerial photographs. 
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 Page 14 of 50 

2.6.4 Digital Image Classification

Geographic image processing software applications use a wide variety of algorithms to process DN 

for the purposes of image classification. Image processing algorithms can have Boolean, algebraic, 

spatial, and/or statistical functions. Image processing algorithms can also be unsupervised or 

supervised image classifiers. Unsupervised classification algorithmic groups image pixels into like 

classes to which a photointerpreter can later assign landscape features. In supervised classification, 

a photointerpreter identifies groups of pixels that are representative of features in a scene for use as 

input to an algorithm for interpolating the identified classes across the remainder of the image. 

In digitally scanned, false color near-infrared photography, red pixel values are analogous to the 

reflective intensity of light in the NIR band of the spectrum; green DN are analogous to the 

reflective intensity of light in the red band; and blue DN are analogous to the reflective intensity of 

light in the green band. A common algorithm developed for use with electronically sensed spectral 

data, the normalized vegetation difference index (NVDI), exploits the wide difference in spectral 

response of vegetation between the red and NIR bands (Ray 1994) (Figure 3). The NVDI is a band 

ratio algorithm that can be adapted for use in classifying vegetation (including exposed SAV) from 

digital CIR aerial orthophotography. 

NVDI = (NIR - red) / (NIR + red) 
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 Page 15 of 50 

Figure 3. Spectral response curve of exposed seagrass (Z. marina) and macroalgae (Ulva spp.) 

measured in situ on intertidal flats of Yaquina Bay estuary, Oregon.

We have developed a method to digitally map the distribution of tidally exposed seagrass Zostera 

marina which combines techniques of digital image classification and traditional photo 

interpretation. This hybrid method enables a photo interpreter to digitally edit the results of a digital 

image classification. Misclassification of pixels can result from photometric variation due to a 

variety of causes including: intraphoto variation (vignetting), interphoto variation (mosaicing), sun 

angle, vegetation congruency (mixed beds), degree of exposure (bathymetry), and/or obfuscation 

(siltation or epiphytic cover). While a ‘programmatic’ solution to misclassification from such a 

variety of sources would be difficult at best, visual evaluation of elements of aerial photos such as 

pattern, texture, tone, contrast, and context can overrule error caused by simple variation in color. 

The first step in the hybrid method is to digitize the upper boundary of the lower intertidal portion 

of the study area on-screen, using the aerial photomosaic as a background image (Figure 4). The 

resulting polygon is used to mask out terrestrial and emergent marsh areas from the image. In order 

to map the intertidal distribution of seagrass, a second mask is created using a band ratio threshold 

algorithm to mask out unvegetated and inundated portions of the image. 
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 Page 16 of 50 

Figure 4. Aerial photomosaic detail of Yaquina Bay estuary. 
_______________________________________________________________________________ 

 Page 17 of 50 

The algorithm is based on the NVDI derived soil adjusted vegetation index (SAVI) (Huete 1988): 

SAVI = ((NIR - red) / (NIR + red + L)) x (1 + L) 

where NIR is the near-infrared band of the image, red is the red band and L is an empirically 

derived index of vegetation cover ranging from 0 for sparse cover to 1 for high percent cover. (Ray 

1994). 

The following conditional formula is applied to each band of each image in the mosaic: 

if (((i1 - i2)/(i1 + i2 + (0.5)) x (1 + 0.5)) + 1) / 2 > X and inregion (r1) then i3 else null. 

Here SAVI is set for moderate vegetation cover and is adjusted so that it will result in a value 

between 0 and 1. The variables i1 and i2 are the NIR and red bands, respectively, i3 represents the 

band to which the formula is applied and r1 is the lower intertidal polygon. The variable X is an 

interactively set variable that acts as a threshold between nominally vegetated and nonvegetated 

pixel classes. This is nominally set at 0.5 but can be adjusted by the photointerpreter. The resulting 

SAVI adjusted image (Figure 5) would ideally image only SAV but likely contains false-positive 

pixels. In order to eliminate false-positives and/or differentiate between SAV species or genera, 

further processing followed by manual editing is indicated. 
_______________________________________________________________________________ 

 Page 18 of 50 

Figure 5. Detail of the SAVI and shoreline vector masked image of Yaquina Bay estuary. 

The SAVI masked image is then subjected to an unsupervised isocluster classification set to a 

minimum of 6 to maximum of 12 classes. The resulting image will contain single values for 

statistically distinct clusters of pixel values (Figure 6). 
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 Page 19 of 50 

Figure 6. Detail of an unsupervised seven-class isocluster classification of a SAVI masked image of 

Yaquina Bay estuary. 

The image classification steps above were developed using ERMapper® v.6.1 geographical image 

processing software, but may be adapted to other such software. The following steps were 

developed in ESRI ArcMap® desktop and ArcInfo® workstation GIS software.
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 Page 20 of 50 

The isocluster image was converted to an ArcInfo® grid with cell values representing the 

isoclusters. A new binary (0 or 1) grid was created for each value using conditional statements in 

ArcInfo® GRID®. The unsupervised classification value of 1 usually represents null values in the 

SAVI masked image. Initial analysis may eliminate other values from further analysis as primary 

contributors of noise to the signal. 

Each remaining grid is then interactively edited while overlaid on the orthorectified imagery using 

the ArcScan suite of tools in ArcMap. These tools enable the replacement of binary grid cell values 

with 0 or 1, through the on-screen selection using polygons, rectangles or circles. In this case, the 

tools are used to erase false-positive eelgrass pixels by assigning a value of 0. 

Once all the grids are edited, they are merged and the training data are overlaid to provide an initial 

assessment of the results. Further editing is performed on the constituent grids and they are 

reassembled using map algebra for final editing and accuracy assessment. Figure 7 illustrates the 

work flow. 
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 Page 21 of 50 

Figure 7. Hybrid classification work flowchart.

CIR Aerial Photo Mosaic 

Unsupervised Classification 

Classes Split into Binary Grids 

Edit

Edit

Edit

Edit

Edit

Edit

Edit

Edited Grids are Compiled 

SAVI Image into the Hybrid Classification
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 Page 22 of 50 

2.7 CLASSIFICATION ACCURACY 

2.7.1 Theory of Classification Accuracy

A key component of any classification effort is an assessment of its accuracy. Efforts to develop 

methods for obtaining quantitative assessments of photo interpretation began in the 1950's, but the 

importance of this issue was not generally recognized for several decades. A comprehensive 

discussion of this subject has been provided by Congalton and Green (1999), including their 

description of the utility of the error matrix (Table 4 replaces Figure 2-1 below) in assessing the 

accuracy of digital maps, as follows: 

AAn error matrix compares information from reference sites to information on the map for a 

number of sample areas. The matrix is a square array of numbers set out in rows and 

columns that express the labels of samples assigned to a particular category in one 

classification relative to the labels of samples assigned to a particular category in another 

classification (Figure 2-1). One of the classifications, usually the columns, is assumed to be 

correct and is termed the reference data. The rows usually are used to display the map 

labels or classified data generated from the remotely sensed data. Thus, two labels from 

each sample are compared to one another: 

! Reference data labels: the class label of the accuracy assessment site derived from 

data collected that is assumed to be correct; and 

! Classified data or map labels: the class label of the accuracy assessment site 

derived from the map. 

Error matrices are very effective representations of map accuracy, because the individual 

accuracies of each map category are plainly described along with both the errors of 

inclusion (commission errors) and errors of exclusion (omission errors) present in the map. 

A commission error occurs when an area is included in an incorrect category. An omission 

error occurs when an area is excluded from the category to which it belongs. 

In addition to clearly showing errors of omission and commission, the error matrix can be 

used to compute overall accuracy, producer=s accuracy, and user=s accuracy (Story and 

Congalton 1986). Overall accuracy is simply the sum of the major diagonal (i.e., the 

correctly classified pixels or samples) divided by the total number of pixels or samples in 

the error matrix. This value is the most commonly reported accuracy assessment statistic. 

Producer=s and user=s accuracies are ways of representing individual category accuracies 

instead of just the overall classification accuracy@. 
_______________________________________________________________________________ 

 Page 23 of 50 

Reference Data

Land 

Cover ABCD Row Total

A 60 7 2 15 84

B 4 75 11 9 99

C 1 21 80 14 116

D 5 13 0 83 101 Overall Accuracy

Column 

Total 70 116 93 121 400 (60+75+80+83)/400 =

Land 

Cover Producer's Accuracy Land Cover User's Accuracy

A 60/70 = A 60/84 =

B 75/116 = B 75/99 =

C 80/93 = C 80/116 =

D 83/121 = D 83/101 =

Classified 

Data

74.5%

85.7%

64.7%

86.0%

68.6%

71.4%

75.8%

69.0%

82.2%

Table 4. Example error matrix for four hypothetical land cover categories (A – D).

2.7.2 Accuracy Assessment 

In order to compare the final seagrass and bare substrate classifications with the ground survey 

percent cover data, the ArcInfo® Grid Blocksum function with a 10 x 10 pixel kernel is used to 

count the number of 0.25 m pixels classified as seagrass in a 2.5 m array around each pixel. The 

results are then binned using a Grid® conditional statement into classes ‘greater than’ and ‘less than 

or equal to’ 10% of the total. Percent cover values of the ground survey station areas are similarly 

binned into classes greater than and less than or equal to 10% cover. The classification grid and 

validation point cover are overlaid in ArcView® v3.3 (Figure 8), and the Spatial Analyst® Kappa 
_______________________________________________________________________________ 

 Page 24 of 50 

Analysis® v.1.2 extension is used to generate an error matrix, user=s and producer=s accuracy 

statistic, and the Kappa statistic for the accuracy analysis (Jenness and Wynne 2004). 

Figure 8. Seagrass classification grid and validation point cover. 
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 Page 25 of 50 

3.0 SUMMARY

Aerial photography is a powerful tool to survey the distribution (extent and cover density) of 

seagrasses in intertidal estuarine habitats. A number of decisions have to be made in planning an 

aerial survey, ranging from the size of the camera to the elevation of the imaging platform (i.e., 

height of the plane). Each of the key considerations in planning an aerial survey is briefly discussed 

in terms of mission planning. To assist in planning, a spreadsheet tool has been developed that 

calculates the number of photographs required, resolution, computer storage requirements for the 

digitized photographs, etc. Based on these user inputs, the spreadsheet outputs an ArcInfo® AML to 

generate photo centers and photo boundaries as GIS datasets. This planning tool allows users to 

easily evaluate different strategies based on their objectives and resources. Because many aerial 

surveys will be conducted by contracting with a private contractor, example scopes of work for 

acquiring commercial aerial photography, and for subsequent geocoding and orthorectification of 

the photographs to produce digital photomaps, also are provided. 

During the PCEB aerial surveys of Yaquina Bay estuary, Oregon, it became apparent that the 

estuaries in the PNW differ in a number of fundamental characteristics from those on the Atlantic 

and Gulf of Mexico coasts, such as the much larger tidal amplitude in PNW estuaries. In turn, these 

differences require modifications to the procedures that have been used in other regions. It was 

found that the use of CIR film during surveys conducted at low tides provided superior 

classification of the SAV than from TC film. 

An important component of any aerial photography mapping program is an accuracy assessment of 

the classification process, that is, the assignment of each pixel to a specific habitat class (e.g., 

eelgrass vs. bare sediment). Ideally, the accuracy assessment consists of a field survey of the 

photographed site close to the time when the photographs were taken. A statistically rigorous 

accuracy assessment usually takes a considerable field effort, but is required to estimate uncertainty 

in the classification of the images in the orthorectified photographs. The approaches used to date to 

obtain corroborative information on SAV intertidal distributions from ground surveys within one 

PNW estuary have been described in this guide. 
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 Page 26 of 50 

4.0 ACKNOWLEDGEMENTS 

The aerial photography illustrated in this guide was conducted by Bergman Photographic Services, 

Inc. (Portland, OR). The digital terrain model of Yaquina estuary used in the desktop 

orthorectification of the 2004 aerial photographs was developed by Photogrammetric Data Services 

(Eugene, OR) from our 1998 aerial photography. The 2004 ground survey was conducted with the 

assistance of Dynamac, Inc. (Newport, OR). Technical advice was provided by Dr. Thomas 

Mumford and Helen Berry (Department of Natural Resources, Olympia, WA), Dr. William Pickles 

(Lawrence Livermore National Laboratory, CA), Professor Donald Potts (University of California, 

Santa Cruz), Jeff Weber (Department of Land Conservation and Development, Portland, OR), Dr. 

Ralph Garono (Earth Design Consultants, Inc., Corvallis, OR), Dr. Denis White and Dr. Mary 

Kentula (US EPA Western Ecology Division, Corvallis, OR), Jeff Robinson (Humboldt Bay 

Harbor, Recreation & Conservation District, Eureka, CA), and Eric Augustine (Earth Star 

Geographics, San Diego, CA). We also thank Bryan Coleman (CSC, Inc., Newport, OR) and 

Christina Folger, Chris Mochon-Collura, and Chris Eide (US EPA Pacific Coastal Ecology Branch, 

Newport, OR) for their assistance. 

5.0 LITERATURE CITED

Avery, T. E. and G. L Berlin. 1985. Fundamentals of Remote Sensing and Airphoto 

Interpretation (5th ed), pp. 40-43. Prentice Hall, Upper Saddle River, NJ. 

Canada Centre for Remote Sensing - Natural Resources Canada. 2004. Fundamentals of Remote 

Sensing. Available at: http://ccrs.nrcan.gc.ca/resource/tutor/fundam/pdf/fundamentals_e.pdf

Congalton, R. G. 1991. A review of assessing the accuracy of classifications of remotely sensed 

 data. Remote Sensing of Environment 37: 35-46. 

Congalton, R. G. and K. Green. 1999. Assessing the Accuracy of Remotely Sensed Data: 

Principles and Practices. Lewis Publishers, CRC Press, Inc., Boca Raton, FL, 137 p. 

Dobson, J. E., E. A. Bright, R. L. Ferguson, D. W. Field, L. L. Wood, K. D. Haddad, H. Iredale III, 

J. R. Jensen, V. V. Klemas, R. J. Orth and J. P. Thomas. 1995. NOAA Coastal Change 

Analysis Program (C-CAP): Guidance for Regional Implementation. NOAA Technical 

Report NMFS 123. National Oceanic and Atmospheric Administration, U.S. Department of 

Commerce, Silver Springs, MD, 129 p. 

Eastman Kodak Company. 2000. KODAK Infrared Aerographic Film 2424 - KODAK Publication 

No. AS-58. Eastman Kodak Company, Rochester, NY. Available at: 

http://www.phred.org/~josh/photo/ti0132.pdf

Finkbeiner, M., B. Stevenson and R. Seaman. 2001. Guidance for Benthic Habitat Mapping: An 

Aerial Photographic Approach. Technical Report NOAA/CSC/20117-PUB. National 

Oceanic and Atmospheric Administration, U.S. Department of Commerce, Charleston, SC. 

Hauxwell, J., J. Cebrián and I. Valiela. 2003. Eelgrass Zostera marina loss in temperate estuaries: 

relationship to land-derived nitrogen loads and effect of light limitation imposed by algae. 

Marine Ecology Progress Series 247: 59-73. 

Huete, A. R. 1988. A Soil-Adjusted Vegetation Index (SAVI). Remote Sensing of Environment 25: 

295-309. 
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 Page 27 of 50 

Jenness, J. and J. J. Wynne. 2004. Kappa analysis (kappa_stats.avx) extension for ArcView 3.x. 

Jenness Enterprises. Available at: http://www.jennessent.com/arcview/kappa_stats.htm. 

Kölbl, O., M. P. Best, A. Dam, J. W. Douglass, W. Mayr, R. H. Philbrik, P. Seitz and H. Wehrli. 

1996. Scanning and state-of-the-art scanners. In: Digital Photogrammetry: An Addendum 

to the Manual of Photogrammetry, pp. 3-37. American Society for Photogrammetry and 

Remote Sensing, Bethesda, MD. 

Mumford, T. and Berry, H. 2006. Department of Natural Resources, Olympia, WA. Personal 

communication. 

Orth, R. J. 1977. Effect of nutrient enrichment on growth of the eelgrass Zostera marina in the 

Chesapeake Bay, Virginia, USA. Marine Biology 44: 187-194. 

Orth, R .J. and K. A. Moore. 1983. Chesapeake Bay: an unprecedented decline in submerged 

aquatic vegetation. Science 222: 51-53. 

Ray, T. W. 1994. Vegetation in Remote Sensing: FAQs version 1.0. In: ERMapper Applications

6.0 (1998), pp. 99-124. ER Mapper, Inc., San Diego, CA. Also see: 

http://www.yale.edu/ceo/Documentation/rsvegfaq.html

Short, F. T. and D. M. Burdick. 1996. Quantifying eelgrass habitat loss in relation to housing 

development and nitrogen loading in Waquoit Bay, Massachusetts. Estuaries 19: 730-739. 

Story, M. and R.G. Congalton. 1986. Accuracy assessment: A user=s perspective. Photogrammetric 

Engineering and Remote Sensing 52: 397-399. 

Valiela, I., K. Foreman, M. LaMontagne, D. Hersh, J. Costa, P. Peckol, B. DeMeo-Anderson, C. 

D=Avanzo, M. Babione, C-H. Sham, J. Brawley and K. Lajtha. 1992. Couplings of 

watersheds and coastal waters: sources and consequences of nutrient enrichment in Waquoit 

Bay, Massachusetts. Estuaries 15: 443-457. 

Warner, W. S., R. W Graham and R. E. Read. 1996. Small Format Aerial Photography. American 

Society for Photogrammetry and Remote Sensing, Bethesda, MD, 348 p. 

Young, D. R., D. T. Specht, B. D. Robbins and P. J. Clinton. 1999. Delineation of Pacific 

Northwest SAVs from aerial photography: Natural color or color infrared film? In: 

Proceedings of the1999 ASPRS Annual Conference, pp 1173-1178. American Society of 

Photogrammetry and Remote Sensing, Bethesda, MD. 
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 Page 28 of 50 

APPENDIX I: USEFUL LINKS 

DRAFT Standards for Aerial Photography - American Society for Photogrammetry & Remote 

Sensing 

http://www.asprs.org/resources/standards/photography.htm

Fundamentals of Remote Sensing Tutorial - Canada Centre for Remote Sensing 

http://ccrs.nrcan.gc.ca/resource/tutor/fundam/pdf/fundamentals_e.pdf

Guidance for Benthic Habitat Mapping - NOAA Coastal Services Center 

http://www.csc.noaa.gov/benthic/mapping/pdf/bhmguide.pdf

Downloadable Digital Orthophotography, Digital Raster Graphics (USGS Quads), and Digital 

Elevation Models – Natural Resources Conservation Services 

http://www.ncgc.nrcs.usda.gov/products/datasets/index.html

US EPA Remote Sensing Example Applications 

http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=15997

http://www.epa.gov/esd/land-sci/epic/pdf/fs-epic.pdf

http://www.epa.gov/GED/crc/epa620r-01-001h.pdf

http://www.epa.gov/esd/land-sci/epic/aerial-photos.htm

Tide and Current Prediction 

http://tbone.biol.sc.edu/tide/sitesel.html

http://www.wxtide32.com/

GeoTiff Links 

http://www.remotesensing.org/geotiff/geotiff.html
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 Page 29 of 50 

APPENDIX II: SPECIFICATIONS FOR AERIAL PHOTOGRAPHY USED 

BY WED/PCEB FOR AERIAL PHOTOMAP/CLASSIFATION PROJECTS 

BETWEEN 1997 AND 2006

Estuary Year Day-Month Photoscale Format Digitized OrthoRectified Ground Pixel Classified

Yaquina 1997 7/23 7200 CIR Photogrammetric/Diapositive SoftCopy 0.20m Yes

Yaquina 1997 7/23 7200 RGB Photogrammetric/Diapositive SoftCopy 0.20m No

Yaquina 1998 8/10 6000 CIR Photogrammetric/Diapositive SoftCopy 0.15m Yes

Yaquina 1999 7/15 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m Yes

Yaquina 1999 9/10 7200 CIR No No

Yaquina 1999 10/24 7200 CIR No No

Yaquina 2000 6/17 14400 CIR Non-Photogrammetric/Diapositive Desktop 0.20m No

Yaquina 2000 6/17 14400 RGB No No

Yaquina 2000 6/20 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m No

Yaquina 2000 8/2 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m Yes

Yaquina 2000 10/24 3600 CIR Non-Photogrammetric/Diapositive No

Yaquina 2001 5/9 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m No

Yaquina 2001 7/25 7200 CIR No No

Yaquina 2001 10/15 7200 CIR No No

Yaquina 2002 1/11 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m No

Yaquina 2002 8/11 7200 CIR Non-Photogrammetric/Diapositive No

Yaquina 2002 9/23 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m No

Yaquina 2002 5/15 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m No

Yaquina 2003 5/19 10000 CIR Non-Photogrammetric/Diapositive Desktop 0.20m Partial

Yaquina 2003 8/1 10000 CIR No No

Yaquina 2003 10/21 7200 CIR No No

Yaquina 2004 4/9 10000 CIR Non-Photogrammetric/Diapositive Desktop 0.25m Yes

Yaquina 2005 7/21 20000 CIR Photogrammetric/Film Desktop 0.25m No

Yaquina 2006 5/16 20000 CIR Photogrammetric/Film Desktop 0.25m No

Alsea 1999 9/10 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m Yes

Alsea 2004 4/9 10000 CIR Non-Photogrammetric/Diapositive Desktop 0.25m Yes

Siletz 1999 9/10 7200 CIR Non-Photogrammetric/Diapositive Desktop 0.20m No

Salmon 2000 6/20 7200 CIR/RGB Non-Photogrammetric/Diapositive Desktop 0.20m No

Salmon 2004 4/9 10000 CIR Non-Photogrammetric/Diapositive Desktop 0.25m Yes

Nestucca 2004 4/9 10000 CIR Non-Photogrammetric/Diapositive Desktop 0.25m Yes

Tillamook 2004 4/9 10000 CIR Non-Photogrammetric/Diapositive Desktop 0.25m Yes

Tillamook 2005 6/9 20000 CIR Photogrammetric/Film Desktop 0.25m No

Coos 2005 5/26 20000 CIR Photogrammetric/Film Desktop 0.25m Yes

Umpqua 2005 7/24 20000 CIR Photogrammetric/Film Desktop 0.25m Yes

Suislaw 2005 7/24 20000 CIR Photogrammetric/Film No

Cocquille 2005 7/26 20000 CIR Photogrammetric/Film No
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 Page 30 of 50 

APPENDIX III: SPATIAL ACCURACY OF ORTHOPHOTOGRAPHY 

Lincon County Geodetic Control

Control Order Database Premark? Visibility Context Described Min Dist. Max Dist. Mean Dist. Accuracy +/-

SB10 1O LCGC Yes High High Recovered 0.10 0.30 0.20 0.20 0.10

YB32 1O LCGC No Low High Description 0.10 0.45 0.28 0.28 0.45

SEC7 2C1 LCGC No Low Med Description 0.20 1.66 0.93 0.93 1.66

8927 2C1 LCGC No None Poor Description N/A N/A N/A N/A N/A

9021 2C1 LCGC No None Poor Description N/A N/A N/A N/A N/A

9026 2C1 LCGC No Low High Description 0.10 0.51 0.31 0.31 0.51

9029 2C1 LCGC No Low Med Description 0.35 0.50 0.43 0.43 0.50

90103 2C1 LCGC No Low Med Description 0.20 0.50 0.35 0.35 0.50

9136 2C1 LCGC Yes low High Recovered 0.10 0.30 0.20 0.20 0.10

5161 2C1 LCGC No Low Med Description 0.10 0.30 0.20 0.20 0.30

8932 2C1 LCGC No Low Med Description 0.35 0.50 0.43 0.43 0.50

9019 2C1 LCGC No None Med Description N/A N/A N/A N/A N/A

9024 2C1 LCGC No None Med Description N/A N/A N/A N/A N/A

9053 2C1 LCGC No None Med Description N/A N/A N/A N/A N/A

9122 2C1 LCGC No None Med Description 1.00 1.30 1.15 1.15 1.30

AZ9021 3O LCGC No None Low Description 0.40 1.15 0.78 0.78 1.15

AZ9026 3O LCGC No None Poor Description N/A N/A N/A N/A N/A

AZ9029 3O LCGC No None Poor Description N/A N/A N/A N/A N/A

COR90103 3O LCGC No None Poor Description N/A N/A N/A N/A N/A

COR9136 3O LCGC No Low Med Description 0.20 0.40 0.30 0.30 0.40

AZ9024 3O LCGC No None Poor Description N/A N/A N/A N/A N/A

COR9025 3O LCGC No None Poor Description N/A N/A N/A N/A N/A

AZ9053 3O LCGC No None Med Description N/A N/A N/A N/A N/A

AZ9122 3O LCGC No None Med Description N/A N/A N/A N/A N/A

VENTS 1O NOAA No High High Recovered 0.10 0.30 0.20 0.20 0.10

Mean 0.44 0.58

Mean no premark 0.49 0.67

Standard Deviation 0.31 0.49

Standard Deviation no premark 0.32 0.48

Table III-1. Worksheet showing spatial accuracy of orthophotography based on the published 

location of geodetic survey points between U.S. 101 (Yaquina Bay Bridge) in the City of Newport 

and the City of Toledo, Oregon, compared to locations obtained from orthorectified photographs for 

the aerial photosurvey of Yaquina Bay estuary on July 23, 1997. 
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 Page 31 of 50 

APPENDIX IV: PROCEDURES FOR CONDUCTING GROUND SURVEYS 

OF INTERTIDAL VEGETATION PERCENT COVER IN SUPPORT OF 

AERIAL PHOTOGRAPHY HABITAT MAPPING 

1.0 INTRODUCTION

The Pacific Coastal Ecology Branch (PCEB) of the US Environmental Protection Agency, Office of 

Research and Development, National Health and Environmental Effects Laboratory, Western 

Ecology Division (EPA/ORD/NHEERL/WED) conducts aerial photography surveys of Pacific 

Northwest (PNW) estuaries using false color, near-infrared (color infrared, CIR) film. The project 

includes a ‘ground truthing’ component needed both for training the image analyst and (using 

separate, independent data) assessing the accuracy of the final habitat classification (map) of the 

target habitats. A primary guide to the present procedure is the text Assessing the Accuracy of 

Remotely Sensed Data: Principles and Practices (Congalton and Green 1999). This guide 

emphasizes the necessity of using randomly located stations, which may be stratified according to 

target habitat classes if such information is available. The procedure described here relies upon 

previously obtained aerial photomaps, or upon survey reports such as The Oregon Estuary Plan 

Book (Cortright et al. 1987) to provide polygons for target habitats such as eelgrass meadow 

(Zostera marina L.) or nonvegetated substrate in the intertidal zone of estuaries under investigation 

(which generally become covered by green macroalgae in summer). Locations of randomly 

positioned stations are provided by a geographic information system (GIS) specialist for entry as 

‘way points’ into a global positioning system (GPS) used to navigate to these randomly positioned 

stations in the field. 

1.1 PLANNING 

A. Locate the most reliable map of the target habitat classes, such as intertidal eelgrass 

Zostera marina (Zm) and nonvegetated substrate (N) in the study site (e.g., a PNW estuary). 

Transfer it into a GIS. 

B. Using the GIS, create polygons for each target habitat class within the intertidal zone. 

Using a random position program, create 100 randomly positioned stations within each 

habitat stratum, with the percentage in a given polygon being proportional to the area of that 

polygon relative to the total stratum area. Overlay the polygon layer on a layer illustrating 

the areas covered by the individual photographs from the aerial survey; insure that there are 

at least two stations for each stratum in each photo area. For each stratum, number the 

stations from 1 to 100 as they appeared in the random sequence.

C. Print out color maps of each stratum on a base map of the study area, showing the 

locations of the numbered stations. Protect these in waterproof plastic sleeves for use in the 

field. 
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1.2 POSITIONING 

A. Use a differentially-corrected global positioning system (DGPS) instrument with submeter accuracy. 

B. Document the accuracy and precision of this DGPS by taking three 30-second 

positionings at a survey marker with as high an horizontal accuracy rating as possible, 

within the study area or as close to it as possible. At least ten sets should be taken on 

different days. 

C. In the data logger of the DGPS, create a feature list of numbered stations for each 

stratum in the study. 

1.3 GROUND STATION SURVEYING

A. Using the DGPS, navigate to the first station in a given habitat stratum. (PCEB has 

found that the use of a reliable hovercraft vessel is of inestimable value in efficiently 

reaching randomly located positions during exposed conditions on an estuarine intertidal 

mud flat). Place a marker ‘blindly’ by throwing it over a shoulder. This is the center 

position of the 2.5 m x 2.5 m survey area. If any part of this area (oriented with two 

opposing sides pointing toward true north) lies within 2.5 m of the edge of the habitat (e.g., 

an eelgrass meadow margin or a ‘hole’ whose minimum diameter exceeds 2.5 m), move the 

marker ‘inward’ (perpendicular to the habitat local margin) just enough so that no part of the 

survey area is within 2.5 m of the habitat margin. This minimizes the probability that, 

owing to the approximately 2.5 m uncertainty in positioning via the orthorectified digital 

photomap, the area of the image which the analyst classifies lies just across the actual 

margin and outside the habitat surveyed on the ground. Replace the station marker. On the 

field data sheet, record how far, and in which direction, the station marker was moved. 

B. Place a quad (outer dimensions 1.25 m by 1.25 m, strung with two orthogonal sets of 

five equally spaced taut strings) in the southeast sector of the zone around the marker 

(Sector 1), with the northwest corner of the quad just touching the marker. Use a compass 

to orient the quad so that two opposing sides point toward true north. 

C. Without walking into the sectors (and thus disturbing their survey areas), survey the 25 

intersections (points) of the orthogonal strings in Sector 1. Assign a single habitat as most 

representative of the ground cover directly beneath each point. Determine the count (of a 

total of 25 points in the quad area) for each target habitat, leaving bare substrate as the 

default count (remainder). Thus, the count for Sector 1 might be 10 Z. marina, 5 benthic 

green macroalgae and 2 Z. japonica, leaving 8 points represented by bare substrate to 

constitute the total of 25 points. Enter the cover counts for Z. marina, benthic green 

macroalgae, and Z. japonica in the three fields provided in appropriate data field of the data 
_______________________________________________________________________________ 

 Page 33 of 50 

logger. Also record the entries in appropriate fields for that station on a waterproof field 

data sheet (Table IV-1), along with information for that day’s survey. Describe the types 

and counts of any miscellaneous material (that should be subtracted from the bare substrate 

default count) in the ‘Notes’ column or on the following row of the field data sheet. Then 

take a (numbered) photograph of the quad, positioning the camera as near as possible over 

the center of the quad to obtain a vertical photograph of the survey area. Avoid shadows in 

the photo. 

Zm GM Zj Zm GM Zj Zm GM Zj Zm GM Zj Northing Easting

Time Way 

Point 

No. Notes:

Aerial Photomapping Ground Survey

Estuary:

Low Tide Level (ft):

Crew Initials:

Date:

Time:

Vessel:

Photo 

Nos.

Quad1 Quad2 Quad 3 Quad 4 GPS Position

 

 Table IV-1. Example field data sheet for aerial photomapping ground surveys. 

D. Flip the quad over to the west and repeat the procedure outlined in Section 1.3(C) for 

Sector 2 (southwest sector). 

E. Flip the quad over to the north and repeat the procedure, for Sector 3 (northwest sector). 

F. Flip the quad over to the east and repeat the procedure for Sector 4 (northeast sector). 
_______________________________________________________________________________ 

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G. Determine the position of the station marker by placing the DGPS antenna directly over 

it, and obtain one 30-second position reading at one-second intervals. Also record the 

position reading (northing and easting) on the data sheet. 

H. Proceed to the second station of the stratum and repeat the survey procedure. Note: If it 

is very likely that a specific number of the stratum=s stations will be sampled (e.g., 65), for 

efficiency the stations may be sampled out of order (grouping adjacent stations) if it is very 

likely that no gaps (or only a small number) will be left in the station sequence (1 - 65) at 

the end of the ground survey. 

I. Proceed with this sampling as described above. 

1.4 MOVING A STATION INTO A TARGET HABITAT

Owing to insufficient information in planning the ground survey, a station may be found to 

lie outside the target habitat. If the target habitat lies within an estimated 100 m of that 

point (a rough limit of the distance that can be ranged visually), the station may be moved 

into the habitat if this is done in a manner that maintains the randomness of the positioning. 

There are two realistic scenarios: 

1. Case I: If only one ‘front’ of the target habitat lies within this (arbitrary) 100 m 

range, proceed along a track perpendicular to that front until reaching the habitat 

edge. Proceed 2.5 m into the habitat. Then estimate the width of the habitat along a 

projection of this track, within the candidate sampling area bounded by the 2.5 m 

wide ‘buffer zone’ but not more than 100 m (except in special circumstances, noted 

on the field sheet). Using a table of random numbers, enter it blindly and select the 

first number that is less that this net width of the sampling area. Proceed that 

distance from the 2.5 m buffer zone along the track to the new sampling location. 

Record the direction and distance moved to the new station location (so that any user 

may decide whether or not to accept the moving of this station). 

2. Case II: If more than one front lies within 100 m, using a compass determine the 

radial range that encompasses the candidate habitat positions (e.g, from 90 degrees - 

due East - to 270 degrees - due West). Since a random number table typically has 2-

digit numbers, select the first number encounter between 9 and 27, multiply it by 10, 

and select that as the compass heading to a candidate habitat. Then continue 

following the procedure specified in Case I. Again, record the direction and distance 

moved to the new station location.
_______________________________________________________________________________ 

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1.5 MARGIN MAPPING

The Principal Investigator will decide if positioning of the margin (edge) of a habitat, such 

as an eelgrass meadow or patch, is to be part of a ground survey, and if so, the maximum 

length of the sectors (e.g., 100 m) and whether their starting positions are to be selected 

randomly, or arbitrarily in the field. If the mapping is to be done by foot, the field survey 

pair makes a best effort to walk along the edge of the habitat in the selected area with the 

DGPS unit. For seagrass, this edge is defined according to the National Oceanic and 

Atmospheric Administration Coastal Change Analysis Program (C-CAP) protocol (Dobson 

et al. 1995) as the 10% cover contour. The upper margin usually is quite sharp. For a 

shallow meadow, at a good low tide it may be possible to wrap an entire sector by foot. 

Otherwise, only the upper part of the meadow is mapped by foot; the lower margin then 

may be mapped by transporting the DGPS along it from a slow moving boat or hovercraft. 

1.6 DATA ARCHIVING

Upon return to the laboratory, the positions for the day=s surveys are post-processed to yield 

the most accurate differentially-corrected positions. These corrected positions are entered 

into a file that includes the percent cover values for the stations surveyed. The directory or 

file names should include the site (estuary) and date sampled, and indicate whether the data 

are habitat margin positions or percent cover values for positioned stations. The digital 

photographs also should be transferred to a corresponding computer file. 

1.7 APPLICATION OF GROUND SURVEY DATA

A. In the simplest case, the ‘margin mapping’ data (DGPS positions from the ‘line’ mode) 

are provided to the image analyst for training purposes (these locations may be selected 

arbitrarily). In more advanced studies, sectors approximately 100 m in length are randomly 

selected; 20% are provided to the image analyst for training (with a minimum of two sectors 

per image). The remaining line sectors are retained by the Principal Investigator, for 

comparison with (e.g., determining the average deviation from) the margin of the habitat 

classification following completion of the digital photomap. 

B. In the simplest case, for each target habitat class specific locations are determined by the 

image analyst or by the survey team in the field, and surveyed for percent ground cover and 

station position as training data for the analyst. Alternatively, the training data are 

incorporated into the field survey as follows. The ground stations surveyed are randomly 

subsampled, so that both positioning and percent cover data from approximately 20% of the 

stations (again, with some minimum number - e.g., two per image) are provided to the 

image analyst for training. Following completion of the classification, only the positions 

(but not the percent cover data) of the remaining 80% of the ground survey stations are 

provided to the image analyst, who then samples the classifications at these positions. In 

this case, using a pixel ground dimension of 0.25 m, an array of 10 x 10 pixels (equivalent 
_______________________________________________________________________________ 

 Page 36 of 50 

to a ground sampling area of 2.5 m x 2.5 m) is centered around a given station=s position. 

The number of pixels (out of the 100 total pixels) classified as belong to a given habitat 

class (e.g., eelgrass) then is the percent cover of that vegetation class determined at that 

station via the classification. This step is repeated to yield percent cover values for all the 

target habitats (e.g., native eelgrass Z. marina, green macroalgae, non-indigenous ‘dwarf’ 

eelgrass Z. japonica, bare substrate) at that station. It is noted that this procedure results in 

the same shape, orientation, and total area of the station surveyed from the ground and from 

the photomap classification (2.5 m x 2.5 m, with sides oriented toward true north). The two 

classes of percent cover data (from the ground and the image samplings) then are compared 

via an error matrix for predetermined percent cover classes, taking the ground results as the 

reference data (Congalton and Green 1999). In the simplest case, the C-CAP protocol is 

accepted: any station with greater than 10 percent seagrass cover is to be classified as a 

seagrass station. The results for the two classes targeted in this procedure - intertidal 

eelgrass and bare substrate - via the error matrix then are determined. In all cases, the error 

matrix results are to be assessed for accidental agreement via the Kappa correction 

(Congalton and Green 1999; Jenness and Wynne 2004). It is to be noted that, since a rim 

2.5 m wide around each habitat is excluded from the survey (to avoid misinterpreting photo 

positioning error as image classification error), the accuracy assessment results do not apply 

to these unsampled areas. This fact places more importance on including a margin mapping 

component in the ground survey. 

1.8 LITERATURE CITED

Congalton, R. G., and K. Green. 1999. Assessing the Accuracy of Remotely Sensed Data: 

Principles and Practices. Lewis Publishers, CRC Press, Inc., Boca Raton, FL, 137 p. 

Cortright, R., J. Weber and R. Bailey. 1987. The Oregon Estuary Plan Book. Department of Land 

Conservation and Development, Salem, OR. Available at: 

http://www.inforain.org/mapsatwork/oregonestuary/

Dobson, J. E., E. A. Bright, R. L. Ferguson, D. W. Field, L. L. Wood, K. D. Haddad, H. Iredale III, 

J. R. Jensen, V. V. Klemas, R. J. Orth and J. P. Thomas. 1995. NOAA Coastal Change 

Analysis Program (C-CAP). Guidance for Regional Implementation. NOAA Technical 

Report NMFS 123. National Oceanic and Atmospheric Administration, U.S. Department of 

Commerce, Charleston, SC, 129 p. 

Jenness, J. and J. J. Wynne. 2004. Kappa analysis (kappa_stats.avx) extension for ArcView 3.x. 

Jenness Enterprises. Available at: http://www.jennessent.com/arcview/kappa_stats.htm
_______________________________________________________________________________ 

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APPENDIX V: EXAMPLE SCOPE OF WORK – AERIAL PHOTOGRAPHY

SCOPE OF WORK

TITLE: Aerial Photography Survey of Yaquina Bay Estuary, Oregon during 2006.

The United States Environmental Protection Agency (US EPA) National Health and Environmental 

Effects Laboratory - Western Ecology Division/Pacific Coastal Ecology Branch (NHEERLWED/PCEB) is engaging in a study of Oregon coastal estuaries, in order to characterize intertidal 

biological communities and determine potential impacts of multiple stressors. This will include 

color infrared (CIR) aerial photography of Yaquina Bay estuary, illustrated in Attachment I. The 

goal is to obtain the photography in the spring before the mid-summer macroalgal blooms. The 

original photography must be accomplished during the days and hours of lowest tide between April 

29 and August 12, 2006 when the tidal flats are most exposed during daylight hours. Any reflight 

photography required by WED/PCEB must be accomplished within the period specified above. 

The Contractor must have the ability and commitment to utilize the date/time windows necessary to 

obtain all photographs under the conditions specified in the contract. 

SPECIFICATIONS

1.1 LOCATION OF WORK 

The area for data collection shall include those portions of Yaquina Bay estuary illustrated in 

Attachment I. This figure delineates the study area, including the approximate intertidal/subtidal 

areas to be covered by image acquisition and specific flight lines over these areas with photography 

intervals, and precise locations of corresponding photo centers. A digital file containing the 

locations of the photo centers will be provided by WED/PCEB to the Contractor upon request.

1.2 DEFINITIONS

Camera System: The combination of lens, cone, magazine(s), and camera filter(s) which have been 

calibrated as an integral unit. 

Original Photography: All aerial photography, as secured by the Contractor, prior to its inspection 

by EPA/PCEB, including any reflights made at the discretion of the Contractor. 

Reflight Photography: Photography reflown at the request of WED/PCEB, to replace rejected 

original photography. Any replacements shall be provided at no additional cost to the Government. 
_______________________________________________________________________________ 

 Page 38 of 50 

1.3 AERIAL PHOTOGRAPHY REQUIREMENTS

A. For optimum photographic coverage of the intertidal flats, the aerial photography shall occur 

only during the time periods and on the dates (flight windows) specified in Attachment II. The 

following criteria shall be met: 

1. Nominal Photographic Scale: 1:20,000. The flight lines shall be oriented in the westeast direction, numbered from north-to-south (e.g., 1-, 2-), and corresponding photo centers 

from west to east (e.g., -1, -2, -3, -4, -5). 

2. Flight Schedule: Flight windows are scheduled based on tidal exposure windows. These 

flight windows (in Pacific Daylight Saving Time) are provided in Attachment II. 

3. Photographic conditions: Photography shall be undertaken when skies are free from 

smoke and excessive haze, and clouds are above the flight altitude without casting shadows 

that obscure sectors of the estuary. High overcast skies are acceptable. 

4. Aircraft: The design of the aircraft shall be such that when the camera is mounted with 

all its parts within the outer structure, an unobstructed vertical field of view is obtained. The 

field of view shall be shielded from the exhaust gases, oil, effluence and air turbulence. 

Four fiducial marks shall be visible on each frame of the film. 

5. Aerial Camera: 

(a) Forward motion compensating and GPS-triggered camera is required. 

 

(b) Nominal lens focal length: (six) 6 inches or 153 mm 

 

(c) Filter(s): Kodak Wratten filter #12 or equivalent. 

(d) AWAR rating of approximately 90 or higher 

6. Aerial Film: 

(a) Film characteristics: Kodak Aerochrome® Infrared 2443 film, or equal*, as 

specified by the Contractor, in 23 cm x 23 cm (9 in. x 9 in.) format. Color infrared 

film shall be sensitive to the visible and near infrared spectrum from 400 to 900 

nanometers. 

*NOTE: Aequal@ must be specified in response and acceptable to WED/PCEB. 

(b) Film storage and handling: Color infrared film shall be kept refrigerated in a 

waterproof container until one day before being exposed and returned to cold storage 
_______________________________________________________________________________ 

 Page 39 of 50 

after exposure until processed. All rolls of aerial film shall be contained in 

Contractor-furnished sturdy, cylindrical plastic cans. 

(c) Film processing: 

 

(1) The film shall be processed in a continuous roller transport processor to 

achieve consistent and uniform development throughout the roll. 

 

(2) Film shall be processed within 48 hours of exposure to avoid undesirable 

changes in the latent image. 

(d) Physical quality: 

 

(1) All aerial film shall be free from chemicals, stains, tears, scratches, 

abrasions, watermarks, finger marks, lint, dirt and other physical defects. The 

imagery shall be clear and sharp in detail and uniform in density. It shall be 

free from light streaks, static marks, and other defects that would interfere 

with the intended purpose. 

(2) All film shall be thoroughly fixed and washed to ensure freedom from 

chemicals and shall be of archival quality. 

 

(3) Film found to contain an excess of residual chemicals, by testing in 

accordance with manufacturer's procedures, shall be rejected or returned to 

the Contractor for refixing and rewashing at no cost to the government. 

(e) Composition of Film Roll: A roll of aerial film shall consist only of exposures 

made with the same camera system. All film on any roll shall have the same roll 

number. 

(f) Film labeling: 

(1) Placed on each exposure shall be the sponsor identifier 

“EPA/WED/PCEB”, the flight date, time, nominal scale, flight line number 

(e.g., 1- or 2-, north to south - see Section 1.3.A.1) and exposure number 

(e.g, -1 to -5, west to east - see Sector 1.3.A.1) corresponding to the flight 

map. 

(g) Digital Scans: 

(1) Prior to completion of the survey flights, WED/PCEB shall submit to the 

Contractor sets of test diapositives from previous aerial photography surveys 

of Pacific Northwest estuaries, with the choice made by WED/PCEB for the 
_______________________________________________________________________________ 

 Page 40 of 50 

preferred color balance for each set. Based upon this information, the 

Contractor shall select the color balance that best reflects previous selections 

by WED/PCEB, and, using a roll-feed photogrammetric-grade scanner 

capable of scanning original color infrared negatives at 12 micron resolution, 

produce digital scans at a resolution of 12 microns corresponding as close as 

possible to the sample diapositives provided by WED/PCEB. A pilot area 

shall be scanned and approved for color balance by WED/PCEB before 

scanning all images. The film first shall be cleaned of surface dust. Scans 

shall include all fiducial marks complete to the edge of the image. 

WED/PCEB reserves the right to reject any imagery that does not match preapproved color samples. The output format shall be uncompressed TIFF 

image format. The delivery media shall be DVD or portable hard drive, 

which shall be delivered to WED/PCEB within 20 working days of 

completion of the final aerial photography survey. Following satisfactory 

transfer of the digital images to the WED/PCEB computer system, the DVDs 

or hard drive(s) will be returned to the Contractor. 

(h) Flight Log: A copy of the pilot's flight log shall be provided upon delivery of 

the digital scans of the film from the aerial photography surveys. 

1.4 FLIGHT PLAN DATA

A. Areas to be Photographed: 

1. The area of the estuary to be photographed using CIR film is specified on the 

study area map presented in Attachment I, along with a map of required flight lines 

and photo centers. 

B. Photographic Scale: The project flight plan has been designed to achieve a nominal 

photographic scale of 1:20,000, using a lens with a nominal focal length of 6 inches or 153 

mm. 

C. Coverage: 

 

1. Coverage shall be obtained to the terminal points of each flight line, as indicated 

by the terminal marks on the flight line map(s). 

 

2. All flights and reflights shall be made in accordance with the following 

requirements: 

 

(a) Rejection of any exposures shall be cause for rejecting some or all of the 

remaining exposures in that flight line and/or area. 

 
_______________________________________________________________________________ 

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(b) Photography shall be undertaken only during the hours when acceptable 

imagery can be produced in accordance with the photographic conditions as 

specified in 1.3.A.3.and Attachment II. 

D. Horizontal Deviation: 

 1. Compass bearing of each flight line should be within 5 degrees of the charted 

flight line direction. 

E. Tilt shall not exceed 4 degrees for each exposure. Tilt shall not average more that 2 

degrees for the entire project. 

2.1 BUSINESS ARRANGEMENTS

A. Invoicing: 

1. One invoice shall be submitted for the aerial color infrared photography, film 

processing and scanning, and delivery of digital scans. 

B. Schedule for Deliverables: 

 

1. All aerial photography, including reflights, shall be completed by 

August 12, 2006. Prior to completion of the flight(s), WED/PCEB shall submit to 

the Contractor sets of test diapositive from previous aerial photography surveys of 

Pacific Northwest estuaries, with the choice made by WED/PCEB for the preferred 

color balance for each set. Based upon this information, the Contractor shall select 

the color balance that best reflects the previous selections by WED/PCEB, and 

produce the digital scans for the six estuaries surveyed. This digital scan 

information shall be delivered to WED/PCEB within 20 working days of completion 

of the aerial photography survey. 

C. Schedule of Payments 

1. Final billing shall be submitted on or before August 31, 2006. 

The Contractor shall certify to the following: 

3.1 MINIMUM QUALIFICATION REQUIREMENTS

A. Offeror must certify that they meet the following minimum qualification requirements. 

The Contractor shall have: 

1. General aerial photography experience. 
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 2. Coastal/estuarine aerial photography experience. 

 3. Experience with color infrared film photographing, processing and printing. 

 4. Global positioning (GPS) capability on the aircraft, with GPS-triggered camera. 

 5. In-house lab facility or cooperation with outside photo laboratory. 

6. Flexibility of flight schedule to conduct flights during the times specified in 

Attachment II. 

 7. Ability to deliver products within time frames specified in Section 2.1.B. 

 8. The Contractor shall provide documentation that the minimum qualification 

requirements 1 through 7 are met. This documentation will be evaluated by EPA 

based on its previous experience with contracting coastal/estuarine aerial 

photography projects. 

9. Aerial camera calibration: Tested and calibrated precision aerial cameras for 

taking aerial photographs are required. One copy of the Report of Calibration from 

the US Geological Survey, for any camera (including lenses) to be used, is required 

to be submitted with the proposal. A camera report shall not be acceptable if more 

than three years old at the time of the scheduled date for receipt of offers. The three 

year period may be waived if written evidence is furnished of a firm scheduled date 

the camera is to be tested at the US Geological Survey Optical Science Testing 

Laboratory. The fees for such tests are the responsibility of the Contractor. 

 Contact for Calibration Tests 

 US Geological Survey 

 National Mapping Division 

 Attention: Chief, Optical Science Section 

 526 National Center 

 Reston, VA 22092 

 Telephone: (703) 648-4682 

10. Capability for film processing or digital scanning. If the Contractor uses the 

services of an outside lab for film processing or digital scanning, the Contractor shall 

submit a certification as to that laboratory=s qualifications for proper film processing 

and/or digital scanning. 
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Attachment I: Required flight lines and precise locations of photo centers for Year 2006 color 

infrared aerial photography of Yaquina Bay estuary, Oregon. 
_______________________________________________________________________________ 

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Attachment II: Time/tidal elevation (ft) windows for allowable photography of Yaquina Bay 

estuary, Oregon, April 29 – August 12, 2006 (initial page only). 

Tide 

Windows 

2006 

Day 

Date Time Sun Mon Tue Wed Thu Fri Sat 

4/29/2006 900 -1.65

 915 -1.4

 930 -1.09

 945 -0.73

4/30/2006 900 -1.76 

 915 -1.71 

 930 -1.6 

 945 -1.43 

 1000 -1.19 

 1015 -0.91 

 1030 -0.58 

5/1/2006 900 -0.99 

 915 -1.15 

 930 -1.24 

 945 -1.27 

 1000 -1.23 

 1015 -1.14 

 1030 -0.99 

 1045 -0.79 

 1100 -0.54 

5/15/2006 900 -1.5 

 915 -1.37 

 930 -1.18 

 945 -0.94 

 1000 -0.66 

5/16/2006 900 -1.51 

 915 -1.56 

 930 -1.56 

 945 -1.49 

 1000 -1.36 

 1015 -1.17 

 1030 -0.94 

 1045 -0.66 
_______________________________________________________________________________ 

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APPENDIX VI: EXAMPLE SCOPE OF WORK – DIGITAL 

ORTHORECTIFICATION OF AERIAL PHOTOGRAPHS 

SCOPE OF WORK

BACKGROUND

 

The United States Environmental Protection Agency (US EPA) National Health and Environmental 

Effects Laboratory - Western Ecology Division/Pacific Coastal Ecosystems Branch (NHEERLWED/PCEB) is engaging in a study of Yaquina Bay estuary on the Oregon central coast, in order 

to characterize intertidal biological communities and determine potential impacts of multiple 

stressors. This includes color infrared (CIR) aerial photography of a portion of the estuary, 

approximately from river mile 0.5 to river mile 12.5. The original photography is to be 

accomplished by August 31, 1998 at a scale of 1:6000 using a 6 inch lens in 23 cm aerial film 

format during morning when the tidal flats are most exposed. Nine east-west flightlines are to be 

flown with varying numbers of photos per flightline with a standard 60% overlap and 30% sidelap 

totaling 120 exposures. Approximately 105 exposures include aquatic portions of the Yaquina Bay 

estuary. A cross line flightline of 20 exposures also is to be flown at an angle to the main 

flightlines to aid aerotriangulation calculations. 

BID SPECIFICATIONS

 

1.1 DEFINITIONS

A. WED/PCEB

US Environmental Protection Agency, Office of Research and Development, 

National Health and Environmental Effects Research Laboratory, Western Ecology 

Division, Pacific Coastal Ecology Branch located at the Hatfield Marine Science 

Center in Newport, Oregon, 97365-5260. 

B. WED/PCEB GIS system: 

The Geographic Information System in use at the WED/PCEB facility using 

Arc/Info® v.7.1.1; ArcView® 3.0; and ER Mapper® v.5.0 software running on a 

Windows NT Intel platform. Other software used includes Excel® v.5.0, PCGPS®

v.3.2, FieldNotes®, and Image Alchemy PS®. 

C. GeoTIFF

"GeoTIFF" refers to Tagged Image File Format (TIFF) files which have geographic 

(or cartographic) data embedded as tags within the TIFF file. The geographic data 

can then be used to position the image in the correct location and geometry on the 
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screen of a geographic information display. GeoTIFF is a metadata format, which 

provides geographic information to associate with the image data. But the TIFF file 

structure allows both the metadata and the image data to be encoded into the same 

file. The most current version of the GeoTIFF specification is maintained on a 

WWW site at: 

http://www.remotesensing.org/geotiff/spec/geotiffhome.html

D. TIFF

TIFF is a raster data format for storage, transfer, display, and printing of raster 

images. The TIFF imagery file format can be used to store and transfer digital 

satellite imagery, scanned aerial photos, elevation models, scanned maps or the 

results of many types of geographic analysis. 

E. TIFF World File

The world file is an ASCII text file that is associated with an image by the following 

naming convention at ARC/INFO® 7.x and ArcView® (all versions). If the image file 

name has a 3-character extension (e.g., image1.tif), the world file has the same name 

followed by an extension containing the first and last letters of the image's extension 

and ending with a "w" (e.g., image1.tfw). The following summarizes the contents of 

the world file: 

1. line 1: x-dimension of a pixel in map units 

2. line 2: rotation parameter 

3. line 3: rotation parameter 

4. line 4: negative of y-dimension of a pixel in map units 

5. line 5: x-coordinate of center of upper left pixel 

6. line 6: y-coordinate of center of upper left pixel

1.2 PHOTOGRAPHIC HARD COPY

A. Diapositive transparencies of 1998 color infrared aerial photography of Yaquina Bay 

estuary (a total of 140 exposures) will be provided to the Contractor by WED/PCEB. The 

diapositives will be produced by WED/PCEB according to color-model specifications 

developed in consultation with the Contractor. 

B. The diapositive transparencies must be handled in such a manner to keep them clean and 

free from stains, blemishes, uneven spots, fog, and finger marks. 
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2.1 PHOTOGRAPHIC DIAPOSITIVE DIGITIZATION

The Contractor shall digitize the color infrared diapositive photographic transparencies 

required for digital orthorectification of the aquatic portion of Yaquina Bay estuary. 

Scanning shall be accomplished with a high resolution photogrammetric color scanner at a 

scanning resolution of 25 microns or higher in 24 bit color. Scanning shall be conducted in 

a consistent manner that will ensure the highest fidelity to the colors present in the 

photographic diapositive transparencies. The make, model, and calibration settings of the 

scanner used by the Contractor in the production of the above data files shall be provided to 

WED/PCEB by the Contractor prior to product delivery. 

2.2 IMAGE RECTIFICATION

A. Color Infrared Image Rectification

 

1. Aerial Triangulation 

Using diapositives of 1998 color infrared aerial photography of 

Yaquina Bay estuary provided by WED/PCEB; coordinates and 

elevations of photo centers of 1998 color infrared aerial photography 

of Yaquina Bay estuary provided by WED/PCEB; ground control 

points provided by WED/PCEB; and any Contractor-provided 

additional post-flight ground control points; the Contractor shall 

perform and aerial triangulation process that shall include the 

following: 

a. Project preparation 

b. Control and image point selection and coding 

c. Image point marking and cross-marking 

d. Control and image point mensuration 

e. Block adjustment 

f. Results analysis 

2. Digital Elevation Modeling 

Upon request, WED/PCEB shall provide the Contractor spot elevations, 

break line point elevations, and digital orthophotography with a spot 

accuracy of +/- 0.3 meter compiled from July 23, 1997 color infrared 

imagery sufficient to model the aquatic portions of the 1998 CIR imagery. 

3. Orthorectification 

The Contractor shall orthorectify the aquatic portions of the color 

infrared digital imagery (described in Section 2.1 above) to remove 
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displacement effects due to radial distortion and aircraft motion (roll, 

pitch, true heading, altitude, and variations in speed); and 

georeferencing the Roth-rectified digital imagery in a Universal 

Transverse Mercator projection based upon NAD83(91) datum in 

meter units. The orthorectified images shall have a pixel size of 

approximately 0.15 meters in ground units with a horizontal accuracy 

expressed with a nominal horizontal accuracy of +/- 0.5 meter or 

better. The orthorectified images shall be georeferenced, tiled and 

edgematched. Image tiling shall be performed so as to produce 

square images representing uniform ground dimensions. Image tiles 

shall be oriented so that true north (in the UTM projection) is at the 

top of the image. Image tile data files shall not exceed 300 megabytes 

in size. The preferred nominal file size for tiled images is 240 to 300 

megabytes with the exception of image tiles at the edge of the 

orthocoverage which may be of a smaller file size. The resultant 24 

bit color data files are to be provided to WED/PCEB on CD- ROM 

disks in uncompressed GeoTIFF format. The GeoTIFF files shall be 

accompanied with TIFF World Files (.tfw) compatible with the 

WED/PCEB GIS system containing georeferencing data for each 

image. 

B. Ground Control Point Location

The Contractor shall coordinate the location of any post-flight ground control point 

location with WED/PCEB. WED/PCEB has located (in addition to four premarked 

ground control points) several well-defined photo visible first to third order 

horizontal and/or vertical ground control points documented by the National 

Geodetic Survey and/or the Lincoln County Survey Department. The Contractor 

shall provide WED/PCEB with the location, description, and documentation of any 

additional ground control points used for orthorectification described in Sections 

2.2.A and 2.2.B. 

3.1 DIGITAL FILE NAMING CONVENTION

All digital files shall be provided to WED/PCEB using the following file naming 

convention: 

1. Orthotile image names shall reflect: 

a. column number beginning with the westernmost tile and proceeding east 

b. row number beginning with the southernmost tile and proceeding north. 

2. The system developed by the Contractor for the above naming conventions shall 

be supplied as part of the metadata delivered with the above products. 
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3.2 DOCUMENTATION OF IMAGE RECTIFICATION

The Contractor shall provide WED/PCEB with written documentation on the processing of 

the digital data, including description of all geometric corrections. The report shall be 

delivered with the rectified digital data. The report shall include information on: 

1. Procedures used to rectify the data; 

2. The source, location and description of control used for data rectification; 

3. Root mean square error for each file; 

4. The residuals for each control point; 

5. The resampling algorithm and transformation used; 

6. The number of times the data were resampled. 

3.3. QUALITY ASSESSMENT - IMAGE RECTIFICATION

It is the intent of WED/PCEB to incorporate information derived from the color infrared 

digital data into its geographic information system. The quality of the rectification shall be 

judged by: 

1. Registration to existing WED/PCEB geographic information system data; 

2. Root mean square error for each file; 

3. The residuals for each control point; 

4. The order of the rectification algorithm used; 

5. Positional accuracy of a feature's local geometry. 

4.1 BUSINESS ARRANGEMENTS

A. Schedule for Deliverables: 

The Contractor shall establish specifications described in Section 1.2 in consultation with 

WED/PCEB within 15 working days of the award of Contract. The Contractor shall arrange 

to take delivery of all CIR diapositives within ten working days of the establishment of the 

specifications described in Section 1.2 and provide WED/PCEB in writing with an accurate 

estimate of the total number of ortho-image tiles that are expected to be produced. 

1. The following products: 

a. Aerial triangulation results analysis described in Section 2.2.A.1; 

b. All orthorectified color infrared digital images in 24 bit color GeoTIFF 

format described in Section 2.2.A.3; 

c. All TIFF World Files for each GeoTIFF file above; 

d. All color infrared diapositives supplied by WED/PCEB; 

e. All documentation and metadata required above. 
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 2. Shall be delivered according to the following schedule: 

a. The initial delivery (Phase I) shall take place within 40 working days of 

the Contractor=s receipt of the color infrared diapositives and consist of the 

aerial triangulation results analysis described in Section 2.2.A.1; 

b. The second phase delivery (Phase II) shall take place within 50 working 

days of the delivery of Phase I and consist of the CIR ortho-tiles in 

GeoTIFF format along with their associated TIFF World files on CD-ROM 

disks as described in Section 2.2.A.3; 

c. All color infrared diapositives shall be returned to WED/PCEB upon 

completion of Section 4.1.A.1 above; 

d. All documentation and metadata required above shall be delivered upon 

completion of Section 4.1.A.1 above or before as required. 

B. Point of Delivery 

All deliverables shall be shipped to the following address: 

NOTE: Insert address for Deliverables here 

 

(Address in italics) 

C. Schedule of Payments 

NOTE: Insert Payment Schedule here

5.1 TECHNICAL EVALUATION CRITERIA

The Government will award a Purchase Order resulting from this Request for Quote to the 

responsible offeror whose quote will be the most advantageous to the Government, price 

and other factors considered. Offerors shall provide the following information to allow for 

technical evaluation of their quote: 

1. A brief description of their proposed technical approach to complete the 

requirements of the statement of work. Include a discussion of personnel, 

equipment and facilities available to perform the work. 

2. Provide up to three references for whom work of similar scope and size 

was performed within the past year. Include the company or agency name 

and addresses, project title and/or contract number, project officer, 

contracting officer and phone number and time frame in which work was 

performed. This information is used to assess past performance history.