Adam G. Zitello 

Laurie J. Bauer 

Timothy A. Battista 

Peter W. Mueller 

Matthew S. Kendall 

Mark E. Monaco 

NOAA CCMA Biogeography Branch 

NOAA TECHNICAL MEMORANDUM NOS NCCOS 96 U.S. DEPARTMENT OF COMMERCE

NAT OI NAL OCEANIC AND ATMOSPHERIC ADMINISTRAT OI N

Project Report Produced by NOAA’s Biogeography Branch in Cooperation with U.S. National Park Service 

Shallow-Water Benthic Habitats 

of St. John, U.S. Virgin Islands 
Mention of trade names or commercial products does not constitute endorsement or recommendation for their 

use by the United States Government. 

Citation: 

Zitello, A.G., L.J. Bauer, T.A. Battista, P.W. Mueller, M.S. Kendall and M.E. Monaco. 2009. Shallow-Water Benthic Habitats of St. John, U.S. Virgin Islands. NOAA Technical Memorandum NOS NCCOS 96. Silver Spring, 

MD. 53 pp. 
 

Shallow-Water Benthic Habitats of St. John, U.S. Virgin Islands
 

Biogeography Branch 

Center for Coastal Monitoring and Assessment (CCMA) 

NOAA/NOS/NCCOS 

1305 East-West Highway, SSMC4, N/SCI-1 

Silver Spring, MD 20910 

NOAA Technical Memorandum NOS NCCOS 96 

August 2009 

Authors: 

Adam G. Zitello 

Laurie J. Bauer

 Timothy A. Battista 

Peter W. Mueller 

Matthew S. Kendall 

Mark E. Monaco 

U.S. DEPARTMENT OF COMMERCE

NAT OI NAL OCEANIC AND ATMOSPHERIC ADMINISTRAT OI N

United States Department National Oceanic and National Ocean Service 

of Commerce Atmospheric Administration 

Gary Locke Jane Lubchenco John H. Dunnigan 

Secretary Administrator Assistant Administrator 
This page intentionally left blank. 
ABOUT THIS DOCUMENT
 

This report describes the creation and assessment of benthic habitat maps for the nearshore waters of St. John, 

U.S. Virgin Islands. The objective of this effort, conducted by NOAA’s Center for Coastal Monitoring and Assessment - Biogeography Branch in partnership with the U.S. National Park Service (NPS), was to provide spatiallyexplicit information on the habitat types, biological cover and live coral cover of St. John’s coral reef ecosystem. 

These fine-scale habitat maps, generated by visual interpretion of satellite and airborne imagery, represent a significant improvement from NOAA’s 2001 digital maps (Kendall et al.) of the U.S. Caribbean due to an expanded 

habitat classification scheme, smaller minimum mapping unit, and more recent imagery. 

This report consists of four primary components: 1) a description of the benthic habitat classification scheme, 2) 

description of the techniques used for map creation, 3) an assessment of the map accuracy, and 4) summary of 

the findings. The maps will be used by NPS and other local partners for planning research and monitoring activities, and will support the management and conservation of the National Parks, Monuments, and other coastal 

areas around St. John. 

This work is part of NOAA Coral Reef Conservation Program’s national coral reef ecosystem integrated mapping 

and monitoring studies throughout the U.S. Caribbean (Monaco et al. 2001). 

For more information on this effort please visit: 

http://ccma.nos.noaa.gov/ecosystems/coralreef/benthic_usvi.html 

Direct questions or comments to: 

Mark E. Monaco 

Branch Chief 

NOAA/NOS/NCCOS/CCMA/Biogeography Branch 

1305 East West Highway 

SSMC4, N/SCI-1 

Silver Spring, MD 20910 

Phone: (301) 713-3028 x160 

Email: Mark.Monaco@noaa.gov 

Or 

Timothy A. Battista 

Project Manager 

NOAA/NOS/NCCOS/CCMA/Biogeography Branch 

1305 East West Highway 

SSMC4, N/SCI-1 

Silver Spring, MD 20910 

Phone: (301) 713-3028 x171 

Email: Tim.Battista@noaa.gov 

U.S. DEPARTMENT OF COMMERCE

NAT OI NAL OCEANIC AND ATMOSPHERIC ADMINISTRAT OI N

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All photographs provided in this document were taken by NOAA/NOS/NCCOS/Center for Coastal Monitoring 

and Assessment Biogeography Branch in St. John, USVI. 
page 

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EXECUTIVE SUMMARY 

Coral reef ecosystems of the Virgin Islands 

Coral Reef National Monument, Virgin Islands 

National Park and the surrounding waters of 

St. John, U.S. Virgin Islands are a precious 

natural resource worthy of special protection 

and conservation. The mosaic of habitats 

including coral reefs, seagrasses and mangroves, are home to a diversity of marine organisms. These benthic habitats and their associated inhabitants provide many important 

ecosystem services to the community of St. 

John, such as fishing, tourism and shoreline 

protection. However, coral reef ecosystems 

throughout the U.S. Caribbean are under increasing pressure from environmental and anthropogenic stressors that threaten to destroy 

the natural heritage of these marine habitats. 

Mapping of benthic habitats is an integral component of any effective ecosystem-based management approach. 

Through the implementation of a multi-year interagency agreement, NOAA’s Center for Coastal Monitoring and 

Assessment - Biogeography Branch and the U.S. National Park Service (NPS) have completed benthic habitat 

mapping, field validation and accuracy assessment of maps for the nearshore marine environment of St. John. 

This work is an expansion of ongoing mapping and monitoring efforts conducted by NOAA and NPS in the U.S. 

Caribbean and replaces previous NOAA maps generated by Kendall et al. (2001) for the waters around St. 

John. The use of standardized protocols enables the condition of the coral reef ecosystems around St. John to 

be evaluated in context to the rest of the Virgin Island Territories and other U.S. coral ecosystems. The products 

from this effort provide an accurate assessment of the abundance and distribution of marine habitats surrounding 

St. John to support more effective management and conservation of ocean resources within the National Park 

system. 

This report documents the entire process of benthic habitat mapping in St. John. Chapter 1 provides a description of the benthic habitat classification scheme used to categorize the different habitats existing in the nearshore 

environment. Chapter 2 describes the steps required to create a benthic habitat map from visual interpretation 

of remotely sensed imagery. Chapter 3 details the process of accuracy assessment and reports on the thematic 

accuracy of the final maps. Finally, Chapter 4 is a summary of the basic map content and compares the new 

maps to a previous NOAA effort. 

Benthic habitat maps of the nearshore marine environment of St. John, U.S. Virgin Islands were created by 

visual interpretation of remotely sensed imagery. Overhead imagery, including color orthophotography and IKONOS satellite imagery, proved to be an excellent source from which to visually interpret the location, extent and 

attributes of marine habitats. NOAA scientists were able to accurately and reliably delineate the boundaries of 

features on digital imagery using a Geographic Information System (GIS) and fi eld investigations. 

The St. John habitat classification scheme defined benthic communities on the basis of four primary coral reef 

ecosystem attributes: 1) broad geographic zone, 2) geomorphological structure type, 3) dominant biological 

cover, and 4) degree of live coral cover. Every feature in the benthic habitat map was assigned a designation at 

each level of the scheme. The ability to apply any component of this scheme was dependent on being able to 

identify and delineate a given feature in remotely sensed imagery. 

An area of 53 km2 was described by polygons corresponding to the categories described by the habitat classification scheme. Unconsolidated Sediment and Coral Reef and Hardbottom each accounted for 27 km2

 of major 

structure type. Sand was the most common detailed structure type, accounting for 43% of the total mapped 

Coral reef ecosystems provide a variety of ecological and economic services 

to St. John, U.S. Virgin Islands. 

page 

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page 

iv 

area. Pavement was the second most dominant 

structure type overall and was the most common 

reef type, covering 16% of the mapped area. Another common structure type was Aggregate Reef, 

which contributed to 7% of the total area. Although 

ecologically significant, patch reefs, in the form 

of Individual and Aggregated Patch Reefs, only 

comprised 3% of all the nearshore habitat mapped 

around St. John. 

The overwhelmingly dominant major biological 

cover was Algae, which accounted for 74% of the 

53 km2

 mapped area. Although live coral colonies 

exist throughout the St. John seascape and are a 

key component of reef ecosystems, the total area 

of features dominated by live coral cover was only 

0.81 km2 or 1.5% of the mapped area. 

An additional assessment of live coral cover, regardless of biological dominance, suggested that almost all of 

the total mapped area was comprised of less than 50% coral cover. There were 9 km2

 exhibiting a percent coral 

cover of 10% to <50%. These areas accounted for 17% of the study area, while 83% had less than 10% coral 

cover. Furthermore, percent coral cover did not exceed 50% within any polygon delineated in the study. It was 

observed that some areas of St. John were comprised of greater than 50% coral cover, but these areas were 

smaller than the minimum mapping unit of 1,000 m2

. 

Thematic accuracy was characterized for major and detailed geomorphological structure, major and detailed 

biological cover, and percent coral cover. The accuracy assessment revealed successful overall map accuracies 

of over 90% for major structure and cover classes, and over 80% for detailed structure and cover classes. 

The 86% accuracy achieved for detailed structure in NOAA’s new St. John benthic habitat maps were similar to 

that of other recent NOAA benthic habitat maps in the Florida Keys (86%), Palau (90%), and the Main Hawaiian 

Islands (90%). This comparison demonstrates that the needs of coral reef managers and scientists for a dominance based classification scheme were met, with no loss in thematic map accuracy. As a result, these digital 

map products can be used with confidence by scientists and resource managers for a multitude of different applications. 

A multitude of fish species school near the structure of a coral reef. 
TABLE OF CONTENTS 

INTRODUCTION ..................................................................................................................................................1
 

CHAPTER 1: BENTHIC HABITAT CLASSIFICATION SCHEME .......................................................................3
 

1.1. COMPARISON TO PREVIOUS NOAA HABITAT CLASSIFICATION SCHEMES .......................................3
 

1.2. GEOGRAPHIC ZONES.................................................................................................................................4
 

1.3. GEOMORPHOLOGICAL STRUCTURE TYPES ..........................................................................................9
 

1.4. BIOLOGICAL COVER CLASSES ..............................................................................................................15
 

1.5. LIVE CORAL COVER CLASSES ...............................................................................................................20
 

LITERATURE CITED .........................................................................................................................................22
 

CHAPTER 2: BENTHIC HABITAT MAP CREATION ........................................................................................23
 

2.1. GENERAL MAPPING APPROACH ............................................................................................................23
 

2.2. REMOTELY SENSED IMAGERY................................................................................................................24
 

2.3. HABITAT BOUNDARY DELINEATION AND ATTRIBUTION .....................................................................26
 

2.4. GROUND VALIDATION ..............................................................................................................................27
 

2.5. EXPERT REVIEW.......................................................................................................................................29
 

2.6. GIS QUALITY CONTROL...........................................................................................................................31
 

LITERATURE CITED .........................................................................................................................................32
 

CHAPTER 3: CLASSIFICATION ACCURACY ASSESSMENT........................................................................33
 

3.1. FIELD DATA COLLECTION .......................................................................................................................33
 

3.2. EVALUATION OF ASSESSMENT DATA....................................................................................................34
 

3.3. ANALYSIS OF THEMATIC ACCURACY....................................................................................................36
 

3.4. ACCURACY ASSESSMENT RESULTS AND DISCUSSION .....................................................................37
 

3.5. CONCLUSIONS..........................................................................................................................................42
 

LITERATURE CITED .........................................................................................................................................43
 

CHAPTER 4: CONCLUSION.............................................................................................................................45 

4.1. MAP SUMMARY STATISTICS ....................................................................................................................45
 

4.2. COMPARISON TO PREVIOUS NOAA HABITAT MAPS OF ST. JOHN ....................................................47
 

4.3. PROJECT DELIVERABLES.......................................................................................................................50
 

4.4. FUTURE U.S. VIRGIN ISLANDS MAPPING ACTIVITIES .........................................................................50
 

LITERATURE CITED .........................................................................................................................................52
 

ACKNOWLEDGEMENTS ..................................................................................................................................53
 

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List of Tables 

page 

vi 

Table 2.1. Acquisition dates of imagery used for creation of the benthic habitat maps.. ...............................24
 

Table 2.2. Expert review workshop participants and their affiliations. ...........................................................29
 

Table 3.1. Error matrix for major geomorphological structure........................................................................37
 

Table 3.2. Error matrix for major geomorphological structure, using individual cell probabilities. .................38
 

Table 3.3. Error matrix for detailed geomorphological structure....................................................................38
 

Table 3.4. Error matrix for detailed geomorphological structure, using individual cell probabilities...............39
 

Table 3.5. Error matrix for major biological cover. .........................................................................................40
 

Table 3.6. Error matrix for major biological cover, using individual cell probabilities. ....................................40
 

Table 3.7. Error matrix for detailed biological cover. ......................................................................................41
 

Table 3.8. Error matrix for detailed biological cover, using individual cell probabilities. ................................41
 

Table 3.9. Error matrix for major geomorphological structure and percent coral...........................................42
 

Table 4.1. Final deliverable items of NOAA’s St. John benthic habitat mapping effort. .................................45
 

Table 4.2. Area summary of major geomorphological structure classes and the subsets of 

detailed structure classes. ............................................................................................................46
 

Table 4.3. Summary of areas for each biological cover and respective percent cover modifier
 

mapped in St. John.......................................................................................................................47
 

Table 4.4. Area summary of percent coral cover for St. John habitats..........................................................47
 

Table 4.5. Comparison of basic map characteristics between a previous NOAA effort (2001) and
 

the current maps of St. John (2009). ............................................................................................48
 
List of Figures 

Figure 1.1. The classification scheme defines benthic habitats with four primary attributes 

(described by separate boxes) and several hierarchical levels of classifi cation therein. .............3
 

Figure 1.2. The crown of a Christmas Tree Worm (Spirobranchus giganteus) protrudes from a 

colony of Great Star Coral (Montastraea cavernosa) on the south shore of St. John. ................4
 

Figure 1.3. Schematic of each attribute’s position in the UniqueID code of the classifi cation scheme. ........4
 

Figure 1.4. Cross-section of zone types where a barrier reef is present. Reef is separated from the
 

shore by a relatively wide, deep lagoon. .....................................................................................5
 

Figure 1.5. Cross-section of zone types where a fringing reef is present. Reef platform is continuous
 

with the shore. .............................................................................................................................5
 

Figure 1.6. Cross-section of zone types where no emergent reef crest is present........................................5
 

Figure 1.7. Depiction of shoreline delineations on unconsolidated and rocky coastlines. .............................6
 

Figure 1.8. Depictions of the Salt Pond zone just inshore of Europa Bay and Francis Bay. .........................6
 

Figure 1.9. Representation of two different types of Shoreline Intertidal zones. A low energy mangrove
 

shoreline and a high energy rocky shoreline on the east end of St. John. ..................................7
 

Figure 1.10. View of the Lagoon zone on orthophotography at Mary Creek. An example of a
 

seagrass bed located in a shallow Lagoon. ................................................................................7
 

Figure 1.11. Depictions of the Reef Flat zone in Newfound Bay from the shoreline and from 

 orthophotography. ........................................................................................................................8
 

Figure 1.12. A series of orthophotographs illustrating the transition from Reef Crest to Fore Reef

 to Bank/Shelf zones at Lagoon Point. .........................................................................................8
 

Figure 1.13. View of the Dredged zone on orthophotography at the shipping dock of Turner Bay. .................9
 

Figure 1.14. Depictions of Rock Outcrop structure on the west side of the mouth of Hawksnest Bay. ...........9
 

Figure 1.15. Depictions of Boulder structure on the west side of Ram Head. ...............................................10
 

Figure 1.16. Depictions of Aggregate Reef structure in Privateer Bay. .........................................................10
 

Figure 1.17. Comparison of patch reef delineations south of Johnsons Reef. .............................................. 11
 

Figure 1.18. Depictions of Spur and Groove structure on the west side of Reef Bay. ................................... 11
 

Figure 1.19. Several views of Pavement structure in St. John. .....................................................................12
 

Figure 1.20. Depictions of Pavement with Sand Channels off Turner Point in Coral Bay. .............................12
 

Figure 1.21. Depictions of inshore Reef Rubble structure behind a reef crest on St. John’s East End. ........13
 

Figure 1.22. Typical rhodolith bed off the south shore of St. John characterized by growth of fleshy
 

macroalgae and sponges. .........................................................................................................13
 

Figure 1.23. Depictions of Sand as a structure on the northeast shore of St. John. .....................................13
 

Figure 1.24. Depictions of Mud as a structure in the back of Mary Creek. ....................................................14
 

Figure 1.25. Depictions of Sand with Scattered Coral and Rock structure near East End Bay. ....................14
 

Figure 1.26. Representation of Artificial structure at the docks in Cruz Bay. .................................................15
 

Figure 1.27. Guidance chart to understand visual interpreter’s estimation of patchiness in assigning

 percent cover. ............................................................................................................................15
 

Figure 1.28. Depictions of Algae dominated habitats. Underwater pictures illustrate the different algal
 

covers on soft and hardbottoms. ...............................................................................................16
 

Figure 1.29. Extensive Seagrass beds, such as that east of Leinster Point, cover softbottoms around
 

the island. Turtle Grass (Thalassia testudinum) and Manatee Grass (Syringodium filiforme)...16
 

Figure 1.30. In some instances, Live Coral may be the dominant biological cover on St. John’s
 

habitats. Underwater pictures display both octocoral and scleractinian coral homogenous

 environments. ............................................................................................................................16
 

Figure 1.31. Red mangroves (Rhizophora mangle) cover much of St. John’s sheltered coastlines,
 

while extensive mangrove complexes develop in low-lying areas inland from the shoreline. ...17
 

Figure 1.32. Underwater photograph of a Coralline Algae dominated environment......................................17
 

Figure 1.33. Depictions of benthic habitats with No Cover. ...........................................................................18
 

Figure 1.34. Representation of the three percent major cover modifiers (10% - <50%, 50% - <90%,
 

90% - 100%) using a seagrass bed in Fish Bay as an example. ..............................................19
 

Figure 1.35. Both scleractinian and octocorals are considered when defining live coral cover. Typical
 

corals of St. John include the scleractinian boulder coral (Montastraea annularis) 

and several octocorals including sea fans (Gorgonia sp.).. .......................................................20
 

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Figure 1.36. An example of the presence of live coral in the 0% - 10% cover range. ...................................21
 

Figure 1.37. An illustration of live coral, primarily gorgonian, in the 10% - 50% cover range........................21
 

Figure 2.1. Blue Chromis (Chromis cyanea) aggregate over a mixed hardbottom of hydrocorals,
 

octocorals and scleractinian corals............................................................................................23
 

Figure 2.2. U.S. National Park Service vessel Acropora was used to conduct field work in support of
 

habitat map development. .........................................................................................................23
 

Figure 2.3. Geodetic marker from NOAA’s National Geodetic Survey that was used as a ground

 control point. ..............................................................................................................................25
 

Figure 2.4. Oblique view of U.S. Geological Survey’s Digital Elevation Model used to correct terrain
 

displacement during orthorectifi cation process. ........................................................................25
 

Figure 2.5. Many individual patch reefs were smaller than the minimum mapping unit and resulted in
 

aggregation with other habitat classes. .....................................................................................26
 

Figure 2.6. NOAA’s Habitat Digitizer Extension was used to attribute map polygons with all
 

components of the habitat classifi cation scheme. .....................................................................27
 

Figure 2.7. Red dots depict the location of the 444 ground validation sites visited during the mapping
 

process to determine habitat information. .................................................................................28
 

Figure 2.8. Operation of field equipment, including the underwater video camera and GPS receivers. .....28
 

Figure 2.9. Presence of fringing mangroves were often noted from the survey boat on fi eld maps. ...........29
 

Figure 2.10. Mangroves are a common biological cover along the protected coastlines of St. John. ...........30
 

Figure 2.11. A Southern Stingray (Dasyatis americana) moves across a sand and algae bottom 

in St. John..................................................................................................................................31
 

Figure 3.1. Picture of the field crew deploying drop camera and camera approaching bottom...................33
 

Figure 3.2. Red dots depict the location of the 481 sites visited to obtain habitat information for 

assessment of thematic map accuracy. .....................................................................................34
 

Figure 3.3. Example of case where survey track line crossed more than one habitat type/polygon. ..........35
 

Figure 3.4. Example of case where video survey was conducted over an area of continuous seagrass,
 

but examination of the imagery revealed that patchiness of the polygon was 50% - <90%......35
 

Figure 3.5. Sand with scattered coral and rock was occasionally confused with other geomorphological
 

structure types composed of varying combinations of hard and softbottoms............................39
 

Figure 3.6. Juvenile Bluehead Wrasses (Thalassoma bifasciatum) gather around a colony of
 

Montastraea sp..........................................................................................................................42
 

Figure 4.1. NOAA diver characterizes seagrass habitat during a monitoring mission in St. John. ..............45
 

Figure 4.2. Chart illustrating the percent cover of each detailed geomorphological structure type for
 

the entire St. John mapping area. Sand being the most common structure type and 

Pavement the most common hardbottom type..........................................................................46
 

Figure 4.3. Chart depicting the prevalence (~ 75%) of Algae as the dominant biological cover
 

type in the mapped area of St. John..........................................................................................47
 

Figure 4.4. Comparison of 2001 and 2009 NOAA habitat boundaries to illustrate the infl uence of
 

minimum mapping unit on the delineation of patch reefs outside of Reef Bay. .........................48
 

Figure 4.5. Imagery time-series of Rendezvous Bay depicting growth of seagrass beds between
 

1999 and 2007. .........................................................................................................................49
 

Figure 4.6. A large colony of boulder coral (Montastraea annularis) may have varying percentages
 

of live coral cover. ......................................................................................................................49
 

Figure 4.7. Seafloor mapping of Buck Island Reef National Monument and Salt River Bay National 

Historical Park and Ecological Reserve and adjacent areas of St. Croix, USVI. Previously 

collected acoustic data is displayed with management boundaries and proposed

 mapping areas. ..........................................................................................................................51
 
INTRODUCTION

NOAA’s Center for Coastal Monitoring and Assessment - Biogeography Branch has developed analytical protocols used for mapping benthic habitats throughout all U.S. jurisdictions, States, and Territories, including the U.S. 

Caribbean. NOAA, in partnership with the U.S. National Park Service (NPS), has generated spatially resolved 

benthic habitat mapping products of the coral reef ecosystems surrounding St. John, U.S. Virgin Islands. The 

synthesis of existing geospatial data and collection of new data provides the most contemporary compilation 

of remotely sensed and in situ data within the network of NPS-managed marine ocean parks. These products 

provide a fine-scale assessment of the status, abundance, and distribution of marine habitats of St. John. This 

effort equips NPS with increased technical capacity for ocean exploration, management, and stewardship. Potential applications include use as a spatial framework for sampling design, improved assessment of human-use 

impacts, and other marine spatial planning activities. 

Introduction

0 2 4 

Kilometers 

VI Coral Reef National Monument 

Virgin Islands National Park 

Shallow-Water Study Area 

Deep-Shelf Study Area 

Overview of St. John, U.S. Virgin Islands with U.S. National Park Service management boundaries and mapping effort 

extents. 

As part of President Bush’s U.S. Ocean Action Plan, the NPS developed an Ocean Park Stewardship Action Plan 

to focus organizational and scientific capacity on conserving marine, estuarine, and Great lakes resources. The 

Plan strives to prevent the loss of productive fisheries, habitats, and wildlife, and continue to conserve ocean 

resources and recreational activities for park visitors. NPS manages and protects more than 250,000 acres of 

coral reef in ten National Park units, two of which are located in St. John, USVI. The Virgin Islands Coral Reef 

National Monument includes 12,708 acres of submerged lands within 3 miles off the coast of St. John. These 

waters contain some of the most biologically rich and economically important coral ecosystems in the U.S. Caribbean, supporting a diverse and complex system of coral reefs, shoreline mangrove forests, and seagrass 

beds. Additionally, the Virgin Islands National Park includes 5,650 acres of submerged federal lands to protect 

and conserve a rich, but fragile coral reef seascape. As part of the ocean stewardship effort, the Ocean Park 

Stewardship Action Plan calls to improve scientific capacity in order to better understand ocean ecosystems and 

human influence. This includes providing improved products and characterizations to better inform resource 

managers of current resource inventories and benthic habitat distributions. 

page 

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Introduction

 

The NOAA/NPS joint study to map the benthic habitats of St. John has resulted in a suite of products. The project 

deliverables include: 

• Primary data sources, including satellite and airborne imagery, ground validation field data, and 

accuracy assessment field data, 

• Derived datasets, including GIS files of benthic habitats and shoreline, 

• Classification manual, 

• Description of the specific methods used to create the habitat maps, and 

• Assessment of the thematic accuracy of the maps. 

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CHAPTER 1: BENTHIC HABITAT CLASSIFICATION SCHEME 

A habitat classification scheme is a structured system of arranging habitat types into defined groups or classes 

based on ecological characteristics. The initial task in any mapping effort is to clearly identify these classes and 

describe their attributes. The scheme is used to guide the delineation and definition of habitats throughout the 

map creation process. Furthermore, it is critical for map users to have an understanding of how a classification 

system is structured and the definitions of each class. This knowledge allows users to determine the appropriate 

uses and limitations of a map. 

The St. John habitat classification scheme defines benthic communities on the basis of four primary coral reef 

ecosystem attributes: 1) broad 

geographic zone, 2) geomorphological structure type, 3) 

dominant biological cover, and 

4) degree of live coral cover. 

A hierarchical structure of describing features at varying levels of detail was used so that 

numerous detailed habitats are 

encompassed by more broadly 

defined habitat classes. This 

hierarchy provides users with 

the ability to expand and collapse the detail of the habitat 

map to suit their needs. Every 

feature in the benthic habitat 

map is assigned a designation 

from each level of the scheme 

(Figure 1.1). The ability to apply 

any component of this scheme 

is dependent on being able to 

identify and delineate a given 

feature in remotely sensed imagery and assess the accuracy 

of the resulting benthic habitat 

map. 

1.1. COMPARISON TO PREVIOUS NOAA HABITAT CLASSIFICATION SCHEMES 

Many important factors were considered in the development of the habitat classification scheme including: requests of the management community, existing classification schemes for coastal ecosystems, quantitative in 

situ habitat data, minimum mapping unit (MMU) and spectral limitations of remotely sensed imagery (Kendall et 

al. 2001). The habitat classification scheme used in St. John was based on the evolution of schemes developed 

by NOAA in efforts to map the U.S. Caribbean and Pacific Islands (Kendall et al. 2001, Battista et al. 2007a, and 

Battista et al. 2007b). 

The fundamental difference in the St. John scheme, as compared to other NOAAcoral reef classification schemes, 

was the deviation from coral-centric classification rules to a biological dominance scheme in which benthic habitats were classified based on the dominant biological cover type present on each feature. In previous NOAA coral 

reef classification schemes, the biological cover component was assigned to a step-wise progression to first capture the presence of live coral and then attempt to classify any other biological cover if coral was not present. In 

other words, during map creation the interpreter would assign a polygon to the Live Coral biological cover class 

if there was 10% or greater live coral cover even if the polygon was predominantly covered by another biological cover type. For example, a patch reef covered by 15% live coral and 85% turf algae would be described in 

the previous classification schemes as Live Coral 10% - <50%. This approach often mislead map users in overstating the degree of live coral cover at the expense of the more prevalent biological cover type. 

geographic zone 

Land 

Salt Pond 

Shoreline Intertidal 

Lagoon 

Reef Flat 

Back Reef 

Reef Crest 

Fore Reef 

Bank/Shelf 

Bank/Shelf 

Escarpment 

Channel 

Dredged 

Unknown 

geomorphological Structure 

Coral Reef and Hard Bottom 

Rock Outcrop 

Boulder 

Aggregate Reef 

Individual Patch Reef 

Aggregated Patch Reefs 

Spur and Groove 

Pavement 

Pavement with Sand Channels 

Reef Rubble 

Rhodoliths 

Unknown 

Unconsolidated Sediment 

Sand 

Mud 

Biological Cover 

Major Cover 

Algae 

Live Coral 

Coralline Algae 

Mangrove 

Seagrass 

No Cover 

Unknown 

Percent Major Cover 

10% - <50% 

50% - <90% 

90% - 100% 

Unknown 

Coral Cover 

Sand with Scattered Percent Coral Cover 

Coral & Rock 0% - <10% 

Unknown 10% - <50% 

Other Delineations 

Land 

Artificial 

Unknown 

50% - <90% 

90% - 100% 

Unknown 

Figure 1.1. 

scribed by separate boxes) and several hierarchical levels of classification therein. 

The classification scheme defines benthic habitats with four primary attributes (deChapter 1: Benthic Habitat Classification Scheme

page 

3 
Chapter 1: Benthic Habitat Classification SchemeIn NOAA’s new St. John habitat classification scheme, there were no formal hierarchal classification rules; instead biological cover was described as the dominant cover type on each feature of the map. The importance of 

always describing the percent cover of live coral was maintained in the St. John scheme by the introduction of a 

new map attribute Percent Coral Cover. This attribute describes the percent live coral cover for every feature at 

the scale of diver observation in the water, with no regard to dominant biological cover (Figure 1.2). It is important 

to note that Percent Coral Cover refers only to the hardbottom component of any mapped polygon. For instance, 

an area of sand with some small scattered coral heads in it could be classified as 10% - <50% live coral cover 

even though 90% of the polygon is bare sand. 

Figure 1.2. The crown of a Christmas Tree Worm (Spirobranchus giganteus) protrudes from a colony of Great Star Coral (Montastraea 

cavernosa) on the south shore of St. John. 

Every unique combination of classification attributes was provided a distinct 

identifier in the UniqueID field. UniqueID consists of an 8-digit number string 

with each position in the string corresponding to a specific map attribute. See 

Figure 1.3 for a schematic that defines each attribute’s position in the UniqueID. 

Within each attribute, different classifications were assigned discrete codes. 

Through the assembly of these successive codes, it is possible to summarize 

all the information for a polygon feature solely based on the UniqueID. 

1.2. gEOgRAPHIC zONES 

Thirteen mutually exclusive zones can be identified from shore to shelf edge 

corresponding to typical insular shelf and coral reef geomorphology. These 

zones include: Land, Salt Pond, Shoreline Intertidal, Reef Flat, Lagoon, Back 

Reef, Reef Crest, Fore Reef, Bank/Shelf, Bank/Shelf Escarpment, Channel, 

Dredged, and Unknown. Figures 1.4 - 1.6 illustrate zone types across typical 

cross-sections when the reef feature is either separated from shore by a lagoon (Figure 1.4), fringing the shore (Figure 1.5), or not emergent (Figure 1.6). Zone refers only to each benthic 

community’s location and does not address substrate or biological cover types that are found within. For example, the lagoon zone may include patch reefs, sand, or reef rubble; however, these are considered structural 

elements that may or may not occur within the lagoon zone and therefore, are not used to define it at this level in 

the scheme (Kendall et al. 2001). A brief description of each zone is provided in the following text. 

Figure 1.3. Schematic of each attribute’s position in the UniqueID code 

of the classification scheme. 

page 

4 
Chapter 1: Benthic Habitat Classification Scheme

Figure 1.4. Cross-section of zone types where a barrier reef is present. Reef is separated from the shore by a 

relatively wide, deep lagoon. 

Figure 1.5. Cross-section of zone types where a fringing reef is present. Reef platform is continuous with the shore. 

Figure 1.6. Cross-section of zone types where no emergent reef crest is present. 

page 

5 
Land (ID Code = 10)
	

Terrestrial features at or above the spring high tide line. Shoreline delineations describing the boundary between land and submerged zones are established at the wrack line where possible or the wet line at the time 

of imagery acquisition (Figure 1.7).

Chapter 1: Benthic Habitat Classification Scheme

 ̄ 0 25 50

Meters

0 25 50  ̄ Meters

Figure 1.7. Depiction of shoreline delineations on unconsolidated (left) and rocky (right) coastlines. A red line highlights each shoreline 

on orthophotography. 

Salt Pond (11)
	

Enclosed area just landward of the shoreline with a permanent or intermittent flooding regime of saline to 

hypersaline waters (Figure 1.8).
	

Francis

Bay

 ̄ 0 50 100 

Meters 

Figure 1.8. Depictions of the Salt Pond zone just inshore of Europa Bay (left) and Francis Bay (right). A red polygon outlines the feature 

on orthophotography. 

page 

6 
Shoreline Intertidal (12) 

Area between the spring high tide line (or landward edge of emergent vegetation when present) and lowest 

spring tide level. Emergent segments of barrier reefs are excluded from this zone. Typically, this zone is narrow 

due to the small tidal range in the U.S. Virgin Islands (Figure 1.9). While present island-wide, the feature is often 

too narrow to be mapped on steep shorelines due to the scale of the imagery and the MMU. 

Princess Bay 

0 50 100

Meters  ̄ 0 50 100

Meters  ̄

Figure 1.9. Representation of two different types of Shoreline Intertidal zones. A low energy mangrove shoreline (left) and a high energy rocky shoreline (right) on the east end of St. John. 

Lagoon (13) 

Shallow area (relative to the deeper water of the bank/shelf) between the Shoreline Intertidal zone and the Back 

Reef of a reef or a barrier island. This zone is typically protected from the high-energy waves commonly experienced on the Bank/Shelf and Reef Crest zones (Figure 1.10). Typical lagoons are rare in St. John, however 

embayments with limited open ocean exchange restricted by nearly continuous reef crests are included in the 

Lagoon zone. 

Chapter 1: Benthic Habitat Classification Scheme

Mary

Creek

 ̄ 0 50 100 

Meters 

Figure 1.10. View of the Lagoon zone on orthophotography at Mary Creek. A red polygon outlines the feature. An example of a seagrass 

bed located in a shallow Lagoon. 

page 

7 
Reef Flat (14) 

Shallow, semi-exposed area of little relief between the Shoreline Intertidal zone and the Reef Crest of a fringing 

reef. This broad, flat area often exists just landward of a Reef Crest and may extend to the shoreline or drop into 

a Lagoon. This zone is protected from the high-energy waves commonly experienced on the Bank/Shelf and 

Reef Crest zones (Figure 1.11). 

Figure 1.11. Depictions of the Reef Flat zone in Newfound Bay from the shoreline and from orthophotography. A red polygon outlines the feature. 

Newfound Bay

0 50 100 

Meters  ̄

Back Reef (15)
	

Area just landward of a Reef Crest that slopes downward towards the seaward edge of a Lagoon floor or Bank/
 

Shelf. This zone is present only when a Reef Crest exists.
	

Reef Crest (16)
	

The flattened, emergent (especially during low tides) or nearly emergent segment of a reef. This zone of high 

wave energy lies between the Fore Reef and Back Reef or Reef Flat zones. Breaking waves are often visible in 

overhead imagery at the seaward edge of this zone (Figure 1.12).
	

Fore Reef (17)
	

Area along the seaward edge of the Reef Crest that slopes into deeper water to the landward edge of the Bank/
 

Shelf platform. Features not associated with an emergent Reef Crest but still having a seaward-facing slope 

that is significantly greater than the slope of the Bank/Shelf are also designated as Fore Reef (Figures 1.5 and 

1.12).
	

Bank/Shelf (18)
	

Deeper water area (relative to the shallow water in a lagoon) extending offshore from the seaward edge of the 

Fore Reef or shoreline to the beginning of the escarpment where the insular shelf drops off into deep, oceanic 

water. If no Reef Crest is present, the Bank/Shelf is the flattened platform between the Fore Reef and deep open 

ocean waters or between the Shoreline Intertidal zone and open ocean (Figure 1.12).
	

Mary

Creek

0 100 200

Meters

Reef Crest 

 ̄ 0 100 200

Meters

Fore Reef 

 ̄ 0 ̄ 100 200

Meters

Bank/Shelf 

Chapter 1: Benthic Habitat Classification Scheme

Figure 1.12. A series of orthophotographs illustrating the transition from Reef Crest to Fore Reef to Bank/Shelf zones at Lagoon Point. 

Each zone is depicted in color on the respective map. 

page 

8 
Bank/Shelf Escarpment (19)
	

This zone begins on the oceanic edge of the Bank/Shelf, where 

depth increases rapidly into deep, oceanic water and exceeds the 

depth limit of features visible in optical imagery around St. John. 

This zone is intended to capture the transition from the shelf to 

deep waters of the open ocean.
	

Channel (20)
	

Naturally occurring channels that often cut across several other 

zones.
	

Dredged (21)
	

Area in which natural geomorphology is disrupted or altered by 

excavation or dredging (Figure 1.13).
	

Unknown (99)
	

Zone indistinguishable due to turbidity, cloud cover, water depth, or 

other interference with an optical signature of the seafloor. 

1.3. gEOMORPHOLOgICAL STRUCTURE TYPES

Sixteen distinct and non-overlapping geomorphological structure types were identified that can be mapped by 

visual interpretation of remotely sensed imagery. Habitats or features that cover areas smaller than the MMU 

are not considered. For example, sand halos surrounding patch reefs are often too small to be mapped independently. Structure refers only to predominant physical composition of the feature and does not address location 

(e.g., on the shelf or in the lagoon). The structure types are defined in a collapsible hierarchy ranging from four 

major classes (Coral Reef and Hardbottom, Unconsolidated Sediment, Other Delineations, and Unknown), to 

sixteen detailed classes (Rock Outcrop, Boulder, Spur and Groove, Individual Patch Reef, Aggregated Patch 

Reefs, Aggregate Reef, Reef Rubble, Pavement, Pavement with Sand Channels, Rhodoliths, Sand, Mud, Sand 

with Scattered Coral and Rock, Artificial, Land, and Unknown). 

Coral Reef and Hardbottom (1) 

Areas of both shallow and deep-water seafloor with solid substrates including bedrock, boulders and deposition 

of calcium carbonate by reef building organisms. Substrates typically have no sediment cover, but a thin veneer 

of sediment may be present at times especially on low relief hardbottoms. Detailed structure classes include 

Rock Outcrop, Boulder, Spur and Groove, Individual Patch Reef, Aggregated Patch Reefs, Aggregate Reef, Reef 

Rubble, Pavement, Pavement with Sand Channels, and Rhodoliths. 

Rock Outcrop (30)
	

A primarily continuous exposure of solid carbonate blocks or volcanic rock extending offshore from the island 

bedrock. Includes large rock boulders greater than 3 m in diameter (Figure 1.14).
	

Figure 1.13. View of the Dredged zone on orthophotography at the shipping dock of Turner Bay. A red 

polygon outlines the feature on orthophotography. 

Turner Bay 

 ̄ 0 50 100

Meters

0 50 100

Meters

Hawksnest Bay 

 ̄

Chapter 1: Benthic Habitat Classification Scheme

Figure 1.14. Depictions of Rock Outcrop structure on the west side of the mouth of Hawksnest Bay. A red polygon outlines the feature 

on orthophotography. 

page 

9 
Boulder (31)
	

Aggregation of loose carbonate or volcanic rock fragments that have been detached and transported from their 

native beds (Figure 1.15). Individual boulders range in diameter from 0.25 – 3 m as defined by the Wentworth 

scale (Wentworth 1922).
	

 ̄ 0 25 50

Meters

Ram Head 

Chapter 1: Benthic Habitat Classification Scheme Figure 1.15. Depictions of Boulder structure on the west side of Ram Head. A red polygon outlines the feature on orthophotography. 

Aggregate Reef (10)
	

Continuous, high-relief coral formation of variable shapes lacking sand channels of Spur and Groove. Includes 

linear reef formations that are oriented parallel to shore or the shelf edge (Figure 1.16). This class is used for 

such commonly referred to terms as linear reef, fore reef or fringing reef.
	

 ̄ 0 50 100 

Meters 

Figure 1.16. Depictions of Aggregate Reef structure in Privateer Bay. A red polygon outlines the feature on orthophotography. 

page 

10 
Individual Patch Reef (11)
	

Patch reefs are coral formations that are isolated from other coral reef formations by bare sand, seagrass, or 

other habitats and that have no organized structural axis relative to the contours of the shore or shelf edge. They 

are characterized by a roughly circular or oblong shape with a vertical relief of one meter or more in relation to 

the surrounding seafloor (Figure 1.17). Individual Patch Reefs are larger than or equal to the MMU.
	

Aggregated Patch Reefs (12)
	

Having the same defining characteristics as an Individual Patch Reef. This class refers to clustered patch reefs 

that individually are too small (less than the MMU) or are too close together to map separately. Where aggregated patch reefs share sand halos, the halo is included in the polygon (Figure 1.17).
	

 

 ̄ 0 50 100

Meters

0 50 100

Meters  ̄

Individual Patch Reef Aggregated Patch Reefs 

Figure 1.17. Comparison of patch reef delineations south of Johnsons Reef. Due to the influence of minimum mapping units, patch 

reefs of the same complex are designated by either Individual Patch Reef (left) or Aggregated Patch Reefs (right). Red polygons outline 

the features on orthophotography. 

Spur and groove (13)
	

Structure having alternating sand and coral formations that are oriented perpendicular to the shore or reef crest. 

The coral formations (spurs) of this feature typically have a high vertical relief (approximately 1 meter or more)
	

relative to pavement with sand channels and are separated from each other by 1-5 meters of sand or hardbottom 

(grooves), although the height and width of these elements may vary considerably (Figure 1.18). This habitat 

type typically occurs in the Fore Reef or Bank/Shelf Escarpment zone.
	

Chapter 1: Benthic Habitat Classification Scheme

Reef Bay

 ̄ 0 50 100 

Meters 

Figure 1.18. Depictions of Spur and Groove structure on the west side of Reef Bay. A red polygon outlines the feature on orthophotography. 

page 

11 
Pavement (14)
	

Flat, low-relief, solid carbonate rock with coverage of algae, hard coral, gorgonians, zooanthids or other sessile 

vertebrates that are dense enough to partially obscure the underlying surface. On less colonized Pavement features, rock may be covered by a thin sand veneer or turf algae (Figure 1.19).

Chapter 1: Benthic Habitat Classification Scheme

 ̄ 0 50 100

Meters

Figure 1.19. Several views of Pavement structure in St. John. The overhead representation outlined by red polygons illustrates the 

often irregular shape. Also, Pavement may be colonized by a variety of marine flora. 

Pavement with Sand Channels (15) 

Habitats of pavement with alternating sand/surge channel formations that are oriented perpendicular to the Reef 

Crest or Bank/Shelf Escarpment. The sand/surge channels of this feature have low vertical relief (approximately 

less than 1 meter) relative to Spur and Groove formations and are typically erosional in origin. This habitat type 

occurs in areas exposed to moderate wave surge such as the Bank/Shelf zone (Figure 1.20). 

Coral Bay

 ̄ 0 100 200 

Meters 

Figure 1.20. Depictions of Pavement with Sand Channels off Turner Point in Coral Bay. A red polygon outlines the feature on orthophotography. 

page 

12 
Reef Rubble (16)
	

Dead, unstable coral rubble often colonized with filamentous or other macroalgae. This habitat often occurs landward of well developed reef formations in the Reef Crest, Back Reef or Reef Flat zones. Less often, Reef Rubble
 

can occur in low density aggregations on broad offshore sand areas (Figure 1.21).
	

 ̄ 0 25 50

Meters

Figure 1.21. Depictions of inshore Reef Rubble structure behind a reef crest on St. John’s East End. Red polygons outline the features 

on orthophotography. 

Rhodoliths (17)
	

Aggregation of cylindrical, discoidal, or irregular shaped calcareous nodules averaging approximately 6 cm in diameter. These unattached fragments are colonized by successive layers of coralline red algae. Commonly found in offshore topographic depressions (Figure 1.22).
	

Unconsolidated Sediment (2)
	

Areas of the seafloor consisting of small particles (<.25 m) with less than 

10% cover of large stable substrate. Detailed structure classes of softbottom include Sand, Mud, and Sand with Scattered Coral and Rock.
	

Sand (18)
	

Coarse sediment typically found in areas exposed to currents or wave energy (Figure 1.23). Particle sizes range from 1/16 – 256 mm, including pebbles and cobbles (Wentworth 1922). 

Chapter 1: Benthic Habitat Classification Scheme

Figure 1.22. Typical rhodolith bed off the 

south shore of St. John characterized by 

growth of fleshy macroalgae and sponges. 

 ̄ 0 250 500

Meters

Figure 1.23. Depictions of Sand as a structure on the northeast shore of St. John. The overhead representation described by a red 

polygon includes Sand with no biological cover (lighter), as well as with seagrass and algae (darker). 

page 

13 
Mud (19)
	

Fine sediment often associated with river discharge and build-up of organic material in areas sheltered from 

high-energy waves and currents (Figure 1.24). Particle sizes range from <1/256 – 1/16 mm (Wentworth 1922).
	

 ̄ 0 50 100

Meters

Mary Creek 

Chapter 1: Benthic Habitat Classification Scheme Figure 1.24. Depictions of Mud as a structure in the back of Mary Creek. A red polygon outlines the feature on orthophotography. 

Sand with Scattered Coral and Rock (20)
	

Primarily sand bottom with scattered rocks or small, isolated coral heads that are too small to be delineated individually (i.e., smaller than individual patch reef) (Figure 1.25). If the density of small coral heads is greater than 

10% of the entire polygon, this structure type is described as Aggregated Patch Reefs.
	

 ̄ 0 25 50

Meters

Figure 1.25. Depictions of Sand with Scattered Coral and Rock structure near East End Bay. Notice that coral aggregations and rock 

are either too small or sparse to be delineated as Aggregated Patch Reefs. A red polygon outlines the feature on orthophotography. 

Other Delineations (3)
	

Any other type of structure not classified as Coral Reef and Hardbottom or Unconsolidated Sediment. Usually 

related to the terrestrial environment and/or anthropogenic activity. Detailed structure classes include Land and
	

Artificial. 

Land (21)
	

Terrestrial features at or above the spring high tide line. 

page 

14 
 

Artificial (22)
	

Man-made habitats such as submerged wrecks, large 

piers, submerged portions of rip-rap jetties, and the 

shoreline of islands created from dredge spoil (Figure 

1.26). 

Unknown (9)
	

Major structure indistinguishable due to turbidity, 

cloud cover, water depth, or other interference with 

an optical signature of the seafloor. 

Unknown (99)
	

Detailed structure indistinguishable due to turbidity, 

cloud cover, water depth, or other interference with 

an optical signature of the seafloor.
	  ̄ 0 50 100

Meters

Cruz Bay 

Figure 1.26. Representation of Artificial structure (outlined in red 

on orthophotography) at the docks in Cruz Bay. 

1.4 BIOLOgICAL COVER CLASSES 

Eighteen distinct and non-overlapping biological cover classes were identified that 

could be mapped through visual interpretation of remotely sensed imagery. Cover 

classes refer only to the dominant biological component colonizing the surface of the 

feature and do not address location (e.g., 

on the shelf or in the lagoon) or structure 

type. Habitats or features that cover areas 

smaller than the MMU were not considered. 

The cover types are defined in a collapsible 

hierarchy ranging from eight major classes 

(Algae, Seagrass, Live Coral, Mangrove, 

Coralline Algae, No Cover, Unclassified 

and Unknown), combined with a modifier 

describing the distribution of the dominant 

cover type throughout the polygon (10%-

<50%, 50%-<90%, and 90%-100%). 

It is important to reinforce that the modifier 

represents a measure of the level of patchiness of the biological cover at the scale of 

delineation and not the density observed by 

divers in the water. For example, a seagrass 

bed can be described as covering 90%-

100% of a given polygon, but may have 

sparse densities of shoots when observed 

by divers. Figure 1.27 aids interpreter’s visual estimation of patchiness in assigning 

percent cover. 

Chapter 1: Benthic Habitat Classification Scheme

Figure 1.27. Guidance chart to understand visual interpreter’s estimation of 

patchiness in assigning percent cover. Note that each large square denotes a 

minimum mapping unit. 

Relative Patch 

Aggregation Less More 

90-100% 

Continuous 

70-<90% 

Patchy 

50-<70% 

Patchy 

30-<50% 

Patchy 

10-<30% 

Patchy 

0-<10% 

No Cover 

Percent Cover 

Category 

page 

15 
Major Cover 

Algae (1)
	

Substrates with 10% or greater distribution of any combination of numerous species of red, green, or brown algae. May be turf, fleshy or filamentous species. Occurs throughout many zones, especially on hardbottoms with 

low coral densities and softbottoms in deeper waters of the Bank/Shelf zone (Figure 1.28).

Chapter 1: Benthic Habitat Classification Scheme

Great Cruz 

Bay 

 ̄ 0 50 100

Meters

Figure 1.28. Depictions of Algae dominated habitats. Underwater pictures illustrate the different algal covers on soft and hardbottoms. 

A red polygon outlines the feature on orthophotography. 

Seagrass (2)
	

Habitat with 10% or more of the mapping unit dominated by any single species of seagrass (e.g. Syringodium
 

sp., Thalassia sp., and Halophila sp.) or a combination of several species (Figure 1.29).
	

 ̄ 0 100 200

Meters

Figure 1.29. Extensive Seagrass beds, such as that east of Leinster Point, cover softbottoms around the island. Turtle Grass (Thalassia 

testudinum) (left) and Manatee Grass (Syringodium filiforme) (right) are both common. A red polygon outlines the feature on orthophotography. 

Live Coral (3)
	

Substrates colonized with 10% or greater live reef building corals and other organisms including scleractinian 

corals (e.g., Acropora sp.) and octocorals (e.g., Briareum sp.) (Figure 1.30). 

page 

16 

0 100 200

Meters  ̄

Figure 1.30. In some instances, Live Coral may be the dominant biological cover on St. John’s habitats. Underwater pictures display both 

homogenous octocoral and scleractinian coral dominated environments. A red polygon outlines the feature on orthophotography. 
Mangrove (4) 

This habitat is comprised of semi-permanently, seasonally or tidally flooded coastal areas occupied by any species of mangrove (Figure 1.31). Mangrove trees are halophytes; plants that thrive in and are especially adapted 

to salty conditions. In the Virgin Islands there are three species of mangrove trees: red mangrove (Rhizophora 

mangle), black mangrove (Avicennia germinans), and white mangrove (Laguncularia racemosa); another tree, 

buttonwood (Conocarpus erectus) is often associated with the mangrove formation. Red mangrove grows at 

the water’s edge and in the tidal zone. Black mangrove and white mangrove grow further inland in areas where 

flooding occurs only during the highest tides. Generally found in areas sheltered from high-energy waves. This 

habitat type is usually found in the Shoreline Intertidal zone. 

 ̄

Reef Bay 

0 100 200

Meters

Figure 1.31. Red mangroves (Rhizophora mangle) cover much of St. John’s sheltered coastlines (left), while extensive mangrove 

complexes develop in low-lying areas inland from the shoreline (right). Red polygons outline the features on orthophotography. 

Coralline Algae (5) 

An area with 10% or greater coverage of any combination of numerous species of encrusting or coralline algae (Figure 1.32). May occur along reef 

crest, in shallow back reef, relatively shallow waters on the bank/shelf zone, and at depth. Broad 

enough coverage to constitute dominant biological 

cover in a MMU is particularly rare in the U.S. Caribbean. 

Figure 1.32. Underwater photograph of a Coralline Algae dominated 

environment. 

Chapter 1: Benthic Habitat Classification Scheme

page 

17 
No Cover (6)
	

Substrates not covered with a minimum of 10% of any of the other biological cover types. This habitat is usually 

found on sand or mud bottoms. Overall, No Cover is estimated at 90%-100% of the bottom with the possibility of 

some very low density biological cover (Figure 1.33).

Chapter 1: Benthic Habitat Classification Scheme

 ̄ 0 25 50

Meters

Figure 1.33. Depictions of benthic habitats with No Cover. Illustrated in the underwater photograph (left), No Cover may include some 

biological cover as long as it comprises less than 10% of the bottom. 

Unclassified (7)
	

A different biological cover type, such as upland, deciduous forest, that is not included in this habitat classification 

scheme dominates the area. Most often used on polygons defined as Land with terrestrial vegetation.
	

Unknown (9)
	

Biological cover is indistinguishable due to turbidity, cloud cover, water depth, or other interference with an optical signature of the seafloor. 

page 

18 
Percent Major Cover 

10% - <50% (2)
	

Discontinuous cover of the major biological type with breaks in coverage that are too diffuse to delineate or 

result in isolated patches of a different dominant biological cover that are too small (smaller than the MMU) to 

be mapped as a different feature. Overall cover of the major biological type is estimated at 10% - <50% of the 

polygon feature (Figure 1.34).
	

50% - <90% (3)
	

Discontinuous cover of the major biological type with breaks in coverage that are too diffuse to delineate or 

result in isolated patches of a different dominant biological cover that are too small (smaller than the MMU) to 

be mapped as a different feature. Overall cover of the major biological type is estimated at 50% - <90% of the 

polygon feature (Figure 1.34).
	

90% - 100% (4) 

Major biological cover type with nearly continuous (90-100%) coverage of the substrate (Figure 1.34). May 

include areas of less than 90% major cover on 10% or less of the total area that are too small to be mapped 

independently (less than the MMU).
	

Mary

Creek

 

0 50 100

Meters

10% - <50% 

 ̄ 0 50 100

Meters

50% - <90% 

 ̄ 0 50 100

Meters  ̄

90% - 100% 

Figure 1.34. Representation of the three percent major cover modifiers (10% - <50%, 50% - <90%, 90% - 100%) using a seagrass bed 

in Fish Bay as an example. Each zone is depicted in color on the respective map. 

Not Applicable (5)
	

An estimate of percent cover is not appropriate for this particular major biological cover class. Regularly accompanies the use of Unclassified as the major biological cover. 

Unknown (9)
	

Percent estimate of the biological cover is indistinguishable due to turbidity, cloud cover, water depth, or other 

interference with an optical signature of the seafloor. 

Chapter 1: Benthic Habitat Classification Scheme

page 

19 
 

Chapter 1: Benthic Habitat Classification Scheme1.5. LIVE CORAL COVER CLASSES 

Four distinct and non-overlapping percent live coral classes were identified that can be mapped through visual 

interpretation of remotely sensed imagery. This attribute is an additional biological cover modifier used to maintain information on the percent cover of live coral, both scleractinian and octocorals (Figure 1.35), even when it 

is not the dominant cover type. In order to provide resource managers with additional information on this cover 

type of critical concern, four range classes were used (0% - <10%, 10% - <50%, 50% - <90%, and 90% - 100%). 

Hardbottom features are classified into these range classes based on the amount of combined scleractinian and 

octocoral present in a polygon. Distinction of scleractinian coral versus octocoral was limited by the current state 

of remote sensing technology and could not be separated in the Live Coral Cover modifier. 

Figure 1.35. Both scleractinian and octocorals are considered when defining live coral cover. Typical corals of St. John include the scleractinian boulder coral (Montastraea annularis) and several octocorals including sea fans (Gorgonia sp.). 

Unlike the biological cover modifier, live coral cover describes the percent coverage on hardbottom features at 

the observed fine-scale (i.e., diver scale), not the distribution at the scale of delineation. For this reason, extensive in situ data is critical to correct attribution of the live coral cover modifier. The observed fine-scale used for 

live coral cover assessment was approximately 1 m to 3 m off the bottom feature and its associated field of view. 

As a result of these varying scales of interpretation, the percent biological cover and percent live coral cover 

modifiers are not additive properties within the same mapping unit. In many cases, they will sum to greater than 

100%. For example, an aggregate reef can have continuous (90%-100%) cover of algae throughout a mapping 

unit, as well as 10%-50% density of coral at the fine-scale. It is important to note that Percent Coral Cover refers only to the hardbottom component of any mapped polygon. For instance, an area of sand with some small 

scattered coral heads in it could be classified as 10% - <50% live coral cover even though 90% of the polygon 

is bare sand. 

page 

20 
0% - <10% (1)
	

Live coral cover of less than 10% of 

hardbottom substrate at a scale several meters above the seafloor (Figure 

1.36). 

10% - <50% (2)
	

Live coral cover between 10% and 50% 

of hardbottom substrate at a scale several meters above the seafloor (Figure 

1.37). 

50% - <90% (3)
	

Live coral cover between 50% and 

90% of hardbottom substrate at a scale 

several meters above the seafloor. 

90% - 100% (4)
	

Continuous live coral consisting of 

90% or greater cover of the hardbottom substrate at a scale several meters above the seafloor. 

Not Applicable (5)
	

An estimate of percent live coral cover 

is not appropriate for this particular 

feature. Only occurs in areas describing the terrestrial environment. 

Unknown (9)
	

Percent estimate of coral cover is indistinguishable due to turbidity, cloud 

cover, water depth, or other interference with an optical signature of the 

seafloor. 

Figure 1.36. An example of the presence of live coral in the 0% - 10% cover range. 

Figure 1.37. An illustration of live coral, primarily gorgonian, in the 10% - 50% cover 

range. 

Chapter 1: Benthic Habitat Classification Scheme

page 

21 
Chapter 1: Benthic Habitat Classification SchemeLITERATURE CITED 

Battista, T.A., Costa, B.M., and S.M. Anderson, S.M. 2007a. Shallow-Water Benthic Habitats of the Main Eight 

Hawaiian Islands (DVD). NOAA Technical Memorandum NOS NCCOS 61, Biogeography Branch. Silver Spring, 

MD. 

Battista, T.A., Costa, B.M., and S.M. Anderson, S.M. 2007b. Shallow-Water Benthic Habitats of the Republic of 

Palau. NOAA Technical Memorandum NOS NCCOS 59, Biogeography Branch. Silver Spring, MD. 

Kendall, M.S., C.R. Kruer, K.R. Buja, J.D. Christensen, M. Finkbeiner, R.A. Warner and M.E. Monaco. 2001. 

Methods Used to Map the Benthic Habitats of Puerto Rico and the U.S. Virgin Islands. NOAA Technical Memorandum NOS NCCOS CCMA 152. Silver Spring, MD. 

Wentworth, C.K. 1922. A Scale of Grade and Class Terms for Clastic Sediments. Journal of Geology. 30 (5): 

377-392. 

page 

22 
 

Chapter 2: BenthiC haBitat map Creation 

Benthic habitat maps of the nearshore marine environment of St. John, U.S. Virgin Islands were 

created through visual interpretation of remotely 

sensed imagery. Remotely sensed imagery, including color orthophotography and IKONOS satellite 

imagery, proved to be an excellent source from 

which to derive the location, extent and attributes 

of marine habitats. NOAA scientists were able to 

accurately and reliably delineate the boundaries 

of features on digital imagery using a Geographic 

Information System (GIS) and a custom extension 

to ArcGIS 9.3 that enabled easy delineation and 

attribution of bottom features. Field investigations 

were conducted from small marine vessels in order 

to ground validate the spectral signature created 

by the myriad submerged features in the marine 

environment (Figure 2.1). Once digital maps were 

produced, experts with local knowledge of the coral reef ecosystem of St. John were consulted at an 

on-site workshop and their feedback was incorporated into the final maps. Through this process, natural resource managers and researchers are provided with 

spatially and thematically accurate maps of marine features and their ecological characteristics. 

2.1 general mapping approaCh 

NOAA Biogeography Branch’s approach to shallow-water benthic habitat mapping of coral reef ecosystems was 

a six-step process: 

1. Imagery Acquisition – The first step in map creation was the acquisition and processing of a comprehensive 

dataset of remotely sensed imagery. All imagery was geo-positioned to ensure acceptable spatial accuracy 

in the mapping product. In the case of St. John, two separate data types were used (color orthophotography 

and IKONOS satellite imagery) in order to capture the full mappable extent using remote sensing techniques. 

2. Habitat Boundary Delineation – A first draft of the benthic habitat map was generated by delineating all 

features that could be identified by visual inspection of the remotely sensed imagery. During the creation 

of this first draft, the interpreter placed discrete points on the map that were difficult to distinguish and that 

warranted further field investigation. These sites were labeled as “ground validation” positions. 

3. Ground Validation – NOAA field scientists explored the ground validation locations with a 

suite of assessment techniques depending on 

the conditions at each site. A combination of 

underwater video, free diving, snorkeling and 

surface observations were used to survey the 

ecological characteristics at each location 

(Figure 2.2). This information was analyzed 

and the initial maps were edited to generate a 

second draft map improved by the field observations. 

4. Expert Review – The second draft map was 

then reviewed by local marine biologists, coral reef scientists and resource managers at 

a one-day workshop in Cruz Bay, St. John. 

Comments were integrated into the map products to generate a final draft map. 

Chapter 2: Benthic Habitat Map Creation

Figure 2.1. Blue Chromis (Chromis cyanea) aggregate over a mixed 

hardbottom of hydrocorals, octocorals and scleractinian corals. 

Figure 2.2. U.S. National Park Service vessel Acropora was used to 

conduct field work in support of habitat map development. 

page 

23 
 

Chapter 2: Benthic Habitat Map Creation

5. Accuracy Assessment – An independent team of NOAA scientists not associated with map creation, conducted field investigations at pre-defined locations to assess the classification accuracy of the final draft 

map. Locations were generated with a stratified random sampling design that allowed for a statistically rigor­

ous assessment of map accuracy. 

6. Final Products Creation – A final benthic habitat map for St. John was generated by correcting any inaccu­

racies revealed by the accuracy assessment. Additionally, all associated datasets, including GIS files, field 

video and metadata were packaged and provided to project partners and the public. 

2.2 remotelY SenSeD imagerY 

Remotely sensed imagery is a valuable tool for natural resource managers and researchers since it provides an 

excellent record of the location and extent of seafloor habitats. Typically, feature detection of seafloor habitats 

in the U.S. Caribbean is possible from the shoreline to water depths of approximately 30 meters, depending on 

water clarity and sea state. Benthic habitat maps of St. John, USVI were created through visual interpretation 

of remotely sensed imagery. Habitat boundaries were delineated around unique signatures in the orthorectified 

imagery corresponding to habitat types in the classification scheme described in Chapter 1. Two different remote 

sensors were used to collect overhead imagery of St. John: 

1. ADS40 digital photography, and 

2. IKONOS multispectral satellite imagery 

Digital orthophotography 

An orthophoto is remotely sensed image data in which displacement of features in the image caused by terrain 

relief and sensor orientation have been mathematically removed. Orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. After an image has been orthorectified, visual 

interpreters can accurately and reliably delineate the boundaries of features in the imagery as they appear on the 

computer monitor using a software interface. Through this process, natural resources managers and research

­

ers are provided with spatially accurate maps of habitats and other features visible in the imagery. 

True-color digital orthophotography obtained with an ADS40 digi- table 2.1. Acquisition dates of imagery used for creation of the benthic habitat maps. Notice the two re­ tal sensor was the primary imagery source used for delineating mote sensing platforms used and the corresponding benthic habitats of St. John. As described in Table 2.1 imagery individual scene names. 

was obtained in September and October of 2007 to produce orthophotos with a one foot ground sample distance (GSD). Flight 

height was maintained at 8,650 ft above ground level throughout 

the acquisition effort and was collected at 30% sidelap. Imagery 

was collected by 3001, Inc. under contract to the U.S. Army Corps 

of Engineers and was later provided to NOAA for this mapping 

effort. 3001, Inc. reported 1:4,800 scale RMSE accuracy of 1.25 

m, but NOAA calculations with known ground control locations 

resulted in RMSE accuracy of 2.15 m. For a more complete description of the product please see the metadata report included 

with the project deliverables. 

iKonoS Satellite imagery 

At limited locations throughout the mapping area, the digital orthophotography was not suitable for habitat delineation; in which case, IKONOS multispectral satellite imagery was used as a replacement. Four IKONOS 

scenes with varying acquisition dates (Table 2.1) were obtained to supplement mapping efforts. The IKONOS 

satellite, owned and operated by GeoEye Inc., provided commercially available panchromatic (black and white) 

and four-band multispectral (blue, green, red and near-infrared) imagery. The panchromatic imagery had a 1 m 

pixel dimension and the multispectral imagery had a 4 m pixel dimension. The IKONOS imagery was acquired in 

11 km wide swaths that were mosaicked together to produce complete images covering the area of interest. 

image iD aCQUiSition Date 

Orthophotography

18064-C4-01-03 10/22/2007 

18064-C4-05-07 10/10/2007 

18064-C4-09-10 9/7/2007 

18064-C7-02-04 10/22/2007 

18064-C7-06-08 10/10/2007 

18064-C7-10-12 9/7/2007 

IKONOS

304713_0000000 2/23/2000 

184799_0010000 12/26/2005 

191555_0000000 9/18/2005 

191556_0000000 9/18/2005 

page 

24 
Unlike the orthophotos obtained from the U.S. Army Corps of Engineers, the IKONOS imagery required additional processing to ensure suitability for shallow-water benthic mapping. The following four processing steps 

were completed in order for each image and are described in detail in subsequent text: 

1. Geo-positioned with satellite ephemeris data and supplemental ground control, 

2. Corrected for terrain displacement, 

3. Pan-sharpened, and 

4. Removed sun glint. 

The IKONOS imagery was purchased in National Imagery Transmission Format (NITF) with the associated 

Rational Polynomial Coefficients, also known as RPCs or satellite ephemeris data. When using image analysis 

software capable of reading NITF files and associated RPCs, the positioning error of uncorrected imagery typically approaches 15 m, but after positioning to ephemeris data, the final positioning error is reduced to only a 

few meters of error. Geo-referencing of the imagery was performed using PCI OrthoEngine module. The NITF 

IKONOS imagery were orthorectified using the Rational Functions extracted from the NITF, then further supplemented with stereo ground control point positioning using a robust polynomial math model through bundle adjustment of all the satellite scenes. 

Fixed ground features visible in the IKONOS imagery (Figure 2.3) were selected for ground control 

points (GCPs) to be used in geo-referencing the 

imagery; in other words, link the image pixels to 

a real world coordinate system such as Universal 

Transverse Mercator. NOAA scientists occupied 

multiple locations throughout St. John using L1 

Trimble GeoXT mapping grade GPS. GPS observations were adjusted using the continuously-operating base station (VITH CORS) located in St. 

Thomas, USVI. NOAA obtained points with a wide 

distribution throughout the imagery whenever possible, as it results in the most accurate registration 

throughout each image. Only ground control points 

for terrestrial features were collected due to the difficulty of obtaining precise positions for submerged 

features. IKONOS scene 304713_0000000 presented a difficult task in fine-scale positioning 

efforts because it was primarily over open water 

where ground control points were not available. In 

this case, image to image tie-points were used to further co-register the imagery with other better positioned 

scenes. Tie points are distinct features, such as street intersections, piers, coral heads, reef edges, and bridges, 

which were visible in overlap areas of each image. These features were precisely aligned between scenes, thus 

providing exterior orientation control to co-register the scene. 

Terrain displacement was corrected for in the orthrectification bundle adjustment using the U.S. Geological Survey’s Digital Elevation Model (DEM) generated from airborne LiDAR data (Figure 2.4). 

Figure 2.3. Geodetic marker from NOAA’s National Geodetic Survey 

that was used as a ground control point. 

Chapter 2: Benthic Habitat Map Creation

Figure 2.4. Oblique view of U.S. Geological Survey’s Digital Elevation Model used to correct terrain displacement during 

orthorectification process. 

page 

25 
Chapter 2: Benthic Habitat Map CreationPCI OrthoEngine Pansharpening module was employed to create a high-resolution color image to be used for 

visual interpretation by NOAA scientists. Pan-sharpening, also known as image fusion, is the concept of compiling multiple images into a composite product, which maintains the spectral signatures of the input color images 

while enhancing the spatial features with the input panchromatic image. It was applied to the IKONOS imagery 

to increase the spatial resolution of the 4 m multispectral data to the panchromatic data resolution of 1 m. 

Furthermore, image enhancements were conducted on the positioned and pan-sharpened imagery to remove 

specular reflection from the sea surface. Reflection of solar radiation on non-flat water surfaces often results in 

areas of bright white sun glint in remotely sensed imagery. Typically, sun glint forms bands of white along wave 

edges on the windward side of nearshore environments. Sun glint can obscure bottom features and should be 

removed before habitat delineation. The method for removal of sun glint described in Hedley et al. (2005) was 

applied to the IKONOS imagery. 

2.3 haBitat BoUnDarY Delineation anD attriBUtion 

As described by BAE Systems (2007), traditional methods of stereoplotter digitizing of photo interpreted habitat 

classes have gradually been replaced by the increased access and functionality of GIS software for on-screen 

“head’s up” digitizing. GIS-based techniques have several distinct advantages, including: •		 Elimination of intermediate steps required to go from hardcopy to digital maps, which reduces slight distor

­

tions in habitat boundaries, 

•		 Enhanced productivity in map creation due to gained efficiency, •		 Development of a dynamic link between habitat delineations and the associated attributes in a database, 

and 

•		 Increased analytical capabilities through the use of spatial analysis routines in the GIS. 

St. John’s benthic habitat map and mapping methods were developed using ESRI’s ArcGIS 9.3 (ESRI 2008) and 

an ArcGIS extension created by NOAA’s Biogeography Branch, the Habitat Digitizer Extension (NOAA 2009). 

The Habitat Digitizer Extension is a GIS tool designed to use a hierarchical classification scheme to delineate 

features by visually interpreting geo-referenced images. The extension allowed the interpreter to create the 

custom classification scheme described in Chapter 1, digitize polygons using standard ArcGIS editing tools, and 

attribute the features using a dialog containing the created scheme. The extension allowed for rapid delineation 

and attribution of polygons, which significantly improved the efficiency of map creation. 

The Habitat Digitizer Extension allowed several 

critical digitizing parameters to be set in advance 

that standardized the habitat map output. The 

Minimum Mapping Unit (MMU) restriction was set 

to 1,000 m2 (0.25 acre). St. John mapping efforts 

mark the first time NOAA coral reef ecosystem 

maps have been generated at an MMU of less than 

4,000 m2 (1 acre). This reduction was in response 

to the coral reef management community’s interest 

in having finer resolution maps to make resource 

management decisions with. However, there were 

still features visible in the imagery, such as patch 

reefs (Figure 2.5), which were smaller than the 

MMU and were not included as individual features 

in the map. 

Digitizing scale was set to 1:2,000 and a comput­

er generated message informed the interpreter if 

polygon creation was being initiated at any other 

scale. The interpreter was allowed to zoom in and 

out to varying scales when assessing an area, but always returned to 1:2,000 before boundary delineation. Qualitative experimentation results adapted from Kendall et al. (2001) indicated that digitizing at this scale optimized 

Figure 2.5. Many individual patch reefs were smaller than the minimum 

mapping unit and resulted in aggregation with other habitat classes. 

page 

26 
the tradeoff between positional accuracy of lines and time spent digitizing. Given the higher spatial resolution 

of imagery and reduced MMU for St. John mapping, a reduction of digitizing scale to 1:2,000 from 1:6,000 in 

Kendall et al. (2001) and 1:4,000 in Battista et al. (2007) was warranted. In general, line placement conducted 

while zoomed in at fine scales results in excellent line accuracy and detail, but can be quite time consuming. 

Conversely, while zoomed out, lines can be drawn quickly, but lack both detail and positional accuracy. 

Habitat boundary delineation and attribution techniques were adopted from Kendall et al (2001): 

Using the Habitat Digitizer, habitat boundaries 

were delineated around spectral signatures of particular color and texture patterns in the remotely 

sensed imagery that corresponded to habitat types 

in the classification scheme described in Chapter 

1 (Figure 2.6). This was often accomplished by 

first digitizing a large boundary polygon such as 

the habitats that compose the shoreline and then 

appending new polygons to the initial boundary 

polygon. Another technique was to draw one large 

polygon around a feature of similar type and then 

split it down into smaller, more specific polygons; 

which was often the case with seagrass beds of 

varying percent covers. Each new polygon was 

attributed with the appropriate habitat designation according to the classification scheme. It was 

believed that the positional accuracy of polygon 

boundaries was similar to that of the source imagery since delineations were performed directly on 

the remotely sensed imagery. 

Brightness, contrast and color stretching of the source imagery were often manipulated in ArcGIS to enhance 

the interpretability of some subtle features and boundaries. This was particularly helpful in deeper water where 

differences in color and texture between adjacent features tend to be more subtle and boundaries more difficult 

to detect. Particular caution was used when interpretation was performed from altered images, since results from 

color and brightness manipulations can sometimes be misleading. Additional ancillary datasets were consulted 

to improve the understanding of particular areas. These data types included previously-completed habitat maps 

(Kendall et al. 2001, Mumby 2001, Beets et al. 1986), bathymetry, nautical charts, and imagery from different 

time periods. 

2.4 groUnD ValiDation 

The creation of high-quality benthic habitat maps required extensive field work to enhance accuracies of habitat 

attribution and, to a lesser degree, habitat delineation. Following the generation of an initial draft benthic habitat 

map, a team of NOAA field scientists explored selected locations to verify existing habitat information on the 

seafloor. These “ground validation” (GV) sites were targeted by the interpreter to satisfy one of the following two 

objectives: 

1. Explore areas in the imagery with confusing or difficult to determine spectral signatures, or 

2. Establish a transect moving from shore to deeper waters to better understand habitat transitions in a given 

area. These transects are important because a single habitat type may provide a different signature depending on water depth and sea state. 

Numerous GV locations were established while the photo interpreter was generating the draft habitat map. Before field work began, a subset of these initial GV sites was reduced to only priority locations that could be completed during a two-week field mission. Geographic coordinates were extracted for these sites and uploaded into 

Garmin GPS 76 WAAS-enabled hand-held devices. The remaining sites were retained and were later assessed 

with the GV field dataset to update these omitted confusing areas where field data may have been similar. 

Chapter 2: Benthic Habitat Map Creation

Figure 2.6. NOAA Biogeography Branch’s Habitat Digitizer Extension 

(NOAA 2009) was used to attribute map polygons with all components 

of the habitat classification scheme. 

page 

27 
Chapter 2: Benthic Habitat Map Creation

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Figure 2.7. Red dots depict the location of the 444 ground validation sites visited during the mapping process to determine habitat 

information. 

Data were collected on 444 GV sites (Figure 2.7) over a two-week field mission from January 5-16, 2009 aboard 

National Park Service small research vessels. At the start of every morning, the boat captain selected a general 

region to begin the day’s work. Most often this consisted of starting in areas typically prone to more challenging 

sea conditions and moving to inshore, more protected areas as the day progressed. Navigating to field loca­

tions was accomplished using a Garmin GPS 76 device with the uploaded GV site coordinates. The boat cap­

tain maneuvered the vessel to within 5 m of the target location and made every effort to maintain that location 

without jeopardizing crew and equipment safety. Once on site, NOAA scientists would simultaneously deploy a 

SeaViewer Sea-Drop 950 camera and begin logging a waypoint on a Trimble GeoXT GPS receiver (Figure 2.8). 

The drop camera reached the bottom in approximately 5 - 10 seconds and bottom imagery was recorded to minidigital video tapes using a Sony Walkman video recorder. The camera operator adjusted the camera position to 

get a downward view at approximately 2 m from the bottom and a side view of the habitat at each location. This 

allowed for accurate measurements of percent biological cover and a broader sense of the structure at each site. 

No attempt was made to standardize the amount of bottom time the camera would capture in order to avoid the 

confusion of viewing multiple habitat types. In fact, it was often advantageous for the vessel to drift across habitat transitions, thus allowing the interpreter to understand the ecotone at many locations. Position logging in the 

page 

28 

Figure 2.8. Operation of field equipment, including the underwater video camera and GPS receivers. 
Trimble receiver was optimized to plot every epic (i.e., position) along a waypoint. This allowed for accurate depiction of the vessels drift line at a single GV location and was utilized in subsequent assessment of the data. 

While the video camera was capturing bottom imagery, an observer viewed the video real-time on a Panasonic 

Toughbook aboard the survey vessel. They categorized each site according to the levels of the habitat classification scheme: major and detailed geomorphological structure, major biological cover, percent major biological 

cover and percent coral cover. Data was entered into a custom data dictionary generated in Trimble Pathfinder 

Office software and loaded onto the Trimble data logger. Field sheets representing an exact replicate of the digital data dictionary were also populated as back-up to the digital classification information. 

The preceding description of field data collection was the preferred method, as it provided the most reliable 

data. Of the 444 sites occupied during ground validation, 427 were assessed with the underwater drop camera. 

However, environmental conditions and boat safety issues, such as close proximity to shore, precluded 17 sites 

from being assessed with this preferred method. In those cases, several other field assessment methods were 

used, including snorkeling, free diving and visual inspection from the vessel. Field scientists documented these 

GV sites with digital pictures to maintain a visual record of the location. 

Water-proof field maps illustrating the draft habitat map and source imagery were used on-board 

the survey vessel to facilitate comparison of signatures in the imagery to actual habitats at each 

site. In many cases, suggestions on boundary 

delineation and habitat classifications were made 

directly on the field maps with permanent marker. 

For instance, if a fringing mangrove (Figure 2.9) 

area was passed en route to the next GV location, a note was drawn on the map depicting an 

approximate boundary. This effort provided even 

more information to improve the draft map in addition to the GV sites. 

Trimble Pathfinder Office software was used to 

post process and differentially correct the raw 

GPS data to the Continually Operating Reference 

System (CORS) station at St. Thomas, U.S. Virgin 

Islands (VITH). Precise GPS positions and the associated classification data were viewed in a GIS to enhance 

the accuracy of the draft benthic habitat map. Polygon boundaries and habitat classifications were revised where 

field data necessitated changes. 

Figure 2.9. Presence of fringing mangroves were often noted from the 

survey vessel on field maps. 

Chapter 2: Benthic Habitat Map Creation

2.5 eXpert reVieW 

Before the draft map was considered final and ready table 2.2. Expert review workshop participants and their affiliations. 

for accuracy assessment, a panel of local experts reviewed the maps at an Expert Review Workshop. Local marine biologists, coral reef scientists and resource 

managers assembled at National Park Service facilities in Cruz Bay, St. John for a one-day workshop on 

March 31, 2009. NOAA produced tabloid-sized hardcopy atlases of the entire mapped area for the review. 

Experts were asked to comment on the habitat classification scheme, habitat boundary delineations and 

polygon attributes of the draft maps in order to improve 

the quality and accuracy of the final map products. Table 2.2 shows the list of attendees and their affiliation.
	

attendee name Affiliation

Rafe Boulon National Park Service – St. John

Jeff Miller National Park Service – St. John

Caroline Rodgers U.S. Geological Survey – St. John 

Ron Hill NOAA Fisheries – Galveston 

Tyler Smith University of the Virgin Islands 

Jeremiah Blondeau University of the Virgin Islands 

Mark Monaco NOAA Biogeography Branch – Silver Spring 

Adam Zitello NOAA Biogeography Branch – Silver Spring 

page 

29 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 2: Benthic Habitat Map CreationThe workshop resulted in the following key recommendations: 

• Attendees agreed that assigning a percent live coral modifier to each mapping unit was useful, 

o Change attribute name from Coral Density to Coral Cover to avoid confusion with the more traditional 

use of density 

• Concern was expressed over the combining of scleractinian and octocorals when assigning the Coral 

Cover modifier,
	

o It was explained that distinguishing between these coral types using photo-interpretation is quite 

difficult, if not impossible 

o NOAA Biogeography committed to exploring the feasibility of distinguishing between the coral types, 

possibly using in situ monitoring data 

o However, it was agreed that this information was not to be part of the products of this effort 

• Possibly include a new structure type that describes the transition between aggregate reef and aggregated 

patch reefs, 

o In order to describe aggregate reefs with sand patches intermixed that are smaller than the MMU (dis 

continuous in nature, but still constituting a single feature) 

o A suggested type name: Aggregated Coral Heads 

• Improve habitat classification scheme manual, 

o Define polygon patchiness and how it relates to percent cover 

o Should include more photographs of structure and biological covers to improve understanding 

beyond text descriptions (Figure 2.10) 

o Provide flow diagram of how the classification process is conducted for an example mapping unit 

o In text descriptions, include actual site locations in St. John where structure and cover types exist as 

illustrations for those familiar with St. John 

• Avoid use of terms hard and soft coral, instead use scleractinian and octocoral 

• Explore explicitly linking in situ monitoring data with the final map product 

• As part of the final report, compare the new map to the previous NOAA map for St. John 

o Possibly in the number of acres of certain categories, polygons and other critical map statistics 

• The atlas maps were difficult to utilize for review 

o Frames should be adjusted so that breaks minimize interruption of features 

o Low print quality made it difficult to read the colors on the maps, especially with blue background 

o A possible solution would be to use solid colors instead of transparency 

page 

30 

Figure 2.10. Mangroves are a common biological cover along the protected coastlines of St. John. 
2.6 giS QUalitY Control 

All GIS deliverable products generated throughout the mapping process were closely examined for error. Particular attention was given to polygon geometry of the benthic habitat map and attribution of both the habitat map 

and GV and AA field GIS datasets. Multipart, sliver and void polygons were all removed using standard ArcGIS 

Spatial Analyst tools. Two custom ArcGIS extensions were employed to identify the following conditions: 

1. Adjacency – polygons that shared a common boundary and exact attribute combination that were delineated 

separately (Buja 2008a) 

2. Overlap – polygons sharing the same geographic space, thus violating mutual exclusion (Buja 2008b) 

Errors resulting from either of these GIS routines were corrected on draft maps and eliminated in the final prod

uct. 

A review of habitat boundaries by a NOAA staff member not involved in imagery interpretation concluded that all 

areas mapped as Unknown were indeed indistinguishable on the source imagery. 

A visual inspection of attributes on a feature-by-feature basis was conducted to correct for any misspellings or 

illogical attribute combinations. These types of errors were minimal; as the use of the Habitat Digitizer Extension 

standardized the process of populating GIS attribute tables. In the rare instances where manual attribution was 

required, particular attention was given to control these processes. The aforementioned visual inspection ac

counted for any potential errors. 

GIS data from this work were determined to be topologically clean and free of attribution errors. In addition, 

metadata summaries were prepared in an FGDC-compliant format for all GIS products that were supplied during 

final delivery (Figure 2.11). 

­

­

Chapter 2: Benthic Habitat Map Creation

Figure 2.11. A Southern Stingray (Dasyatis americana) moves across a sand and algae bottom in St. John. 

page 

31 
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Mumby, P. 2001. Habitat Mapping of St. Thomas and St. John. University of Exeter, UK. On Khaled bin Sultan 

Living Oceans Foundation: http://www.livingoceansfoundation.org/. [Accessed December 2008]. 

NOAA. 2009. Habitat Digitizer Extension. NOAA Biogeography Branch. Silver Spring, MD. Available: http://ccma. 

nos.noaa.gov/products/biogeography/digitizer/welcome.html. 

page 

32 
CHAPTER 3: AssEssmEnT of ClAssifiCATion ACCuRACy 

A comprehensive assessment was conducted to evaluate the thematic accuracy of the St. John benthic habitat 

map. Thematic accuracy was characterized for major and detailed geomorphological structure, major and detailed biological cover, and percent coral cover classifications (see Chapter 1 for classification scheme description). 

3.1. fiEld dATA CollECTion 

Target locations for the accuracy assessment (AA) procedure were determined by an iterative, GIS-based, stratified random sampling technique to ensure that all bottom classifications would be assessed. Based on guidelines from other recent accuracy assessment analyses (Battista et al. 2007a, 2007b), a minimum of 25 points 

were assigned to each of the 13 detailed structure classes within the draft habitat map. An additional 175 points 

were distributed based on the proportion of area of each detailed structure class in the map. Points were randomly placed within each class using Hawth’s Analysis Tools (Beyer 2004) in ArcGIS at a minimum distance of 

50 m apart. The minimum distance was selected to ensure there would be no overlap between surveys. No buffer from polygon edges was used. Next, the number of points that fell within each detailed primary cover class 

was calculated. Where necessary, additional points were randomly added and re-distributed from classes with 

many points to ensure that there was a minimum of 25 points within each detailed cover class, with the exception 

of live coral, due to the small number of polygons in the draft map that received this classification. These steps 

resulted in a total of 520 sample target locations. 

Data were collected over a two-week field mission from February 9-20, 2009. Sample locations were navigated 

to using a hand-held Garmin 76 WAAS-enabled GPS unit. Underwater video from a SeaViewer Sea-Drop 950 

camera was taken at each site, provided the location was safely accessible by the survey vessel (Figure 3.1). 

A weight was tied to the bottom of the camera to help lower the camera to the bottom, and the camera operator 

adjusted the camera position to get a downward and side view of the habitat at each location. Video length depended on the habitat type and vessel drift and ranged from approximately 30 seconds to two minutes. Videos 

of large, homogeneous sand habitats were generally short while heterogeneous hardbottom habitats, especially 

edges, were typically longer. While the video was being recorded, GPS waypoints were recorded on board the 

vessel using a Trimble GeoXT GPS receivers. At least three epics (i.e., points) were logged at each site, but this 

number was generally much higher and depended on the satellite signal, length of the video clip, current speed 

and vessel drift. This resulted in a string of epics that tracked boat position at each site. An observer categorized 

each site according to the video for each level of the map classification scheme: major/detailed geomorphological structure, major/detailed biological cover, and percent coral. Data was entered into a custom data dictionary 

on the Trimble data logger and recorded on waterproof data sheets. Videos were recorded to tape using a Sony 

Walkman video recorder, and converted to digital video clips using Final Cut Pro software. 

Chapter 3: Assessment of Classification Accuracy

figure 3.1. Picture of the field crew deploying drop camera (left) and camera approaching bottom (right). 

page 

33 
 

Not all sites were accessible by survey vessel and the drop camera. Shallow, nearshore sites were surveyed by 

snorkel. Sites were categorized in the same way, but in lieu of drop camera video, a digital camera in an underwater housing was used to take pictures. Mangrove target locations were generally assessed from the boat after 

approaching the target as close as possible, and were again documented with digital pictures. In these situations, an exact GPS waypoint could not be taken at the survey site. A few targets were inaccessible using either 

of these methods due to high surf or unsafe sea conditions and were not surveyed. In addition, several sites 

that were targeted in inland mangrove lagoons were inaccessible by road and could not be surveyed. In a few 

cases, poor sea conditions or turbidity precluded a positive classification of the habitat, and these points were 

removed from the analysis. A total of 481 sites were sufficiently surveyed to be included in the accuracy assessment (Figure 3.2). An additional five survey sites were successfully surveyed, but fell outside the boundaries of 

the final benthic habitat map. 

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0 1 2

Kilometers  ̄

figure 3.2. Red dots depict the location of the 481 sites visited to obtain habitat information for assessment of thematic map accuracy. 

3.2. EVAluATion of AssEssmEnT dATA 

The GPS data were processed using Trimble Pathfinder software. GPS data, which were originally recorded as 

code phase signals, were differentially post-processed to the Continually Operating Reference System (CORS) 

station at St. Thomas, U.S. Virgin Islands (VITH). The true positional accuracy of individual epics was determined 

to be within 1 m for 96% of the points. For each survey site, individual epics were averaged to generate an “average” GPS point. The GPS data were then exported and plotted in ArcGIS along with the corresponding field notes. 

In most cases, the average point 

was a sufficient representation 

of the survey site; however in 

cases where the survey was 

conducted along or crossed a 

polygon edge, the average GPS 

point did not always fall into the 

polygon that was assessed. In 

these cases, the survey point 

was shifted to the portion of the 

transect and polygon that was 

classified (Figure 3.3). For sites 

where no Trimble data was collected (e.g., sites surveyed by 

snorkel), the target GPS point 

was used.		 figure 3.3. Example of case where survey track line, represented by the green points, crossed

more than one habitat type/polygon. Although the “average” point (orange) fell in sand (left), 

the adjacent individual patch reef was the polygon that was actually assessed, therefore the 

point was shifted slightly north (right). 

Chapter 3: Assessment of Classification Accuracy

page 

34 
Prior to analysis, each video clip and digital picture 

was re-analyzed and viewed in concert with the 

benthic habitat map overlaid on the orthophotography. It should be noted that all analysis at this 

stage was made by a photointerpreter independent of the scientist who created the map. Patchiness of the biological cover was assessed at the 

polygon level, and hence it was often necessary to 

adjust the classifications that were initially recorded in the field to reconcile the differences between 

the video and map scales. For example, a site 

may have been classified as continuous seagrass 

based on the video clip alone, but if the patchiness 

of the polygon was actually only 50% - <90% upon 

examination of the imagery, the patchiness for the 

survey point was changed to 50% - <90% (Figure 

3.4). Similar adjustments were sometimes necessary to correctly characterize detailed structure. 

For example, heterogeneous hardbottom classes, 

such as pavement with sand channels, could not 

always be correctly classified from the video alone. 

In other cases, additional information on the position, size and shape of hardbottom features was needed to determine whether the structure should be classified as aggregate reef or a patch reef (either individual or part of 

an aggregated patch reef feature if below the MMU). 

Following these adjustments, data were then spatially joined to the benthic habitat layer to extract the map classification for each point. Sites that differed between field notes and map classification were evaluated both in 

GIS and from video to determine possible source of disagreement. At this stage, additional special cases were 

identified that were a product of the differences in scale between the video data and imagery. For example, there 

were several occurrences where the survey video documented sand with no cover, but the point was located 

within a heterogeneous polygon that was mapped as sand with patchy Seagrass or Algae, Sand with Scattered 

Coral and Rock, or Aggregated Patch Reefs that could only be perceived at the broad scale of the aerial photography. For these cases, the points were only classified for structure based on both the video and imagery. Since 

the mapped polygon cover was not observed in the accuracy assessment video, they were not included in the 

assessment of biological cover. 

In some cases, the patchiness of biological cover within softbottom polygons could not be determined from the 

imagery due to turbidity. These polygons were primarily located within Coral Bay and were mapped with advice 

from the expert review workshop. Accuracy assessment points that fell within these polygons were handled in 

two ways. First, as described above, points that would otherwise have been classified as No Cover were removed from the analysis of biological cover and analyzed for structure only. If algal or seagrass cover was documented in the video, these points were included for major cover (e.g., Seagrass or Algae) but their patchiness 

was classified as Unknown because it cannot be estimated from the remotely sensed imagery and they were not 

included in the detailed cover analysis. In total, 24 sites were excluded in the major biological cover analysis and 

an additional 15 sites were excluded from the detailed biological cover analysis for one of the reasons described 

above. 

Percent coral cover was classified for both hardbottom and softbottom habitats; however it is defined as the percent coral cover on the hardbottom substrate within that polygon (see Chapter 1). If a site was determined to be 

located within a hardbottom polygon but no hardbottom was seen in video (e.g., Aggregated Patch Reefs), coral 

cover could not be sufficiently assessed at that site. Hence, such sites were not included in the error matrix for 

percent coral cover. 

Following this process, 481 points were included in the accuracy assessment analysis for major and detailed 

structure, 457 for major biological cover, 442 for detailed biological cover, and 475 for percent coral cover. 

figure 3.4. Example of case where video survey was conducted over 

an area of continuous seagrass, but examination of the imagery revealed that patchiness of the polygon was 50% - <90%. 

Chapter 3: Assessment of Classification Accuracy

page 

35 
95% CI = Te ± Zα/2(σr

2

)

0.5

Individual cell probabilities = ij j ij nnP j / ˆ

Overall Variance =

r

i

c ii i ii nppPV i

1

)/)() ˆ (

Overall Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

c PVP c

Producer’s Variance = (/)([) )( ]/) ˆ ( 4 2

j ij ij ii i ii ji

r

ij

iiii i ijii npppnpppppV

Producer’s Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

ii V ii

User’s Variance = iiii i ii nppV ii

2 /)() ˆ (

User’s Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

ii V ii

Tau coefficient = Te = (Po – Pr) / (1 – Pr),

where Pr = 1/r. The variance of Tau (Ma and Redmond 1995) was calculated as:

Variance of Tau coefficient = σr

2 = Po(1 – Po) / n(1 – Pr)

2

Individual cell probabilities = ij j ij nnP j / ˆ

Overall Variance =

r

i

c ii i ii nppPV i

1

)/)() ˆ (

Overall Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

c PVP c

Producer’s Variance = (/)([) )( ]/) ˆ ( 4 2

j ij ij ii i ii ji

r

ij

iiii i ijii npppnpppppV

Producer’s Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

ii V ii

User’s Variance = iiii i ii nppV ii

2 /)() ˆ (

User’s Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

ii V ii

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter 3: Assessment of Classification Accuracy3.3. AnAlysis of THEmATiC ACCuRACy 

The thematic accuracy of the St. John benthic habitat map was characterized in several ways from these data. 

Error matrices were computed for the attributes major and detailed geomorphological structure, major and detailed biological cover, and percent coral cover. Overall accuracy, producer’s accuracy, and user’s accuracy were 

computed directly from the error matrices (Story and Congalton 1986). The error matrices were constructed as a 

square array of numbers arranged in rows (map classification) and columns (accuracy assessment, or groundtruthed classification). The overall accuracy (Po

) was calculated as the sum of the major diagonal (i.e. correct 

classifications, divided by the total number of accuracy assessment samples). 

The producer’s and user’s accuracies were calculated to characterize the classification accuracy of individual 

map categories. The producer’s accuracy (omission/exclusion error) is a measure of how well the mapper classified a particular habitat (e.g., the percentage of times that substrate ground-truthed as sand was correctly 

mapped as sand). The user’s accuracy (commission/inclusion error) is a measure of how often map polygons 

of a certain habitat type were classified correctly (e.g., the percentage of times that a polygon classified as sand 

was actually ground-truthed as sand). Each diagonal element was divided by the column total to yield a producer’s accuracy and by the row total to yield a user’s accuracy. 

In addition, the Tau coefficient (Te

), a measure of the improvement of classification accuracy over a random assignment of map units to map categories (Ma and Redmond 1995), was calculated. As the number of categories 

increases, the probability of random agreement (P ) diminishes, and T approaches P . Values of T were calcu­ r e o e 

lated as follows: 

Tau coefficient = Te = (Po – Pr) / (1 – Pr), 

where Pr = 1/r. The variance of Tau (Ma and Redmond 1995) was calculated as: 

Variance of Tau coefficient = σr 

2 = Po(1 – Po) / n(1 – Pr)

2 

Confidence intervals were then calculated for each Tau coefficient at the 95% confidence level (1-α), using the 

following generalized form: 

2

)

0.5 95% CI = Te ± Zα/2(σr 

While stratification ensures adequate evaluation of all map categories, it has the undesired effect of introducing 

bias into the error matrix (Hay 1979; Card 1982). A minimum number of sites were targeted within each mapping 

category, which caused rare map categories to be sampled at a greater rate than common map categories. For 

example, although Sand habitat comprised 44% of the map area, only 23% of the target points were allocated 

for this habitat. Conversely, Aggregated Patch Reefs comprised only 1% of the map area, but received 5% of the 

allocated target sample points. The bias introduced by differential sampling rates was removed using the method 

of Card (1982), which utilizes the known map marginal proportions, i.e. the proportional areas of map categories 

relative to the total map area. The map marginal proportions were calculated as the area of each map category 

divided by the total mapped area of the St. John benthic habitat map. The map marginal proportions were also 

utilized in the computation of confidence intervals for the overall, producer’s, and user’s accuracies (Card 1982; 

Congalton and Green 1999). This method was also used in the recent accuracy assessment of the NOAA Florida 

Keys benthic habitat map (Walker and Foster 2009). 

The known map marginal proportions (πj

) were computed from the GIS layer of the draft benthic habitat map 

for each of the four error matrices (major and detailed geomorphological structure, major and detailed biological 

cover), by dividing the area of each category by the total map area. Marginal proportions were not computed for 

the percent coral cover matrix, as this would have required an estimate of the percent hardbottom within each 

polygon to truly estimate the area of live coral. The map areas were exclusive to categories present in the error 

matrix. For the example of detailed structure category sand, πj was 0.44 (23.3 km2

/53.4km2). The individual cell 

probabilities, i.e. the product of the original error matrix cell values and πj

, divided by the row marginal (total map 

classifications per category), were computed for the off-diagonal elements using the following equation: 

page 

36 
Tau coefficient 

 Te  (Po Pr) / (1 Pr),

where Pr = 1/r. The variance of Tau (Ma and Redmond 1995) was calculated as:

Variance of Tau coefficient = σr

2 = Po(1 – Po) / n(1 – Pr)

2

95% CI = Te ± Zα/2(σr

2

)

0.5

Individual cell probabilities = ij j ij nnP j / ˆ

Overall Variance =

r

i

c ii i ii nppPV i

1

)/)() ˆ (

Overall Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

c PVP c

Producer’s Variance = (/)([) )( ]/) ˆ ( 4 2

j ij ij ii i ii ji

r

ij

iiii i ijii npppnpppppV

Producer’s Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

ii V ii

User’s Variance = iiii i ii nppV ii

2 /)() ˆ (

User’s Confidence Interval = CI = 2/1 )] ˆ ([2 ˆ

ii V ii

 

 

 

 

 

 

Individual cell probabilities = Pˆ

ij jnij / n j

The relative proportions of the cell values within a row of the error matrix were unaffected by this operation, but 

the row marginals were forced to the known map marginal proportions (i.e. the row total of a particular habitat 

now equaled the fraction of map area occupied by that habitat, instead of the total number of accuracy assess

ment points). The estimated true marginal proportions (pi

) were computed as the sum of individual cell probabili

ties down each column of the error matrix. 

The πj

-adjusted overall, producer’s, and user’s accuracies were then computed from the new error matrix, now 

populated by individual cell probabilities. The values of the πj

-adjusted overall and producer’s accuracies dif

fer by design from those of the original error matrix, as they have been corrected for the areal bias introduced 

by the stratified random sampling protocol. The user’s accuracy, in contrast, is not affected. The variances and 

confidence intervals of the overall, producer’s, and user’s accuracies were then computed from the following set 

of equations (Card 1982; Walker and Foster 2009): 

Overall Variance = 
	V (Pˆ

c ) ii ) / ) ni

i

ii i pp

1 

( 

Overall Confidence Interval = CI = Pˆ

c [V(Pˆc )]1/ 2 2

[
 pii

r

ij

Producer’s Variance = V pij 
 ) ˆ ( ii p pii i

4 ( j p ) / n j ( i pii )(
 pi pii )

2 / ni j] ij

 ˆ

ii 2[V ii ( ˆ )]1/ 2 Producer’s Confidence Interval = CI = 

User’s Variance = V
 ii ( ii )/ i

2

ii ni ) ˆ ( p i p

User’s Confidence Interval = CI = 
	 ˆ

ii 2 2/1 )] ˆ ([ V ii

 

 

 

 

­

­

­

Chapter 3: Assessment of Classification Accuracy

r

3.4 ACCuRACy AssEssmEnT REsulTs And disCussion 

major Geomorphological structure
 

Error matrices for major geomorphological Table 3.1. Error matrix for major geomorphological structure.
	

structure are displayed in Tables 3.1 and Accuracy Assessment (i)
 

3.2. The overall accuracy (Po

) at the major 

geomorphological structure level was 96% 

(Table 3.1). The Tau coefficient for equal 

probability of group membership is 0.941 ± 

0.026 (α=0.05). The error matrix in Table 3.2 

is populated by the individual cell probabilities (pij), which in review are the product of 

the original error matrix cell values (Table 

3.1) and the map marginal proportions, divided by the row marginal of the original 

matrix (i.e., total map classifications per catmap data

(j) 

egory). The adjusted overall accuracy, corrected for bias using the true map marginal 

proportions, was 96.7 (±1.7)% (α=0.05). 

The user’s and producer’s accuracies were 

similarly high for both hard and softbottom 

habitats (Table 3.2). 

Hard soft other n-j 

user's 

Accuracy (%) 

Hard 291 8 0 299 97.3% 

soft 10 171 1 182 94.0% 

other 0 0 0 0 n/a 

ni­ 301 179 1 n=481 

Po = 96.0% Producer's 

Accuracy (%) 96.7% 95.5% n/a 

Te = 0.921 ± 0.035 

page 

37 
t

detailed Geomorphological structure 

Error matrices for detailed geomorphological structure are displayed in Tables 3.3 

and 3.4. The overall accuracy (Po

) at the 

detailed geomorphological structure level 

was 85.7%, with a Tau coefficient (Te

) of 

0.846 ± 0.034 (α=0.05) (Table 3.3). The 

adjusted overall accuracy, corrected for 

bias using the true map marginal propor

tions, improved slightly to 88.8 (±2.9)% 

(α=0.05), because the classes that covered the most area were also the most 

correctly interpreted. 

Adjusted user’s accuracy was above 70% 

for all categories with the exception of the 

Spur and Groove and Mud categories, 

which had a calculated user’s accuracy of 60.0% and 63.9%, respectively (Table 3.4). Five of the fifteen points 

mapped as Spur and Groove ware validated as Pavement with Sand Channels. Three of these points were located within the same polygon, along with two points that were positively classified as Spur and Groove. Since the 

difference in the two classifications is primarily determined by the relief of the hard substrate, it is possible that 

varying degrees of relief within individual polygons contributed to this error. Often these two bottom types occur 

adjacent to each other and represent a continuum in range of relief rather than clearly distinct classes. Twelve of 

Hard Soft 

Hard 0.484 0.010 

Soft 0.021 0.484 

Other 0 0 

pi 0.505 0.494 

Producer's 95.8% 97.9% Accuracy (%) 

Producer's CI 2.8% 1.6% (±%)

Map data

(j)

Accuracy Assessment (i)

User's 

Other ʌ-j Accuracy

(%) 

0 0.494 97.9% 

0.001 0.506 95.6% 

0 n/a n/a 

0.001 ʋ=1

n/a Po = 96.7% 

n/a CI(±) = 1.7% 

User's CI

(±%)

1.6% 

3.0% 

n/a 

Table 3.2. Error matrix for major geomorphological structure, using individual

cell probabilities. The overall accuracy and producer’s accuracy were corrected 

for bias using the true map marginal proportions.

Chapter 3: Assessment of Classification Accuracy

­

Table 3.3. Error matrix for detailed geomorphological structure. 

Accuracy Assessment (i) 

map data (j) a 

Aggregate

Reef

Aggregate

Patch Reef

individual

Patch Reef

spur and

Groove

Pavement

Pav w/ sand

Channels

Rock

outcrop

Boulder

Reef Rubble

Rhodolith

sand w/ sCR

sand

mud

land

n-j 

user's 

Accuracy 

(%) 

Aggregate 

Reef 38 1 6 1 46 82.6% 

Aggregate 

Patch Reef 28 1 1 30 93.3% 

individual 

P h R f Patch Reef 9 9 100 .0% 

spur and 

Groove 9 1 5 15 60.0% 

Pavement 1 1 59 2 63 93.7% 

Pav w/ sand 

Channels Channels 1 3 3 27 31 87.1% 

Rock 

outcrop 1 1 34 2 38 89.5% 

Boulder 1 2 10 13 76.9% 

Reef Rubble 1 1 24 2 5 33 72.7% 

Rhodolith 1 1 19 21 90.5% 

sand w/ 

sCR 4 2 15 21 71.4% 

sand 1 1 2 4 117 125 93.6% 

mud 12 23 1 36 63.9% 

land 0 n/a 

ni­ 43 32 12 11 74 32 36 13 29 19 22 134 23 1 n=481 

Po = 85.7% 

Producer's 

Accuracy 

(%) 

88.4% 87.5% 75.0% 81.8% 79.7% 84.4% 94.4% 76.9% 82.8% 100.0% 68.2% 87.3% 100.0% n/a 

page 

38 

Te = 0.846 ± 0.034 
 

the 36 survey sites mapped as Mud were groundtruthed as Sand, the majority of which were located 

in the Coral Bay vicinity. Sand and Mud habitats in 

this area were often difficult to distinguish since the 

substrate composition was often a mixture of fine 

and coarse sediment rather than clearly separate 

and distinct classes. For example, sand was sometimes covered with a thin layer of silt. 

Categories with the lowest adjusted producer’s 

accuracy were Individual Patch Reef, Sand with 

Scattered Coral and Rock, Spur and Groove, and 

Reef Rubble (Table 3.4). In all cases, there was a 

high degree of variance, and two of the categories 

(Individual Patch Reef and Spur and Groove) were 

relatively undersampled compared to the other 

map categories. There were several reasons why 

the resulting number of samples in these two categories were fewer than planned, including inaccessibility, different classifications in the final map 

compared to the draft map, and inadvertent sampling of an adjacent polygon. Patch reef and spur and groove features were often small and/or narrow, so the 

probability of drifting into an adjacent habitat tended to be more frequent than with larger features. Several points 

ground-truthed as Sand with Scattered Coral and Rock (Figure 3.5) were mapped as habitats that were similar 

in structure (i.e. Sand, Reef Rubble and Aggregated Patch Reefs). 

Table 3.4. Error matrix for detailed geomorphological structure, using individual cell probabilities. The overall accuracy and producer’s 

accuracy were corrected for bias using the true map marginal proportions. 

Accuracy Assessment (i) 

figure 3.5. Sand with scattered coral and rock was occasionally confused with other geomorphological structure types composed of varying 

combinations of hard and softbottoms. 

Chapter 3: Assessment of Classification Accuracy

Map data (j) 

Aggregate

Reef

Aggregate

Patch Reef

Individual

Patch Reef

Spur and

Groove

Pavement

Pav w/ Sand

Channels

Rock

Outcrop

Boulder

Reef Rubble

Rhodolith

Sand w/ SCR

Sand

Mud

Land

ʌ-j 

User's 

Accuracy 

(%) 

User's 

CI (±%) 

Aggregate 

Reef 0.0576 0.0015 0.0091 0.0015 0.070 82.6% 11.18% 

Aggregate 

Patch Reef 0.0199 0.0007 0.0007 0.021 93.3% 9.11% 

Individual 

Patch Reef 0.0045 0.005 100.0% 0.00% 

Spur and 

Groove 0.0042 0.0005 0.0023 0.007 60.0% 25.30% 

Pavement 0.0025 0.0025 0.1478 0.0050 0.158 93.7% 6.14% 

Pav w/ Sand 

Channels 0.0018 0.0053 0.0480 0.055 87.1% 12.04% 

Rock 

Outcrop 0.0008 0.0008 0.0271 0.0016 0.030 89.5% 9.96% 

Boulder 0.0011 0.0021 0.0106 0.014 76.9% 23.37% 

Reef Rubble 0.0014 0.0014 0.0325 0.0027 0.0068 0.045 72.7% 15.51% 

Rhodolith 0.0043 0.0043 0.0812 0.090 90.5% 12.81% 

Sand w/ 

SCR 0.0048 0.0024 0.0179 0.025 71.4% 19.72% 

Sand 0.0035 0.0035 0.0070 0.0140 0.4087 0.437 93.6% 4.38% 

Mud 0.0148 0.0284 0.0012 0.044 63.9% 16.01% 

Land n/a n/a n/a 

pi- 0.070 0.025 0.009 0.007 0.171 0.050 0.029 0.014 0.049 0.081 0.035 0.430 0.028 0.001 ʋ=1

Po = 

CI(±) = 

88.8% 

2.9% 

Producer's 

Accuracy 

(%) 

82.3% 80.6% 49.0% 62.0% 86.4% 95.4% 92.7% 77.3% 66.6% 100.0% 50.8% 95.0% 100.0% n/a 

Producer's 

CI (±%) 14.6% 14.2% 31.5% 36.5% 6.3% 3.3% 8.8% 21.6% 20.6% 0.0% 21.7% 2.0% 0.0% n/a 

page 

39 
 

map data

major Biological Cover 

Error matrices for ma

jor biological cover are 

displayed in Tables 3.5 

and 3.6. The overall ac

curacy (Po

) at the major 

biological cover level was 

93.7%, with a Tau coeffi

cient (Te

) of 0.921 ± 0.045 

(α=0.05). The adjusted 

overall accuracy, correct

ed for bias using the true 

map marginal propor

tions, was similar at 93.0 

(±2.4)% (α=0.05). 

­

Chapter 3: Assessment of Classification Accuracy

­

­

­

­

Table 3.5. Error matrix for major biological cover. 

Algae 

Algae 

316 

Accuracy Assessment (i) 

live Coral mangrove seagrass 

1 12 

no Cover 

2 

user's 

n-j Accuracy 

(%) 

331 95.5% 

live Coral 2 5 7 71.4% 

(j) 

mangrove 15 1 16 93.8% 

seagrass 

no Cover 

niProducer's 

Accuracy (%) 

6 65 71 91.5% 

5 

329 

96.0% 

6 15 77 

83.3% 100.0% 84.4% 

27 32 84.4% 

30 n=457 

90.0% Po = 93.7%

Te = 0.921 ± 0.045 

Accuracy was high for all 

major cover levels. The 

category with the lowest 

producer’s and user’s accuracy was Live Coral, but 

the number of accuracy 

assessment points in this 

category was too few to 

robustly assess this category. The low sample size 

was due to the rarity of 

polygons mapped where 

coral was mapped as the 

dominant cover. However, 

a better assessment of the 

accuracy of mapped coral 

cover will be discussed in 

the section Percent Coral 

Cover. The other major 

source of producer’s error 

was in the Seagrass category, due to the misclassification as Algae. 

detailed Biological Cover 

Error matrices for detailed biological cover are displayed in Tables 3.7 and 3.8. The overall accuracy (Po

) at the 

detailed biological cover level was 81.7%, with a Tau coefficient (Te

) of 0.798 ± 0.040 (α=0.05). The adjusted overall accuracy, corrected for bias using the true map marginal proportions, was similar at 81.0 (±3.1)% (α=0.05). 

The greatest source of confusion at the detailed biological cover level was degrees of patchiness within Algae 

and Seagrass categories. For example, the adjusted user’s and producer’s accuracy of the Seagrass 10%-<50% 

were 16.7% and 10.8%, respectively (Table 3.8). Of the 12 sites mapped as Seagrass 10%-<50%, 10 were interpreted to have 50%-<90% patchiness in the accuracy assessment. However, it should be noted there were fewer 

sites surveyed within the 10% - <50% algae and seagrass categories than planned. As described in the methods, 

sites that were surveyed in a sand patch of a polygon that was mapped as patch vegetation were not included in 

the analysis, because the available information was insufficient to identify the major cover in the polygon. Many 

of these sites that were consequently removed were located in polygons that were mapped as submerged vegetation with a patchiness of 10% - <50%, contributing to the final lower sampling size in these categories. It is 

possible that a revised sampling technique, such as more points per polygon or a longer transect, is necessary 

to fully characterize heterogeneous habitats. Map data (j) 

Algae 

Live Coral 

Mangrove 

Seagrass 

No Cover 

piProducer's 

Accuracy (%) 

Producer's 

±

User's Live No User's CI Algae Mangrove Seagrass ʌ-j Accuracy Coral Cover (±%) (%) 

0.7089 0.0020 0.0272 0.0076 0.746 95.1% 2.4% 

0.0047 0.0085 0.013 64.3% 36.2% 

0.0060 0.0004 0.006 93.8% 12.1% 

0.0147 0.1322 0.147 90.0% 7.1% 

0.0137 0.0741 0.088 84.4% 12.8% 

0.742 0.010 0.006 0.159 0.082 ʋ=1

95.5% 81.2% 100.0% 83.0% 90.3% Po = 93.0% 

2.1% 33.7% 0.0% 9.4% 9.2% CI(±) = 2.4% 

Accuracy Assessment (i)

CI ( %) 

Table 3.6. Error matrix for major biological cover, using individual cell probabilities. The overall accu

racy and producer’s accuracy were corrected for bias using the true map marginal proportions. 

­

page 

40 
Table 3.7. Error matrix for detailed biological cover. 

Accuracy Assessment (i) 

map data (j)

Algae 

10% - <50% 

Algae 

50% - <90% 

Algae 

90% - 100% 

live Coral 

50% - <90% 

live Coral 

90% - 100% 

mangrove 

50% - <90% 

mangrove 

90% - 100% 

seagrass 

10% - <50% 

seagrass 

50% - <90% 

seagrass 

90% - 100% 

no Cover 

90% - 100% n-j 

user's 

Accuracy 

(%) 

Algae 

10% - <50% 16 3 2 1 1 23 69.6% 

Algae 

50% - <90% 9 71 9 1 90 78.9% 

Algae 

90% - 100% 2 16 180 1 1 2 1 1 204 88.2% 

live Coral 

50% - <90% 2 2 100.0% 

live Coral 

90% - 100% 1 1 3 5 0.0% 

mangrove 

50% - <90% 0 n/a 

mangrove 

90% - 100% 1 14 1 16 87.5% 

seagrass 

10% - <50% 2 10 12 16.7% 

seagrass 

50% - <90% 2 22 1 25 88.0% 

seagrass 

90% - 100% 1 3 2 27 33 81.8% 

no Cover 

90% - 100% 4 1 27 32 84.4% 

ni­ 31 93 195 6 0 1 14 6 37 29 30 n=442 

Po = 81.7% 

Producer's 

Accuracy 

(%) 

51.6% 76.3% 92.3% 33.3% n/a 0.0% 100.0% 33.3% 59.5% 93.1% 90.0% 

Te =0.798 ± 0.040 

Table 3.8. Error matrix for detailed biological cover, using individual cell probabilities. The overall accuracy and producer’s accuracy 

were corrected for bias using the true map marginal proportions. Map data (j) 

Accuracy Assessment (i) 

Chapter 3: Assessment of Classification Accuracy

page 

41 

Algae 10% 

- <50% 

Algae 50% 

- <90% 

Algae 90% 

- 100% 

Live Coral 

50% - <90% 

Live Coral 

90% - 100% 

Mangrove 

50% - <90% 

Mangrove 

90% - 100% 

Seagrass 

10% - <50% 

Seagrass 

50% - <90% 

Seagrass 

90% - 100% 

No Cover 

90% - 100% ʌ-j 

User's 

Accuracy 

(%) 

User's CI 

(±%) 

Algae 

10% - <50% 0.0901 0.0169 0.0113 0.0056 0.0056 0.130 69.6% 19.2% 

Algae 

50% - <90% 0.0214 0.1692 0.0214 0.0024 0.214 78.9% 8.6% 

Algae 90% 

- 100% 0.0039 0.0315 0.3544 0.0020 0.0020 0.0039 0.0020 0.0020 0.402 88.2% 4.5% 

Live Coral 

50% - <90% 0.0014 0.001 100.0% 0.0% 

Live Coral 

90% - 100% 0.0024 0.0024 0.0071 0.012 0.0% 0.0% 

Mangrove 

50% - <90% 0.000 n/a n/a 

Mangrove 

90% - 100% 0.0004 0.0056 0.0004 0.006 87.5% 16.5% 

Seagrass 

10% - <50% 0.0019 0.0094 0.011 16.7% 21.5% 

Seagrass 

50% - <90% 0.0034 0.0374 0.0017 0.042 88.0% 13.0% 

Seagrass 

90% - 100% 0.0028 0.0085 0.0056 0.0762 0.093 81.8% 13.4% 

No Cover 

90% - 100% 0.0110 0.0027 0.0741 0.088 84.4% 12.8% 

pi- 0.126 0.226 0.390 0.010 0.000 0.000 0.006 0.018 0.062 0.080 0.082 ʋ=1

Producer's 

Accuracy 

(%) 

71.3% 75.0% 90.9% 13.5% n/a 0.0% 100.0% 10.8% 60.3% 95.4% 90.3% Po = 81.0% 

Ci(±) = 3.1% Producer's 

CI (±%) 11.6% 8.6% 4.1% 8.4% n/a n/a 0.0% 16.0% 14.8% 6.2% 13.0% 
As mentioned previously, seagrass and algae on softbottom habitats were sometimes mapped incorrectly. This 

is to be expected, as it can be difficult to distinguish between the two in remotely sensed imagery. In addition, 

there is often a mix of vegetation types rather than a homogeneous seagrass or algae field. 

Percent Coral Cover Table 3.9. Error matrix for major geomorphological structure and percent coral. 

The error matrix for Accuracy Assessment (i)

Chapter 3: Assessment of Classification Accuracy percent coral cover is 

displayed in Table 3.9. 

The overall accuracy 

(Po

) at the detailed biological cover level was 

85.7%, with a Tau coefficient (Te

) of 0.809 

± 0.042 (α=0.05). As 

mentioned previously, 

a second matrix using 

the true map marginal 

proportions, was not 

computed for percent 

coral cover. 

map data (j) 

softbottom, 

Coral <10% 

softbottom, 

Coral 

10% - <50% 

Hardbottom, 

Coral <10% 

Hardbottom, 

Coral 

10% - <50% 

n-j 

user's 

Accuracy (%) 

softbottom, 

Coral <10% 171 6 177 96.6% 

softbottom, 

Coral 10% - <50% 3 3 0.0% 

Hardbottom, 

Coral <10% 9 172 24 205 83.9% 

Hardbottom, 

Coral 10% - <50% 26 64 90 71.1% 

ni­ 179 0 207 88 n=475 

Po = 85.7% Producer's 

Accuracy (%) 95.0% n/a 83.1% 72.7% 

Te = 0.809 ± 0.042 

Only two of the possible coral categories were present in the map and accuracy assessment data (<10% and 

10%-<50%). Accuracy was very high for the softbottom habitats, where a low amount of coral is to be expected. 

There was lower accuracy for percent coral on hardbottom habitats. The decision between <10% and 10% -

<50% is often difficult to determine, especially if there is a mix of octocorals and sclerectinians. Since percent 

coral cover was recorded at all sites regardless of whether it was the dominant cover type, this is a better measure of coral accuracy than is found under Major Biological Cover. 

3.5 ConClusions 

Although the classification schemes are not directly comparable due to region-specific categories, the level of 

accuracy for detailed structure was similar to that of other recent NOAA benthic habitat maps in the Florida Keys 

(86.2% [91.5% adjusted], Walker and Foster 2009), Palau (90.0%, Battista et al. 2007b), and the Main Hawaiian 

Islands (90.0%, Battista et al. 2007a). 

Comparisons with other accuracy assessments 

at the biological cover level are difficult due to the 

differences in the classification scheme. Previous 

mapping efforts utilized a hierarchical classification scheme to characterize biological cover, in 

comparison to the dominance based scheme used 

here. 

In comparison to the other aforementioned accuracy assessments, which were conducted in 

a subset, or test area, of their respective habitat 

maps, the relative small size of the St. John benthic habitat map enabled the entire mapping area 

to be included in the accuracy assessment. As a 

result, we were able to capture the full diversity of 

habitats in the survey (Figure 3.6) and produce a 

spatially comprehensive evaluation of the thematic 

accuracy. figure 3.6. Juvenile Bluehead Wrasses (Thalassoma bifasciatum) 

gather around a colony of Montastraea sp. 

page 

42 
liTERATuRE CiTEd 

Battista, T.A., Costa, B.M., and S.M. Anderson, S.M. 2007a. Shallow-Water Benthic Habitats of the Main Eight 

Hawaiian Islands (DVD). NOAA Technical Memorandum NOS NCCOS 61, Biogeography Branch. Silver Spring, 

MD. 

Battista, T.A., Costa, B.M., and S.M. Anderson, S.M. 2007b. Shallow-Water Benthic Habitats of the Republic of 

Palau. NOAA Technical Memorandum NOS NCCOS 59, Biogeography Branch. Silver Spring, MD. 

Beyer, H.L. 2004. Hawth’s Analysis Tools for ArcGIS. Available at http://www.spatialecology.com/htools. 

Card, D.H. 1982. Using known map categorical marginal frequencies to improve estimates of thematic map accuracy. Photogrammetric Engineering and Remote Sensing 48: 431-439. 

Cohen, J. 1960. A coefficient of agreement for nominal scale. Educational and Psychological Measurement 20: 

37-46. 

Congalton, R.G. and K. Green. 1999. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. CRC/Lewis Press, Boca Raton, FL. 137 pp. 

Ma, Z. and R.L. Redmond. 1995. Tau coefficients for accuracy assessment of classification of remote sensing 

data. Photogrammetric Engineering and Remote Sensing 61: 435-439. 

Steel, G.D. and J.H. Torrie. (1960) Principles and Procedures of Statistics. McGraw-Hill Book Company, Inc., 

New York. 481 pp. 

Story, M. and R. Congalton. (1986) Accuracy assessment: A user’s perspective. Photogrammetric Engineering 

and Remote Sensing 52: 397-399. 

Walker, B.K. and G. Foster. 2009. Final Report: Accuracy Assessment and Monitoring for NOAA Florida Keys 

mapping: AA ROI-1 (near American Shoal). National Coral Reef Institute, Nova Southeastern University, Dania 

Beach, FL. 32 pp. 

Chapter 3: Assessment of Classification Accuracy

page 

43 
Chapter 3: Assessment of Classification Accuracy

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page 

44 
CHAPTER 4: CONCLUSION 

NOAA’s Biogeography Branch, with support from the U.S. National Park Service, has completed benthic habitat 

mapping and subsequent field validation and accuracy assessment of the nearshore marine environment of St. 

John, U.S. Virgin Islands. An independent accuracy assessment revealed successful overall map accuracies of 

over 90% for major structure and cover classes, and over 80% for detailed structure and cover classes. As a result, these digital map products can be used with confidence by scientists and resource managers for a multitude 

of different applications (Figure 4.1). The scientific and management communities have used previous NOAA 

benthic habitat maps to structure monitoring programs, support management decisions, and establish and manage marine conservation areas in coral reef ecosystems. 

Chapter 4: Conclusion

Figure 4.1. A NOAA diver characterizes seagrass habitat during a monitoring mission in St. John. 

The final delivery consisted of the benthic habitat maps in several formats and all ancillary data 

generated in support of map creation. These 

items are listed in Table 4.1 with a description of 

the format type and quantity when appropriate. 

4.1 MAP SUMMARY STATISTICS 

An area of 131.49 km2 was considered during 

the mapping process; of which, 78.05 km2 were 

designated as Unknown due to water depth and 

clarity issues. The remaining 53.44 km2 were described by 1,939 polygons corresponding to the 

structure and biological cover types of the habitat classification scheme outlined in Chapter 1. 

Table 4.1. Final deliverable items of NOAA’s St. John benthic habitat mapping effort. Additional information is given on the item type and a quantitative descriptor. 

Item Format Quantity 

Benthic Habitat Map GIS 1,940 polygons 

Source Imagery GIS 

Map Atlas PDF 

Interactive Map Project On-line 

Ground Validation Dataset GIS 444 locations 

Accuracy Assessment 

Dataset GIS 481 locations 

Video of Bottom Imaging Quicktime Movie 807 videos 

Final Report PDF 

FGDC-compliant Metadata 

for GIS Files Text 

page 

45 
 

 

 

 

 

 

 

 

Of these 53.44 km2, Unconsolidat- Table 4.2. Area summary of major geomorphological structure classes and the subsets of 

ed Sediment and Coral Reef and detailed structure classes.

Chapter 4: Conclusion Hardbottom each accounted for 

26.71 km2 of Major Structure type 

(Table 4.2). Equivalence in area 

of Unconsolidated Sediment and 

Coral Reef and Hardbottom was 

not an intentional design element; 

rather, it was an unforeseen coincidence. Together, Unconsolidated Sediment and Coral Reef and 

Hardbottom account for 98.98% of 

Major Structure type; the remaining 0.02% corresponds to Artificial

structures. The 0.01 km2 of Artificial

type is located in Cruz Bay at the 

ferry dock and NPS boat dock. 

Detailed Structure map summary 

statistics highlight the composition 

of Major Structure types (Table 4.2). 

Coral Reef and Hardbottom is subdivided into ten Detailed Structure 

categories, while Unconsolidated 

Sediment is segmented into three. 

Note in Table 4.2, that Detailed 

Structure percentages are derived 

from total mapped area, not within 

the corresponding Major Structure 

classification. 

Sand is the most common detailed structure 

type, accounting for 43% of the total mapped 

area (Figure 4.2). Mud and Sand with Scattered Coral and Rock are considerably less 

common Unconsolidated Sediment types, 

accounting for 4.37% and 2.62% respectively. At 16.35% of total area, Pavement is 

the second most dominant structure type 

overall and the predominant detailed structure type within Coral Reef and Hardbottom. 

Other common structure types are Rhodoliths, which account for 8.93% of total area, 

and Aggregate Reef, which contributes to 

6.99% of total area. Although ecologically 

significant, patch reefs, in the form of Individual Patch Reefs and Aggregated Patch 

Reefs, only comprise just over 3% of all the 

nearshore habitat of St. John. 

Biological Cover map summary statistics 

(Figure 4.3) reveal that the overwhelmingly 

dominant Major Cover is Algae, which accounts for 74.28% of the 53.44 km2 study 

area (Table 4.3). About half of the 39.69 km2 

MAJOR 

STRUCTURE 

AREA 

(km2) 

PERCENT 

AREA 

DETAILED 

STRUCTURE 

AREA 

(km2) 

PERCENT 

AREA 

Coral Reef and 

Hardbottom 26.71 49.99 

Rock Outcrop 1.62 3.03 

Boulder 0.74 1.39 

Aggregate Reef 3.74 6.99 

Individual Patch Reef 0.25 0.47 

Aggregated Patch Reef 1.49 2.79 

Spur and Groove 0.33 0.61 

Pavement 8.74 16.35 

Pavement with Sand 

Channels 

2.68 5.02 

Reef Rubble 2.36 4.41 

Rhodoliths 4.77 8.93 

Unconsolidated 

Sediment 26.71 49.99 

Sand 22.98 43.00 

Mud 2.33 4.37 

Sand with Scattered 

Coral and Rock 

1.40 2.62 

Other 

Delineations 

(Land excluded) 

0.01 0.02 Artificial 0.01 0.02 

Total 53.44 100 53.44 100 

Figure 4.2. Chart illustrating the percent cover of each detailed geomorphological structure type for the entire St. John mapping area. Sand being the most 

common structure type and Pavement the most common hardbottom type. 

Rock Outcrop

Boulder

Aggregate Reef

Individual Patch Reef

Aggregated Patch Reef

Spur and Groove

Pavement

Pavement w/ Sand Chan.

Reef Rubble

Rhodoliths 

Percent Area

0 10 20 30 40 50 

Rock Outcrop 

Boulder 

Aggregate Reef 

Individual Patch Reef 

Aggregated Patch Reef 

Spur and Groove 

Pavement 

Pavement w/ Sand Chan. 

Reef Rubble 

Rhodoliths 

Sand 

Mud 

Sand w/ Scattered C/R 

Artificial 

Percent Area 

page 

46 
of algal dominance is covered by a continuous distribution 

(90% - 100%). This is in large part due to the inclusion of 

turf algae as a mapped species, since much of St. John’s 

hardbottom is covered by turf in the absence of live coral. At 

14.68%, Seagrass is the second most common Major Cover type. Areas with No Cover account for 8.84% of the total 

area. Live Coral and Mangrove are rare Major Covers; the 

former constitutes 1.51% and the latter 0.66% of the study 

area. Although live coral colonies exist throughout the St. 

John seascape, the total area of features dominated by live 

coral cover was only 0.81 km2

. Coralline Algae was not found 

to be a Major Cover within the study area. 

Map summary statistics suggested that almost all of the total mapped area is comprised of less than 50% coral cover 

(Table 4.4). There are 9.29 km2 exhibiting a Percent Coral 

Cover of 10% to <50%. 

These areas account 

for 17.39% of the study 

area, while 82.59%, or 

44.12 km2

, have less 

than 10% coral cover. 

Furthermore, Coral 

Cover does not exceed 

50% within any single 

minimum mapping 

unit of the study area. 

For this, it is important to remember the 

influence of minimum 

mapping units in the 

habitat mapping process. It was observed 

that some areas of St. 

John are comprised of 

greater than 50% coral 

cover, but these areas 

were not large enough 

to be mapped with a 

minimum mapping unit 

of 1,000 m2

. 

Table 4.3. Summary of areas for each biological cover and respective percent cover modifier mapped

in St. John. 

Mangrove No Cover 

Algae 

Seagrass 

Live Coral 

Figure 4.3. Chart depicting the prevalence (~ 75%) of Algae as the dominant biological cover type in the mapped 

area of St. John. 

Chapter 4: Conclusion

MAJOR COVER AREA (km2) PERCENT 

AREA PERCENT COVER AREA (km2

) PERCENT AREA 

39.69 74.28 

10% - <50% 7.16 13.40 

Algae 50% - <90% 12.07 22.59 

90% - 100% 20.46 38.30 

7.85 14.68 

10% - <50% 0.48 0.89 

Seagrass 50% - <90% 2.47 4.63 

90% - 100% 4.90 9.17 

0.81 1.51 

10% - <50% 0.12 0.23 

Live Coral 50% - <90% 0.10 0.19 

90% - 100% 0.58 1.09 

0.35 0.66 

10% - <50% 0.01 0.01 

Mangrove 50% - <90% 0.01 0.02 

90% - 100% 0.34 0.63 

0 0 

10% - <50% 0 0 

Coralline Algae 50% - <90% 0 0 

90% - 100% 0 0 

No Cover 4.73 8.84 90% - 100% 4.73 8.84 

Artificial 0.01 0.02 N/A 0.01 0.02 

Total 53.44 100.00 53.44 100.00 

4.2 COMPARISON TO 

PREVIOUS NOAA HABITAT MAPS OF ST. JOHN 

The 2009 benthic habitat mapping effort described in this 

report marks the second such effort NOAA has conducted to map the shallow-water coral reef ecosystems of St. 

John, USVI. The Kendall et al. (2001) digital benthic habitat maps of St. John were a significant improvement over 

previous paper copy maps (Beets et al. 1986). However, 

as the complexities of resource management and the capabilities of mapping techniques developed over the past 

Table 4.4. Area summary of percent coral cover for St. John 

habitats. 

PERCENT 

CORAL COVER 

AREA (m2) AREA 

(km2) 

PERCENT 

AREA 

0 - <10% 44,131,783 44.13 82.59 

10% - <50% 9,293,135 9.29 17.39 

50% - <90% 0.00 0.00 0.00 

90% - 100% 0.00 0.00 0.00 

N/A 10,548 0.01 0.02 

Total 53,435,466 53.44 100.00 

page 

47 
Chapter 4: Conclusiondecade, the management and scientific communities Table 4.5. Comparison of basic map characteristics between a 

previous NOAA effort (2001) and the current maps of St. John have required benthic habitat maps with greater spa­ (2009). tial and thematic detail. In response to these requests, 

NOAA, in cooperation with the U.S. National Park Service, has completed new fine-scale habitat maps that 

reflect the most current conditions at the Virgin Islands 

Coral Reef National Monument, Virgin Islands National Park and the surrounding waters. Components of 

this new mapping product include an expanded habitat classification scheme (as described in Chapter 1), 

smaller minimum mapping units, more recent imagery, 

and improved positional accuracy (Table 4.5). 

NOAA’s revised approach to mapping nearshore coral 

reef ecosystems has provided significant advantages 

to better represent the natural environment. As displayed in Table 4.5, the 2009 maps were created with finer-scale mapping standards in both scale of delineation 

and minimum mapping unit. The map interpreter delineated polygon boundaries at a scale of 1:2,000, which is 

three times as spatially resolute as that of the 1:6,000 of the 2001 mapping effort. In addition, the source imagery 

of the 2009 habitat maps had a pixel resolution of 0.3 m, as compared to the 2.4 m resolution imagery used by 

Kendall et al. (2001). These factors resulted in enhanced line accuracy and line detail as more vertices were able 

to be created along the same amount of line distance with a more detailed view of the seafloor. 

A reduction in MMU from approximately 4,000 m2 to 

1,000 m2 in the 2009 mapping effort, had a large impact 

on the final content of the habitat map product. The 

smaller minimum mapping unit resulted in over three 

times as many polygons and about three times as small 

average polygon area (Table 4.5). Figure 4.4 illustrates 

the influence of minimum mapping unit on the delineation of patch reefs outside of Reef Bay. Smaller patch 

reefs that were formerly too small to map individually 

(< 4,046 m2), under the 2001 standards, are delineated 

as separate polygons in the 2009 habitat map. Additionally, reduced MMUs allow for more accurate depictions 

of other patchy environments, as patches were more 

readily delineated. For instance, large pavement areas 

formerly mapped as homogeneous hardbottom are 

now depicted as pavement with smaller sand patches 

intermixed throughout the broader polygon. The true 

heterogeneous nature of many marine features was 

more accurately mapped due to the reduction in minimum mapping unit. 

NOAA MAPPING EFFORT 

2001 2009 

MAP 

Source Imagery Date 1999 2007 

Scale of Delineation 1:6,000 1:2,000 

Minimum Mapping Unit (m2) 4,046 1,000 

Positional Accuracy (m) 4.31 (+/- 5.2) 2.15 (+/- 0.7) 

FEATURE

Number of Polygons 537 1,939 

Mean Polygon Area (m2) 173,971 53,378 

Sum of Polygon Edges (km) 1,137 2,303 

Mean Polygon Edge (km) 2.12 1.19 

2009 Habitats 

2001 Habitats 

Figure 4.4. Comparison of 2001 and 2009 NOAA habitat boundaries to illustrate the influence of minimum mapping unit on the 

delineation of patch reefs outside of Reef Bay. 

Marine systems are recognized as dynamic, and subject to changes ranging from a single storm event to longterm ecological shifts due to climate change. It was essential for NOAA to use the most current, available source 

imagery from which to generate the new benthic habitat maps. High resolution orthophotography collected in 

late 2007 afforded a more recent depiction of the habitats of St. John, as opposed to the 1999 aerials used in 

Kendall et al. (2001). 

It is well documented that St. John has experienced changes in the coral environment, particularly live coral 

cover, over the past decade (Waddell and Clarke 2008). NOAA’s 2009 mapping effort supports this conclusion 

on softbottom habitats as well. In comparison to Kendall et al. (2001), preliminary spatial comparisons have indicated that seagrass growth has increased dramatically in areas off the coast of St. John. For instance, softbottoms covered by seagrass in Rendezvous Bay have increased from 0.22 km2 in 1999 to 0.74 km2 in 2007 (Figure 

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48 
4.5). Growth of 0.52 km2 of seagrass in a 1.23 km2 embayment, such as Rendevous Bay, over an 8 year period 

is significant development of submerged aquatic vegetation. The present map results indicate that other bays 

on the south shore, including Reef Bay, Europa Bay and Little Lameshur Bay, have experienced similar trends 

in seagrass growth. 

1999 2007 

Figure 4.5. Imagery time-series of Rendezvous Bay depicting growth of seagrass beds between 1999 (left) and 2007 (right). The 

yellow polygon outlines the area of new seagrass growth. 

Chapter 4: Conclusion

Beyond the changes in mapping technique and standards, NOAA’s 2009 effort marked a significant alteration of 

the benthic habitat classification scheme used to map other coral reef ecosystems. As outlined in Chapter 1.1 

Comparison to Previous NOAA Habitat Classification Schemes, treatment of the biological cover classification 

has evolved over the years. In Kendall et al. (2001), biological cover was not explicitly stated for each feature in 

the map. Instead, the specific biological cover type was only reported for softbottoms colonized by submerged 

aquatic vegetation. For example, sand bottoms with patchy seagrass were fully reported in the old scheme. 

However, linear reefs colonized by a mix of turf algae and gorgonians were only classified as Linear Reef, with 

no reference to biological cover. Moreover, the Kendall et al. (2001) scheme made no reference to the amount 

of live coral cover present on polygon features (Figure 4.6). In contrast, the 2009 effort described the percentage 

of live coral cover in ranges for every seafloor feature. Other differences exist between the habitat classification 

scheme used in 2001 and that of 2009; including division of some structure types into more detailed groups. For 

instance, Colonized Bedrock was subdivided into Rock Outcrop and Boulder, with an associated dominant biological cover. These differences in habitat classification scheme make a direct comparison between NOAA-generated, St. John habitat maps difficult. An analysis 

comparing both maps is beyond the scope of this 

report, but should be considered in future efforts. 

Overall, the transition to the current version of 

NOAA’s dominance habitat classification scheme 

from previous iterations was a success. As described in Chapter 3.5 Conclusions, the 85.7% accuracy achieved for detailed structure in NOAA’s 

2009 St. John benthic habitat maps was similar to 

that of other recent NOAA benthic habitat maps in 

the Florida Keys (86.2%, Walker and Foster 2009), 

Palau (90.0%, Battista et al. 2007b), and the Main 

Hawaiian Islands (90.0%, Battista et al. 2007a). 

This indicates that the needs of coral reef managers and scientists for a dominance based classification scheme were met, with no loss in thematic 

map accuracy. 

Figure 4.6. A large colony of boulder coral (Montastraea annularis) may 

have varying percentages of live coral cover. 

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Chapter 4: Conclusion4.3 PROJECT DELIVERABLES 

The NOAA and NPS collaborative effort to map the benthic habitats of St. John resulted in a suite of products. 

These products were provided directly to NPS project partners by data drive and are available to the public on 

a NOAA Biogeography Branch website devoted to this mapping effort (http://ccma.nos.noaa.gov/ecosystems/ 

coralreef/benthic_usvi.html). The project deliverables include: 

• Benthic habitat maps in GIS format, 

• Remotely sensed imagery, including satellite and airborne imagery, 

• Underwater video of ground validation and accuracy assessment field sites, including GIS files of their 

locations, 

• Classification manual (contained in this report), 

• Description of the specific methods used to create the habitat maps (contained in this report), 

• Assessment of the thematic accuracy of the maps (contained in this report), 

• FGDC-compliant metadata for all GIS products, 

• Map atlas panels in PDF format, and 

• An interactive, web-based map that allows users to query and display all spatial datasets and 

underwater video. 

4.4 FUTURE U.S. VIRGIN ISLANDS MAPPING ACTIVITIES 

NOAA’s Biogeography Branch is undertaking an effort to develop similar habitat maps of the moderate depth 

area (20 m – 55 m) south of St. John, including the Mid-Shelf Reef. The same habitat classification scheme from 

the shallow-water maps will be applied to habitat maps derived from acoustic data collected with a multibeam 

echosounder (MBES). The Biogeography Branch has developed a semi-automated classification technique, 

combining object and pixel-based approaches to classify acoustic data. The moderate depth mapping area 

begins at the deepest edge of the shallow-water mapping described in this report (see figure in Introduction). 

Integration of the shallow-water mapping with the moderate depth mapping will provide NPS and others with one 

seamless habitat map derived from two different technologies. 

Upon completion of the moderate depth mapping effort, the Biogeography Branch, in collaboration with NOAA’s 

Coastal Services Center, will implement a translation of the NOAA dominance habitat classification scheme 

for coral ecosystems (described in Chapter 1) to the Coastal and Marine Ecological Classification Standard 

(CMECS) (Madden et al. 2009). CMECS is a national-scale classification scheme that describes an aquatic setting and provides additional detail through five underlying components that describe different aspects of the relevant ecology. Project partners will evaluate the “cross-walking” of these two classification schemes to determine 

the ability of CMECS to capture the needs of the coral reef management and scientific communities currently 

described in NOAA’s scheme. 

Using the knowledge gained from the St. John integrated mapping effort, the Biogeography Branch will conduct 

a similar approach to St. Croix, U.S. Virgin Islands. The project includes acquisition of acoustic data and production of benthic habitat maps for the Buck Island Reef National Monument (BUIS) and the Salt River Bay National 

Historical Park and Ecological Reserve (SARI) (Figure 4.7). While NOAA and NPS have collaboratively conducted extensive habitat mapping and biological monitoring inside and outside parts of BUIS and SARI, funding 

and vessel access has never afforded the opportunity to conduct complete bathymetric and seafloor characterization within all of the marine protected areas (MPA). The Biogeography Branch proposes to conduct small boat 

operations using acoustic systems which are ideally suited to mapping the remaining shallow areas, to produce 

integrated shallow to deep water bathymetric and habitat maps within the MPA’s. 

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50 
Chapter 4: Conclusion 

Figure 4.7. Seafloor mapping of Buck Island Reef National Monument and Salt River Bay National Historical Park and Ecological Reserve 

and adjacent areas of St. Croix, USVI. Previously collected acoustic data is displayed with management boundaries and proposed mapping areas. 

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51 
Chapter 4: ConclusionLITERATURE CITED 

Battista, T.A., B.M. Costa, and S.M. Anderson, S.M. 2007a. Shallow-Water Benthic Habitats of the Main Eight 

Hawaiian Islands (DVD). NOAA Technical Memorandum NOS NCCOS 61, Biogeography Branch. Silver Spring, 

MD. 

Battista, T.A., B.M. Costa, and S.M. Anderson. 2007b. Shallow-Water Benthic Habitats of the Republic of Palau. 

NOAA Technical Memorandum NOS NCCOS 59, Biogeography Branch. Silver Spring, MD. 

Beets, J., L. Leewand, and E.S. Zullo. 1986. Marine community descriptions and maps of bays within the Virgin 

Islands National Park/Biosphere Reserve. Biosphere Reserve Research Report Number 2, National Park Service. 118 pp. 

Kendall, M.S., C.R. Kruer, K.R. Buja, J.D. Christensen, M. Finkbeiner, R.A. Warner, and M.E. Monaco. 2001. 

Methods Used to Map the Benthic Habitats of Puerto Rico and the U.S. Virgin Islands. NOAA Technical Memorandum NOS NCCOS CCMA 152. Silver Spring, MD. 

Madden, C.J., K. Goodin, R.J. Allee, G. Cicchetti, C. Moses, M. Finkbeiner, D. Bamford. 2009. Coastal and Marine Ecological Classification Standard, Version III. NOAA and NatureServe. 109 pp. 

Waddell, J.E. and A.M. Clarke (eds.). 2008. The State of Coral Reef Ecosystems of the United States and Pacific 

Freely Associated States: 2008. NOAA Technical Memorandum NOS NCCOS 73. Biogeography Branch. Silver 

Spring, MD. 569 pp. 

Walker, B.K. and G. Foster. 2009. Final Report: Accuracy Assessment and Monitoring for NOAA Florida Keys 

mapping: AA ROI-1 (near American Shoal). National Coral Reef Institute, Nova Southeastern University, Dania 

Beach, FL. 32 pp. 

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acknowledgements 

Funding for this study was provided by the U.S. National Park Service. This report would not have been possible 

without the numerous people who shared their data, information and time throughout this process. We appreciate the support of Park Service staff including Jeff Cross, Rafe Boulon and Jeff Miller, as well as Caroline Rodgers from the U.S. Geological Survey. Also, NPS boat captains, Dave Sapio and Jessica Hornbeck, were critical 

in maintaining a safe and productive field effort. An expression of thanks goes to NOAA’s CCMA and CRCP for 

the ability to provide the labor necessary to complete this mapping effort. As always, the entire Biogeography 

Branch provided endless support. Thanks to Jamie Higgins for organizing the content of this report into what you 

see before you. Many thanks to Kim Woody for answering the many questions that came up during the mapping 

process. Finally, Charlie Menza and Zach Hecht-Leavitt were instrumental in acquiring and processing field data 

and their work is greatly appreciated. 

Acknowledgements

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United states department of commerce

gary locke

secretary

national oceanic and atmospheric administration

Jane lubchenco

administrator

national ocean service

John H. dunnigan

assistant administrator

U.S. DEPARTMENT OF COMMERCE

NAT OI NAL OCEANIC AND ATMOSPHERIC ADMINISTRAT OI N