r/EPA
United States
Environmental Protection
Agency
EPA 600/R-07/062 | August 2007 | www.epa.gov/ord
/
A Guide to Mapping Intertidal
Eelgrass and Nonvegetated
Habitats in Estuaries of the
Pacific Northwest USA
-------
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)TPacific 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 Arclnfo® 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
DIM 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-l 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 Zoster a 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 cost-
effective 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 um - 0.7 um). Infrared
(IR) panchromatic film has added sensitivity into the near-infrared (NIR) wavelengths (~ 0.25 um -
0.9 um). Natural or TC film is sensitive to visible light in blue band (0.4 um - 0.5 um), green band
(0.5 um - 0.6 um) and red band (0.6 um - 0.7 um) 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 um - 0.9 um) (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.
L3
20-
DC
10-
Vegetation
water
04
T
T
0.5 0.6 0.7 C.G
\Afevelen gtti(piFTi)
eccRS/MT
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
1:10,000
1:20,000
1:40,000
LENGTH / WIDTH (km)
2.3
4.6
9.2
AREA (km2)
5.29
21.16
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 S AV. An example of an on-line tide
prediction utility, 'WWW Tide and Current Predictor', can be found at:
http: //tb one. bi ol. sc. edu/ti de/site sel. 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 rule-
of-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 0.67m + 0.14m.
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 Arclnfo® macro language (AML) text for generating photo
center points and photo footprint polygons using Arclnfo® geographic information systems.
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Page 9 of 50
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Orientation of Flight Line
Length of Flight Line
Width of Study Area
B
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7100
5600
Flight Altitude (m) 3051
Ground Length of Photo 4600
Ground Width of Photo
Area of Photo (m!)
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Overlap Gain(%)
Number of Flight Lines
Number of Photos per Flight Line
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Width of Line Pair (m)
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Ground Pixel Size (m) 0.2401891
Nominal Image Resolution (m) 0.4803783
Smallest Possible Mapping Unit ( 0.7205674
"Megabytes in Image
"Megabytes in Project
Other Computational Factors
Project Center x
Project Center y
width factor
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399060
4658680
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length factor 368
photopoint inline separation
photopoint parallel separation 2760
Lower Left Pholocenter X ' 396300
Lower Left Photocenter Y
Number of photos E-W
Number of photos N-S
Map Legend
PhotoScale:
Overlap:
Sidelap:
Photopoint Inline Separation:
Pholopoint Parallel Separation:
Total Number of Photographs:
Number of FlightLines:
4657300
(m)
[ml
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Page 10 of 50
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PCEB Aerial Photography - Yaquina Bay, OR
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areas can be generated through the use ofPCEB_FlitePlannr.xls.
Page 11 of 50
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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 Photo interpretation
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 on-
screen, 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 (Kolbl 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 12 of 50
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0.42
0.21
0.16
0.13
0.12
0.11
0.10
0.09
0.08
0.06
0.05
0.85
0.42
0.32
0.25
0.23
0.21
0.20
0.18
0.17
0.13
0.10
1.02
0.51
0.38
0.30
0.28
0.25
0.23
0.22
0.20
0.15
0.12
2.03
1.02
0.76
0.61
0.55
0.51
0.47
0.44
0.41
0.30
0.24
3.39
1.69
1.27
1.02
0.92
0.85
0.78
0.73
0.68
0.51
0.41
Pixel Ground Resolution (m) vs. Scanning Resolution
Photo Scale 5000 10000 12000 24000 40000
Scanning Resolution
dpi microns
300 85
600 42
800 32
1000 25
1100 23
1200 21
1300 20
1400 18
1500 17
2000 13
2500 10
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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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)
Page 14 of 50
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35.00%
30.00%
Average In-Situ Spectral Response of Z. marina and Ulva spp.
0.40 0.45 0.49 0.53 0.57 0.61 0.65 0.69 0.73 0.77 0.81 0.85 0.88 0.92
Wavelenth (jim)
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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Figure 4. Aerial photomosaic detail of Yaquina Bay estuary.
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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 (((il - i2)/(il + 12 + (0.5)) x (1 + 0.5)) + 1) / 2 > X and inregion (rl) then 13 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 il and i2 are the NIR and red bands, respectively, i3 represents the
band to which the formula is applied and rl 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.
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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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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 Arclnfo® workstation GIS software.
Page 19 of 50
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The isocluster image was converted to an Arclnfo® grid with cell values representing the
isoclusters. A new binary (0 or 1) grid was created for each value using conditional statements in
Arclnfo® 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 eel grass 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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CIR Aerial Photo Mosaic
Edited Grids are Compiled
into the Hybrid Classification
Unsupervised Classification
Classes Split into Binary Grids
Figure 7. Hybrid classification work flowchart.
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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:
"An 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 22 of 50
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Class
Di
rifled
ita
Land
Cover
A
B
C
D
Reference Data
Land
Cover
A
B
C
D
Column
Total
A
60
4
1
5
70
B
7
75
21
13
116
C
2
11
80
0
93
Producer's Accuracy
60/70 = 85.7%
75/116= 64.7%
80/93 = 86.0%
83/121 = 68.6%
D
15
9
14
83
121
Row
Total
84
99
116
101
400
Land
Cover
A
B
C
D
Overall Accuracy
(60+75+80+83)7400 =
User's Accuracy
60/84= 71.4%
75/99 = 75.8%
80/116= 69.0%
83/101 = 82.2%
74.5%
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 Arclnfo® 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 Arc View® v3.3 (Figure 8), and the Spatial Analyst® Kappa
Page 23 of 50
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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).
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Figure 8. Seagrass classification grid and validation point cover.
Page 24 of 50
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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 Arclnfo® 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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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
Geographies, 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/~iosh/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. Cebrian 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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Jenness, J. and J. J. Wynne. 2004. Kappa analysis (kappa_stats.avx) extension for Arc View 3.x.
Jenness Enterprises. Available at: http://www.jennessent.com/arcview/kappa stats.htm.
Kolbl, 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. ERMapper, 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. andR.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 the!999 ASPRS Annual Conference, pp 1173-1178. American Society of
Photogrammetry and Remote Sensing, Bethesda, MD.
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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: //ccr s. nrcan. gc. ca/re source/tutor/fundam/pdf/fundamental s_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: //tb one. bi ol. sc. edu/ti de/site sel. html
http://www.wxtide32.com/
GeoTiff Links
http://www.remotesensing.org/geotiff/geotiff.html
Page 28 of 50
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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
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Yaquina
Alsea
Alsea
Siletz
Salmon
Salmon
Nestucca
Tillamook
Tillamook
Coos
Umpqua
Suislaw
Cocquille
1997
1997
1998
1999
1999
1999
2000
2000
2000
2000
2000
2001
2001
2001
2002
2002
2002
2002
2003
2003
2003
2004
2005
2006
1999
2004
1999
2000
2004
2004
2004
2005
2005
2005
2005
2005
7/23
7/23
8/10
7/15
9/10
10/24
6/17
6/17
6/20
8/2
10/24
5/9
7/25
10/15
1/11
8/11
9/23
5/15
5/19
8/1
10/21
4/9
7/21
5/16
9/10
4/9
9/10
6/20
4/9
4/9
4/9
6/9
5/26
7/24
7/24
7/26
7200 CIR
7200 RGB
6000 CIR
7200 CIR
7200 CIR
7200 CIR
14400 CIR
14400 RGB
7200 CIR
7200 CIR
3600 CIR
7200 CIR
7200 CIR
7200 CIR
7200 CIR
7200 CIR
7200 CIR
7200 CIR
10000 CIR
10000 CIR
7200 CIR
10000 CIR
20000 CIR
20000 CIR
7200 CIR
10000 CIR
7200 CIR
7200 CIR/RGB
10000 CIR
10000 CIR
10000 CIR
20000 CIR
20000 CIR
20000 CIR
20000 CIR
20000 CIR
Digitized
Photogrammetric/Diapositive
Photogrammetric/Diapositive
Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
No
No
Non-Photogrammetric/Diapositive
No
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
No
No
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
No
No
Non-Photogrammetric/Diapositive
Photogrammetric/Film
Photogrammetric/Film
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Non-Photogrammetric/Diapositive
Photogrammetric/Film
Photogrammetric/Film
Photogrammetric/Film
Photogrammetric/Film
Photogrammetric/Film
OrthoRectifled
SoftCopy
SoftCopy
SoftCopy
Desktop
No
No
Desktop
No
Desktop
Desktop
No
Desktop
No
No
Desktop
No
Desktop
Desktop
Desktop
No
No
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
Desktop
No
No
Ground Pixel
0.20m
0.20m
0.15m
0.20m
0.20m
0.20m
0.20m
0.20m
0.20m
0.20m
0.20m
0.20m
0.25m
0.25m
0.25m
0.20m
0.25m
0.20m
0.20m
0.25m
0.25m
0.25m
0.25m
0.25m
0.25m
Classified
Yes
No
Yes
Yes
No
No
Yes
No
No
No
No
Partial
Yes
No
No
Yes
Yes
No
No
Yes
Yes
Yes
No
Yes
Yes
Page 29 of 50
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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
YB32
SEC7
8927
9021
9026
9029
90103
9136
5161
8932
9019
9024
9053
9122
AZ9021
AZ9026
AZ9029
COR90103
COR9136
AZ9024
COR9025
AZ9053
AZ9122
VENTS
Mean
1O
1O
2C1
2C1
2C1
2C1
2C1
2C1
2C1
2C1
2C1
2C1
2C1
2C1
2C1
3O
3O
3O
3O
3O
3O
3O
3O
3O
1O
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
LCGC
NOAA
Yes
No
No
No
No
No
No
No
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
High
Low
Low
None
None
Low
Low
Low
low
Low
Low
None
None
None
None
None
None
None
None
Low
None
None
None
None
High
High
High
Med
Poor
Poor
High
Med
Med
High
Med
Med
Med
Med
Med
Med
Low
Poor
Poor
Poor
Med
Poor
Poor
Med
Med
High
Recovered
Description
Description
Description
Description
Description
Description
Description
Recovered
Description
Description
Description
Description
Description
Description
Description
Description
Description
Description
Description
Description
Description
Description
Description
Recovered
0.10
0.10
0.20
N/A
N/A
0.10
0.35
0.20
0.10
0.10
0.35
N/A
N/A
N/A
1.00
0.40
N/A
N/A
N/A
0.20
N/A
N/A
N/A
N/A
0.10
0.30
0.45
1.66
N/A
N/A
0.51
0.50
0.50
0.30
0.30
0.50
N/A
N/A
N/A
1.30
1.15
N/A
N/A
N/A
0.40
N/A
N/A
N/A
N/A
0.30
0.20
0.28
0.93
N/A
N/A
0.31
0.43
0.35
0.20
0.20
0.43
N/A
N/A
N/A
1.15
0.78
N/A
N/A
N/A
0.30
N/A
N/A
N/A
N/A
0.20
Mean no preniark
Standard Deviation
Standard Deviation
no preniark
0.20
0.28
0.93
N/A
N/A
0.31
0.43
0.35
0.20
0.20
0.43
N/A
N/A
N/A
1.15
0.78
N/A
N/A
N/A
0.30
N/A
N/A
N/A
N/A
0.20
0.44
0.49
0.31
0.32
0.10
0.45
1.66
N/A
N/A
0.51
0.50
0.50
0.10
0.30
0.50
N/A
N/A
N/A
1.30
1.15
N/A
N/A
N/A
0.40
N/A
N/A
N/A
N/A
0.10
0.58
0.67
0.49
0.48
Table III-l. 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.
Page 30 of 50
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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 eel grass 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 eel grass
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 sub-
meter 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 32 of 50
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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.
Aerial Photomapping Ground Survey
Estuary:
Low Tide Level (ft):
Crew Initials:
Way
Point
No.
Time
is
£z
Quadl
Zm
GM
Zj
Date:
Time:
Vessel:
Quad2
Zm
GM
Zj
Quad 3
Zm
GM
zj
Quad 4
Zm
GM
Zj
GPS Position
Northing
Easting
Notes:
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).
Page 33 of 50
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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 35 of 50
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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 Arc View 3.x.
Jenness Enterprises. Available at: http://www.jennessent.com/arcview/kappa_stats.htm
Page 36 of 50
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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 (NHEERL-
WED/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 37 of 50
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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 west-
east 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: "equal" 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
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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.I) and exposure number
(e.g, -1 to -5, west to east - see Sector 1.3.A.I) 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
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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 pre-
approved 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. Offerer 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.I.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.
PCEB Aerial Photography - Yaquina Bay, OR
70723456789 10 Kilometers
PhotoScale: 1 : 20000
Overlap: 40%
Sidelap: 40%
Photopoint Inline Separation: 2760 m
Photopoint Parallel Separation: 2760 m
Total Number of Photographs: 10
Number of FlightLines: 2
Max Photos per FlightLine: 5
FlightMap Projection
Projection: UTM
Zone: 10
Datum: NAD83
Units: meters
LL Photocenter 417200E 4937875N
UR Photocenter 431000E 4940635N
Photo Center
Photo Edge
(D
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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
Date
4/29/2006
4/30/2006
5/1/2006
5/15/2006
5/16/2006
Time
900
915
930
945
900
915
930
945
1000
1015
1030
900
915
930
945
1000
1015
1030
1045
1100
900
915
930
945
1000
900
915
930
945
1000
1015
1030
1045
Day
Sun
-1.76
-1.71
-1.6
-1.43
-1.19
-0.91
-0.58
Mon
-0.99
-1.15
-1.24
-1.27
-1.23
-1.14
-0.99
-0.79
-0.54
-1.5
-1.37
-1.18
-0.94
-0.66
Tue
-1.51
-1.56
-1.56
-1.49
-1.36
-1.17
-0.94
-0.66
Wed
Thu
Fri
Sat
-1.65
-1.4
-1.09
-0.73
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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 (NHEERL-
WED/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; Arc View® 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 Arc View® (all versions). If the image file
name has a 3-character extension (e.g., imagel.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., imagel.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.I;
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.I;
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.I.A.I 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 offerer whose quote will be the most advantageous to the Government, price
and other factors considered. Offerers 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.
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SCIENCE
&EPA
United States
Environmental Protection
Agency
Office of Research and Development (81 OR)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA
PERMIT NO. G-35
Recycled/Recyclable Printed on paper that contains a minimum of
50% postconsumer fiber content processed chlorine free
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