National Park Service 

U.S. Department of the Interior 

Natural Resource Program Center 

Landsat Derived Map and Landcover Descriptions for 

Gates of the Arctic National Park and Preserve 

Natural Resource Technical Report NPS/GAAR/NRTR—1999/001 
ON THE COVER 

Thematic Mapper satellite image mosaic for Gates of the Arctic National Park and Preserve. 

Mosaic by: EarthSat Corp. 
Landsat Derived Map and Landcover 

Descriptions for Gates of the Arctic National Park 

and Preserve 

Natural Resource Technical Report NPS/GAAR/NRTR—1999/001 

Keith Boggs 

Ann Garibaldi 

Alaska Natural Heritage Program 

Environment and Natural Resources Institute 

University of Alaska Anchorage 

707 A Street, Anchorage, Alaska 99501 

Todd Helt 

Jennifer L. Stevens 

EarthSatellite Corporation 

6011 Executive Blvd, Suite 400 

Rockville, Maryland 20852-3801 

October 1999 

U.S. Department of the Interior 

National Park Service 

Natural Resource Program Center 

Fort Collins, Colorado 
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Please cite this publication as: 

Boggs, K., A. Garibaldi, J. L. Stephens, and T. Helt, 1999. Landsat derived map and landcover 

descriptions for Gates of the Arctic National Park and Preserve. Natural Resource Technical 

Report NPS/GAAR/NRTR—1999/001. National Park Service, Fort Collins, Colorado. 

NPS D-48, October 1999 
TABLE OF CONTENTS 

LIST OF TABLES

LIST OF FIGURES

ACKNOWLEDGEMENTS

ABSTRACT

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

 

1.1 Background 

1.2 Scope of the Project 

1.3 Literature Review 

1.4 Description of Project Area and Environment 

1.5 Ecoregions and Climate Influences on Landcover 

1.6 Generalized Surficial Geology Interpretation 

2. METHODS .........................................................................16 

 

2.1 Overview Of The Landcover Classification System 

2.2 Pre-processing of Satellite Image Data 

2.3 Pre-processing of FirePro Database 

2.4 Development of a Preliminary (Pre-Field Work) Landcover Map 

2.5 Sampling Design and ‘Field Verification Area’ Selection 

2.6 Field Data Collection 

2.7 Development and Evaluation of Spectral Signature Database 

2.8 Supervised Maximum Likelihood Satellite Image Classification 

2.9 Spectral and Environmental Modeling 

2.9.1 Three Stages of the Modeling 

2.9.2 Summary of Key Data Layers Used for Modeling 

2.9.3 Consideration of Ecoregions in Modeling and Editing 

2.9.4 Modeling to Reduce Spectral Confusion Between Mapping 

Classes 

2.10 Raster Editing and Filtering Approach 

2.11 Quality Control and Evaluation 

 

3. RESULTS AND DISCUSSION ................................................61 

 

3.1 Distribution of Landcover within GAAR 

3.2 Accuracy Assessment 

3.3 Discussion of Accuracy of Landcover Classes 

3.4 Discussion of Applications and Limitations 

3.5 Key to Landcover Classes 

3.6 Landcover Class Descriptions 
3.7 Plant Association Description 

3.8 Surficial Geology Influences on Landcover 

LITERATURE CITED ................................................................. 196 

GLOSSARY ...............................................................................203 

APPENDICES

METADATA

 

INTERACTIVE MAP
LIST OF TABLES 

 

Table 1. List of data layers used or produced to derive the GAAR Landcover 

 Map (1997-1999). 

 

Table 2. Landcover classes used in the field to map GAAR. 

Table 3. Preliminary map classes for GAAR from the scoping meeting. 

 

Table 4. Plant associations found in GAAR and arranged by GAAR. 

 

Table 5. Number of Field Verification Areas by Landsat scene by surficial 

 geology type by ecoregion. 

 

Table 6. Number of Field Verification Areas found on each aspect per Landsat 

 scene by ecoregion by surficial geology type. 

Table 7. Ground cover categories and definitions (adapted from Jensen et al. 

 1992). 

Table 8a. Modeling parameters for Landsat TM Path 73, Row 12. 

 

Table 8b. Modeling parameters for Landsat TM Path 73, Row 13. 

 

Table 8c. Modeling parameters for Landsat TM Path 75, Row 12. 

 

Table 8d. Modeling parameters for Landsat TM Path 75, Row 13. 

 

Table 8e. Modeling parameters for Landsat TM Path 77, Row 12. 

 

Table 8f. Modeling parameters for Landsat TM Path 77, Row 13. 

 

Table 9. Landcover composition of buffered GAAR area (based on 2 acre 

 minimum mapping unit (MMU)). 

Table 10a. Confusion matrix for landcover map x accuracy assessment data 

 (5 acre MMU landcover). 

Table 10b. Confusion matrix for landcover map x training data (5 acre MMU 

landcover). 

Table 11a. Confusion matrix for general (22 class) landcover map x accuracy 

 assessment data (5 acre MMU landcover). 

Table 11b. Confusion matrix for general (22 class) landcover map x training 

signature data (5 acre MMU landcover). 
LIST OF TABLES continued 

Table 12. Analysis of number and size of polygons for each landcover class. 

 

Table 13. Percent cover of landcover classes for the major surficial geology features 

 in GAAR. 
LIST OF FIGURES 

 

Figure 1. Location of GAAR 

Figure 2. Landsat Thematic Mapper data selected for deriving the 

landcover map 

Figure 3a. Ecoregions as defined by Gallant et al. (1995) of GAAR 

Figure 3b. Longitudinal cross-section of ecoregions, vegetation, and 

topography of GAAR 

Figure 4. Low relief hills and terraces in the arctic foothills 

ecoregion 

Figure 5. Idealized cross-section of a mountain valley in the south half 

of the GAAR showing various surficial geology deposits and 

landcover types 

Figure 6. Valley in northern half of GAAR 

Figure 7. Valley in South half of GAAR 

Figure 8. Valley in the interior forested lowlands and uplands 

ecoregion 

Figure 9a. Flowchart for project overview 

Figure 9b. Flowchart for preprocessing of imagery 

Figure 9c. Flowchart for preliminary spectral classification 

Figure 9d. Flowchart for post-field classification refinement 

Figure 9e. Flowchart for environmental modeling 

Figure 9f. Flowchart for evaluation of landcover map 

Figure 10. Mosaic design of primary Landsat TM scenes (with FirePro data) 

Figure 11. Landscape strata used for placement of the 1998 Field 

Verification Transects 

Figure 12. Field form used to gather fly-over information per 

polygon. 
LIST OF FIGURES continued 

Figure 13. Vegetation description form for ‘ground’ polygon 

Information 

Figure 14. Physical site description form for ‘ground’ polygon 

Information 

Figure 15. Example of Illumination profile for training signatures 

Figure 16. Examples of Band 5 profile for training signatures 

Figure 17. Profile for entire GAAR area for elevation and training 

Signatures 

Figure 18a. Profile for Path 73, Row 12 Landsat TM bands 3,4,5 and 

training signatures 

Figure 18b. Profile for Path 73, Row 13 Landsat TM bands 3,4,5 and 

training signatures 

Figure 18c. Profile for Path 75, Row 12 Landsat TM bands 3,4,5 and 

training signatures 

Figure 18d. Profile for Path 75, Row 13 Landsat TM bands 3,4,5 and 

training signatures 

Figure 18e. Profile for Path 77, Row 12 Landsat TM bands 3,4,5 and 

training signatures 

Figure 18f. Profile for Path 77, Row 13 Landsat TM bands 3,4,5 and training 

 signatures 

Figure 19a. Profile for Path 73, Row 12 TNDVI and training signatures 

Figure 19b. Profile for Path 73, Row 13 TNDVI and training signatures 

Figure 19c. Profile for Path 75, Row 12 TNDVI and training signatures 

Figure 19d. Profile for Path 75, Row 13 TNDVI and training signatures 

Figure 19e. Profile for Path 77, Row 12 TNDVI and training signatures 

Figure 19f. Profile for Path 77, Row 13 TNDVI and training signatures 

Figure 20. Profile for slope of all training signatures in GAAR 
LIST OF FIGURES continued 

Figure 21. Patches of dense-open white spruce forest mixed with other 

types 

Figure 22a&b. Open black spruce-like forest (35% black spruce) 

Figure 23. Mature open white spruce stands along river (45 % spruce) 

 

Figure 24a&b Spruce-lichen woodland (10-15% spruce and mat of lichen) 

Figure 25. Spruce woodland on side slope (20% white spruce) 

Figure 26a&b. Closed paper birch-aspen forest (85% paper birch) 

Figure 27. Closed Balsam Poplar 

Figure 28a&b. Open paper birch-aspen forest (30-35% paper birch on south 

 aspect sideslope 

Figure 29a&b. Open balsam poplar forest (40% balsam poplar) with thick 

alder shrub understory 

Figure 30a&b. Closed spruce-broadleaf forest (20% white spruce, 40% balsam 

poplar) 

Figure 31a&b. Open spruce-broadleaf forest (10% spruce, 15-20% paper birch) 

Figure 32a&b. Closed tall alder shrub on steep side slope with scattered white 

spruce and paper birch 

Figure 33a&b. Open tall shrub (alder) on upslope, with patches of closed tall 

shrub 

Figure 34a&b. Shrub birch-willow-tussock tundra 

Figure 35a&b. Shrub birch-ericaceous-willow in valley (50% dwarf birch, 

25% prostrate shrub) 

Figure 36a&b. Closed low willow (75% willow) 

Figure 37a&b. Prostrate shrub-rock in arctic foothills (45% dryas, 40% bare 

rock) 

Figure 38a&b. Prostrate shrub-lichen (30% prostrate shrub, 25% bare rock, 

30% lichen) 
LIST OF FIGURES continued 

Figure 39a&b. Prostrate shrub (55% prostrate shrub, 25% herbaceous, 

10% bare rock, 5% water, 5% moss) 

Figure 40a&b. Dry herbaceous (clumps of graminoid grasses) on lateral sand 

dunes along the Killik River 

Figure 41. Mesic herbaceous (70% herbaceous, 25% moss, 5% dwarf 

shrub, 80% tussocks) 

Figure 42. Wet herbaceous area on edge of lake 

Figure 43a&b. Sparsely vegetated steep rock and talus slope (~15% 

dryas/moss) 

Figure 44. Bedrock interspersed with a sparse covering of prostrate 

shrub 

Figure 45. Landsat image that has silty water (blue color), clear water 

(black and dark blue) and an area mapped as mosaic/patterned 

vegetation outlined by the polygon 

Figure 46. Partially stabilized sand dunes along Killik River 

Figure 47. Salix alaxensis plant association 

Figure 48. Salix lanata subspecies richardsonii plant association 

Figure 49. Salix lanata subspecies richardsonii/Carex membranacea plant 

 association 

Figure 50. Betula glandulosa/Carex bigelowii plant association 

Figure 51. Salix lanata subspecies richardsonii/Carex bigelowii plant

association 

Figure 52. Salix planifolia subspecies pulchra/Carex bigelowii plant association 

Figure 53. Salix planifolia subspecies pulchra/Carex aquatilis plant association 

Figure 54. Betula glandulosa plant association 

Figure 55. Lichen-Betula Glandulosa plant association 

Figure 56. Salix planifolia subspecies pulchra (open) plant association 
LIST OF FIGURES continued 

Figure 57. Dryas octopetala-rock plant association 

Figure 58. Vaccinium uliginosum/fructicose lichen plant association 

Figure 59. Dryas octopetala-Cassiope tetragona plant association 

Figure 60. Dryas octopetala plant association 

Figure 61. Salix reticulata plant association 

Figure 62. Carex bigelowii plant association 

Figure 63. Carex membrancea plant association 

Figure 64. Eriophorum russeolum plant association 

Figure 65. Arctophila fulva plant association 

Figure 66. Carex aquatilis plant association 

Figure 67. Carex saxatilis plant association 

Figure 68. Eriophorum angustifolium plant association 

Figure 69. Landsat image of bedrock showing covering of prostrate shrub 

 [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 70. Landsat image of colluvial slope in arctic foothills ecoregion 

 [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 71. Colluvial slope in the arctic foothills ecoregion 

Figure 72. Solifluction lobes 

Figure 73. Idealized cross-section of a solifluction lobe 

Figure 74. Rock glacier in the Brooks Range ecoregion 

Figure 75. Landsat image of alluvial fans north of treeline [Scale = 

 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 76. Alluvial fan in the South half of GAAR 
LIST OF FIGURES continued 

Figure 77. Alluvial fan North of treeline 

 

Figure 78. Landsat image of glacial till in the south half of GAAR 

 [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 79. Landsat image of glacial till north of treeline [Scale = 

 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 80. Landsat image of lacustrine deposits [Scale = 1:63,360, 

 Landsat TM bands 4,5,3 (RGB)] 

Figure 81. Idealized cross-section of geomorphic and vegetation succession 

 on a floodplain (adapted from Krieg and Reger 1982). 

Figure 82. Oxbows on floodplain altered by ground ice 

Figure 83. Landsat image of floodplain surficial geology type in the south 

 half of GAAR [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 84. Landsat image of the floodplain surficial geology type in the north 

 half of GAAR [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 85. River floodplain north of treeline dominated by willows 

 (Salix) and tussock tundra 

Figure 86. Stream in the south half of GAAR whose floodplain is 

 dominated by alder (Alnus) and willow (Salix) 

Figure 87. Stream in the north half of GAAR whose floodplain is 

 dominated by willow (Salix) 

Figure 88. Pingo (~40 m diameter) in alluvial valley 

Figure 89. Idealized representation of the formation of an ice wedge polygon 

 according to the contraction crack theory. 

Figure 90. Landsat image of thermokarst [Scale = 1:63,360, Landsat TM 

 bands 4,5,3 (RGB)] 

Figure 91. Thermokarst north of Anaktuvuk Pass 

Figure 92. Water tracts on a loess covered bedrock outcrop 

 in the arctic foothills ecoregion 
APPENDICES 

Appendix 1. Key to landcover classes for GAAR 

 

Appendix 2. The mean and range in elevation for field sampled polygons 

based on comparison with digital elevation model 

 

Appendix 3. Aggregated surficial geology units - from Hamilton (1999) - used for 

 the surficial geology map 

 

Appendix 4. Percent cover of landcover classes for the major surficial geology 

features south of treeline 

 

Appendix 5. Percent cover of landcover classes for the major surficial geology 

features north of treeline in GAAR including the 10-mile buffer 

Appendix 6. Percent cover of surficial geology types north and south of treeline 

in GAAR 

 

Appendix 7. The mean slope (%) for each landcover class 

 

Appendix 8. Comparison of hierarchical levels of GAAR landcover map 

classification adapted from Viereck et al. 1992 and the national 

vegetation classification system (Grossman et al., 1998) 

 

Appendix 9. List of plant species identified during ground sampling, 1998 

 

Appendix 10a. Percent cover and acreage of landcover classes for the different 

land jurisdictional categories for GAAR 

 

Appendix 10b. Administrative Park Boundaries in the GAAR Study Area 
ACKNOWLEDGEMENTS 

The authors wish to thank and acknowledge the National Park Service-Alaska 

Support Office (NPS-AKSO) for financial support of this project, and GAAR staff for 

logistic support for data collection in GAAR. We also thank Rob Lipkin (Alaska 

Natural Heritage Program) for help identifying plant species, Julie Michaelson and 

Julia Lenz (Alaska Natural Heritage Program) for reviewing the draft report, Wanda 

Seamster (Environment and Natural Resources Institute) for producing several of the 

graphics, and Michael Okoye, Gregory Koeln and Greg Rowe (EarthSat) for writing 

portions of the document. A special thanks goes to Denny Grossman and Anthony 

Curtis (The Nature Conservancy) for their advice and tremendous support in pursuing 

this project and ensuring its success. Jess Grunblatt (National Park Service), Page 

Spencer (National Park Service), George Dickison (National Park Service), Patty 

Rost (National Park Service), Jeff Mow (National Park Service), Mike Haubert 

(National Park Service), Craig Johnson (National park Service), Buster Points 

(National Park Service), Beth Koltun (National Park Service), Jim Drake (The Nature 

Conservancy), Kathleen O’Keife (Greenhorne & O’Mara), Will Koenitzer (Forest 

Data Inc.), and Ray Kreig (Ray Kreig and Associates) all gave valuable advice in the 

initial stages of the project. Andy Waxman (Waxman Development Services) 

provided essential programming for development of the Interactive Map product. We 

especially thank Sara Wesser (National Park Service) for reviewing the map and this 

document, and for her patience, help, and input in all stages of the project. 

Commercial off-the-shelf (COTS) software was used for most of the image 

processing and GIS production on this project. ERDAS Imagine 8.3 and ESRI 

ArcView 3.1 were the principal software tools used in the processing and analysis. 

Precision image orthorectification processing was performed using Image Processing 

System (IPS), EarthSat’s proprietary image processing software. Hardware platforms 

were primarily an SGI Indigo workstation, and a high-end (dual processor, 500 Mhz) 

desktop NT workstation. 
ABSTRACT 

As part of the Inventory and Monitoring Program of the National Park Service (NPS) 

in Alaska, the Alaska Support Office (NPS-AKSO) commissioned Earth Satellite 

Corporation (Rockville, MD), and the Alaska Natural Heritage Program (University 

of Alaska Anchorage), to produce a landcover map and supporting documents for 

Gates of the Arctic National Park and Preserve (GAAR). Using Landsat Thematic 

Mapper multi-spectral imagery as the primary data source, landcover was mapped at 

intermediate scales (1:63,360 - 1:100,000) with 30 classes following a modified 

version of the Alaska Vegetation Classification (Viereck et al. 1992) system at levels 

III and IV. The principal results include a digital thematic landcover map, landcover 

class descriptions, plant association descriptions, study area description, surficial 

geology type and process descriptions, and an accuracy assessment of the landcover 

map. 

The primary purpose of this document is to provide information which will allow 

users to interpret, apply, understand, and utilize the landcover map. This document 

complements an ArcView geographic database which includes the primary data 

layers developed and utilized in the mapping project. Also, the final digital landcover 

map and an associated geographic database are accessible through an interactive map 

and html-formatted version of this users’ guide document distributed on CD media by 

NPS-AKSO. 

The development of the GAAR landcover map involved collection and analysis of 

extensive field-verified datasets and the analysis and interpretation of remotely 

sensed imagery (satellite and aerial photography). It also involved the development 

and application of models using ancillary digital data to distinguish among confused 

landcover (spectral) classes and an accuracy assessment of the derived landcover 

map. A supervised digital image processing approach, using the Maximum 

Likelihood (ML) classifier, was performed on each of the six Landsat TM scenes 

covering the study area. The base landcover map derived from the ML process was 

refined through iterative modeling using environmental and spectral data layers such 

as illumination, slope, Normalized Difference Vegetation Index (NDVI), winter 

satellite imagery, “clustered” data (250 spectral classes), and individual channels of 

the Landsat TM data, to produce the 30 landcover class filtered 2 acre mapping unit 

and unfiltered (pixel) map product. A more general 22 class landcover map was also 

created through combining several of the less spectrally separable classes. The digital 

image processing was guided by visual interpretation of the Landsat TM data, review 

of field data, and spot checking of 1:60,000 high altitude color infrared photography. 

The landcover classification system was based primarily on vegetation structure 

(plant height) and form (tree, shrub or herbaceous), and to lesser extent genera 

(Picea) and species (Picea mariana) information. The mapping classification, with 

modifications, follows The Alaska Vegetation Classification (Viereck et al. 1992) 

system at levels III and IV. A stratified random approach—based on ecoregions, 

surficial geology and unsupervised Landsat TM imagery—was used to place 
polygons for field sampling. The classification system was field checked during late 

June and early July 1998 using both fixed-wing and a helicopter to reach sampling 

polygons. Fly-over and ground data were collected for each polygon and included 

vegetation structure, plant species,% cover, elevation, as well as other site 

information. Existing vegetation data were used extensively to support the 

development of both the classification system and the landcover map.

Ground data were used to define plant associations in order to provide a hierarchical 

link between the relatively coarse scale landcover classes and the species information. 

 Plant association is the finest level of both the Viereck et al. (1992) and National 

Vegetation Classification System (Grossman et al. 1998) classifications. It is defined 

as “a plant community type of definite floristic composition, uniform habitat 

conditions, and uniform physiognomy” (Flahault and Schroter 1910). A total of 40 

plant associations were defined; due to limited field reconnaissance and project 

scope, plant associations were not defined for the forested or tall shrub landcover 

classes. 

A ‘Literature Review’ section provides a synopsis of present and past landcoverrelated projects. An ‘Ecoregions and Climate’ section provides the reader with a 

generalized picture of the topography, climate and vegetation within GAAR. A 

‘Surficial Geology’ section, based on Hamilton (1999c), is a reference guide to the 

major surficial geology units that currently influence vegetation in GAAR. The 

distribution of landcover types in the GAAR project area is as follows: 

• 17.69% area in needleleaf forest or woodland, 

• 0.53% in broadleaf forest, 

• 0.54% in mixed forest, 

• 5.88% in tall shrub, 

• 22.10% in low shrub, 

• 24.42% in prostrate shrub, 

• 6.47% in herbaceous, 

• 16.17% sparse or barren, 

• 1.15% water, 

• 0.36% snow/ice, and 

• 4.52% indeterminate (mostly clouds and terrain shadow). 

An accuracy assessment of the 30 class landcover map was performed to evaluate the 

reliability of the employed remote sensing techniques in achieving the mapping 

project objectives, and to provide users of the map an indication of relative confusion 

among mapping classes. The result showed an estimated overall accuracy for all the 

landcover classes to be 83.1%, based on the 5 acre minimum mapping unit (MMU) 

dataset. The user’s accuracies for general landcover types are as follows: 78.9% for 

needleleaf forest and woodland, 79.2% for broadleaf forest, 93.0% for mixed forest, 

90.1% for tall shrub, 87.0% for low shrub, 78.6% for prostrate shrub, 72.0% for 

herbaceous, 90.7% for sparse /bare-ground, 99.8% for water, and 99.9% for snow/ice. 

 This document presents moredetaileddiscussions of the methods and results of the 

 GAAR landcover mapping project. 
1 

CHAPTER ONE 

INTRODUCTION 

1.1 BACKGROUND 

The Inventory and Monitoring Program of the National Park Service (NPS) is 

designed to provide reliable and consistent information for assessing the status and 

trends in the condition of National Park ecosystems. Vegetation mapping is 

conducted under the inventory portion of the program in order to provide basic 

information readily useful for making resource management decisions, and to collect 

data that can be aggregated on a service-wide level for designing monitoring 

programs. Landcover maps can also be used to understand habitat and fuels 

availability, model the occurrence of archaeological sites and sensitive species, for 

park planning, and to provide baseline information about natural resources in the 

park. This users’ guide document presents detailed discussion of the methods and 

results of the digital landcover mapping project, conducted in (1997-1999) by the 

Alaska Support Office of NPS (NPS-AKSO), Earth Satellite Corporation, Rockville, 

MD, and the Alaska Natural Heritage Program (University of Alaska Anchorage), on 

Gates of the Arctic National Park and Preserve (GAAR) in Alaska. 

Figure 1. Location of GAAR 
2 

Figure 1 shows the general location of GAAR, and Figure 2 shows the entire project 

area which includes 8.2 million acres in GAAR, as well as approximately 30 million 

acres of adjacent areas of the Northern Interior, North Slope, Anaktuvuk Pass, and 

pipeline corridor contained within the six primary Landsat Thematic Mapper (TM) 

scenes. The decision to use Landsat TM for the project was based on the very remote 

and vast project area, the level of mapping information required by NPS, the spatial 

and spectral characteristics of the available sensors/data, and the time and budget 

resources available for the project. The "buffered GAAR area" refers to those areas 

within a 10-mile buffer of the GAAR boundary. This was the primary area of interest 

for development of the landcover map and supporting documentation, and includes 

approximately 13.7 million acres (Figure 2). 

77/12

28 August 95

77/13

28 August 95

75/12

17 July 85

75/13

04 July 86

73/13

19 July 85

73/12

19 July 85

 

 Figure 2. Landsat Thematic Mapper data selected for deriving the landcover map 

1.2 SCOPE OF THE PROJECT 

The scope and design of the GAAR landcover mapping project was established by a 

project team consisting of representatives from Earth Satellite Corporation 

(Rockville, MD), Alaska Natural Heritage Program (Anchorage, AK), Greenehorne 

and O’Mara (St. Petersburg, FL), Forest Data Inc (Corvallis, OR), the Nature 

Conservancy (Washington, DC), and resource managers from the NPS-AKSO and 

GAAR. The project team met in December 1997 to discuss, plan and develop 

logistics for the GAAR landcover mapping project. Their discussions included the 

project objectives and goals, user needs and requirements, mapping classes and 

classification system development, plans and logistics for the 1998 field work, and 

evaluation of existing datasets and remote sensing data (satellite imagery, air photos, 
3 

existing vegetation data, etc.) for developing the landcover map. The team developed 

a comprehensive Project Design document that details map specifications, methods 

and procedures used to develop the landcover map, and delivered this document to 

NPS-AKSO in May 1998. 

The landcover for GAAR was mapped at intermediate scales (1:63,360 - 1:100,000) 

with 30 classes, using a classification based primarily on vegetation structure (plant 

height) and form (tree, shrub or herbaceous), and to lesser extent genera (Picea) and 

species (Picea mariana) information. The mapping classification, with 

modifications, follows The Alaska Vegetation Classification (Viereck et al., 1992) 

system at levels III and IV. 

The usefulness of the map to land managers is increased dramatically when the 

landcover classes are linked to finer scale units that reflect plant species and 

vegetation structure, such as given in plant associations. Plant association, 

consequently, were also described and are the finest level of both the Viereck et al. 

(1992) and the National Vegetation Classification System (NVCS; Grossman et al., 

1998) classifications—i.e., plant association equals level V of Viereck et al., 1992. 

The development of the GAAR landcover map involved collection and analysis of 

ground truth or field-verified data, analysis and interpretation of remotely sensed 

imagery (satellite and aerial photography) and accuracy assessment of data derived 

from these, and the development and application of models using ancillary digital 

data to distinguish among confused landcover (spectral) classes. The landcover map 

products are useful for understanding the distribution of the mapped units, broad 

scale wildlife habitat distribution, and for conducting coarse scale analyses including 

regional ecological planning. The importance of knowledge of the distribution of the 

various plant associations to biologists is well established. The results of the GAAR 

landcover mapping project will help wildlife biologists evaluate forage availability 

for moose and caribou and to understand the distribution of wetlands, rare habitats 

and species. The fine scale vegetation structural information provides ornithologists 

important information for understanding passerine bird habitat distribution. 

The primary results of this project were a digital thematic landcover map, landcover 

class descriptions, plant association descriptions, surficial geology type and process 

descriptions, and an accuracy assessment of the landcover map. A full list of all 

products associated with this project is given in Table 1. A version of the digital data 

as an interactive map and on-line version of this document is available through NPSAKSO. 

The entire database in the table below is available in the GAAR Land Cover Field 

Data Viewer Project (ArcView 3.1)*. For metadata, follow the links in the table to 

the appropriate Data Layer (Theme). 

Table 1. List of data layers used or produced to derive the GAAR Landcover Map

(1997-1999). 
4 

Data Layer (Theme) Data Type Source 

 

GAAR Landcover (Unfiltered) Image (GRID) EarthSat, AKHNP 

GAAR Land Cover (2 ac mmu) Image (GRID) EarthSat, AKHNP 

GAAR Land Cover Legend Shape File EarthSat, NPS- AKSO 

Landsat TM Mosaic–Bands 4,5,3 Image (Imagine) EarthSat 

* Other related products produced under the GAAR Landcover Mapping Services 

contract include the ArcView Surficial Geology Project and the environmental and 

spectral modeling data layers derived for each primary TM scene. These products are 

available through NPS-AKSO. 

1.3 LITERATURE REVIEW 

The only vegetation maps that cover all of GAAR were developed on a statewide 

scale. Viereck and Little (1972) developed a statewide map of vegetation using eight 

vegetation classes and one ice and snow class. An AVHRR—1-km pixel—map for 

Alaska was developed by Fleming (1997). The Alaska regional profiles, Arctic 

region (Selkregg, 1975) also provides general maps and descriptions of the regions 

people, economics, wildlife, geology and vegetation. 

A variety of vegetation classifications—often with associated maps—have been 

developed that cover all or portions of GAAR. The Alaska Vegetation Classification 

(Viereck et al. 1992) provides in-depth descriptions of vegetation at multiple scales 

for Alaska. Few vegetation studies for GAAR had been completed when The Alaska 

Vegetation Classification was developed and, consequently, it is not fully inclusive of 

all the map classes that exist in the Park. Several other classifications centered on the 

Haul Road (Markon 1980, Walker and Webber 1979, Webber et al. 1978). Walker 

and Webber (1979) and Webber et al. (1978) mapped vegetation adjacent to the Haul 

Road from the Yukon River to Prudhoe Bay. They interpreted a vegetation 

classification system they developed using 1:6,000 scale aerial photographs. The 

vegetation classification uses community physiognomy as the key component, along 

with community floristics, and was similar to levels III and IV of Viereck et al. 

(1992). Webber et al. (1978) also investigated weeds and weedy vegetation along the 

Haul Road, and vegetation response to disturbance. Terrestrial and aquatic habitats 

were mapped along the proposed Alaskan Natural Gas Pipeline corridor in 1979 

(Markon 1980), and paralleled the Trans-Alaska oil pipeline through GAAR. Sixtynine map classes were used to stereoscopically interpret 1:24000 and 1:36000 true 

color aerial photographs. The map classes are similar to levels II, III and IV of 

Viereck et al. (1992). 

Several vegetation classifications and maps were specific to single drainages within 

GAAR (Batten 1974, Densmore 1980, Odasz 1983, 1988, Cooper 1983, 1986a, 

1986b,). In the upper Alatna River drainage, the vegetation pattern of white spruce at 
5 

treeline was studied by Odasz (1983, 1988). Plant associations (level V of Viereck et 

al. 1992) along with soil information were described. The results indicate a mosaic of 

mesotopo graphical-scale plant associations. Vegetation of the John River Valley 

was described by Batten (1974). Batten defined vegetation classes similar to levels II 

and III of Viereck et al. (1992), and gives species lists and their relationship to 

topographic position (i.e., floodplain, sideslope, bedrock). A level V classification 

was developed for the upper Arrigetch Creek valley above treeline by Cooper (1983, 

1986a). Community composition and the structure and pattern of vegetation are 

described, the plant associations are related to soils, climate, geological substrate, 

geomorphic process, and a complete list of vascular, lichen and bryophyte species is 

provided. Cooper also develops hypotheses on the evolution of the present day 

vegetative cover. The occurrence of white spruce above treeline is also described for 

the Arrigetch Peaks region by Cooper (1986b). Site characteristics and the vegetation 

type each tree occurs in are given. General descriptions of vegetation classes similar 

to levels IV and V of Viereck et al. (1992) for the upper Dietrich River Valley are 

given by Densmore (1980). Aspect and edaphic factors in relation to elevational 

gradients are discussed in relation to the vegetation. Particular attention is given to 

white spruce dynamics at treeline. 

Other studies that include vegetation classifications, maps or species occurrences in 

GAAR include Spetzman (1959), Gustafson (1980), and Shea (1994). General 

descriptions of ecoregions, plant communities, vegetation succession and species 

distribution are described for arctic Alaska, including GAAR, by Spetzman (1959). 

Four ecoregions are described and are similar to those defined by Gallant et al. (1995) 

and Bailey et al. (1994). Six major plant communities are described and are 

comparable to level II and III of Viereck et al. (1992). The relationships of Dryas 

integrifolia (entire-leaf mountain-avens) and D. octopetala (white mountain-avens) to 

environmental factors in the Brooks Range were studied by Gustafson (1980). 

Species composition and soil characteristics of sites sampled are provided. A 

vegetation map and classification using low altitude color and color infrared aerial 

photography for monitoring human impacts was developed for the north-central 

portion of GAAR (Shea 1994). 

The various flora of Alaska proved valuable for understanding species distribution in 

GAAR. These included three vascular plant floras of Alaska (Hulten 1968, Viereck 

and Little 1972, Welsh 1974). One taxonomic treatment was specific to GAAR, a 

genus key to the lichens of Alaska (Hasselbach and Neitlich 1998). Other nonvascular treatments for arctic Alaska include Thomson (1984) and Steere (1978). 

Swanson (1996) also described the distribution of fruticose lichens in the Kobuk 

Preserve Unit of GAAR. 

Surficial geology maps and descriptions are valuable for understanding the 

distribution of landcover classes and the processes that control them. A series of 

1:250,000 scale surficial geology maps have been developed for GAAR by Hamilton 

(1978a, 1978b, 1979a, 1979b, 1980, 1981, 1984a, and 1984b). Examples of mapped 

surficial geology units include fan deposits, alluvium undifferentiated, lacustrine 
6 

deposits, landslide deposits, sand deposits, drift of fan mountain phase I, and 

outwash. The mapping comprised ten 1:250,000 quadrangle sheets plus part of one 

additional sheet, and subsequently has been combined into a single GIS product for 

GAAR plus a 10-mile peripheral buffer zone. A limited amount of information was 

lost during the combining of the quadrangle sheets, consequently, individuals desiring 

more information on specific areas should obtain 1:250,000 scale quadrangles 

maintained electronically by the U.S. National Park Service or in the published U.S. 

Geological Survey geologic maps. 

Krieg and Reger (1982) describe landscapes along the route of the trans-Alaska 

pipeline. The landscapes (floodplain, pingo, alluvial fan) are similar to the surficial 

geology units described by Hamilton (1978a). Descriptions include soils, ice-mass, 

processes, vegetation and topographic locations. Other physiographic maps and 

publications describing processes, glaciation and bedrock geology exist for the 

Brooks Range but were not directly applicable to the study (Detterman et al. 1958, 

Ferrians 1965, Hamilton and Porter 1975, Sloan et al. 1976, Gedney and Marshall 

1981, Hamilton 1982, 1984c, 1986, 1994, 1999a, 1999b, Grantz et al. 1983, Ellis and 

Calkin 1984, Nilsen and Moore 1984, Moore et al. 1994, Brown et al. 1997, Avé 

Lallemant et al. 1998). 

Two soil maps are available for GAAR (Rieger et al. 1979, Swanson 1995). The 

statewide soil survey (Rieger et al. 1979) provides coarse level soils information for 

Alaska but was too coarse to be useful for vegetation mapping purposes. The second 

map was developed by Swanson (1995) for the Kobuk Preserve Unit of GAAR. The 

project was an integrated study of landforms, soils, and vegetation for the purpose of 

helping park managers predict the potential impacts of road development. Its major 

results include physiographic map unit descriptions (similar to surficial geology units 

described by Hamilton 1981), soil descriptions and vegetation site type descriptions. 

The physiographic map unit descriptions describe landforms, geologic materials and 

the soils of landscape units such as floodplain, terrace, colluvial slope and mountains. 

 Soil descriptions are for types such as cryaquepts, cryofluvents, histosols, orthents 

and typic cryorthents. The descriptions provide information on drainage class, parent 

material, slope range, typical pedon, location, and range in characteristics. 

Vegetation site type descriptions include units such as alpine small stream 

floodplains, gravelly colluvium, ribbed fens and tussock wetland. The detailed 

information includes plant species lists and cover values, the setting, map-unit 

components, soils, and succession. 

Two coarse scale ecoregional maps are currently widely used in Alaska: ecoregions 

of Alaska by Gallant et al. (1995) and ecoregions and subregions of the United States 

by Bailey et al. (1994). They have been developed for the purposes of implementing 

ecosystem management, which requires working definitions of ecosystems and 

supporting inventories of the components that comprise ecosystems. Both 

ecoregional maps use similar approaches to defining and describing ecoregions. For 

GAAR, both ecoregional maps are only available at the scale, 1:5,000,000. The units 

are defined based on similar patterns in potential natural communities, soils, 
7 

hydrologic function, landform and topography lithology, climate, and natural 

processes such as nutrient cycling, productivity, succession, and natural disturbance 

regimes associated with flooding, wind, or fire. Climate, as modified by topography, 

is the dominant criterion at the scale mapped for GAAR. 

1.4 DESCRIPTION OF PROJECT AREA AND ENVIRONMENT 

The Project Area includes approximately 8.2 million acres included in GAAR, as 

well as approximately 30 million acres of adjacent areas of the Northern Interior, 

North Slope/Arctic Foothills, Anaktuvuk Pass, and pipeline corridor contained within 

the six primary Landsat Thematic Mapper (TM) scenes (Figure 2). The GAAR 

Landcover Project Area includes a 10-mile buffer around the GAAR boundary and is 

covered by 6 primary Landsat TM scenes, which encompass the entirety of GAAR 

plus the adjacent areas. The 10-mile buffered GAAR area was the primary area of 

interest for development of the landcover map and supporting documentation, and 

includes approximately 13.7 million acres (Figure 2). However, several of the 

resulting image products were extended beyond the Project Area to include the entire 

extent of the six Landsat TM scenes (for example, the Lansat TM image mosaic). 

The ‘Ecoregions and Climate Influences on Landcover’ section provides the reader 

with a general picture of the topography, climate and vegetation within GAAR. The 

‘Generalized Surficial Geology Interpretation’ section is provided as a guide to the 

major surficial geology units that influence vegetation in GAAR. It is not, however, 

meant to be used as a surficial geology classification. 

1.5 ECOREGIONS AND CLIMATE INFLUENCES ON LANDCOVER 

GAAR encompasses much of the central Brooks Range, and is approximately 180 

miles long by 90 miles wide, and covers 8,202,517 acres. Its elevation ranges from 

approx. 500 feet to 8,570 feet. To more easily describe the climate and geography of 

GAAR we present the three ecoregions described by Gallant et al. (1995), the arctic 

foothills, the Brooks Range, and the interior forested lowlands and uplands (Figures 

3a and 3b). 
8 

 Figure 3a. Ecoregions as defined by Gallant et al. (1995) of GAAR 

 Figure 3b. Longitudinal cross-section of ecoregions, vegetation, and topography of 

 GAAR 
9 

Arctic Foothills Ecoregion 

The arctic foothills ecoregion is located north of the Brooks Range and consists of 

treeless rolling hills and plateaus (Figures 3a and 3b). Elevation ranges to 2,000 feet. 

 The hills are bedrock outcrops often covered by loess, moraines, ancient outwash 

and floodplain terraces, and various glacial derived landforms (Figure 4). The 

ecoregion is underlain by thick permafrost and many ice-related surface features are 

present such as ice-cored hills and thermokarst. Tussock tundra dominates the area 

and few trees are present (Gallant et al. 1995). The arctic foothills ecoregion covers 

two% of GAAR. 

 

Figure 4. Low relief hills and terraces in the arctic foothills ecoregion 

Many of the bedrock outcrops are mesa-like with less than a 500-foot vertical rise. 

Their crests and upper slopes are a mixture of bare gravel and prostrate shrubs. The 

mid- and lower-slopes are composed of tussock tundra and narrow water tracks. The 

water tracks are dominated by open water, diamondleafed willow (Salix planifolia 

subspecies pulchra) and sedges (Carex species). Surrounding the bedrock outcrops 

are rolling low relief hills and terraces sloping down to the north flowing rivers that 

drain the Brooks Range. The hills and terraces are Pleistocene and older glacial till, 

kettle kame topography, outwash plain terraces, floodplain terraces, and sand deposits 

including dunes. The surface is predominantly tussock tundra, water tracks, some 

solifluction on sloping ground, and patterned ground on the more level areas. 

Polygonal ground was visually evident on level to slightly sloping ground and on 

relatively dry sideslopes. Frost scars are also a common feature in the tussock tundra. 

Brooks Range Ecoregion 

The Brooks Range ecoregion consists of steep mountains and wide glaciated valleys 
10 

(Figures 3a and 3b). It covers 83% of GAAR and the elevation ranges from 

approximately 500 feet to 8,570 feet. The mountains “consist of folded and faulted 

stratified Paleozoic and Mesozoic sedimentary deposits that were uplifted during the 

Cretaceous period (Gallant 1995)”. Small and scattered glaciers still persist within 

the headwaters of the higher peaks. Major surficial geology types along an 

elevational gradient—high to low—change from bedrock, to colluvium, alluvial fans 

or glacial drift, and then to floodplain or lacustrine deposits (Figure 5). 

Figure 5. Idealized cross-section of a mountain valley in the South half of the GAAR 

showing various surficial geology deposits and landcover types. 

Bedrock is subjected to intense frost action and nivation that produces erosional 

landforms—terraces, scarps, and cliffs—and erosional debris. The erosional debris is 

transported downslope via snow avalanches, rock fall, mass movement, streams, and 

rock glacier movement to form surficial deposits such as colluvial slopes and alluvial 

fans. Soil mass movement—solifluction and stream erosion—continue to move the 

colluvial and alluvial fan deposits downslope. Glacial drift, including moraines and 

glacial till, deposited during the last glacial retreat dominate the sideslopes and valley 

floors. Permafrost plays a significant role in valley bottoms and leads to the growth 

of large masses of ground ice that form tundra polygons, thermokarst and pingos. 

Frost action also leads to accelerated mechanical soil weathering. Another significant 

disturbance factor is caused by rivers and streams that constantly erode and deposit 

sediment, forming floodplains and outwash features. 

Landcover is dramatically different between the north and south halves of the Brooks 

Range ecoregion. In the north half moving downslope, bedrock and talus give way to 

prostrate shrubs, then low shrubs, tussock tundra, and, along river courses, tall shrubs 

(Figure 6). Wet herbaceous vegetation occurs on some level valley bottoms. In the 

south half, moving downslope, bedrock and talus give way to prostrate shrubs, then 
11 

low or tall shrubs, and then forests (Figure 7). Talus slopes and avalanche paths are 

often free of trees and are dominated by alder and willow. On south facing slopes, 

trees are more common and extend further upslope. 

Figure 6. Valley in northern half of GAAR

Figure 7. Valley in South half of GAAR 
12 

Interior Forested Lowlands and Uplands Ecoregion 

The interior forested lowlands and uplands ecoregion occurs south of the Brooks 

Range (Figures 3a and 3b). It represents a patchwork of ecological characteristics 

including a continental climate, a mantling of undifferentiated alluvium and slope 

deposits, a predominance of forests dominated by spruce and hardwood species, a 

very high frequency of lightening fires, and a lack of Pleistocene glaciation (Gallant 

et al. 1995). Elevation ranges from approximately 500 feet to 3,000 feet, and the 

ecoregion covers 15% of GAAR. 

The uplands are bedrock hills typically covered by loess and glacial drift, and 

sideslopes of colluvium and solifluction deposits. The valley bottoms are dominated 

by floodplains, terraces, lacustrine deposits and peat deposits. Where the Brooks 

Range ecoregion meets the interior forested lowlands and uplands ecoregion, glacial 

drift is common including glacial till, kettle-kame topography, outwash and moraines. 

 Lakes are common in the valley bottoms due to thermokarst and oxbows along 

floodplains. 

Figure 8. Valley in the interior forested lowlands and uplands ecoregion 

Plant diversity increases within the ecoregion as compared with the Brooks Range 

and arctic foothills ecoregions. Vegetation forms a complex pattern due to the effects 

of fire, permafrost, soils, and surface water. The hills are better-drained and support 

large stands of paper birch, white spruce (Picea glauca), black spruce (Picea 

mariana) and quaking aspen (Populus tremuloides) (Figure 8). The ridges are often 

dominated by the prostrate shrubs and lichen. The valley bottoms are, in general, 

wetter environments than the hills. Open black spruce and white spruce forests 

dominate, along with peatlands. Areas of dwarf black spruce growing to about 12 
13 

feet are also present. Within GAAR this occurs primarily in the lower southeast 

portion of the park. On floodplains, tall shrubs, balsam poplar, and white spruce are 

common. Black spruce is generally found on river terraces and flat to rolling uplands 

because terraces are moderate to poorly drained. 

Climate

GAAR has long severe winters and short cool summers. The arctic foothills 

ecoregion has winter temperatures ranging from –290C to –200C (Gallant 1995). 

Summer temperatures range from 10C to 150C, with temperatures occasionally 

reaching 240C in some areas. Although freezing can occur any time of the year, July 

and August are usually frost-free. In the Brooks Range ecoregion, winter 

temperatures are colder and range from –300C to –220C, while summer temperature 

fluctuates from 30C to 160C (based on one weather station at Anaktuvuk Pass). 

Freezing may occur in any month of the year. South of the Brooks Range, winter 

temperatures differ from west to east, with a minimum of -180C to -110C in the west 

and -350C to -220C in the east. Summer temperatures range from a minimum of 80C 

to 110

C to a maximum of 170C to 220C. June through mid-September is usually frost 

free at the lower elevations. 

Precipitation is low throughout GAAR. The arctic foothills ecoregion annual 

precipitation at the base of the Brooks Range is approximately 7.6 inches, and 

receives 52 to 60 inches of snow. In the Brooks Range at Anaktuvuk Pass, summer 

precipitation is 11 inches, and winter precipitation averages 64 inches of snow per 

year. Elevation, aspect, and winds result in a highly variable climate. South of the 

Brooks Range, average annual precipitation is 10 to 22 inches, and increases with 

elevation. Convection storms in the summer provide most of the annual precipitation. 

 Of the annual precipitation, 50 to 82 inches of it occurs as snowfall. Snow remains 

on the landscape for over half of the year on north facing slopes, shadowed areas, and 

at higher elevations. 

Wildfire 

Fire occurrence is low in the arctic foothills ecoregion. An average wildfire is 185 

ha, with a range of <1 acre to 4,000 acres (Gallant 1995). Fires are common in the 

Brooks Range ecoregion ranging in size from <1 acres to 273,162 acres according to 

fire records, with an average size of 4,475 acres. Fires occur frequently in the interior 

south of the Brooks Range from June to early August. Average fire size is 4,075 

acres, with a range of 0.5 acres to 652,000 acres. The high number of fires is related 

to low precipitation, warm summers, lightening storms, and large number of trees 

with low lying branches. 

Land Use and Settlement 

The arctic foothills and Brooks Range are the traditional home to the Nunamiut 

(Inuit) peoples, and are an important area for subsistence practices including hunting, 

fishing, and wild plant gathering (Gallant 1995). Caribou, moose, bear, ground 

squirrel, and ptarmigan are all subsistence resources. Recreational hunting and 

fishing also occurs throughout the region, and edible greens, roots, and berries are 
14 

harvested throughout the summer months. The Kutchin and Koyukon Athabascans 

also use the Brooks Range for subsistence purposes. South of the Brooks Range, both 

subsistence and recreational hunting occurs (Gallant 1995). People living in the 

uplands primarily hunt caribou and moose. People living in the lowlands and riverine 

areas rely heavily on game and freshwater fish. Small mammals and ptarmigan are 

hunted by all peoples of the area. Berries, roots, and wild greens are also harvested. 

1.6 GENERALIZED SURFICIAL GEOLOGY INTERPRETATION 

Generalized surficial geology was initially delineated through interpretation of a 

1:350,000 scale photoprint mosaic of the Landsat TM (bands 4,5,3) data---a 24-bit 

enhanced false color infrared product which allowed maximum discrimination of 

vegetation. The surficial geology types to be interpreted were taken from surficial 

geology maps developed for GAAR by the USDI United States Geological Survey 

(Hamilton 1978a, 1978b, 1979a, 1979b, 1980, 1981, 1984a, 1984b). For stratification 

purposes it was not practical to use all the surficial types defined on the surficial 

geology maps, and, consequently, it was necessary to combine some. These surficial 

geology types include: 

• Bedrock. Bedrock with little or no soil development primarily restricted to 

upper- and mid-mountain slopes, and ridgetops in the Brooks Range region. 

• Bedrock, low elevation, overlain by loess. Bedrock that is typically covered 

by thin talus, solifluction, loess, or lacustrine deposits. This type is restricted 

to mountain outliers north and south of the main mountain mass (Brooks 

Range ecoregion) of GAAR. 

• Active floodplain. This surficial geology type consists of floodwaterinfluenced lands that include floodplains, active terraces, streambeds and 

outwash plains. It occurs throughout GAAR. 

• Mixture of colluvium, fans, rock glacier. This type is a combination of 

deposits that occur within GAAR’s main mountain mass (Brooks Range 

ecoregion) between the bedrock surficial geology type and the active 

floodplain type. It includes fan deposits, colluvium (landslides, flows, talus 

rubble, rock-glaciers, protalus rampart deposits, and solifluction deposits), 

sand deposits, lateral and terminal moraines, and lacustrine deposits. 

• Terraces 10 m above streams. This type occurs in the arctic foothills 

ecoregion and was delineated because it is spectrally and geomorphically 

distinct from the surroundings. It consists of Pleistocene age alluvial terraces 

greater than 10 m vertically above the active floodplain. 

• Older glacial moraines, sand, drift, kettle-kame. This type is a combination of 

deposits that were difficult to separate spectrally within the arctic foothills 
15 

ecoregion and the Interior forested lowlands and uplands ecoregion. It 

includes moraines, sand dunes, loess, lacustrine deposits, drift, some terrace 

deposits, inactive glacial outwash, and kettle-kame topography. 

• Younger glacial moraines, sand, drift. This type is similar to the “Older 

glacial moraines, sand, drift, kettle-kame” surficial geology type but is 

spectrally distinct. It also is a combination of deposits that were difficult to 

separate spectrally within the arctic foothills ecoregion and the Interior 

forested lowlands and uplands ecoregion. It includes moraines, sand dunes, 

loess, lacustrine deposits, drift, some terrace deposits, inactive glacial 

outwash, and kettle-kame topography. 

• Thermokarst on areas with relief. This surficial geology type is distinguished 

from others due to the presence of numerous lakes and ponds in areas with 

low hills. This type is likely due to a combination of thermokarst and kettlekame topography. It occurs on a variety of deposits (sand deposits, drift, and 

floodplain) throughout GAAR. 

• Thermokarst on low relief lands. This surficial geology type is distinguished 

from others due to the presence of numerous lakes and ponds and occurs on 

level land. These surfaces are likely thermokarst floodplains or outwash. It 

occurs primarily in the interior forested lowlands and uplands ecoregion. 
16 

CHAPTER TWO 

METHODS 

Flowcharts depicting the various methods employed in this study are found in Figures 

9a, 9b, 9c, 9d, 9e, 9f. Further details on these methods are described in the following 

sections. 

Figure 9a. Flowchart for project overview 

PreProcessing of Imagery

- Ortho-rectification

- Subset needed layers for future processing

Preliminary Spectral Classification (Pre-field)

 Develop FirePro Spectral Sigs Run Hybrid Isodata-ML Clustering

Compute Zonal Statistics

Assign Spectral Classes

 Evaluate in Field

Post Field Classification Refinement

- Update signature database w/ new field data

- Create thematic Signature File of Ground Truth database

- Create AA database from reserved FirePro sites

- Evaluate training signature database

- Run supervised ML classifier on 6-band (bands2-5,7 & illumination layer) dataset

based on training signature database

 Environmental Modeling

 Summarize Spectral Data Layers: Prepare/Process Physical Data Layers:

 5-band, NDVI, Isodata/ML, Spectral Digital elevation model (DEM), Slope,

 Spectral Distance file Illumination, Relief Intensity,Curvature

Create spectral profiles for each Create mapping class site profiles:

mapping class:

Compute Zonal Statistics w/

Training Signature Dbase

 Refine Classes

 Evaluate

Evaluation

Evaluation of pre-field and post field classifications

 Raster Editing Accuracy Assessment

Reporting and Documentation

-On-line user's guide

- On-line project management tool

- Presentation of final products to NPS

- Delivery of final products
17 

Figure 9b. Flow chart for preprocessing of imagery 
18 

Figure 9c. Flowchart for preliminary spectral classification 

Assemble FirePro Data

(Ground Truth Database)

Evaluate FirePro Point and

Poly Data:

Acceptable?

Delineate and attribute

vector signatures on TM

imagery

Create Raster Thematic of

training (FirePro) spectral

signatures

Compute Zonal Statistics

on Isodata/ML layer w/

FirePro Signature

Thematic Layer

Run ML classification on

250 class signature file to

create Isodata/ML

Thematic Layer

Run Isodata Clustering on

5 band (2,3,4,5,7) Imagine

file to create ~ 250 class

sig file

Produce planning documents for

field work and future analysis:

1:100k image maps (4,5,3)

1:250k image maps (4,5,3)

Evaluate zonal

statistics and assign

spectral classes

accordingly

Use Dendogram and Threshold for

Quantitative Statistical Evaluation

Use 4,5,3 color for Qualitative Visual

Evaluation

Delineate/Produce Landform map for

field work / sampling design

Create Signature

Distance File

Create Dendrogram

from ~250 class sig.

file

Produce enlargements of CIR

photography for field work

Yes

No

Discard
19 

Figure 9d. Flowchart for post-field classification refinement 

Delineate FVA Polygons on CIR

enlargements and collect new field data

for FVA's

- Site Descriptions

 - FVA Polygon Verification

 - Incidental Image Delineation

 - FVA Orientation Video

Type of Field Data Collected:

Refine

Classification

System TNC

EarthSat

AKNHP

Transfer / Vectoize Coverage

Attribute and Develop ArcView Field

Data Viewer Project

Combine FirePro and Fieldwork

Signature Polygons to create Thematic

Signature Database

Use approximately 90% of FirePro and

fieldwork sigs used for training (841 sigs)

Reserve remaining 10% of FirePro sigs

and combine with 1998 detailed field

collection sites to develop an accuracy

assessment database (64 sigs)

Evaluate Training Signatures

Run Supervised ML Classifier

on 5-Band TM data with

training signatures

Run Supervised ML Classifier

on 6-Band (TM data +

illumination layer) with training

signatures

5-Band TM

data + Band

illumination 5-Band TM

Data
20 

Figure 9e. Flowchart for environmental modeling 

5-Band TM data

Isodata/ML file

Spectral Dist. file

NDVI file

DEM

Slope

Aspect

Illumination

Relief Intensity

Landform

Surficial Drainage Spectral Data Layers: Physical Data Layers:

Training

Dbase

Compute Zonal Statistics Compute Zonal Statistics

Evaluate

Zonal

Statistics

Training

Dbase

Identify

Effective

Modeling

Layers

Create Spectral Profile

for each class

Create Environmental Site Profile

for each class

Develop Spectral Model

Parameters

Develop Terrain Model

Parameters

Apply models

(Conditional Statements)

Interactive review of model outputs

Acceptable?

Begin interactive evaluation

editing steps

Refine Model

Parameters

EarthSat

AKNHP

NPS

Yes

No
21 

Figure 9f. Flowchart for evaluation of Landcover map 

Landcover Classification

for each primary TM

scene (6 scenes - 43

classes each)

Compute error matrix for

each scene using training

database

Stage 1

modeling

Return to modeling for additional

iterations

Mosaic 6 land cover scenes

Subset buffered GAAR area

Recode to endpoint classes

GAAR

Land cover

(30 classes)

GAAR

Land cover

(22 classes)

Recode to general classes

Stage 2 and 3

modeling

Compute error matrix

w/ training databases

Per scene accuracy

acceptable?

Evaluate results with

training data

Accuracy acceptable?

- Filter to 5 ac MMU

- Compute error matrix w/ AA

 dbase.

-Report User's/Producer's Overall

 Accuracy

Raster Editing

Compute error matric

w/ accuracy assess ment

databases

Report Accuracy per Class

Review (QC)

Process w/ AKNHP

& EarthSat

draft

prelim.

map

draft

final

map

models

Yes

No

No

Yes

No
22 

2.1 OVERVIEW OF THE LANDCOVER CLASSIFICATION SYSTEM 

A landcover classification system was developed using suggestions from NPS 

personnel familiar with the Park and data collected during the field season, and 

followed—with modifications—the Alaska Vegetation Classification (Viereck et al. 

1992) system at levels III and IV. A stratified random approach—based on 

ecoregions, surficial geology and Landsat TM imagery—was used to select polygons 

for field sampling. Fly-over and ground data were collected for each polygon and 

included vegetation structure, plant species, percent cover, elevation, as well as other 

site information. 

A combination of spectral image processing, environmental site and spectral 

modeling and raster editing were required in order to map landcover from Landsat 

TM data at the required level of geometric accuracy (1:63,360) and classification 

system detail (30 classes). An initial landcover classification system was developed to 

train the Landsat TM scenes prior to fieldwork, to increase the accuracy of the field 

effort, and to classify the spectral signatures during the field season. The landcover 

classification system was modified after the field season to better represent landcover 

classes observed in the field (Table 2), and to determine what could actually be 

interpreted from the Landsat TM imagery. 
23 

The classification system was developed from three sources, and, in general, followd 

The Alaska Vegetation Classification (Viereck et al. 1992) system. First, USDI 

National Park Service (NPS) personnel with experience in GAAR provided a list of 

possible classes (Table 3). Second, Alaska Vegetation Classification (Viereck et al. 

1992) classes were assigned to previously collected Firepro data from GAAR. Third, 

a list of plant associations and map classes was developed through a literature review 

of GAAR (Table 4). A total of 30 classes were provided by NPS personnel, 58 

classes were derived from the FirePro data (based on 1,000+ points and polygons), 

and a total of 54 classes were extracted from the 12 published vegetation studies. 
24 

The mapped classes were refined during a scoping meeting attended by NPS 

personnel and members of the mapping team (Earth Satellite Corporation, Alaska 

Natural Heritage Program, Forest Data, Inc., Greenhorne & O’Mara, and Ray Kreig 

& Associates). Several assumptions were made during the refinement of the classes. 

The group agreed that the mapping classes must be based on landcover characteristics 

that could be recognized by Landsat imagery, and had to be flexible enough to 

describe potential new classes derived from Landsat imagery. The mapping classes 

were derived from the Alaska Vegetation Classification (Viereck et al., 1992) 

however we did not strictly adhere to this hierarchy. This was primarily because the 

Alaska 
25 
26 
27 
28 

The Vegetation Classification did not necessarily correspond well to the classes that 

would be detected by Landsat imagery. In addition, little vegetation information was 

available from GAAR during development of the Alaska Vegetation Classification. 

Consequently, classes within the Alaska Vegetation Classification hierarchy did not 

necessarily correlate well with vegetation classes existing within GAAR. 

Although the FirePro data and literature review provided more detailed information 

than the NPS landcover class list, both sources of information were important for 

confirming the classes developed by NPS personnel, indicating new classes, and 

providing relative abundance estimates for each class. Several iterations of the list 

were developed and reviewed before the final classes used for fieldwork were 

developed. After the field season, the landcover classification was modified 

following field observations and Landsat imagery interpretation. A landcover class 

key of final landcover classes is provided in Appendix 1. 

2.2 PRE-PROCESSING OF SATELLITE IMAGE DATA 

An extensive data search resulted in the selection of 10 scenes that provided complete 

nearly cloud-free coverage of the project area during the short window of opportunity 

to capture northern Alaska vegetation at peak (July). The two western scenes 

acquired on August 28, 1995, were determined to be too late in the summer for 

optimum vegetation discrimination but were still the best available option. The other 

four primary scenes were acquired in July of 1985 and 1991 (Figure 2). 

Prior to further processing, the TM imagery had to be orthorectified to create a stable 

and geometrically accurate base map. Recently completed 1:63,360 USGS Digital 

Elevation Models (DEM) were obtained and mosaiked to complete a parkwide DEM 

database. Horizontal controls were selected from 1:63,360 USGS topographic 

mapsheets for the area. In all, 387 ground control points (GCP’s) were selected. A 

rigorous photogrammetric block adjustment process was performed resulting in an 

RMS of 49.5 meters. Image-to–image co-registration was within 2 pixels. 

Qualitative evaluation with other layers such as the limited 1:63,360 derived 

hydrology vector coverages was also very positive. 

2.3 PRE-PROCESSING OF FIREPRO DATABASE 

Over the past 15 years NPS AKSO has collected an extensive database in support of 

fire history and succession studies, landcover mapping and fire fuel modeling. Under 

the AKSO Landcover Mapping program, the spatial coordinates or locations of the 

FirePro data points were digitized, and the tabular data were automated for use in 

landcover mapping projects. The FirePro database represented the best available 

vegetation or landcover information within GAAR project area. This database, which 

is comprised of ARC/INFO coverages with approximately 1,350 georeferenced 

points, 1:60,000 high altitude aerial photos, 35-mm photo slides, and field forms, was 
29 

utilized extensively in the GAAR landcover project. 

The FirePro data included detailed vegetation composition and information on 

dominant plant communities in sampled sites, and tree cores and cross sections to aid 

in determining when the site burned. Since 1987, remote sensing specialists in the 

AKSO GIS office have delineated polygons of homogeneous signature and 

representative vegetation types on aerial photos, which the FirePro crews then 

sampled. The sampled areas were qualitatively selected so as to approximate the full 

range of spectral and vegetative variation in the park. Summaries of the FirePro 

database were utilized during development of the classification system for the GAAR 

landcover project. 

In order to directly integrate this database into the automated landcover project, it 

was necessary to generate a spectral signature for each FirePro plot. To accomplish 

this, spectral signature coverages were developed based on the review of each FirePro 

site’s species composition, percent cover, aerial photos, site photographs, and field 

forms by an image analyst or botanist. The FirePro polygon was then redrawn on the 

Landsat TM image base to capture the spectrally homogenous portion of the polygon, 

and assigned the appropriate mapping class label. FirePro sites that showed 

inconsistencies in the database, photos, or field-forms were generally not used as 

spectral signatures. The FirePro derived signature database went through a number of 

revisions and refinements before use. In all, about 1100 FirePro sites were evaluated 

resulting in the development of 608 spectral signatures distributed throughout the 6 

Landsat TM scenes covering the GAAR project area (Figure 10). This translated to a 

55% success rate of FirePro sites useable as supervised spectral signatures. 

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 Figure 10. Mosaic design of primary Landsat TM scenes (with FirePro data shown in 

red) 
30 

2.4 DEVELOPMENT OF A PRELIMINARY (PRE-FIELDWORK) 

LANDCOVER MAP

In preparation for fieldwork, a preliminary landcover map was developed based on 

the FirePro derived signatures. ISODATA (Iteratively Self-Organizing Data Analysis 

Technique)---an unsupervised image classification method--- was then performed on 

each 5-band (bands 2-5 and 7) Landsat TM scene to produce 250 spectral classes. 

The ISODATA algorithm uses the minimum spectral distance formula to iteratively 

cluster or classify pixels, refine the criteria for each class, and classify again, so that 

the spectral distance patterns in the data gradually emerge. The ISODATA 

algorithms require the user or image analyst to set a number of parameters including 

the desire number of clusters to produce, the maximum number of iterations, etc. The 

parameter values used in this analysis were as follows: 

 

 Number of Classes = 250 

 Maximum Iterations = 20 

 Convergence Threshold = .999 

 Skip Factor = 5 pixels (in both x and y directions) 

 Initialization Statistics = 2 Standard Deviation 

The 250 spectral classes were then assigned to the field mapping landcover classes 

(Table 2) based on FirePro-derived signatures. The mapping class for the majority 

occurring FirePro-derived signature in each spectral cluster was assigned to the 

cluster. This preliminary 43 class landcover map was taken to the field so that 

spectrally confused classes could be identified and targeted for refinement of the 

signatures or the classification system, or both. 

2.5 SAMPLING DESIGN AND ‘FIELD VERIFICATION AREA’ 

SELECTION 

Field sampling consisted of selecting 25 areas to record landcover characteristics 

from both the air and on the ground. These areas were termed field verification areas 

(FVA’s). Individual FVA’s represented the range in variability of landcover in its 

specific area, such as across a mountain valley. The FVA’s, in combination, were 

meant to represent the total range in variability of landcover across GAAR. 

The selection of FVA’s within GAAR was based on stratified sampling (MuellerDombois and Ellenberg 1974, Steel and Torrie 1960) and involved: 1) a coarse scale 

stratification of GAAR by ecoregion (Gallant et al. 1995), 2) a fine scale stratification 

primarily by surficial geology type, aspect and spectral signature, and 3) selectively 

locating sampling points within these strata. The ecoregions and surficial geology 

types used in this methods section were similar to but not always the same as the 

ecoregions and surficial geology types given in the “Project Area and Environment” 

section. The differences were due to scale rather than observations. 
31 

For coarse scale stratification purposes, GAAR was divided into five ecoregions. 

Four of the ecoregions were based on Gallant et al. (1995), and are arctic foothills, 

Brooks Range, interior forested lowlands and uplands, and interior highlands 

(partially given in Figures 3a and 3b). A fifth ecoregion was defined by the authors. 

It occurs on the western edge of the park—primarily the Noatak River valley—and is 

dominated by Pleistocene epoch glaciated valleys overlain by lacustrine deposits. 

Low elevation hills also occur along with some glacial drift and eolian deposits. 

These five ecoregions were then delineated on the Landsat mosaic. 

Surficial Geology Strata:

Active floodplain, outwash plain

Bedrock

Bedrock, low elevation, overlain by loess

Mixture of colluvium, fans, rock glacier

Older glacial moraines, sand, drift, kettle-kame

Terraces 30m above rivers, 10m above streams

Thermokarst on areas with relief

Thermokarst on low relief lands

Younger glacial moraines, sand, drift

1998 Field Verification Transects (FVTs)

10-Mile Buffer

Park Boundary

Figure 11. Landscape strata used for the placement of the 1998 Field Verification 

Transects (FVTs) 
32 

Twenty-five FVA’s were placed within GAAR based primarily on the 22 

combinations of ecoregion and surficial geology types (Figure 11, Table 5). 

Additional factors affecting FVA placement were as follows: 

• All aspects (north, south, east, and west) on mountain slopes were included 

(Table 6). 

• Both large and small valleys within the Brooks Range ecoregion were 

sampled. 

• Areas with FirePro information were avoided. 

• The Kobuk Boot region of GAAR was avoided because extensive past 

sampling were sufficient to understand the regions landcover distribution. 

One FVA was sampled in the northern portion. 
33 

Alaska Native lands (including selected, hunting camps and private in-holdings) 

were avoided except those lands north of the Park’s boundaries. 

• Distinct landcover signatures from the raw Landsat imagery were sampled. In 

general, these coarse level vegetation changes corresponded to the defined 

surficial geology types and ecoregions of GAAR. 

• Sampling within Landsat scene overlap areas was maximized (14 of the 25 

FVA’s were in scene overlaps). 

• Each Landsat scene was visually weighted by the amount of area each scene 

encompassed in GAAR to ensure adequate representation of the 22 ecoregion 

and surficial geology type combinations. 

• Two floodplains in the southern portion of GAAR were sampled to capture 

additional samples of the dense-open white spruce class. 

• The AVHRR landcover map for Alaska (Fleming 1997) was used to readjust 

FVA locations. 

Within each FVA, one complete or discontinuous transect was laid out on the Landsat 

mosaic to encompass the FVA’s full variation of environmental factors. These 

environmental variables included ecoregion, surficial geology types, aspect, and 

distinct Landsat landcover signatures. In the Brooks Range ecoregion each transect 

spanned an entire valley, from ridgetop to ridgetop. In the remaining four ecoregions, 

transects that encompassed the environmental variability were often too long to fully 

sample. Consequently, we formed discontinuous transects with transect segments 

falling in each distinct environment to be sampled. 

 

Polygons representing all the distinct landcover classes found along each transect 

were then photo interpreted on 1:12,000 scale enlargements of 1:60,000 AHAP color 

infrared aerial photography to be used as field maps. Polygons were delineated based 

on homogeneity and appropriate for the mapping scale (approximately 10 ac). 

Landcover classes not captured by the transect but found nearby were also delineated 

and sampled. Approximately 3,200 acres were delineated per FVA. Due to the 

variable lengths of each transect, polygons may or may not be adjacent to each other. 

Following the photo delineation work, the landcover classes were tallied. Some 

readjustment of the FVA’s and polygons was made in an attempt to ensure a 

minimum of five polygons per landcover class would be sampled for each of the six 

Landsat TM scenes. 

2.6 FIELD DATA COLLECTION

The primary goal of the 1998 fieldwork was to collect the number of samples 

required to create the landcover map product. The intent of this transect-polygon 
34 

sampling approach was to both collect samples that could be used to generate spectral 

training signatures for use in the automated image classification, and also to gain a 

complete picture of the occurrences of the mapping classes for areas over all 

slope/aspect/landform positions in the FVA. This transect “snapshot” was essential 

to establishing realistic parameters in the environmental and spectral models used to 

refine the landcover map. A secondary goal during field data collection was to obtain 

more specific site information that could be used to describe plant associations, and to 

tie this more detailed vegetation information back to the landcover mapping classes. 

To support these objectives, field data were collected by a three-person crew at three 

different levels of detail: 

FVA ‘fly over’ polygons 

The purpose of this level of field data collection was specifically to provide 

additional training signatures for the automated image processing and modeling 

required to produce the landcover map. Information was recorded on field forms 

(Figure 12) and included the data required to select a landcover mapping class call for 

each sampled polygon. This information included air photo number, polygon code, 

latitude and longitude, landcover class name and code, date, surveyors, photos, 

azimuth, audio tape, video tape, slope, aspect, landform, surficial geology, and 

hydrologic regime. Landcover information included percent of polygon covered by 

the dominant species, species height, and total percent cover for the following 

lifeform categories: needleleaf forest, broadleaf forest, shrub (tall, low, dwarf, 

prostrate), herbaceous, lichen, water, bare soil, and tussocks. Dominant species and 

percent cover always summed to 100%. Photographs were collected at each site. 

Canopy cover was ocularly estimated (Brown 1954) for the dominant species, and 

defined as percent of the ground in the polygon covered by the gross outline of an 

individual plant's foliage (canopy), or the outline collectively covered by all 

individuals of a species or life form within the polygon (Daubenmire 1959). Percent 

bare ground was also estimated. 

When arriving at the FVA transect area, the image analyst and botanist flew a 

reconnaissance of the transect and landed at one end of the FVA (typically on a high 

vantage point). From here, the image analyst and the botanist surveyed the potential 

sample sites and compared them to the polygons already delineated on the 1:12,000 

CIR (color infrared) enlargements and to the 1:100,000 Landsat TM image map of 

the FVA. Polygons were then adjusted on the CIR photo to ensure that they were 

sufficiently large (~10 acre) and recognizable on both the CIR photo and TM image. 

Each polygon was sampled by slow fly-by in the helicopter. Approximately 9 

polygons were visited at each FVA for a total of 225 samples. Most FVA polygons 

were sampled using a helicopter, but fixed wing Super Cub ‘slow fly-by’ or float 

plane ‘drop and pickup’ missions were also flown in several FVA’s where there was 

limited helicopter access. 
35 

Site ‘on the ground’ descriptions 

The purpose for this level of data collection was to support classification system 

refinement, to provide a more thorough understanding of the mapping classes and 

improved class descriptions, and to provide the required information for linking the 

landcover map to the plant communities. 
36 

One hundred and twelve ‘on the ground’ site descriptions were gathered during the 

field season by sampling within FVA polygons used for development of the GAAR 

map. One ground person was let off at a FVA and visited as many polygons as time 

allowed. Within a polygon, selection of sample sites was similar to the approach 

termed "subjective sampling without preconceived bias" as described by MuellerDombois and Ellenberg (1974). Site selection was based on homogeneous 

vegetation. Sample sites (homogeneous landcover units) were not chosen with regard 

to their position in any classification, extant or envisioned, or by applicability to 

specific management considerations. 

The ground person walked through a polygon and recorded vegetation composition, 

structure, and site variables. Vegetation description and physical site description 

forms were used to record information (Figures 13 and 14). Vascular and 

nonvascular vegetation information within the polygons was collected, and six letter 

codes were used to abbreviate species names. In most cases a full species list was 

obtained, however, if time was insufficant, only the dominant species from each 

structural layer was recorded. The six-letter code for a species combined the first 

three letters from the genus and specific epithet, and was based on Hulten (1968). 

Canopy cover was ocularly estimated (Brown 1954) for each species and could sum 

to greater than 100%. Dominant plant species not identified in the field were 

collected and identified in the office. Canopy height was estimated for the dominant 

species. 
37 
38 

Ground cover information was collected for each polygon. The categories are 

presented in Table 7. The percentages for the ground cover categories typically sum 

to approximately 100%. The percent surface within the polygon that was covered by 

woody debris greater than 5 inches in diameter was also recorded. 

 
39 

Table 7. Ground cover categories and definitions (adapted from Jensen et al. 

1992) 

Category Description 

Bare Soil <1/16 inch diameter soil particles and ash. 

Gravel 1/16 < 3 inches diameter. 

Rock >3 inches diameter. 

Litter and Duff Litter includes leaves, needles, twigs, fecal material, bark, and 

fruits; duff is the fermentation and humus sections of the 

organic layer. 

Wood Downed wood fragments > 1/4 inch diameter. 

Cryptograms All bryophytes, club mosses, and lichens. 

Basal Vegetation The soil surface taken up by the live basal or root crown 

portion of plants. 

Water That portion of the polygon's area that is covered by water at 

the time of the sampling. 

The following site variables were recorded within each polygon: slope, aspect, 

landform, surficial geology, hydrologic regime (dry, mesic, wet, aquatic), depth of 

soil peat, A, B and C horizons, depth to permafrost, and depth to water. Other 

recorded variables included air photo number, polygon code, landcover class name, 

landcover class code, date, surveyors, photos, latitude and longitude, environmental 

comments and disturbance comments. A photographic record was taken for each site. 

 The vegetation information recorded for fly-over descriptions was also recorded for 

each ground description. 

Incidental Observations 

The third level of detail was very general observations annotated on 1:100,000 and 

1:250,000 Landsat TM image maps during transit to and from FVA transect areas. 

These observations typically include a general vegetation call indicating, for example, 

“tussock tundra” without providing any indication as to the percentages of 

herbaceous, low shrub, tussocks, hydrologic regime, etc. They also often represented 

broad landscapes rather than particular sites. Photographs were often collected for 

these sites, and in some cases GPS points were recorded. The purpose of these sites 

was to provide a ‘reality check’ on the Landsat TM derived landcover map, and to 

provide additional general information for editing the map. Because of the long 

distances between FVA’s, nearly every major valley in GAAR was well represented 

by this type of observation. There were 631 incidental observation recorded and 

entered into the ArcView project database. 
40 

2.7 DEVELOPMENT AND EVALUATION OF SPECTRAL SIGNATURE 

DATABASE 

Field data collected in GAAR in ’98 were digitized and attributed. The FVA 

polygons were utilized to generate over 200 additional spectral signatures. A total of 

608 signatures were derived from the FirePro database. Therefore, the total number 

of signatures defined for GAAR was approximately 850. All of these signatures were 

evaluated for spectral homogeneity and size (minimum of 9 pixels). They were also 

interactively evaluated through interpretation of the simulated 4,5,3 (RGB) color 

associated with each signature. Finally, each signature was rechecked for proper 

mapping class assignment. The number of traininf signatures for each mapping class 

can be found in Appendix 2. 

2.8 SUPERVISED MAXIMUM LIKELIHOOD SATELLITE IMAGE 

CLASSIFICATION 

The derived signature files described above were utilized as input into a supervised 

classification of the TM scenes using the Maximum Likelihood (ML) classifier. ML 

classification was run on the 5-band (bands 2,3,4,5,7) TM image dataset. The output 

from the supervised ML classification of Landsat TM scene can be improved by the 

addition of other data or modeling layers that have the potential to improve the 

spectral classification. Illumination or shaded relief was found to improve the 

accuracy of the supervised ML output when included as a layer in the spectral 

database for separating aspect differences, and upslope versus floodplain. An 

illumination data layer was integrated with the 5 TM bands to create a 6-band (band 

2, 3, 4, 5, 7 and illumination) file, and the ML classifier was run on both the 5-band 

and 6-band files. The addition of the illumination layer resulted in approximately 5% 

improvement in the classification of the training data for most of the study area. An 

example of an illumination profile for the training signatures is provided in Figure 15. 

 However, due to the low stature of the vegetation and fairly low relief in arctic 

foothill region, the illumination layer of the 6-band TM data created a smoothing 

effect that reduced quality of the landcover map significantly in this area. Hence, the 

arctic foothill ecoregion was reprocessed as a 5 band data set (i.e., without an 

illumination layer). 
41 

Due to the large number of spectral signatures (over 200/scene), each TM scene was 

treated as a separate stratum for automated image classification. This situation was 

ideal for maximizing vegetation discrimination within each individual scene. The 

exceptions were the Path 77, Row 12 and Row 13 images which were processed as a 

unit due to the low number of spectral classes available in these two scenes. The 

training signatures were further evaluated based on a confusion matrix for each 

Landsat TM scene and training data for that scene. Classes that were below 75% 

accuracy were targeted for refinement of signatures. Signatures were added and 

deleted as appropriate from the signature files for each Landsat TM scene, and the 

supervised ML classifications rerun. 

2.9 SPECTRAL AND ENVIRONMENTAL MODELING 

2.9.1 Three Stages of the Modeling 

The output from the supervised ML classification for each Landsat TM scene was 

further refined through extensive modeling, using additional data layers that showed 

great potential for improving the spectral classification. These layers included slope, 

illumination (shaded relief), Transformed Normalized Difference Vegetation Index 

(TNDVI), and 4 Landsat TM bands 3, 4 and 5 (especially band 5), and Winter MSS 

Band 4. Not all classes of the ML classification required refinement or modeling, and 
42 

classes requiring modeling were selected based on their low per class accuracy on the 

training data confusion matrices of each classified TM scene. Three sequential stages 

of spectral and environmental modeling were implemented. 

Stage 1. Target mapping class level (43 classes) identified initially confused classes, 

suggested relevant modeling layers for discrimination between confused classes, 

established initial classification parameters, and refined the classification system for 

the entire Project Area. 

Stage 2. Endpoint mapping class level (30 classes) further refined techniques for 

discriminating confused classes within the 10-mile buffered GAAR area. 

Stage 3. Final endpoint mapping class level (30 classes) developed and tested the 

final models on 10-mile buffered GAAR area. These models were based on 

assumptions regarding landcover and terrain/landscape/surficial geology 

relationships, and summary statistics of vegetation distribution by surficial geologyderived landscape categories. Classes requiring modeling were selected based on 

their low class accuracy on the training data confusion matrices for the target 

mapping classes (43 classes). The primary goal of the Stage 1 modeling was to 

identify confused classes in each individual Landsat TM scene area, and determine 

what ancillary data from the environmental/spectral modeling database would be 

useful for separating the confused classes. The confusion matrices for the target 

mapping level (43 classes) were also reviewed in refining the classification system 

and revising the endpoint mapping classes (30 classes). 

Based on the evaluation of summary statistics for the training signatures with 20 

spectral/environmental modeling layers, modeling was focused on 10 of these layers 

that were determined to provide the highest potential for improving the landcover 

map. These modeling layers, the ML classification output, and the confusion matrices 

were reviewed interactively with ANHP in Anchorage in November 1998 to identify 

problems and class confusion in the ML classification, and to determine which 

modeling layers and parameters were useful and appropriate for correcting these 

problems. The key modeling layers identified were slope, illumination (shaded 

relief), elevation, Transformed Normalized Difference Vegetation Index (TNDVI), 

Landsat TM (Bands 3,4,5, especially band 5) and Winter MSS (Band 4). An example 

of a band 5 profile for the training signatures is provided in Figure 16. 
43 

A profile for the entire GAAR area of training signatures and mean elevation values 

is depicted in Figure 17. 
44 

For each of the key modeling layers, a graphic spectral and environmental profile was 

generated from the summary statistics showing the average value of the modeling 

layer for each of the 43 target mapping classes. Profiles for Bands 3,4,5 and TNDVI 

for each primary TM scene are located in Figures 18a, 18b, 18c, 18d, 18e, 18f and 

19a, 19b, 19c, 19d, 19e, 19f, respectively. This also was an essential tool for 

identifying spectrally confused classes based on the separability of the training 

signatures in these particular Landsat TM data layers (TM bands 4,5,3). Slope 

profiles for the training signatures were also developed to determine differences in 

slope characteristics of landcover classes which could be modeled to improve the 

landcover map (Figure 20). 
45 
46 
47 
48 
49 
50 

A secondary goal of Stage 1 modeling was to develop the “index” mapping classes in 

each individual TM strata. Index classes are those mapping classes which are readily 

identifiable through image interpretation (such as water, bare rock, and terrain and/or 
51 

cloud shadow) and provide a realistic frame of reference for future modeling or 

editing of the more challenging vegetation classes. 

Following model development, refinement and testing, the 43 target mapping classes 

were recoded to the 30 endpoint mapping classes. Stages 2 and 3 focused on 

improving the discrimination of these endpoint mapping classes using the key model 

layers identified in Stage 1. All Stage 2 and Stage 3 modeling (as well as all raster 

editing) was implemented at the 30 endpoint mapping class level. 

In Stage 2, models for discriminating confused classes were developed and applied to 

the ML output for each of the six individual Landsat TM scene areas. Because of the 

spectral variability between TM scenes, each scene (strata) was modeled separately. 

However, the model parameters were optimized and applied only to the portion of the 

TM scene contributing to the 10-mile buffered GAAR area mosaic (Figure 11). 

Initial parameters for modeling these classes were established based on review of the 

graphic spectral/environmental profiles for the key modeling layers. These 

parameters were refined using an interactive display of the classification viewerlinked to the model layer displayed with candidate parameter values color coded. If 

this visual evaluation showed promise, the model was executed on a class-by-class 

basis, and the model output layer was then visually checked through overlay and 

swiping operations on the ML classification (the pre-model version). An 

ecological/biophysical justification was required for every model implementation. 

Following each iteration, the model results were reviewed interactively to ensure 

accuracy and consistency. If the model output passes this evaluation, it was 

mosaicked into the thematic landcover database, or further modeled as appropriate. 

Additional iterations of the ML classification for each scene were conducted as 

particular signatures contributing to class confusion were refined and/or eliminated. 

This required review and reiteration of the models (or mosaicking in the earlier model 

outputs) on the revised ML classification. The decision to rerun the models or utilize 

the earlier version of the model outputs was based on interactive review of the 

original model outputs for a particular class overlaid on the revised ML classification. 

 In mid-Feb '99, a draft version of the landcover database (with most modeling steps 

and edits implemented) was reviewed with the project team botanists and ecologists 

from AKNHP and NPS in Anchorage. Based on this feedback, several additional 

modeling and editing steps were identified and implemented to develop the draft 

landcover map which was then thoroughly reviewed by NPS staff familiar with the 

project area and mapping project. Based on the NPS’s review of the draft landcover 

database, numerous edits were performed. Edits that could be accomplished through 

further modeling were incorporated in Stage 3 post-processing modeling. Most of the 

requested edits required interactive raster editing to implement. 

Final Stage 3 modeling involved development and application of terrain and 

landscape/surficial geology models to further refine the landcover classification 

through a post-processing step. These models were based on assumptions regarding 

landcover and terrain/landscape/surficial geology relationships. This involved first 

developing summary statistics of the draft landcover data with the major surficial 
52 

geology types (derived from Hamilton, 1999c), and then developing modeling 

parameters to exploit any strong terrain/surficial geology/landcover relationships. 

Due to the scale of the surficial geology data (1:250,000) relative to the Landsat TM 

data (~1:100,000) and the indirect and varying influence of surficial geology on 

vegetation, the surficial geology was not determined to be of great value for 

improving the landcover map through modeling. However, the 1:63,360 derived 

digital terrain data (slope and illumination) were found useful for modeling several 

classes based on upslope/floodplain occurrences. Illumination was also useful in 

representing the partial shadow effect as an additional data layer in the spectral 

database. 

2.9.2 Summary of Key Data Layers Used for Modeling 

The TNDVI (Transformed Normalized Difference Vegetation Index) was useful for 

refining the prostrate shrub classes, sparsely vegetated, and bare-ground classes 

because of the direct relationship of relative “greenness” to separability of these 

classes. Spectral reflectance of the TNDVI layer is less affected by terrain shadow, 

which was particularly important for discriminating these classes in alpine areas of 

the Brooks Range. 

Illumination/aspect was useful for refining upslope versus floodplain and aspect 

differences. Because of the various illumination conditions dependent on local 

aspect, slope and neighboring terrain, and the limited direct relationship between 

illumination and vegetation, this layer was determined to best represent the modeling 

as a continuous variable (as opposed to discrete aspect categories such as S, SE, SW, 

etc.). This layer also improved the accuracy of the supervised ML output when 

included as a layer in the spectral database, particularly in areas that were in partial 

terrain shadow. 

Winter MSS Imagery was useful for separating woodland/open spruce from wetland 

herbaceous, or wet herbaceous from other classes. It was also useful for 

distinguishing low shrub classes from woodland/spruce forest. However, this 

application was limited due to low sun angle and extreme shadow problem in winter 

imagery. 

Band 5 TM was useful for establishing thresholds for mapping classes based on 

moisture/amount of standing water, for example, refining mesic herbaceous areas 

with areas of very dark (wet) areas to wet herbaceous. Band 5 was also used 

extensively with delineation of AOI's to refine water classes. 

Slope was useful for discriminating floodplain from upslope and water/shadow 

separation. The raw slope layer (based primarily on 1:63,360 level DEMs) contained 

too many contour line relics to be useful for modeling. Several different approaches 

and scales to eliminating relics were investigated, and it was determined that a 5x5 

smoothing (low pass) filter removed most problems while preserving the essential 

detail for upslope/floodplain modeling. 
53 

Several methods were investigated to utilize the illumination layer to improve the 

landcover classification. The most successful was incorporating the illumination 

layer into the 5-band TM spectral database utilized in the supervised ML 

classification process. TNDVI was effective for modeling the bare-ground, sparse, 

and prostrate classes. TM Band 5 was effective in separating these classes and 

improving characterization of water areas, as well as separating the wet herbaceous

class from mesic herbaceous or shrub birch-willow-tussock tundra. Winter MSS data 

(band 4) were used to improve the woodland and spruce forest separation, reducing 

confusion between woodland and low shrub (Shrub birch-ericaceous-willow and 

shrub birch-willow-tussock tundra) and improving the graminoid-forb wet classes 

(this reduced commission error with woodland/spruce). However, the low sun 

angle/large shadow during Winter image acquisition limited the effectiveness of these 

data to well illuminated areas. Slope was useful in separating floodplain from 

upslope area, and was therefore used to separate balsam poplar forest (floodplain) 

from aspen-birch forest (upslope). It was also used to separate black spruce 

(floodplain) from white spruce (upslope). A latitudinal treeline coverage was also 

developed and used to ensure no forested areas occurred north of treeline. Most of 

these problems occurred in terrain shadow areas, or in very wet sites (wet herbaceous

or silty/clear water classes). 

2.9.3 Consideration of Ecoregions in Modeling and Editing 

As described in Section 1.5, the GAAR project area encompasses three ecoregions: 

1) Arctic foothills 

2) Brooks Range 

3) Interior forested lowlands and uplands 

Each region includes climate, landscape, and ecological processes that influence 

vegetation. Based on previous studies and literature review, field data collected as 

part of the FirePro program and the 1998 field season, and applying this information 

in interpreting Landsat TM imagery, we have more precisely delineated each of the 

regions (Figure 3a). This delineation was necessary in order to utilize the relatively 

small scale (1:1,000,000) existing ecoregions information in editing the relatively 

large scale (~1:100,000) landcover database. 

Based on interactive review of the incidental observations coverages from the 1998 

field season, the digitized annotations from NPS’s 1:250K quadrangle mapsheets, and 

the mosaiked multispectral TM imagery (displayed as 4,5,3 RGB), a latitudinal 

treeline coverage was developed for the buffered GAAR area. This coverage was 

utilized for defining the northern extent of the Interior forested lowlands and uplands 

region. The arctic foothills region was interpreted from the TM imagery and a 

preliminary version (2/12/99) of the landcover database. The Brooks Range region 

was defined as the area north of the northern boundary of the Interior lowland/upland 

region region (treeline) and south of the arctic foothills region. For purposes of 
54 

establishing surficial geology/landcover relationships (Section 1.6), the Brooks Range 

and arctic foothills regions (areas north of latitudinal treeline) were combined as one 

stratum. The Forested interior lowland/upland region (south of treeline) was 

determined to have significantly different surficial geology/landcover combinations, 

and was therefore treated as a second stratum. 

In the Brooks Range and interior lowland/upland region regions, the quantity and 

distribution of spectral signatures and “natural” stratification of the TM scenes 

corresponding with the regions (Brooks Range – Landsat TM Row 12; Interior - Row 

13) resulted in a good characterization of the landcover in these regions based on the 

multispectral ML classification. However, significant post-processing was required 

to account for the diversity of mapping classes, and spectral confusion. 

In the case of the arctic foothills, it was determined that the similarity in stature and 

form of the vegetation (relative to the 28.5m TM data) in the region required separate 

 spectral processing and modeling. 

In general, north of treeline and south of the arctic foothills, open deciduous forests 

were recoded to open tall alder-willow, and closed deciduous forest or mixed 

broadleaf-spruce forest were recoded to tall closed alder-willow. In the arctic 

foothills ecoregion, these classes were recoded to tall open willow, and tall closed 

willow respectively. In several areas in the North portion of the project area, these 

darker signatures initially mapped as open spruce, mixed forest or woodland were 

actually patterned ground, and were recoded as such. North of treeline, open spruce 

and woodland spectral classes were recoded to sparsely vegetated or terrain 

shadow/indeterminate (primarily this class occurred in drainages as mixed pixels of 

bare-ground, rock partially obscured by shadow). 

2.9.4 Modeling to Reduce Spectral Confusion Between Mapping Classes 

Models and parameters applied to each individual Landsat TM scene (strata) are 

detailed in Tables 8a, 8b, 8c, 8d, 8e, 8f. These models and the underlying 

physiological process permitting separation by one or more modeling layers are 

summarized in the following paragraphs (listed approximately in order of model 

iteration from first model to last model applied). 

Water / Shadow confusion. In areas of high terrain and extensive terrain shadows, 

erroneous water often appeared in areas of shadow or partial shadow. A combination 

of illumination, slope, and the preliminary classification (ISODATA) was used to 

ensure that overclassified water areas were recoded to shadow based on the principal 

that mappable water bodies only occur on low slope areas, and not in terrain shadow 

areas. The illumination and preliminary classification were again used to enhance the 

shadow class. 

Prostrate shrub-rock / Sparsely vegetated / Bare-ground confusion. The “greenness” 

as indicated by NDVI was used to separate the prostrate shrub-rock/sparsely 
55 

vegetated/bare-ground rock classes. This layer was particularly useful because of 

partial penetration of terrain shadow. 

Snow/Ice and Bare-ground confusion. The preliminary (ISODATA derived) 

classification was used to develop a snow/ice and bare rock layer. Particular clusters 

corresponding with snow, ice, and bare rock were selected from the ISODATA 

classification, and used as a mask for these classes. 

Prostrate / Prostrate shrub-rock / Prostrate shrub-lichen confusion. Once the 

prostrate classes were separated from the sparsely vegetated and bare-ground classes, 

further thresholding with NDVI was used to break out the prostrate from the 

prostrate-rock class. The prostrate shrub-lichen was more spectrally unique, and 

generally was well represented in the ML classification output. 

Water / Bare-ground confusion. Water and bare-ground areas were confused, 

particularly along rivers and lake edges. Landsat TM Band 5 was used extensively 

during editing to reduce this problem. Slope and illumination were also again used to 

ensure that lakes were realistically depicted. 

Wet herbaceous / Spruce woodland confusion. Wet herbaceous was initially 

overclassified in numerous sites. In the southern and central portions of the project 

area, woodland (or open spruce forest) were misclassified as wet herbaceous. Winter 

MSS (Band 4 NIR) imagery and the illumination data layer were utilized to 

discriminate correctly classified wet herbaceous areas from misclassified woodland 

areas. For integrating Winter MSS data in moderately well illuminated areas, low 

stature vegetation has brighter reflectance (white response due to homogenous snow 

pack) than woodland (gray response due to snow/spruce shadow pattern) or open 

spruce forest (darker gray response due to more spruce shadow dominated snow 

pattern). The misclassified wet herbaceous areas were recoded to woodland. Due to 

low sun angle in the Winter MSS imagery (and resulting severe terrain shadow 

particularly in the Brooks Range region), this model was only useful in moderately 

well illuminated aspects (S and SE). 

Spruce woodland / Low shrub confusion. Although incorporation of the illumination 

layer in the spectral database reduced this type of confusion, areas of fairly low 

illumination continued to show some spectral confusion between the woodland and 

low shrub classes. Winter MSS (Band 4 NIR) was useful in correcting woodland 

areas misclassifed as low shrub (shrub birch-willow-tussock tundra and shrub birchericaceous-willow). Again, however, this model could only be used in moderately 

well illuminated areas. In the central and southern portions of the project area, low 

shrub in partially shadowed aspects was misclassified as woodland. In these areas, 

raster editing based on the FirePro and 1998 field data and image annotations was 

utilized to determine whether the woodland on partially shadowed aspects was 

legitimate or was actually a low shrub or prostrate class (depending on northern 

latitude and context). Determining the specific low shrub class was also based on the 

context of the site (review of the mapping classes of surrounding areas). This 
56 

approach was very difficult in the transition areas between the Forested 

Lowlands/Uplands and Brooks Range ecoregions (in this area, woodland did occur on 

low to moderate north aspects). Where woodland occurred on the south aspect of an 

E-W drainage, the north aspect was usually dominated by low shrub (generally shrub 

birch-willow-tussock tundra in floodplain, and shrub birch-ericaceous-willow on 

upslopes. There were too many exceptions to this rule to allow realistic model-based 

separation of these two low shrub classes). Where low shrub or open tall shrub

occurred on the south aspects of an E-W drainage, the north aspect was usually 

dominated by prostrate shrub with low shrub stringers. 

Wet herbaceous / Mesic herbaceous / Shrub birch-willow-tussock tundra confusion. 

Wet herbaceous is also misclassified North of treeline. Wet herbaceous was 

extensively overclassified in the ML classification in the Brooks Range and arctic 

foothills ecoregions. Band 5 TM data was very useful for thresholding very wet sites 

within the wet herbaceous mapping class from less wet sites (mesic herbaceous). In 

the Arctic foothills, many of these resulting wet herbaceous areas are closely grouped 

sub-pixel patterns of water tracks. 

In the northern portion of Path 73, Row 13 (hereafter abbreviated as “p73r13”), wet 

herbaceous was confused with shrub birch-willow-tussock tundra. This is for the 

most part North of treeline. Here also, Band 5 was used to threshold actual wet 

herbaceous from those sites that were either mesic herbaceous or shrub birch-willowtussock tundra. 

On the south side of Noatak River, wet herbaceous also appeared to be overclassified 

and required recode to mesic herbaceous utilizing TM Band 5. Also in glaciated 

valleys of eastern portion of the arctic foothills, patterned ground class was 

misclassified as wet herbaceous, and required raster editing. This is due to 

heterogeneity of the patterned ground class, and reduced spectral reflectance due to 

the dominant water component of this class (particularly sub-pixel size low-centered 

polygons). 

Mesic herbaceous / Shrub birch-willow-tussock tundra confusion. This confusion 

occurred North of the treeline boundary (primarily in Row 12 scenes in the arctic 

foothills and south into those valleys forming the headwaters of the north flowing 

rivers out of the Brooks Range). This error also occurred in the valleys of the Brooks 

Range region. Because of the high number of training samples (signatures) of mesic 

herbaceous and low shrub birch-willow-tussock tundra, the spectral based 

classification was relied on as the primary discriminator between these classes. In the 

arctic foothills, incorporation of the illumination layer in the TM spectral database as 

part of the ML classification was determined to create additional spectral confusion 

between the mapping classes. Also, several errors in signatures were noted in this 

region. All signatures were reviewed and the ML classification reiterated with only 

the TM spectral database (w/o illumination) for this region (TM scenes p73r12, 

p75r12, p77r12). This process improved the preservation of linear features (water 

tracks and small shrub-line streams) as well as the consistency of the landcover 
57 

information in this region. 

Mesic herbaceous / Prostrate shrub confusion. In the higher elevation valleys, mesic 

herbaceous areas were found adjacent to prostrate shrub areas. This confusion was 

particularly problematic when the herbaceous content of the prostrate shrub areas 

was close to the 25% upper threshold for this mapping class. Because of the large 

number of training samples (signatures) for each of these two classes, the spectral 

classification was relied heavily for discriminating these two classes. Other modeling 

layers were ineffective at separating the two classes, and image interpretation and 

review of CIR photos was also not effective at reducing the confusion. 

Balsam poplar forest / Paper birch-aspen forest and Mixed spruce-birch-aspen forest

/ Mixed spruce-balsam poplar forest confusion. Slope was used to model these 

classes based on the assumption that balsam poplar occurred only in floodplain 

(minimal slopes) while aspen-birch occurred only on upslope areas. The “raw” slope 

data proved to be unusable due to contour line relics from the interpolation process 

during DEM creation. However, several iterations or tests were performed to 

determine a suitable filtering method. Applying a 5x5 majority filter to the raw data 

resulted in a dataset suitable for modeling this level of general site slope 

characteristics. Erroneous open balsam poplar primarily in upslope areas in the south 

park buffer (forested lowland and upland interior ecoregion) also required extensive 

editing based on image interpretation. These areas were generally edited to be open 

white spruce or woodland classes. 

Closed tall shrub/ Open and closed paper birch-aspen forest confusion. Spectral 

confusion between the closed tall shrub class (mainly alder) and the paper birchaspen forest classes was observed in the southern portions of the buffered GAAR 

area, particularly in the 10-mile buffer area around the park (where ground reference 

data was very limited). These problems were in relatively small areas and mainly 

errors of omission for the broadleaf forest classes, but errors of commission for the 

closed tall shrub class. Because limited training signatures were available for the 

broadleaf forest classes (approximately 4 signatures for each of the four different 

broadleaf forest types), raster editing based on review of the FirePro and 1998 field 

data, image annotations, and image interpretation (with CIR spot checking) was 

relied on for improving these classes. The tall shrub classes were very well 

represented by training signatures (approximately 70 signatures total for open and 

closed tall shrub classes), and within the park appeared to be accurately depicted. In 

the forested interior areas to the south of the park (but within the 10-mile buffer), the 

broadleaf forest or mixed forest was more prevalent, and underrepresented by our 

FirePro 1998 field data derived signature database. 

Rivers and small lakes/ponds. In the spectral based ML classification and initial 

modeling for each TM scene, the continuity of the water class in a number of 

primary/secondary rivers required improvement. Also, the distinction between silty 

water and clear water classes was inconsistent. Changes in water levels between the 

multiple dates of scenes also resulted in problems in maintaining continuity of rivers 
58 

at TM scene boundaries. Also, small ponds (less than 4 pixels) appeared to be 

underrepresented. 

To correct these problems, an additional modeling step was added during the 

interactive raster editing process. This involved first creating a clear water/silty 

water/shadow “candidate” layer by establishing thresholds in TM Band 5 through 

interactive interpretation. This layer was then raster edited simultaneously with the 

complete landcover database using the TM imagery and selected airphotos as a guide. 

 Areas in the water candidate layer that were visually interpreted as “true” water were 

maintained as water classes, while shadow areas were eliminated from further 

consideration as water types. Following completion of raster editing, this “corrected” 

water layer was mosaiked into the landcover database. 

Spruce characterization. The open all spruce forest areas were recoded to either open 

black spruce forest class or open white spruce forest class based on terrain and aspect 

site characteristics. Open spruce, unspecified which occurred in the floodplain 

landscapes was recoded as open black spruce-like forest while open spruce, 

unspecified which occured on upslope positions was recoded as open white sprucelike forest. 

This editing step was implemented as the final edit to the 30 class draft landcover 

database. A combination of modeling with illumination and slope was utilized to 

make the distinction between floodplain and well illuminated upslope spruce forests. 

Several potential slope thresholds were investigated, applied, and provided to NPS in 

hardcopy and digital form for review. Based on this review, a threshold of 10% slope 

was chosen as the lower limit of the open white spruce-like forest class, with open 

black spruce-like forest occurring between 0 and 10% slope. This assumption 

required modifying the open black spruce-like forest class description to include open 

white spruce forest occurring in the floodplain (often found along river 

meanders/oxbows). 

Due to some errors resulting from the assumptions regarding spruce landscape site 

characteristics, as well as scale limitations of the digital elevation and derived slope 

and illuminating information, a version of the digital database was also developed 

which collapses the two open spruce categories into a single open spruce class 

(species unspecified). This version of the landcover database is available through 

NPS-AKSO. 

2.10 RASTER EDITING AND FILTERING APPROACH 

Raster editing is the process of changing, adding, or deleting raster attributes or data 

values of thematic and continuous raster data. Raster editing is used in image 

classification to correct bad or noisy data values, or to recode or reassign pixels to 

another class. The image analyst can use modeling functions for computing the values 

to replace noisy pixels or areas in the image data. In the GAAR landcover project, 
59 

raster editing was focused on classes that could not be separated effectively through 

models, but could be positively identified through image interpretation and review of 

the GAAR Landcover Database (FirePro, 1998 field data, annotations/notes). 

During preliminary product development, the landcover map was first reviewed at 

small scale (1:250,000) to identify obvious problems. More detailed editing was 

conducted at approx. 1:100,000 throughout the GAAR project area. In most cases, 

areas requiring edits were analyzed to determine whether problems could be resolved 

through further modeling. Many edits were completed through this approach (further 

refinement of and application of models on a local or ecoregion basis). The FirePro 

database and coverages from the 1998 field season implemented in the Field Data 

Browser were also used extensively in editing/reviewing the landcover map. CIR 

aerial photos (1:60,000) were used to spot check questionable areas in the landcover 

map. 

Airphoto interpretation was used to verify and spot check TM image interpretation. 

Prior to implementing edits, all FVA's were evaluated extensively with airphoto 

enlargements, image prints, and the Field Data Viewer (FirePro and '98 data). 

Problem classes were identified for FVA areas, and then other non-FVA areas 

investigated to look for similar problems. Raster editing at a display scale of 

1:100,000 was planned. However, the hard copy review materials were required at 

1:63,360 (unfiltered), and therefore much of the editing was completed at 1:63,360 or 

larger scale. To reduce focusing edits on insignificantly small areas, a 2 acre filtered 

version of the database was linked to the unfiltered version being edited. This 

permitted identification of large problem areas (rather than noise) that would appear 

in the unfiltered database. Priority for raster editing was focused along mosaic scene 

boundaries, and within the park boundaries (where virtually all ground reference data 

was located). Substantial editing was also required within the 10-mile park buffer. 

This editing was difficult due to the lack of field data for areas outside the park (other 

than incidental observations and image annotations). Further edits were required 

following modeling to clean-up bare-ground and sparsely vegetated/shadow areas 

(particularly in the western portion of the project area covered by p77r12 and 

p77r13), and also to clean up problems in the cloud obscured north-west portion of 

the buffered GAAR area (p73r12). Additional edits to other classes in p77r12 and 

p77r13 were required due to the radiometry/low vegetation response of these late 

August satellite images. Further edits were completed based on comments from NPS 

review of the draft landcover classification in July/August 1999. This review focused 

mainly on the evaluation of hardcopy 1:63,360 products for the entire project area (16 

tiles). NPS staff familiar with the park or particular areas reviewed and annotated 

recommendations on the draft plots. EarthSat reviewed these comments with NPS, 

and implemented all requested edits (including refinement of existing models). 

Following implementation of all NPS requested edits, the unfiltered pixel map was 

filtered through a three step process to arrive at the 2 acre minimum mapping unit 

(MMU). First, all single “detached” pixels were identified and recoded to the 

mapping class of the majority occurring pixels surrounding the detached pixel. 
60 

Second, the resulting map was run through a clumping algorithm which grouped 

connected pixels into millions of individual clusters of like mapping class pixels. 

Third, an elimination algorithm was then applied to this clumped file so that all 

groups of less than approximately 2 acres (9 pixels) were automatically recoded to 

the majority occurring class surrounding the clump. [Note: Although 9 pixels is 

actually about 1.5 acres, a nine pixel MMU is consistent with a 3 pixel by 3 pixel 

window, which is simpler to visualize when using the landcover map.] The 5 acre 

MMU product was created by simply passing the 2 acre MMU through a 5 x 5 (low 

pass) majority filter. 

2.11 QUALITY CONTROL AND EVALUATION 

Throughout the project, from fieldwork to final product, the image analyst, botanists, 

and ecologist team remained consistent. This ensured a high level of consistency in 

the landcover map. Several face-to-face modeling and evaluation steps resulted in 

the involvement of the project team in discussions regarding classification system and 

editing/modeling. Flexibility and customization in terms of mapping classes, scale of 

hardcopy draft products, and final MMU resulted in a more useable suite of products. 

 A detailed review of the draft product by NPS and substantial feedback resulted in 

significant edits to the landcover map to produce the final map product. 
61 

CHAPTER THREE 

RESULTS AND DISCUSSION 

3.1 DISTRIBUTION OF LANDCOVER WITHIN GAAR 

The distribution of landcover in the GAAR Project Area is as follows (Table 9): 

• 17.69% area in needleleaf forestand woodland, 

• 0.53% in broadleaf forest, 

• 0.54% in mixed forest, 

• 5.88% in tall shrub, 

• 22.10% in low shrub, 

• 24.42% in prostrate shrub, 

• 6.47% in herbaceous, 

• 16.17% sparsely vegetated or bare-ground, 

• 1.15% water, 

• 0.36% snow/ice, 

• 0.18% mosaic/pattern vegetation, and 

• 4.52% indeterminate (mostly clouds and terrain shadow). 
62 

3.2 ACCURACY ASSESSMENT

Both qualitative and quantitative evaluations of errors were made at various stages of 

developing the GAAR landcover map for the purpose of improving or refining the 

mapping process. Accuracy assessments were performed on the endpoint (30 class) 

and general (22 class) final GAAR landcover in order to quantitatively determine 

what proportion of the overall landcover map decision is correct, the probability that 

individual landcover classes are correctly mapped, which landcover classes are 
63 

overestimated or underestimated, and the distribution of errors between mapping 

classes. Due to the relatively small number of samples in the reserved accuracy 

assessment database (64 sites total), the authors consider the much larger training 

database (851 sites) to be a more representative dataset to draw conculsions as to 

mapping class confusion and reliability. Therefore, this training dataset is used as the 

source for all accuracy statements in this report. However, the complete confusion 

matrices, and user’s and producer’s accuracies for both the accuracy assessment 

database (reserved from training/processing) and the training database (included in 

the processing and therefore biased) are included in this document as Tables 10a, 

10b, 11a, and 11b. 

An estimate of overall accuracy (based on comparison of the 5 acre MMU landcover 

data with the approximately 850 training areas) for the 30 landcover classes is 83% 

(Table 10b). The user’s accuracies for general landcover types are as follows: 78.9% 

for needleleaf forest and woodland, 79.2% for broadleaf forest, 93.0% for mixed 

forest, 90.1% for tall shrub, 87.0% for low shrub, 78.6% for prostrate shrub, 72.0% 

for herbaceous, 90.7% for sparse /barren, 99.8% for water, and 99.9% for snow/ice. 

Error matrices (also called confusion matrices) and associated statistics have been 

adopted by the remote sensing community as the standard technique for accuracy 

assessment (Campbell 1987, Congalton 1991, Jensen, 1996). 

An error matrix is a square array of numbers set out in rows and columns that 

represents the number of information classes or classification categories, used to 

compare on a category-by-category basis, the relationship between known reference 

data and the corresponding results of a classification (Tables 10a, 10b, 11a, and 11b). 

The columns and rows of an error matrix show the number of sample units assigned 

to a particular landcover class (classification data) relative to the actual number of 

sample units that belong to the landcover class (reference data). From an error matrix 

the overall accuracy of the classification of a landcover map can be quantified along 

with both the producer’s accuracy (or errors of omission or exclusion) and user’s 

accuracy (or errors of commission or inclusion). The overall accuracy is computed as 

the sum of all the main diagonal cells in the error matrix divided by the total number 

of sample units used in the error matrix. The overall accuracy shows the proportion of 

the classification that is correct but it does not indicate how the accuracy is 

distributed across the individual landcover classes. (Story and Congalton 1986). 

The producer’s accuracy is the sum of all correctly classified sample units in a 

landcover class divided by the total number of reference data in that landcover class. 

The producer’s accuracy indicates how well members of a particular landcover are 

classified, or shows the ease or difficulty with which members of a particular 

landcover class are correctly identified, classified or mapped by the mapping 

methodology. On the other hand, the user’s accuracy indicates the probability that a 

particular landcover class (classification data) would represent that landcover class in 

the reference or ground truth data. The user’s accuracy, computed as the sum of all 

correctly classified sample units in a landcover class divided by the total number of 
64 

classification data in that landcover class, is termed a measure of reliability in specific 

map categories. The error of commission is computed as 100% minus the producer’s 

accuracy and error of omission is 100% minus user’s accuracy. 

Typically, ground reference data are reserved for accuracy assessment purposes from 

those data used for supervised training signatures. This procedure was followed in 

the GAAR landcover project. However, because of the relatively small accuracy 

assessment database for GAAR (64 polygons), and the limited representation within 

this database of many of the landcover classes, an additional accuracy assessment was 

performed using the training signature data. As previously stated, the estimates of 

accuracy throughout this document are primarily based on a 5 acre minimum 

mapping unit landcover database with the training data set. However, both sets of 

confusion matrices are included for additional reference related to accuracy and 

mapping class confusion (Tables 10a, 10b, 11a, 11b). 
65 
66 
67 
68 
69 

3.3 DISCUSSION OF ACCURACY OF LANDCOVER CLASSES 

The estimated overall accuracy for the 30 class landcover data at 5 ac MMU when 

compared to the training database was 83% (or 79% based on comparison with the 

accuracy assessment database). 

The estimated overall accuracy for the 22 class landcover data at 5 acre MMU when 

compared to the training data was 89% (or 95% based on comparison with the 

accuracy assessment database). 

Classes showing primary confusion are discussed below. Additional details 

regarding spectral confusion can be found in Section 3.6. Landcover Class 

Descriptions. All accuracies refer to the 30 class landcover data at a 5 acre mapping 

unit. 

Mapping classes showing a particularly high degree of confusion (less than 65% 

producer’s or user’s accuracy) included open black spruce-like forest, open white 

spruce-like forest, spruce woodland, open balsam poplar forest, closed spruce 

broadleaf forest, open tall shrub, and shrub birch-willow-tussock tundra, and wet 

herbaceous. 

The producer’s accuracy for the open black spruce-like class was 63.9%, with a 

user’s accuracy of 53.5%. The producer’s accuracy for the open white spruce-like

class was 37%, with a user’s accuracy of 47%. Most of the errors of commission and 

omission were due to confusion between the two open white spruce-like classes and 

to a lesser extent with the woodland classes. The open black spruce-like forest sites 

with tall shrub understory also exhibited some confusion with the mixed sprucebroadleaf forest and the tall shrub and low shrub classes. This is due to the high IR 

(infrared) response characteristic of the broadleaf tree and shrub species. Because of 

the substantial spectral confusion between the two open spruce classes, slope and 

illumination models were utilized based on the assumption that open white sprucelike forest occurs on well illuminated upslopes, while open black spruce-like forest

was assumed to occur on low slopes and floodplains, under average to well 

illuminated conditions. When considering the open black spruce-like and open white 

spruce-like forest classes as a single mapping class, the producer’s accuracy increases 

to 84%, while the user’s accuracy also improves to 84%. 

The producer’s accuracy for the open balsam poplar forest class was 20%, with a 

user’s accuracy of 62%. Errors of commission and omission were due to confusion 

with the open paper birch-aspen forest class and the open tall shrub class. Slope was 

used to model these classes based on the assumption that balsam poplar occurred only 

in floodplain (minimal slopes) while aspen-birch occurred only on upslope areas. 

Because limited training samples were available for the closed paper birch-aspen 

forest classes (4 signatures), raster editing based on review of the FirePro and ’98 

field data, image annotations, and image interpretation (with CIR spot checking) was 

relied on for improving these classes. The Landsat TM 4,5,3 (RGB) signatures for 
70 

this class are light orange-red, with increasing red and orange brightness 

corresponding to the low density of the low shrub understory. When considering all 

the closed and open broadleaf forest classes as a single broadleaf forest mapping 

class, the producer’s accuracy is 82%, while the user’s accuracy is 79%. 

The producer’s accuracy for the spruce woodland class was 72%, with a user’s 

accuracy of 51%. Some of the errors of commission and omission were due to 

confusion with the open black and open white spruce-like forest classes. This 

generally occurred when a spruce woodland site included 15-24% lichen, but not 

enough to be classified as a spruce-lichen woodland site (> 25% lichen required). 

However, of greater concern is the large errors of commission found in the low shrub 

classes, and in particular, the shrub birch-ericaceous-willow class. This confusion 

generally occurred on partially shadowed aspects that resulted in darker signatures 

that a well illuminated low shrub class. Although incorporation of the illumination 

layer in the spectral database reduced this type of confusion, areas of fairly low 

illumination continued to show some spectral confusion between the woodland and 

low shrub classes. Where woodland occurred on the south aspect of an E-W drainage, 

the north aspect was usually dominated by low shrub (generally shrub birch-willowtussock tundra in floodplain, and shrub birch-ericaceous-willow on upslopes, but 

with too many exceptions to this rule to allow realistic model-based separation of 

these two low shrub classes). Where low shrub or tall shrub occurred on the south 

aspects of an E-W drainage, the north aspect was usually dominated by prostrate 

shrub with low shrub stringers. When considering the spruce woodland and sprucelichen woodland classes as a single mapping class, the producer’s accuracy increases 

to 75%, while the user’s accuracy also improves to 56%. 

The producer’s accuracy for the closed spruce-broadleaf forest class was 57%, with a 

user’s accuracy of 88%. Errors of commission and omission were due primarily to 

confusion with the open spruce-broadleaf forest and the open white spruce-like forest

classes. The spruce-broadleaf forest classes are by definition spectrally mixed, and 

are very difficult to separate spectrally from open spruce forests with tall shrub 

understory. Manual editing based on review of the FirePro and ’98 field data, image 

annotations, and image interpretation (with CIR spot checking) was relied on for 

improving these classes. Because this class was relatively rare, efforts were made 

during field work to make extensive image annotations identifying areas of closed 

spruce-broadleaf forest. When considering all the closed and open spruce-broadleaf 

forest classes as a single mixed spruce-broadleaf forest mapping class, the producer’s 

accuracy is 77%, while the user’s accuracy is 93%. 

The producer’s accuracy for the open tall shrub class was 60%, with a user’s 

accuracy of 83%. Errors of commission and omission were due primarily to 

confusion with the closed tall shrub and the shrub birch-ericaceous-willow and shrub 

birch-willow-tussock tundra classes. The confusion with these low shrub classes was 

found mainly on partial terrain shadowed areas, where the low shrub classes were in 

significant abundance as the understory. Incorporation of the illumination (shaded 

relief) data in the supervised spectral classification reduced this confusion; However, 
71 

this class did require substantial editing based on review of the FirePro and ’98 field 

data, image annotations, and image interpretation. When considering both the closed

and open tall shrub classes as a single tall shrub mapping class, the producer’s 

accuracy is 77%, while the user’s accuracy 

is 90%. 

The producer’s accuracy for the shrub birch-willow-tussock tundra class was 64%, 

with a user’s accuracy of 77%. Errors of commission and omission were due 

primarily to confusion between shrub birch-willow-tussock tundra class and to a 

lesser extent with the prostrate shrub classes (with a relatively large herbaceous 

component) or the mesic herbaceous class (with a relatively large shrub component). 

 Because of the high number of training signatures for shrub birch-willow-tussock 

tundra , mesic herbaceous and shrub birch-ericaceous-willow, the spectral based 

classification was relied on as the primary discriminator between these classes. There 

was also confusion north of treeline with the wet herbaceous class. The wettest 

shrub birch-willow-tussock tundra sites were usually spectrally separable from the 

drier of the shrub birch-ericaceous-willow sites (however, these wet tussock tundra 

sites were usually confused with the mesic or wet herbaceous classes). Finally, there 

were some commission errors with the woodland classes. Part of this confusion was 

often due to partial terrain shadow. Another factor believed to contribute to 

commission errors in woodland areas were sites with relatively low spruce cover (10-

15%) with understory dominated by low shrub. When considering the shrub birchwillow-tussock tundra, shrub birch-ericaceous-willow, and closed low willow classes 

as a single low shrub mapping class, the producer’s accuracy is 82%, while the user’s 

accuracy is 87%. 

The producer’s accuracy for the wet herbaceous class was 60%, with a user’s 

accuracy of 98%. Errors of commission and omission were due primarily to 

confusion between the shrub birch-willow-tussock tundra and mesic herbaceous

classes, as well as some confusion with the silty water class. Based on the Landsat 

TM 4,5,3 (RGB), signatures for this class typically are darker grey to blue with red 

tones. Signatures for sites in early or late season (when minimal active vegetation 

covers the site) often appear even darker due to the spectral absorption characteristics 

of the seasonally wet site. There was also significant commission errors with the 

open spruce forest classes. Modeling with winter imagery (Landsat MSS Band 4) 

resulted in some reduction in these errors. Modeling with TM Band 5 (which is 

highly sensitive to water/moisture) was effective at separating the wet herbaceous

sites from the mesic herbaceous sites. When considering the wet herbaceous, mesic 

herbaceous, and the aquatic herbaceous classes as a single herbaceous mapping 

class, the producer’s accuracy is 79%, while the user’s accuracy is 72%. 

3.4 DISCUSSION OF APPLICATIONS AND LIMITATIONS 

To properly interpret and apply the landcover classes developed in the GAAR 

mapping project, users must bear in mind the characteristics of the data used to derive 
72 

the map, as well as the characteristics of the vegetation and other landcover types of 

interest. It is important to note that the GAAR landcover project had the objectives 

to 1) map landcover characteristics that could be recognized by Landsat imagery, and 

2) delimit mapping classes that are flexible enough to describe potential new classes 

derived from Landsat imagery. Hence, although the mapping classes were derived 

from the Alaska Vegetation Classification (Viereck et al. 1992), they did not strictly 

adhere to this classification hierarchy. In the GAAR project, the landcover 

classification system was customized so as to take advantage of the characteristics of 

the Landsat TM data, while balancing the mapping detail needs of the end user. This 

classification system and the determination of final mapping classes remained open 

for discussion well into the image processing phases of the project. Review of the 

Landcover Class Descriptions (Section 3.6) and this section provide additional insight 

into the characteristics of the mapping class species composition as related to the 

Landsat TM data. 

For the 7-band Landsat TM data with a pixel size of 28.5m, the scale of derived maps 

should be no larger than 1:63,360. However, at this large of scale very few landcover 

types can be consistently mapped without generating a great deal of “noise” or 

scattered pixels. A more appropriate mapping unit for Landsat TM derived landcover 

products is 5 acre (25 pixels). At this size of mapping unit, many of the small linear 

features (streams, riparian shrub areas, ridge lines, pipelines) can be lost in the 

filtering process. In order to preserve more of the spatial detail found in the 

unfiltered landcover data, the final landcover database was filtered to approx. 2 ac (9 

pixels). While this mapping unit resolution provides a good compromise for 

legibility (not pixilated), 5 ac is still recommended as the appropriate minimum 

mapping unit for this landcover data. For purposes of estimating class accuracy in 

this report, the 5 ac landcover data was utilized. 

However, both the 2 ac and unfiltered (pixel) landcover data are included in the 

ArcView 3.1 GAAR Landcover Field DataViewer product (Table 1). Further 

environmental and ecological factors important for optimal use of the landcover map 

are discussed in the following paragraphs by ecoregion. 

Arctic Foothills 

Within the arctic foothills, low shrub and herbaceous mapping classes dominate the 

region. Mesic herbaceous in the Brooks Range northern foothills and arctic foothills 

may include a high sphagnum moss component. This decreases the proportion of 

exposed water/moist detritus resulting in a higher visible and IR reflectance, and 

lighter signature. Farther South in the valleys of the Brooks Range, the moss 

component may be less significant. This results in more exposed water, more vis/IR 

absorption, and a darker signature. 

Low shrub birch-ericaceous-willow-tussock tundra sites on the northern foothills of 

the Brooks Range vary greatly depending on moisture/wetness, degree of patterning 

interspersed frost boils with prostrate shrubs, and herbaceous and moss content, and 

temperature/permafrost (macroscale freeze/thaw status). In some mesic herbaceous 

sites, tussocks covered over 80% of the site, however there was no significant shrub 
73 

component (70% herbaceous / 25% moss). These sites appeared ruby red to maroon 

in the TM imagery (4,5,3 RGB). 

Also on the northern foothills, lighter areas (white tones) were indicative of higher 

prostrate shrub content on sub-pixel frost heaves or local morainal ridge remnants 

and/or higher lichen content in shrub birch-willow-tussock tundra or mesic 

herbaceous mapping classes. These lighter signatures also were indicative of drier 

sites. The darker maroon tones, primarily found in the mesic herbaceous sites are 

linear sub-pixel wide wetter areas (water tracks). Sites where% shrub was not high 

enough to be considered in the shrub birch-willow-tussock tundra class, or the% 

tussock was near the lower limit to be considered a tussock site, were considered to 

be mesic herbaceous sites. The wettest of these areas with a significant portion of 

surface covered by water (greater than 10%), were classified as wet herbaceous. 

Although these sites contained emergent vegetation, the principal difference 

discernible through analysis of the Landsat TM data in these sites from the mesic 

herbaceous sites was the amount of exposed water (primarily in the form of large or 

multiple water tracks). 

Brooks Range 

Within the Brooks Range, terrain shadow presented the greatest challenge to 

development of the landcover map. The shadow/indeterminate mapping class was 

reserved for only those areas completely obscured by terrain shadow (or clouds/cloud 

shadow). Fortunately, the dominant vegetation in this region were the prostrate 

mapping classes which were very well represented by spectral signatures (176 

signatures total). With this abundance of samples, the assumption that all reflectance 

variations of the prostrate mapping classes (including those variations due to 

illumination conditions) is fairly realistic. As a result, most of the spectral confusion 

in this region was between the three prostrate shrub classes. Confusion between the 

prostrate shrub classes and other vegetation mapping classes (such as shrub birchwillow-tussock tundra, or shrub birch-ericaceous-willow tundra) was minimal. 

Exceptions were mesic herbaceous areas occurring in relatively high elevation alpine 

areas. These sites were on the drier end of the mesic regime (as opposed to the wetter 

mesic herbaceous found in the floodplain areas). Prostrate shrub sites with a high 

herbaceous component had a very similar spectral response to this alpine mesic 

herbaceous type (both are fairly bright red) and were therefore confused in the ML 

classification. Raster editing using FirePro and 1998 field sites was utilized to assist 

in editing these areas. 

The prostrate shrub-rock mapping class usually had a reddish-green spectral 

response, with the green due to the significant contribution of bare rock (and high TM 

band 5 response in relation to TM band 4). The prostrate shrub-rock class was often 

distinguishable based on less uniform vegetation pattern and context/slope position 

(generally very steep slopes, and often upslope of prostrate shrub areas). The 

prostrate shrub class generally had a much higher IR response, with a pink or red 

signature (depending on ratios of dryas/cassiope, lichen, herbaceous, and rock). 

Generally, the sites with more green vegetation (and less rock or lichen) exhibited 
74 

redder responses, while those sites with less green vegetation and more lichen and 

rock tended to be lighter red to pink. Prostrate shrub-lichen areas (found mainly in 

transitional zones between Brooks Range/Forested interior transition region) are 

nearly always found on ridge tops above This prostrate class is spectrally distinct 

from other prostrate classes, with a white to whitish-pink signature. 

Interior Forested Lowlands/Uplands 

The interior forested lowlands/uplands ecoregion encompasses the greatest variety of 

mapping classes, and was the most difficult area to map because of spectral confusion 

between many classes. This was complicated by the fact that most of the training 

data used to develop the ML classification was more representative of the other two 

ecoregion (arctic foothills and Brooks Range). This was understandable considering 

that only a small portion of the park itself was included in the interior forested 

lowlands and uplands ecoregion. This includes the Kobuk “boot” area, and forested 

valleys running predominantly N-S into the Brooks Range. However, the dominant 

open spruce forest and spruce woodland classes that make up majority of the area in 

this region were spectrally distinct, and could be consistently mapped in the 

automated classification. The dense open white spruce-like forest signature appears a 

dark brown color, while the open black and open white spruce-like forest appears 

medium brown/gray, and the spruce woodland a lighter gray brown. Open black and 

open white spruce-like forest classes could not be separated spectrally; however effort 

was made to model these based on slope and aspect. Open spruce forest (with tall 

shrub alder understory) had significant spectral confusion with the open and closed 

mixed forest classes. Both of these have dark reddish-brown signatures. These types 

were also often intermixed, or occur within close proximity to each other. The 

FirePro and '98 field data and image annotations were also used extensively to check 

these classes. The latitudinal position (northern extent) was an important factor 

during editing to eliminate the mixed forest possibility (and generally determined that 

the site was open spruce with tall shrub understory. However, although depending on 

the site shadow effects these areas were also recoded to closed or open tall shrub). 

The broadleaf forest classes were not spectrally separable, and upslope and floodplain 

models were developed using slope to separate birch aspen (open and closed) from 

balsam poplar (open and closed) respectively. The closed broadleaf forest classes 

appeared as bright deep red signatures, with less pronounced bright red color where 

more open broadleaf forest was prevalent. Closed tall shrub also was spectrally 

confused with these open and closed broadleaf forest classes. The proportionally 

representative number of training signatures for the tall shrub classes (70 signatures) 

as compared to the broadleaf forest (20 signatures) helped reduce the amount of error 

from this confusion. In the south park buffer area, where aspen-birch becomes more 

prevalent than represented by the training database, additional raster editing was 

required. 

The signature color of the spruce-lichen woodland class (whitish-pink to white-gray) 

varied a great deal depending on the amounts of spruce, size of spruce, proportion of 

lichen, and amount of low and tall shrub. Because of the relatively few training 
75 

samples (11 signatures), additional raster editing was required to improve the 

accuracy of this class. The areas where more pink tones were visible usually 

indicated more dwarf birch low shrub. The whiter sites indicated more lichen and 

usually less shrub and/or spruce. The grayish-white sites indicated a “typical” 

spruce-lichen woodland site balanced with ~20% spruce, and 30% or more lichen. 

Darker gray tones indicated higher spruce cover, and these sites were often classified 

as spruce woodland or open black or open white spruce-like forest if the white lichen 

was not obvious in the image. 

Burn areas also presented problems in this region. Burn areas were generally 

classified as low shrub or tall shrub, and often included spruce woodland patches. 

However, the significant burn areas since the primary 1985 satellite imagery, and the 

succession/regrowth of burn areas visible in the 1985 imagery, will most likely not be 

represented appropriately utilizing these landcover maps. Approximate burn areas 

were annotated on the image maps when possible during the '98 field season, and 

these annotations digitized. However, because of the sporadic and incomplete nature 

of this ancillary data layer, they were used only for reference during raster editing 

(not modeling). No attempt was made to incorporate these annotations directly in the 

landcover map for burn areas unless the burn was clearly visible in the circa 1985 

imagery base. 

3. 5 KEY TO LANDCOVER CLASS 

A key to the landcover classes used is found in Appendix 1. 

3.6 LANDCOVER CLASS DESCRIPTIONS 

The names and Viereck codes of the landcover classes in the GAAR project area are 

listed below. This is followed by full descriptions and accuracy assessment 

statements for each individual GAAR landcover class. Landcover class descriptions 

were derived from several sources including literature descriptions, Firepro data, 

Natural Resources Conservation Service data (Swanson 1996), 1998 FVA fly-over 

data, and 1998 on the ground site descriptions. For some of the mapping classes, on 

the ground site descriptions (and literature review) added some plant association 

information to the landcover class descriptions, in addition to vegetation structure, 

site moisture level, and soil characteristics. 
76 

LANDCOVER CLASS NAMES CODE

Dense-open white spruce forest (I.A.1.J) 

Open black spruce-like forest (I.A.2.F) 

Open white spruce-like forest (I.A.2.E.) 

Spruce woodland (I.A.3) 

Spruce-lichen woodland (I.A.3.1.) 

Closed paper birch-aspen forest (I.B.1.F.) 

Closed balsam poplar forest (I.B.1.C.) 

Open paper birch-aspen forest (I.B.2.X.) 

Open balsam poplar forest (I.B.2.C.) 

Closed spruce-broadleaf forest (I.C.1.X.) 

Open spruce-broadleaf forest (I.C.2.Y.) 

Closed tall shrub (II.B.1.) 

Open tall shrub (II.B.2.) 

Shrub birch-willow-tussock tundra (II.C.2.X.) 

Shrub birch-ericaceous-willow (II.C.X.) 

Closed low willow (II.C.2.B.) 

Prostrate shrub-rock (II.D.Y.) 

Prostrate shrub-lichen (II.D.X.C.) 

Prostrate shrub (II.D.X.) 

Dry herbaceous (III.X.1.) 

Mesic herbaceous (III.X.2.) 

Wet herbaceous (III.X.3.) 

Aquatic herbaceous (III.D.X) 

Sparsely vegetated (IV.X) 

Bare-ground (V.X.1.) 

Clear water (V.X.2.) 

Silty water (V.X.3.) 

Snow/ice (V.X.4.) 

Mosaic/patterned vegetation (V.X.5.) 

Shadow/indeterminate (V.X.6.) 

Sand dunes (V.X.7.) 
77 

Dense-open white spruce forest landcover class (I.A.1.J) 

Classification. Tree canopy cover is between 50 to 65% with greater than 75% of the 

total tree cover as needleleaf. The growth form and habitat of needleleaf trees is 

white spruce-like; that is they grow in well drained, sunny areas, with little knarled or 

stunted growth (Figure 21). 

 Figure 21. Patches of dense-open white spruce forest mixed with other types 

Class description. The dense-open white spruce forest map class occurs on 

floodplains and valley bottoms. These areas are sunny with well-drained, loamy or 

sandy soils. White spruce thrives in these areas as long as the ground remains well 

drained. Sampled sites have little to no slope and most of the disturbance originates 

from alluvial and fire processes. Elevation ranges up to 1,391 feet (Appendix 2). 

This map class covers 0.04% of GAAR (Table 9) and is concentrated in the south half 

of the Brooks Ranges ecoregion (Figures 3a and 3b), commonly in the Alatna River, 

John River, Allen River and Koyukuk River valleys. Dense-open stands are 

relatively small in size, the sampled polygons ranging up to 142 acres in size (Table

12). The map class is commonly found adjacent to closed balsam poplar, open 

balsam poplar, open black spruce-like, open white spruce-like, and spruce woodland

map classes. No stands of spruce (either white or black) with greater than 65% total 

tree cover were sampled within GAAR, as the park may be too far north to support 
78 

thicker stands of white spruce. 

Tree height can reach greater than 50 feet. Alders [such as Alnus crispa (American 

green alder)] and willows are found growing in canopy breaks along with ericaceous 

shrubs such as Arctostaphylos rubra (red-fruit bearberry), Vaccinium vitis-idaea (low 

bush cranberry), and Vaccinium uliginosum (bog blueberry). Mosses such as 

Hylocomium splendens (feathermoss), Rhytidiadelphus triquetrus, and Pleurozium 

schreberi are common in these stands as well as small amounts of lichen. 

Interpretation key. It was not possible to consistently distinguish white spruce from 

black spruce from a helicopter. We believe that growth form and habitat were the 

best characteristics from the air to help separate white from black spruce. 

Consequently, trees that were small (15 to 30 feet tall), with sparse lower branches, 

knarled or stunted growth and growing on poorly drained soils were considered black 

spruce. Large (25 to 70 feet tall) narrow sharp pointed trees and found on well 

drained soils were considered white spruce. The word “like” was added to the end of 

black spruce and white spruce—i.e., black spruce-like—to indicate we were uncertain 

of the species determination and mapping was based on habitat and physiognomy. In 

addition, any dwarf tree scrub classes as defined in the Alaska Vegetation 

Classification were included in one of the needleleaf forest classes, because it was not 

possible to spectrally separate spruce trees based on height. 
79 

The dense-open white spruce class is not defined in the Alaska Vegetation 

Classification. It was described, however, in our classification because it 

encompassed spruce forests with the highest cover values (50 to 65%) that could be 

spectrally separated from signatures with lower cover values (25 to 49%). No areas 

were found with greater than 65% white spruce cover. Due to the higher percentage 

of spruce cover, this mapping class was spectrally distinguishable from the open 

white spruce-like forest and open black spruce-like forest classes, and no slope or 

illumination (aspect) models were required in order to map the dense-open white 

spruce forest class. 

Accuracy assessment and mapping issues. The producer’s accuracy for the denseopen white spruce forest class was 89.9%, with a user’s accuracy of 59.9% (Table 

10b). All of the errors of commission and omission were due to confusion with the 

open white or open black spruce classes. Mapping of this class was based primarily 

on the quantitative spectral characteristics (training signatures statistics) for 2 sites 

within GAAR. The Landsat TM 4,5,3 (RGB) signatures for this class appeared as a 

dark brownish-grey, going to a lighter brownish grey with decreasing canopy closure. 

 Confusion with the open spruce class therefore occurred at sites where the% canopy 

cover was close to the 50% cut between the open spruce and dense-open spruce 

classes. Although partial or complete terrain shadow can also produce a dark 

brownish-grey signature, this confusion was avoided through very effective modeling 

of the shadow/indeterminate mapping class. 
80 

Open black spruce-like forest (I.A.2.F) 

Classification. Tree canopy cover is between 25 to 49% with greater than 75% of the 

total tree cover as black spruce-like trees (Figures 22a and b). 

 Figure 22a. Open black spruce-like forest (35% black spruce) 

Figure 22b. Open black spruce-like forest (35% black spruce) 
81 

Class description. Positive identification of spruce species is not possible from a 

helicopter. Consequently, the open black spruce-like forest map class was identified 

based on growth form. Black spruce are typically small in height (15 to 30 feet), 

have knarled or stunted growth, have a relatively high number of lower branches, and 

grow on poorly drained soils. 

The map class is concentrated in the south half of the Brooks Range ecoregion and 

the interior forested lowlands and uplands ecoregion of GAAR (Figures 3a and 3b). 

It covers 8.1% of the Park (Table 9), and its elevation ranges from 320 feet to over 

2,700 feet on sites sampled (Appendix 2). It occurs on sand deposits, lacustrine 

deposits, glacial till, eolian deposits, colluvium, and alluvial plains. Slopes range 

from 00

 on the floodplains to over 200 on colluvial and glacial drift sideslopes. The 

soils are mesic to wet often with a thick peat layer. The pH of these sites tends to be 

slightly acidic, with lower pH (more acidic) values occurring in the flat peatlands. 

Areas affected by thawing of ground ice produce saturated soils that support black 

spruce along with peat accumulation. 

Open stands of black spruce are often found adjacent to the spruce woodland, closed 

tall shrub and open tall shrub map classes. The open black spruce-like forest map 

class is relatively contiguous in distribution with an average area of 46 acres and 

ranging up to 227,000 acres in size (Table 12). However, canopy cover commonly 

fluctuates between open and woodland. 

Tree height can reach 30 feet and averages 15 feet. Associate species found in the 

map class include Salix (willow) species, Betula glandulosa (resin birch) or Betula 

nana (dwarf arctic birch), Vaccinium uliginosum (bog blueberry), Ledum palustre 

(Labrador tea), and Potentilla fruticosa (shrubby cinquefoil). Graminoids such as 

Eriophorum russeolum (russett cottongrass), Carex aquatilis (water sedge) and Carex 

bigelowii (Bigelow sedge) are also found, as well as a groundcover of mosses such as 

Sphagnum (peat moss) species and Pleurozium schreberi. Lichens growing in these 

stands include Cladonia species, Nephroma species, Cetraria species, and Peltigera

species. 

Interpretation key. The open black spruce-like class corresponds to the similarly 

named class in the Alaska Vegetation Classification. However, we used a lower tree 

cover value (25 to 49%) than the Alaska Vegetation Classification (25 to 60%). 

Accuracy assessment and mapping issues. The producer’s accuracy for the open 

black spruce-like class was 63.9%, with a user’s accuracy of 53.5% (Table 10b). 

Most of the errors of commission and omission were due to confusion with the open 

white spruce-like forest class and to a lesser extent with the woodland class. 

Mapping of this class was based primarily on the quantitative spectral characteristics 

(training signatures statistics) for 16 sites within GAAR. The Landsat TM 4,5,3 

(RGB) signatures for this class varied a great deal depending upon the understory 

composition, from a medium brownish-grey for small stature trees or open low shrub 

understory, to a vivid reddish-brown for those areas with closed tall shrub understory. 
82 

 These black spruce sites with tall shrub understory also exhibited some confusion 

with the mixed spruce-broadleaf forest and the tall shrub and closed low shrub 

classes. This was due to the high IR (infrared) response characteristic of the 

broadleaf tree and shrub species. In particularly wet sites, the signature was often a 

darker grayish-brown. Because of the substantial spectral confusion between the two 

open spruce classes, slope and illumination models were utilized based on the 

assumption that white spruce tends to occur on well illuminated upslopes, while black 

spruce tends to occur on low slopes and floodplains, under below average to well 

illuminated conditions. When considering the open black and open white spruce-like 

forest classes as a single combined open spruce forest mapping class, the producer’s 

and user’s accuracy increases to 84%. 

Open white spruce-like forest (I.A.2.E.) 

Classification. Tree canopy cover is between 25 to 49% with greater than 75% of the 

total tree cover as white spruce-like trees (Figure 23). 

 Figure 23. Mature open white spruce stands along river (45% spruce) 

Class description. The positive identification of spruce species is not possible from a 

helicopter and, consequently, the open white spruce-like forest map class was 

identified based on growth form. White spruce are assumed to be relatively tall in 

height (35 to 75 feet average), are narrow and sharp pointed, and display little to no 
83 

knarled or stunted growth. 

The map class is concentrated in the south half of the Brooks Range ecoregion and in 

the interior forested lowlands and uplands ecoregion of the park (Figures 3a and 3b). 

It covers 3.0% of GAAR, primarily on well drained, sunny areas such as floodplains, 

but is also found on colluvial and glacial drift sideslopes, and lacustrine deposits 

(Table 9). Elevations range from about 460 feet to over 2,800 feet on sites sampled 

(Appendix 2). The slope ranges from 00 on the floodplains to over 250 on the 

colluvial slopes. Soils are mesic to dry. The pH of white spruce sites tend to be 

higher (neutral) than that of black spruce forests. 

This map class commonly occurs adjacent to closed tall shrub and open tall shrub

map classes on the steep sideslopes of narrow valleys, and intermixed with spruce 

woodland found on the thermokarst and peatlands of wide valleys. The open white 

spruce-like forest map class is relatively contiguous in distribution with an average 

area of 21 acresand ranging up to 2,872 acres in size (Table 12). However, canopy 

cover commonly fluctuates between open and woodland. 

Plant species found within these areas include Alnus crispa (American green alder), 

Vaccinium uliginosum (bog blueberry), Spiraea beauverdiana (Alaska spiraea), 

Betula papyrifera (paper birch) in small amounts, Equisetum species, Betula nana

(dwarf arctic birch) or Betula glandulosa (resin birch), Salix (willow) species, and, if 

the stand is near a river, small amounts of Populus balsamifera (balsam poplar). In 

canopy breaks where tall shrubs are not present, prostrate shrubs are found. Mosses 

occur in high quantities, such as Hylocomium splendens and Dicranum species. 

Lichens are also found. 

Interpretation key. The open white spruce-like class corresponds to the similarly 

named class in the Alaska Vegetation Classification. However, we used a lower tree 

cover value (25 to 49%) than the Alaska Vegetation Classification (25 to 60%). This 

class was not spectrally separable from the open black spruce-like forest class. 

Models based on slope and illumination (related to aspect) were used to separate the 

upslope open spruce forest as the open white spruce-like forest class, and the 

floodplain open spruce forest as the open black spruce-like forest class. It should be 

noted that open black spruce-like forest is likely to occur in the floodplain within 

areas mapped as the open white spruce-like forest class. 

Accuracy assessment and mapping issues. The producer’s accuracy for the open 

white spruce-like forest class was 37%, with a user’s accuracy of 47% (Table 10b). 

Most of the errors of commission and omission were due to confusion with the open 

black spruce-like forest class and to a lesser extent with the spruce woodland class. 

There was also some confusion with the dense-open white spruce forest class. 

Mapping of this class was based primarily on the quantitative spectral characteristics 

(training signatures statistics) for 27 sites within GAAR. The Landsat TM 4,5,3 

(RGB) signatures for this class varied a great deal depending upon the understory 

composition, from a medium brownish-grey for small stature trees or open low shrub 
84 

understory, to a vivid reddish-brown for those areas with tall shrub understory. A tall 

shrub alder or alder-willow understory was typical of the upslope white spruce-like 

sites and showed some confusion with the mixed spruce-broadleaf forest and the tall 

shrub and low shrub classes. This was due to the high IR (infrared) response 

characteristic of the broadleaf tree and shrub species which can easily dominate 

spectral signature for open spruce classes. Because of the substantial spectral 

confusion between the two open spruce classes, slope and illumination models were 

utilized based on the assumption that open white spruce-like forest occurs on well 

illuminated upslopes, while open black spruce-like forest was assumed to occur on 

low slopes and floodplains, under average to well illuminated conditions. When 

considering the open black and white spruce-like classes as a single mapping class, 

both the producer’s and user’s accuracy increase to 84%. 

Spruce-lichen woodland (I.A.3.1.) 

Classification. Tree canopy cover is between 10 to 35% with greater than 75% of the 

total tree cover as needleleaf trees. The fruticose lichen cover is greater than 25% 

(Figures 24a and b). 

 

Figure 24a. Spruce-lichen woodland (10-15% spruce and mat of lichen) 
85 

Figure 24b. Spruce-lichen woodland (10-15% spruce and mat of lichen) 

Class description. The spruce-lichen woodland map class is concentrated within the 

Brooks Range ecoregion (Figures 3a and 3b). Sampled sites range in elevation from 

about 700 feet to over 2,700 feet, with most stands occurring below 1,000 feet 

(Appendix 2). Slope varies from 00

 to 350 on sampled sites and the aspect is 

generally north to northwest. The map class covers 0.64% of GAAR (Table 9), and is 

typically found on alluvial fans, moraines and stream terraces. They are generally 

easy to distinguish on aerial photos and on satellite imagery. The soils are mesic. 

Stands range up to 747 acres and are often discontinuous and oval in shape (Table 

12). Adjacent map classes are often prostrate shrub-lichen, shrub birch-ericaceouswillow (with a significant lichen component), and most of the forest and woodland 

landcover classes. 

Both white and black spruce occur in the spruce-lichen woodland map class, and 

fruticose lichen cover is often greater than 60%. Trees reach 30 feet in height. 

Ericaceous shrubs such as Empetrum nigrum (crowberry), Vaccinium vitis-idaea (low 

bush cranberry), Vaccinium uliginosum (bog blueberry) and Ledum palustre 
86 

(Labrador tea), as well as Betula glandulosa (resin birch) or Betula nana (dwarf arctic 

birch), are common associates. Lichens include Cladina rangiferina, Peltigera

species, and Stereocaulon species. 

Interpretation key. The spruce-lichen woodland class is not described in the Alaska 

Vegetation Classification. It was included as a distinct class in the GAAR 

classification because, from an ecological perspective, the class was distinct in 

structure and composition from other map classes. In addition, it was readily 

distinguishable spectrally. Again, white spruce could not be distinguished from black 

spruce for this class. 

Accuracy assessment and mapping issues. The producer’s accuracy for the sprucelichen woodland class was 80%, with a user’s accuracy of 87% (Table 10b). Most of 

the errors of commission and omission were due to confusion with the spruce 

woodland class. This generally occurred when a spruce woodland site included 

more than 25% lichen, but also a significant component of low shrub (usually shrub 

birch-ericaceous-willow) which results in a much less spectrally distinct signature in 

the satellite image. Mapping of this class was based primarily on the quantitative 

spectral characteristics (training signatures statistics) for 11 sites within GAAR. The 

Landsat TM 4,5,3 (RGB) signatures for this class varied depending upon the amount 

of spruce, lichen, and shrub (usually dwarf birch). The characteristic signature was a 

whitish-grey which is a combination of the white reflectance of the lichen and the 

brown-grey reflectance of the spruce. Red tones in the signature represent the open 

low shrub understory. Although not reported in the 

accuracy assessments, the spruce-lichen woodland class can also be confused with 

other mapping classes with high lichen cover (>25%) such as the prostrate shrublichen class, and in some cases the shrub birch-ericaceous-willow class. This 

confusion typically occured when the spruce cover was near the low threshold for 

consideration as a woodland (10-15%). 

Spruce woodland (I.A.3) 

Classification. Tree canopy cover is between 10 and 24% with greater than 75% of 

the total tree cover as needleleaf trees. The needleleaf species may be either black 

spruce or white spruce (Figure 25). 
87 

Figure 25. Spruce woodland on side slope (20% white spruce) 

Class description. The spruce woodland landcover class is concentrated in the 

southern portion of the Brooks Range ecoregion and in the interior forested lowlands 

and uplands ecoregion (Figures 3a and 3b), and covers 5.9% of GAAR (Table 9). 

Elevation ranges up to 2,900 feet (Appendix 2). The map class typically contains 

either white spruce or black spruce and not a mixture of the two. Occasionally stands 

are found with both species growing together, although these stands tend to be 

smaller in size and more limited in distribution. Because black spruce and white 

spruce occupy distinct sites—they are described separately below—each is analogous 

to an alliance. The map class is relatively contiguous in distribution with an average 

size of 17 acres and ranging up to 19,549 acres in size (Table 12). 

Black spruce woodland alliance. Black spruce is found on floodplains, terraces, 

outwash, colluvial deposits, glacial drift on sideslopes, and eolian deposits. The sites 

are often large and continuous, intermixed with other needleleaf forest map classes. 

The soils are mesic to wet with poor drainage and may contain a peat layer. The pH 

is neutral to acidic. Slopes range from 00

 on terraces and floodplains to 550 on 

colluvial and glacial drift sideslopes. 

Tree height reaches 30 feet and averages 15 feet. Associated understory species 

include Ledum palustre (Labrador tea), Vaccinium uliginosum (bog blueberry), 

Vaccinium vitis-idaea (low bush cranberry), and Alnus crispa (American green alder). 

 Prostrate shrubs such as Arctostaphylos rubra (red-fruit bearberry) and Dryas

species are also found in these sites. Mosses include Sphagnum (peat moss) species, 

Hylocomium splendens (feather moss), and Pleurozium schreberi. Lichens such as 

Cladina species, Cladonia species, and Stereocaulon species are also common. 
88 

White spruce woodland alliance. Sites dominated by white spruce, in contrast, 

occur in well drained, mesic soils, south facing slopes and sunny areas. They are 

located in narrow bands on floodplains, on alluvial fans frequently with a high 

percentage of lichen, and occasionally on colluvial and glacial drift slopes. At 

treeline, trees are short with a sparse distribution. The tree line does not have an 

abrupt edge. The slope of these sites range from 00

 to 320 in the sites sampled. White 

spruce sampled sites were generally found at slightly higher elevations than black 

spruce, occurring between 466 feet to 2,822 feet (Appendix 2). 

These stands occupy areas similar to open white spruce-like stands. In fact, the 

spruce woodland and open white-like spruce map classes together often form large 

continuous stands. Both the open and closed tall shrub map classes commonly grow 

near white spruce stands along floodplains and on sideslopes. 

Tree height averages 15 feet, however they can reach over 40 feet. Both alder and 

tall willow are found in large canopy gaps of spruce woodland, while low growing 

willows invade smaller openings. The tall shrubs tend to grow in a clumped pattern 

throughout the stands, however they can reach greater than 55% of the total 

vegetation cover in some stands. 

Species associated with the spruce woodland map class include Alnus (alder) species, 

Salix alaxensis (feltleaf willow), Salix monticola (park willow), Betula nana (dwarf 

arctic birch) or Betula glandulosa (resin birch), Vaccinium uliginosum (bog 

blueberry), Empetrum nigrum (crowberry), Rubus species, Spiraea beauverdiana and 

Ledum palustre (Labrador tea). Mosses and lichens are also found in these areas such 

as Cladonia species, Cetraria cucullata, Rhytidiadelphus triquetrus, Hylocomium 

splendens (feather moss), and Sphagnum (peat moss) species in small quantities. 

Grasses and forbs typically have low cover values in these sites. 

Interpretation key. The black spruce-like woodland and white spruce-like woodland

classes used for mapping in the field were collapsed into a single class—spruce 

woodland. We were unable to spectrally separate the two woodland classes. In the 

descriptions for these two classes, we describe slope and surficial geology 

characteristics that provide some basis for separation through modeling. However, 

the relationship was not found to be strong enough to improve mapability of the two 

individual classes. The spruce woodland class is the same as the Alaska Vegetation 

Classification spruce woodland class. 

Accuracy assessment and mapping issues. The producer’s accuracy for the spruce 

woodland class was 72%, with a user’s accuracy of 51% (Table 10b). Some of the 

errors of commission and omission were due to confusion with the open black and 

white spruce-like forest classes. This generally occurred when a spruce woodland 

site included 15-24% lichen, but not enough to be classified as a spruce-lichen 

woodland site (> 25% lichen required). However, of greater concern is the large 

errors of commission found in the low shrub classes, and in particular, the shrub 
89 

birch-ericaceous-willow class. This confusion generally occurred on partially 

shadowed aspects that resulted in darker signatures that a well illuminated low shrub 

class. Although incorporation of the illumination layer in the spectral database 

reduced this type of confusion, areas of fairly low illumination continued to show 

some spectral confusion between the woodland and low shrub classes. Winter MSS 

(Band 4 NIR) was useful in correcting woodland areas misclassifed as low shrub 

(shrub birch-ericaceous-willow-tussock tundra and shrub birch-ericaceous-willow). 

Again, this model could only be used in moderately well illuminated areas. In the 

central and southern portions of the project area, low shrub in partially shadowed 

aspects was misclassified as woodland. In these areas, raster editing based on the 

FirePro and ’98 field data and image annotations was utilized to determine whether 

the woodland on partially shadowed aspects was legitimate or was actually a low 

shrub or prostrate class (depending on northern latitude and context). Determination 

of which low shrub class was also based on the context of the site (review of the 

mapping classes of the surrounding areas). This approach was very difficult in the 

transition areas between the forested lowlands/uplands and Brooks Range ecoregions 

(in this area, woodland did occur on low to moderate north aspects). Where 

woodland classes occurred on the south aspect of an E-W drainage, the north aspect 

was usually dominated by low shrub (generally shrub birch-ericaceous-willowtussock tundra in floodplain, and shrub birch-ericaceous-willow on upslopes, but 

there were too many exceptions to this rule to allow realistic model-based separation 

of these two low shrub classes). Where low shrub or tall shrub occurred on the south 

aspects of an E-W drainage, the north aspect was usually dominated by prostrate 

shrubs with low shrub stringers. Mapping of this class was based primarily on the 

quantitative spectral characteristics (training signatures statistics) for 34 sites within 

GAAR. The Landsat TM 4,5,3 (RGB) signatures for this class varied depending 

upon the amount of spruce, lichen, and shrub (usually dwarf birch). The 

characteristic signature was a light to medium reddish-grey. Red tones in the 

signature usually represent the low shrub scattered tall shrub understory. Darker grey 

tones in the signatures are usually related to increased spruce cover. When 

considering the spruce woodland and spruce-lichen woodland classes as a single 

mapping class, the producer’s accuracy increased to 75%, while the user’s accuracy 

improved to 56%. 

Closed paper birch-aspen forest (I.B.1.F.) 

Classification. Tree canopy cover is 60 to 100% with Betula papyrifera (paper birch) 

and Populus tremuloides (quaking aspen), individually or combined, with greater 

than 50% of the total tree cover (Figures 26a and b). 
90 

 

 Figure 26a. Closed paper birch-aspen forest (85% paper birch) 

 Figure 26b. Closed paper birch-aspen forest (85% paper birch) 
91 

Class description. The closed paper birch-aspen forest map class has a limited 

distribution within GAAR, occurring primarily within the most southern portions of 

the park, specifically the “Kobuk boot” area and the southern limits of the North Fork 

River within the park boundaries (Figure 1). It occupies colluvial and glacial drift 

sideslopes and floodplains, and covers 0.1% of the GAAR study area. The map class 

has a patchy distribution with an average size of 7.6 acres and ranging up to 397 acres 

(Table 12) 

Landcover classes found growing adjacent to the closed paper birch-aspen forest

map class varies with the surficial geology type on which these stands occur. On 

floodplains and lower sideslopes, needleleaf map classes as well as balsam poplar 

stands, mix with the map class. On the upper sideslopes, tall shrub map classes occur 

near closed paper birch-aspen stands. Areas with gentle relief as well as relatively 

steep slopes (greater than 700) can also support paper birch-aspen stands. Elevation 

varies from about 900 feet on the floodplains and lower sideslopes to over 2,200 feet 

on mountain slopes (Appendix 2). 

Betula papyrifera (paper birch) and Populus tremuloides (quaking aspen) form a 

mixed overstory in most stands. In canopy openings Alnus crispa (American green 

alder) and Salix glauca (grayleaf willow) occur. Additional species include 

Vaccinium vitis-idaea (low bush cranberry), Rosa acicularis (prickly rose), Ledum 

palustre (Labrador tea), and Spiraea beauverdiana (Alaska spiraea). Mosses, such as 

Hylocomium splendens (feather moss), may be present in high quantities, and 

fruticose and crustose lichens occur in moderate quantities. 

Interpretation key. The closed paper birch-aspen forest class is not spectrally 

separable from the closed balsam poplar forest. However, this distinction can be 

modeled fairly well in GAAR using slope. Balsam poplar was only observed along 

riparian corridors. So the two classes were distinguished on this basis. Balsam 

poplar has been noted to occur on uplands in the Kobuk Boot area, but what not 

distinguishable in the satellite imagery. 

Accuracy assessment and mapping issues. The producer’s accuracy for the closed 

paper birch-aspen forest was 73.0%, with a user’s accuracy of 79.0% (Table 10b). 

Errors of commission and omission were due to confusion with the closed balsam 

poplar forest class. Slope was used to model these classes based on the assumption 

that balsam poplar occurred only in floodplain (minimal slopes) while aspen-birch 

occurred only on upslope areas. There was also some confusion with the closed tall 

shrub due to the similarity in broadleaf forest canopy reflectance. In areas of partial 

terrain shadow, some confusion also occurred with the open tall shrub class. 

Mapping of this class was based primarily on the quantitative spectral characteristics 

(training signatures statistics) for 5 sites within GAAR. Because limited training 

samples were available for the closed paper birch-aspen forest classes, raster editing 

based on review of the FirePro and 1998 field data, image annotations, and image 
92 

interpretation (with CIR spot checking) was relied on for improving these classes. 

The Landsat TM 4,5,3 (RGB) signatures for this class were bright red with a smooth 

texture for lower stature forests, and a slightly courser texture for forest with larger 

stature trees. The difference in forest stature for the closed paper birch-aspen forest 

class is typically only recognizable in the satellite imagery along the boundaries of 

stands where an abrupt transition to a lower stature shrub or broadleaf forest type 

occurs. Transition to stands of open spruce or mixed forest types is recognizable by 

distinct brown-grey tones intermixed in the forest stand related to the occurrence of 

spruce species. When considering all the closed and open broadleaf forest classes as 

a single broadleaf forest mapping class, the producer’s accuracy becomes 82%, while 

the user’s accuracy becomes 79%. 

Closed balsam poplar forest (I.B.1.C.) 

Classification. Tree canopy cover is 60 to 100% and balsam poplar has greater than 

50% of the total tree cover (Figure 27). 

Figure 27. Closed Balsam Poplar 

Class description. The map class is concentrated in the interior forested lowlands 

and uplands ecoregion of GAAR (Figures 3a and 3b), and is restricted to floodplains 

and, occasionally, on uplands of the Kobuk Boot area. These riparian areas generally 

support only small stands of balsam poplar with a somewhat patchy distribution, 
93 

averaging 8 acres in size (Table 12). Soils are gravelly or sandy and well drained. 

Slope is minimal and the elevation ranges up to approximately 1,170 feet (Appendix 

2). These areas are frequently flooded during river high flows. This map class covers 

0.07% of the park (Table 9). 

Needleleaf map classes and paper birch-aspen stands may be found growing near 

balsam poplar forests. Tall shrub map classes, dominated by willow, occupy gravel 

bars and floodplains and grow adjacent to the balsam poplar stands. 

The overstory of the closed balsam poplar forest map class is almost exclusively 

comprised of Populus balsamifera (balsam poplar). Trees range up to 50 feet in 

height. Picea glauca (white spruce) and Betula papyrifera (paper birch) are 

occasionally found in the understory. Alnus crispa (American green alder), Alnus 

tenuifolia (thinleaf alder), Salix monticola (park willow), and Salix alaxensis (feltleaf 

willow) occur in crown cover breaks along with small quantities of Picea glauca

(white spruce). Additional species include Equisetum species, Galium boreale

(northern bedstraw), Hedysarum alpinum (Eskimo potato), Viburnum edule, Rumex 

arcticus, Calamagrostis canadensis (bluejoint grass), Agrostis species, and 

Hierochloe alpina (alpine holy grass). Mosses and lichens are also present in varying 

amounts including Dicranum species, Drepanocladus species, and Rhytidiadelphus 

triquetrus. 

Interpretation key. The closed balsam poplar forest class is not spectrally separable 

from the closed paper birch-aspen forest. However, this distinction can be modeled 

fairly well using slope. Balsam poplar was only observed along riparian corridors. 

So the two classes were distinguished on this basis. Balsam poplar has been noted to 

occur on uplands in the Kobuk Boot area. 

Accuracy assessment and mapping issues. The producer’s accuracy for the closed 

balsam poplar forest class was 92%, with a user’s accuracy of 69% (Table 10b). 

Errors of commission and omission were due to confusion with the closed paper 

birch-aspen forest class. Slope was used to model these classes based on the 

assumption that balsam poplar occurred only in floodplain (minimal slopes) while 

aspen-birch occurred only on upslope areas. There was also some confusion with the 

closed tall shrub and open tall shrub in riparian areas due to the similarity in 

broadleaf canopy reflectance. In the floodplains, the open tall shrub and closed tall 

shrub classes (dominated by willow) occur along more recently formed river 

meanders/bends, and typically transition into the closed balsam poplar and open 

balsam poplar forest classes, and are often found as a significant portion of the forest 

understory. In areas where the transition from tall shrub to large stature balsam 

poplar forest is abrupt, the forest stand boundary is sometimes recognizable in the 

satellite imagery due to shadows caused by differences in forest/shrub canopy 

heights. In areas of partial terrain shadow, some confusion also occurred with the 

open tall shrub class. Mapping of this class was based primarily on the quantitative 

spectral characteristics (training signatures statistics) for 4 sites within GAAR. 

Because limited training samples were available for the closed balsam poplar forest
94 

classes, raster editing based on review of the FirePro and 1998 field data, image 

annotations, and image interpretation (with CIR spot checking) was relied on for 

improving discrimination of these spectrally confused classes. The Landsat TM 

4,5,3 (RGB) signatures for this class were bright to deep red with a smooth texture 

for lower stature forests, and a slightly courser texture for forest with larger stature 

trees. Areas with larger canopy trees along major drainages in the southern portion of 

the GAAR area appeared as a deeper red, partially due to the effects of canopy 

shadow within the stands. When considering all the closed and open broadleaf forest 

classes as a single broadleaf forest mapping class, the producer’s accuracy improves 

82%, and the user’s accuracy increases to 79%. 

Open paper birch-aspen forest (I.B.2.X.) 

Classification. Tree canopy cover is 25 to 59% with paper birch and Populus 

tremuloides (quaking aspen), individually or combined, with greater than 50% of the 

total tree cover (Figures 28a and b). 

Figure 28a. Open paper birch-aspen forest (30-35% paper birch on south 

aspect sideslope) 
95 

Figure 28b. Open paper birch-aspen forest (30-35% paper birch on south 

aspect sideslope) 

Class description. The open paper birch-aspen forest map class is concentrated in the 

interior forested lowlands and uplands ecoregion of GAAR (Figures 3a and 3b). The 

map class primarily occurs on colluvial and glacial drift sideslopes, but also occupies 

floodplains and alluvial deposits, eolian deposits, and glacial outwash. The soils are 

generally mesic and well drained. These stands can reach over 1,600 feet in elevation 

(Appendix 2) and have up to a 700 slope. This map class covers 0.2% of the park 

(Table 9). 

The open paper birch-aspen forest map class occurs in the same areas and adjacent to 

the closed paper birch-aspen forest map class. The open stands are more common 

than closed stands. Needleleaf forest, balsam poplar and tall shrub map classes are 

also typically found adjacent to the open paper birch-aspen forest map class. 

Needleleaf forests mix with the map class on gentle to moderate sideslopes, balsam 

poplar mixes with these stands on floodplains, and tall shrub map classes—dominated 

by alder and willow—grade into the map class on the upper mountain slopes. The 

map class has a patchy distribution with an average size of 6.2 acres and ranging up 

to 338 acres (Table 12). 
96 

Paper birch and Populus tremuloides (quaking aspen) form a mixed overstory in most 

stands. In canopy openings, a wide variety of understory species are present, 

including Alnus crispa (American green alder) and Salix glauca (grayleaf willow). 

Additional species include Vaccinium vitis-idaea (low bush cranberry), Rosa 

acicularis (prickly rose), Ledum palustre (Labrador tea), and Spiraea beauverdiana

(Alaska spiraea). Mosses, such as Hylocomium splendens (feather moss), may be 

present in high quantities, and fruticose and crustose lichens grow in moderate 

quantities. The larger canopy breaks of the map class versus the closed paper birchaspen forest class allows for a higher percentage of the vegetation cover to be tall 

alder and willow. Other species associated with these stands are quite similar to 

those found in the closed paper birch-aspen forests map class. 

Interpretation key. The open paper birch-aspen forest class is not described in the 

Alaska Vegetation Classification. It was not found to be spectrally distinguishable 

from the open balsam poplar forest class. However, it could be modeled fairly well 

based on slope. Open paper birch-aspen forest was only observed in upslope areas, 

while open balsam poplar forest was only observed along riparian corridors (with the 

rare exception of limited balsam poplar in some upland drainages in the Kobuk 

Boot/Walker Lake area). The two classes were therefore separated through modeling 

upslope/floodplain with the slope data layer. 
97 

Accuracy assessment and mapping issues. The producer’s accuracy for the open 

paper birch-aspen forest class was 75%, with a user’s accuracy of 42% (Table 10b). 

Errors of commission and omission were due primarily to confusion with the open 

balsam poplar forest class and the open tall shrub class. Slope was used to model 

these classes based on the assumption that balsam poplar occurred only in floodplain 

(minimal slopes) while aspen-birch occurred only on upslope areas. Mapping of this 

class was based primarily on the quantitative spectral characteristics (training 

signatures statistics) for 3 sites within GAAR. Because limited training samples were 

available for the open paper birch-aspen forest class, raster editing based on review 

of the FirePro and 1998 field data, image annotations, and image interpretation (with 

CIR spot checking) was relied on for improving this class. The Landsat TM 4,5,3 

(RGB) signatures for this class are light orange-red, with increasing red and orange 

brightness corresponding to higher density of tall shrub or low shrub understory. 

When considering all the closed and open broadleaf forest classes as a single 

broadleaf forest mapping class, the producer’s accuracy becomes 82%, and the user’s 

accuracy increases to 79%. 
98 

Open balsam poplar forest (I.B.2.C.) 

Classification. Tree canopy cover is 25 to 59% and balsam poplar has greater than 

50% of the total tree cover (Figures 29a and b). 

 Figure 29a. Open balsam poplar forest (40% balsam poplar) with thick alder 

 shrub understory 

Figure 29b. Open balsam poplar forest (40% balsam poplar) with thick 

 alder shrub understory 
99 

Class description. The map class is concentrated in the interior forested lowlands and 

uplands ecoregion of GAAR but also occurs in the Brooks Range ecoregion (Figures 

3a and 3b). It covers 0.09% of the park (Table 9). This map class is similar to the 

closed balsam poplar forest map class. Open stands, however, are more common 

within GAAR than closed stands. They grow almost exclusively on floodplains and 

occasionally on uplands in the Kobuk boot area. The soils are typically well-drained 

with a high sand or gravel content. Slope is minimal with maximum elevations of 

about 1,800 feet in the sites sampled (Appendix 2). These areas undergo periodic 

flooding and support small discontinuous stands of the map class. The map class has 

a patchy distribution with an average size of 5 acres and ranging up to 72 acres (Table 

12). 

The overstory of the open balsam poplar forest map class is almost exclusively 

comprised of balsam poplar (Populus balsamifera). Tree height reaches up to 50 feet. 

Alnus crispa (American green alder), Alnus tenuifolia (thinleaf alder), Salix 

monticola (park willow), and Salix alaxensis (feltleaf willow) occur in crown cover 

breaks along with small quantities of Picea glauca (white spruce). Forb 

representation in these stands includes Equisetum species, Galium boreale (northern 

bedstraw), Hedysarum alpinum (Eskimo potato), Viburnum edule (high bush 

cranberry), and Rumex arcticus. Graminoids include Calamagrostis canadensis

(bluejoint grass), Agrostis species, and Hierochloe alpina (alpine holy grass). 

Mosses and lichens are also present in varying amounts, ranging from 3 to 40%. 

Some of the moss species are Dicranum species, Drepanocladus species, and 

Rhytidiadelphus triquetrus. In the sampled stands of open balsam poplar forest, 

slightly higher percentages of both mosses and lichens were noted relative to the 

closed stands. 

Interpretation key. The open balsam poplar forest class was not spectrally 

distinguishable from the open paper birch-aspen forest class. However, it could be 

modeled fairly well based on slope. Balsam poplar was only observed along riparian 

corridors, and the two classes were separated on this basis. Small amounts of balsam 

poplar have been noted to occur on uplands in the Kobuk Boot area in the vicinity of 

Walker Lake. 

Accuracy assessment and mapping issues. The producer’s accuracy for the open 

balsam poplar forest class was 20%, with a user’s accuracy of 63% (Table 10b). 

Errors of commission and omission were primarily due to confusion with the open 

paper birch-aspen forest class and the open tall shrub class. Slope was used to model 

these classes based on the assumption that balsam poplar occurred only in floodplain 

(minimal slopes) while aspen-birch occurred only on upslope areas. Mapping of this 

class was based primarily on the quantitative spectral characteristics (training 

signatures statistics) for 4 sites within GAAR. Because limited training samples were 

available for the open balsam poplar forest classes, raster editing based on review of 

the FirePro and 1998 field data, image annotations, and image interpretation (with 
100 

CIR spot checking) was relied on for improving these classes. The Landsat TM 

4,5,3 (RGB) signatures for this class were light orange-red, with increasing red and 

orange brightness corresponding to higher density of tall or low shrub understory. 

When considering all the closed and open broadleaf forest classes as a single 

broadleaf forest mapping class, the producer’s accuracy becomes 82%, and the user’s 

accuracy becomes 79%. 

Closed spruce-broadleaf forest (I.C.1.X.) 

Classification. Tree canopy cover is 60 to 100% with needleleaf and deciduous trees 

each contributing 25 to 75% of the total tree cover (Figures 30a and b). 

 Figure 30a. Closed spruce-broadleaf forest (20% white spruce, 40% balsam 

 poplar) 
101 

Figure 30b. Closed spruce-broadleaf forest (20% white spruce, 40% balsam 

 poplar) 

Class description. This map class is concentrated in the interior forested lowlands 

and uplands ecoregion (Figures 3a and 3b), and covers 0.24% of GAAR (Table 9). 

These are usually thick stands of trees found on sideslopes and toeslopes. Slopes 

range from 50

 to 500, and the soils are generally mesic. 

White spruce is the most common spruce species, although black spruce occurs, and 

is mixed with either paper birch, aspen or balsam poplar. Trees within the map class 

tend to grow in a clumped distribution, therefore open patches in the canopy are 

frequent and allow for other species to take advantage of the available sunlight. The 

stand size averages 7 acres and ranges up to 414 acres based on sampled polygons 

(Table 12). Low and tall shrubs, such as willow and alder, and herbaceous species 

grow in the canopy breaks. Mosses generally have low cover values (less than 15%). 

Interpretation key. The closed white spruce-birch class was not spectrally separable 

from the closed white spruce-balsam poplar class. Some separation of these types 

based on slope may be possible; however, the significance of this class separation and 

the degree of error involved in attempting to model it prompted us to group these two 

classes into the closed spruce-broadleaf forest class. 

Accuracy assessment and mapping issues. The producer’s accuracy for the closed 

spruce-broadleaf forest class was 57%, with a user’s accuracy of 88% (Table 10b). 

Errors of commission and omission were due primarily to confusion with the open 

spruce broadleaf forest and the open white spruce-like forest sites with a significant 
102 

tall shrub (predominantly alder) understory. The spruce-broadleaf forest classes were 

by definition spectrally mixed, and were very difficult to separate spectrally from 

open spruce forests with close tall shrub understory. Mapping of this class was based 

primarily on the quantitative spectral characteristics (training signatures statistics) for 

7 sites within GAAR. Manual editing based on review of the FirePro and 1998 field 

data, image annotations, and image interpretation (with CIR spot checking) was 

relied on for improving these classes. 

Because this class was relatively rare, efforts were made during field work to make 

extensive image annotations identifying areas of closed spruce-broadleaf forest. The 

Landsat TM 4,5,3 (RGB) signatures for this class were deep brownish orange-red, 

with increases in red and orange brightness corresponding to higher broadleaf 

components, and darker browns/reds corresponding to higher spruce components. 

When considering all the closed and open spruce-broadleaf forest classes as a single 

mixed spruce-broadleaf forest mapping class, the producer’s accuracy becomes 77%, 

while the user’s accuracy is 93%. 

Open spruce-broadleaf forest (I.C.2.Y.) 

Classification. Tree canopy cover is 25 to 59% and needleleaf and deciduous trees 

each contribute 25 to 75% of the total tree canopy cover (Figures 31a and b). 

 Figure 31a. Open spruce-broadleaf forest (10% spruce, 15-20% paper birch) 
103 

 Figure 31b. Open spruce-broadleaf forest (10% spruce, 15-20% paper birch) 

Class description. The open spruce-broadleaf forest map class is concentrated in the 

interior forested lowlands and uplands ecoregion of GAAR (Figures 3a and 3b), and 

covers 0.3% of the park (Table 9). When white spruce is the dominant spruce 

species, the map class is found on colluvial and glacial drift sideslopes and toeslopes. 

 Slope averaged 130

, and elevation ranges from 840 feet to about 2,410 feet. Soils are 

generally mesic. On sites where black is dominant, the soils are mesic to wet. 

Both black spruce and white spruce occur in the overstory mixed with aspen, paper 

birch or balsam poplar. The trees tend to grow in a clumped distribution, therefore 

open patches in the canopy are frequent and allow for other species to take advantage 

of the available sunlight. Both alder and willow grow in the canopy breaks. The 

average stand size is 6.8 acres and ranges up to 222 acres (Table 12). 

Interpretation key. The open black spruce-broadleaf and open white sprucebroadleaf classes were not spectrally separable. Because there can be a fair amount 

of mixing of black spruce and white spruce within the needleleaf components of these 

mixed spruce-broadleaf stands, modeling based on slope and illumination is not likely 

to improve the mapability of these classes. These two classes were therefore 

collapsed into a single open spruce-broadleaf forest class. 

Accuracy assessment and mapping issues. The producer’s accuracy for the open 

spruce-broadleaf forest class was 82%, with a user’s accuracy of 90% (Table 10b). 

Errors of commission and omission were due primarily to confusion with the closed 

spruce broadleaf forest and the open white and open black spruce-like forest classes. 
104 

The spruce-broadleaf forest classes were by definition spectrally mixed, and were 

very difficult to separate spectrally from open spruce forests with tall shrub 

understory. Mapping of this class was based primarily on the quantitative spectral 

characteristics (training signatures statistics) for 9 sites within GAAR. Manual 

editing based on review of the FirePro and 1998 field data, image annotations, and 

image interpretation (with CIR spot checking) was relied on for improving these 

classes. Because this class was relatively rare, efforts were made during field work to 

make extensive image annotations identifying areas of open spruce-broadleaf forest. 

The Landsat TM 4,5,3 (RGB) signatures for this class are deep brownish orange-red, 

with increases in red and orange brightness corresponding to higher broadleaf 

components, and darker browns/reds corresponding to higher spruce components. 

When considering all the closed and open spruce-broadleaf forest classes as a single 

mixed spruce-broadleaf forest mapping class, the producer’s accuracy is 77%, and the 

user’s accuracy is 93%. 

Closed tall shrub (II.B.1.) 

Classification. Tall shrub (>3.5 feet tall) cover is 75 to 100%. Tree canopy cover is 

less than 10% or absent (Figures 32a and b). 

 Figure 32a. Closed tall alder shrub on steep side slope with scattered white 

 spruce and paper birch 
105 

 Figure 32b. Closed tall alder shrub on steep side slope with scattered white 

 spruce and paper birch 

Class description. This map class is characterized by dense stands of shrubs greater 

than 3.5 feet tall ranging up to 15 feet and taller. The closed tall shrub map class 

covers 2.9% of GAAR, and occurs in all the ecoregions (Table 9). Elevation for 

sampled sites range from about 900 feet up to 3,534 feet (Appendix 2). It is 

dominated by nearly pure stands of alder, willow, and resin birch (Betula 

glandulosa), plus mixed alder-willow sites—the four groupings are described below. 

 The average site size is 10.6 acres and ranges up to 1,355 acres (Table 12). 

Alder. Sites dominated by alder within the closed tall shrub map class are found on 

steep colluvial and glacial drift sideslopes averaging 250 and reaching an elevation of 

over 1,100 feet. It is also found on gentle toeslopes, and on recent floodplain 

deposits. Alder generally inhabits floodplains of narrow valleys in contrast to tall 

willow dominated sites that grow in broad valleys. Alder can reach a height of over 

10 feet and grows on soils that are generally mesic. Alder is concentrated in the 

south portion of the Brooks Range ecoregion and the interior forested lowlands and 

uplands ecoregion (Figures 3a and 3b). 
106 

Alder grows adjacent to needleleaf map classes on the toeslopes and mountain 

sideslopes. On the upper slopes it grows adjacent to both prostrate and low shrub 

map classes. Within the closed tall shrub map class alder is often found next to tall 

willow. 

Both Alnus crispa (American green alder) and Alnus sinuata (Sitka alder) are found 

in these sites. Alnus crispa is more common on the floodplains than Alnus sinuata. 

Plants associated with alder dominated sites include Vaccinium uliginosum (bog 

blueberry), Vaccinium vitis-idaea (low bush cranberry), Betula nana (dwarf arctic 

birch) or Betula glandulosa (resin birch), Spiraea beauverdiana (Alaska spiraea), 

Salix alaxensis (feltleaf willow), and other Salix (willow) species. Mosses include 

Sphagnum (peat moss) species, Hylocomium splendens (feather moss), and Dicranum

species. Grasses, sedges and lichens also occur. 

Resin birch. Resin birch (Betula glandulosa) was included within the closed tall 

shrub map class because occasionally it grows upslope in such thick tall stands that it 

is spectrally similar to alder shrub. These resin birch stands generally reach an 

elevation higher than that of alder and may be found adjacent to them. Species 

composition of resin birch dominated stands is similar to the alder dominated sites. 

Willow. Nearly pure stands of willow occur within the closed tall shrub map class. 

These willow-dominated sites occur throughout GAAR in all three ecoregions 

(Figures 3a and 3b). In contrast to the alder dominated sites, they are frequently 

found in the northern portion of the park. Although they occur on colluvial and 

glacial till sideslopes, this mapping class is primarily found on the sandy deposits of 

braided streams, particularly in the northern portion of GAAR. These floodplains 

have dry, well drained soils. When growing on sideslopes, willow may inhabit fairly 

steep slopes at high elevation (3,000 feet). Both open and closed stands of willow 

occur adjacent to needleleaf forests. 

Alder-willow. Mixed sites of alder and willow occur within the closed tall shrub

map class. The sites are often composed of patches of pure willow or pure alder. 

This type is primarily found on colluvial and glacial drift sideslopes, ranging from 

gentle to steep (50 to 550). Mixed alder and willow is commonly found adjacent to 

needleleaf forests and shrub map classes. 

Species associated with willow dominated and mixed alder and willow sites include

Alnus crispa (American green alder), Alnus sinuata (Sitka alder), Salix alaxensis

(feltleaf willow), Salix glauca (grayleaf willow), Salix lanata subspecies richardsonii

 (Richardson willow), Spiraea beauverdiana (Alaska spiraea), Potentilla fruticosa

(shrubby cinquefoil), Empetrum nigrum (crowberry), Ribes triste (red currant), and 

Vaccinium uliginosum (bog blueberry). Both white spruce and black spruce as well 

as paper birch occur in small quantities, as do moss species. 

Plant associations. Two plant associations within this landcover class were defined 

and described: Betula glandulosa (resin birch), and Lichen-Betula glandulosa. 
107 

However, other undescribed plant associations occur including Salix alaxensis

(feltleaf willow), Salix lanata subspecies richardsonii (Richardson willow), Salix 

glauca (grayleaf willow), Alnus crispa (American green alder), and Alnus sinuata

(Sitka alder). 

Interpretation key. The closed tall shrub class is different than the Alaska Vegetation 

Classification closed tall scrub class. We used >3.5 feet in height as the defining 

characteristic, whereas the Alaska Vegetation Classification used >4.5 feet. We 

collected field data using three map classes—closed alder or birch, closed willow and 

closed alder-willow—but collapsed the classes into the closed tall shrub class 

because they could not be separated spectrally. 

Accuracy assessment and mapping issues. The producer’s accuracy for the closed 

tall shrub was 86%, with a user’s accuracy of 83% (Table 10b). Errors of 

commission and omission were due primarily to confusion with the open tall shrub

and the more dense closed canopy shrub birch-ericaceous-willow classes. There was 

also a significant amount of spectral confusion between the closed tall shrub class 

(mainly alder) and the open and closed paper birch-aspen forest classes in the 

southern portions of the buffered GAAR area, particularly in the 10-mile buffer area 

around the park (where ground reference data was very limited). These problems 

were in relatively small areas and were mainly errors of omission for the broadleaf 

forest classes (and commission for the tall shrub classes). Mapping of this class was 

based primarily on the quantitative spectral characteristics (training signatures 

statistics) for 34 sites within GAAR. Because of the large number and dispersion of 

tall closed shrub signatures, and also the large number of shrub birch-ericaceouswillow signatures, the spectral classification was relied on heavily for separating 

these two classes. In confused problem areas (usually in valleys and transitions 

between upslope and floodplain areas) manual edits were implemented based on the 

review of the FirePro and 1998 field data, image annotations, and image 

interpretation. Landsat TM 4,5,3 (RGB) signatures for this class were bright orangered, and very similar to signatures for the broadleaf forest types. When considering 

both the closed and open tall shrub classes as a single tall shrub mapping class, the 

producer’s accuracy becomes 77%, while the user’s accuracy increases to 93%. 
108 

Open tall shrub (II.B.2.) 

Classification. Total tall shrub (>3.5 feet tall) cover is 25 to 74% with shrubs at least 

3.5 feet in height (Figures 33a and b). Tree canopy cover is less than 10% or absent. 

 

 Figure 33a. Open tall shrub (alder) on upslope, with patches of closed tall 

 shrub as well 
109 

 Figure 33b. Open tall shrub (alder) on upslope, with patches of closed tall 

 shrub as well 

Class description. The open tall shrub map class covers 3% of GAAR, and occurs in 

all three ecoregions. This class is similar in distribution and species composition to 

the closed tall shrub map class. It is characterized by open stands of shrubs greater 

than 3.5 feet tall ranging up to 15 feet. The map class is dominated by nearly pure 

stands of alder and willow species, plus mixed alder-willow sites—the three 

groupings are described below. The average site size is 9.2 acres and ranges up to 

834 acres (Table 12). 

Alder. Sites dominated by alder within the open tall shrub map class are found on 

steep colluvial and glacial drift sideslopes as well as gentle toeslopes and floodplains. 

 It is frequently found in narrow valleys rather than broad valleys. The slope of 

sampled sites tended to be slightly higher for open alder sites (400

) versus closed 

alder sites (250

). Open alder sites were found reaching higher elevations (4,029 feet) 

on sampled sites than closed alder sites (3,524 feet) (Appendix 2). Soils are generally 

mesic. The tall shrubs tend to grow in a clumped distribution, therefore open patches 

in the canopy are frequent and allow for other species to take advantage of the 

available sunlight. Alder dominated sites grow adjacent to needleleaf map classes on 

the toeslopes and mountain sideslopes, and occur next to prostrate shrub and low 

shrub map classes on the upslope. Sites dominated by tall willow are also commonly 

found adjacent to alder dominated sites. They are concentrated in the south portion 

of the Brooks Range, in both the Brooks Range ecoregion and the interior forested 

lowlands and uplands ecoregion (Figures 3a and 3b). 
110 

Alnus crispa (American green alder) and Alnus sinuata (Sitka alder) both occur and 

reach a height of over 10 feet. Alnus crispa is more common on the floodplains than 

Alnus sinuata. Plants associated with alder dominated sites include Vaccinium 

uliginosum (bog blueberry), Vaccinium vitis-idaea (low bush cranberry), Betula nana

(dwarf arctic birch) or Betula glandulosa (resin birch), Ledum palustre (Labrador 

tea), Empetrum nigrum (crowberry), Equisetum (horsetail) species, Spiraea 

beauverdiana (Alaska spiraea), Dryas species, Cassiope tetragona (four-angled 

cassiope), Salix glauca (grayleaf willow), and other Salix (willow) species. Mosses 

include Sphagnum (peat moss) species, Hylocomium splendens (feather moss), and 

Dicranum species. Grasses and sedges as well as lichens also occur. 

Willow. Sites dominated by willow within the open tall shrub map class are more 

common than closed tall willow sites within GAAR. Both open and closed willow 

sites are found adjacent to needleleaf forests. Willow is primarily found on the sandy 

well drained deposits of braided streams, particularly in the northern portion of 

GAAR. It also occurs on colluvial and glacial till sideslopes. Stands of willow 

within the map class occur in all the ecoregions of GAAR. Betula nana (dwarf arctic 

birch) or Betula glandulosa (resin birch) are commonly associated with sites 

dominated by willows. 

Alder and willow. Mixed stands of alder and willow occur within the open tall shrub

map class. These sites are primarily found on colluvial and glacial drift sideslopes 

ranging from 00

 to 350 on sampled sites. The mixed alder-willow dominated sites are 

found adjacent to needleleaf forests and tall shrub map classes. Within these sites, 

the alder and willow tends to grow in a clumped distribution. 

Species associated with the mixed alder-willow dominated sites include Spiraea 

beauverdiana (Alaska spiraea), Potentilla fruticosa (shrubby cinquefoil), Empetrum 

nigrum (crowberry), Equisetum (horsetail) species, Alnus crispa (American green 

alder) and Alnus sinuata (Sitka alder), Vaccinium uliginosum (bog blueberry), Salix 

alaxensis (feltleaf willow), Salix barclayi (Barclay willow) and other Salix (willow)

species. Picea glauca (white spruce) and Picea mariana (black spruce) as well as 

Betula papyrifera (paper birch) occur in small quantities. Mosses are common. 

Plant associations. Described plant associations within this landcover class are Salix 

alaxensis (feltleaf willow), Salix lanata subspecies richardsonii/Carex membranacea, 

and Salix lanata subspecies richardsoni (Richardson willow). However, other 

undescribed plant associations occur including Salix glauca (grayleaf willow), Alnus 

crispa (American green alder), and Alnus sinuata (Sitka alder). 

Interpretation key. The open tall shrub class is also different than the Alaska 

Vegetation Classification open tall scrub class. We used >3.5 feet in height as the 

defining characteristic, whereas the Alaska Vegetation Classification used >4.5 feet. 

We collected field data using three map classes—open alder, open willow and open 

alder-willow—but collapsed the classes into the open tall shrub class because they 
111 

could not be separated spectrally. 

Accuracy assessment and mapping issues. The producer’s accuracy for the open tall 

shrub class was 60%, with a user’s accuracy of 83% (Table 10b). Errors of 

commission and omission were due primarily to confusion with the closed tall shrub

and the shrub birch-ericaceous-willow and shrub birch-willow-tussock tundra

classes. The confusion with these low shrub classes was found mainly on partial 

terrain shadowed areas, where the low shrub classes were in significant abundance as 

the understory. Mapping of this class was based primarily on the quantitative spectral 

characteristics (training signatures statistics) for 45 sites within GAAR. 

Incorporation of the illumination (shaded relief) data in the supervised spectral 

classification reduced this confusion; however, this class did require substantial 

editing based on review of the FirePro and 1998 field data, image annotations, and 

image interpretation. Landsat TM 4,5,3 (RGB) signatures for this class were medium 

to dull orange-red. The dull orange red signature was usually indicative of a more 

open tall shrub with low shrub dominating the understory, and also could be 

attributed to partial terrain shadow effects. When considering both the open and 

closed tall shrub classes as a single tall shrub mapping class, the producer’s accuracy 

becomes 77%, while the user’s accuracy increases to 90%. 

Shrub birch-willow-tussock tundra (II.C.2.X.) 

Classification. Shrub height is between 0.3 to 3.5 feet tall and is greater than 25% of 

the total vegetation cover (Figures 34a and b). Tussocks cover greater than 25% of 

the site. Tall shrub (>3.5 feet tall) cover is less than 25%, and tree canopy is less than 

10% or absent. 

Figure 34a. Shrub birch-willow-tussock tundra 
112 

r

Figure 34b. Shrub birch-willow-tussock tundra 

Class description. This mapping class covers 6.7% of GAAR (Table 9) and is 

extremely common in the arctic foothills ecoregion (Figures 3a and 3b). It is found 

on a broad range of surficial geology types including floodplains, colluvial sideslopes 

and glacial drift sideslopes. Slopes on the sites sampled ranged from 00

 to 100, with 

elevation ranging between 610 and 3,363 feet (Appendix 2). The shrub birch-willowtussock tundra map class is found adjacent to the shrub birch-ericaceous-willow, 

mesic herbaceous, and closed low willow, and occasionally adjacent to the tall shrub 

and wet herbaceous classes. The average site size is 17 acres and includes huge 

expanses of tundra ranging up to 33,136 acres (Table 12). 

As its name implies, the shrub birch-willow-tussock tundra map class contains 

tussocks—at least 25% of the total cover. Tussocks are sedges comprised of many 

stems arising from a central crown. They reach 24 inches in height, but are typically 

only 8 inches tall. Shrub layers associated with tussock tundra may be close to 

prostrate height or grow as high as 4 feet tall. Shrub birch species (Betula nana or 

Betula glandulosa) and willow (Salix species) generally decrease in height as you 

move north. 

Species diversity is relatively low within the mapping class. In the overstory, 

commonly found plants include Spiraea beauverdiana (Alaska spiraea), Betula nana

(dwarf arctic birch) or Betula glandulosa (resin birch), Salix lanata subspecies
113 

richardsonii (Richardson willow) and Salix planifolia subspecies pulchra 

(diamondleaf willow). Ericaceous shrubs are also present including Vaccinium 

uliginosum (bog blueberry), Ledum palustre (Labrador tea), and Arctostaphylos rubra 

(red-fruit bearberry). Tussock forming graminoids include Carex aquatilis (water 

sedge), Carex bigelowii (Bigelow sedge), Eriophorum vaginatum (tussock 

cottongrass), and Calamagrostis canadensis (bluejoint grass). Mosses and lichens 

found within the map class include Sphagnum (peat moss) species, Hylocomium 

splendens (feather moss), and Cladina species. 

Plant associations. The following plant associations were defined for the shrub 

birch-willow-tussock tundra mapping class: Betula glandulosa/Carex aquatilis, 

Betula glandulosa/Carex bigelowii, Betula glandulosa/Eriophorum russeolum, 

Vaccinium uliginosum-Ledum palustre/Carex bigelowii, Vaccinium uliginosumLedum palustre/Eriophorum vaginatum, Vaccinium uliginosum-Ledum 

palustre/Eriophorum russeolum, Salix lanata subspecies richardsonii/Carex 

bigelowii, Salix planifolia subspecies pulchra/Carex aquatilis, Salix planifolia 

subspecies pulchra/Eriophorum russeolum, and Salix planifolia subspecies

pulchra/Carex bigelowii. 
114 

Interpretation key. The overall low shrub category is slightly different than the 

Alaska Vegetation Classification level II low scrub category. We used 0.3 to 3.5 feet 

in height as the defining characteristic, whereas the Alaska Vegetation Classification 

used 0.3 to 4.5 feet. The shrub birch-willow-tussock tundra map class is not defined 

in the Alaska Vegetation Classification. 

Accuracy assessment and mapping issues. The producer’s accuracy for the shrub 

birch-willow-tussock tundra class was 64%, with a user’s accuracy of 77% (Table 

10b). Errors of commission and omission were due primarily to confusion of shrub 

birch-ericaceous-willow class and to a lesser extent with the prostrate shrub (with a 

relatively large herbaceous component) or the mesic herbaceous (with a relatively 

large shrub component. Mapping of this class was based primarily on the 

quantitative spectral characteristics (training signatures statistics) for 52 sites within 

GAAR. Because of the high number of training signatures for shrub birch-willowtussock tundra, mesic herbaceous and low shrub birch-ericaceous-willow, the 

spectral based classification was relied on as the primary discriminator between these 

classes. Manual editing based on review of the FirePro and 1998 field data, image 

annotations, and image interpretation was marginally successful and implemented on 

a limited scale. However, manual edits were limited to to ensure map consistency. 

There was also confusion north of treeline with the wet herbaceous class. The 

Landsat TM Band 5 was used to theshold actual wet herbaceous from those sites that 

were either shrub birch-ericaceous-willow (or mesic herbaceous). The wettest shrub 

birch-willow-tussock tundra sites were usually spectrally separable from the drier of 

the shrub birch-ericaceous-willow sites (however, these wet tussock tundra sites were 

usually confused with the mesic or wet herbaceous classes). Finally, there were some 

commission errors with the woodland classes. Part of this confusion was often due to 

partial terrain shadow. Another factor believed to contribute to commission errors in 

woodland areas is relatively low spruce cover (10-15%) with understory dominated 

by low shrub. Models using winter imagery were used to reduce this error. Landsat 

TM 4,5,3 (RGB) signatures for this class are quite variable and included a dull 

orange-red, medium red, and whitish orange. The variation in spectral response was 

typically due to the variations in site moisture (increased water resulted in a 

darker/grayer signature), herbaceous component (generally increase red tones in 

signature) and lichen or moss understory (generally results in whitening/lightening of 

signatures). Partially senesced herbaceous or willow components of the shrub birchwillow-tussock tundra class in the arctic foothills ecoregion also may have 

contributed to the whitening of sites in this region. When considering the shrub 

birch-willow-tussock tundra, shrub birch-ericaceous-willow, and closed low willow

shrub classes a single low shrub mapping class, the producer’s accuracy is 82%, 

while the user’s accuracy is 87%. 

Shrub birch-ericaceous-willow (II.C.X.) 

Classification. Shrub height is 0.3 to 3.5 feet with greater than 25% of the vegetation 

cover as low shrub (Figures 35a and b). Less than 25% of the site is covered by 
115 

tussocks, less than 2/3 of the total low shrub cover is willow, and less than 75% of the 

total shrub cover is shrub birch. Tree canopy cover is less than 10% or absent. 

Figure 35a. Shrub birch-ericaceous-willow in valley (50% dwarf birch, 25% 

 prostrate shrub) 

 Figure 35b. Shrub birch-ericaceous-willow in valley (50% dwarf birch, 25% 

prostrate shrub) 
116 

Class description. The shrub birch-ericaceous-willow class differs from the shrub 

birch-willow-tussock tundra map class in that it is drier—but still mesic—it has less 

than 25% tussocks, and it has a different herbaceous species composition. However, 

the shrub layer is similar. It is found growing on valley bottoms, floodplains, 

toeslopes, and colluvial and glacial drift sideslopes surfaces with 00 to 450 slope. 

Elevations for sites sampled range from about 300 to 4,800 feet (Appendix 2). The 

sites are generally mesic sites, often with small amounts of standing water present. 

On these wetter sites, the willow species grow on the dryer portions (mounds), and 

more hydrophilic vegetation (such as Carex aquatilis) concentrates in the troughs. 

The map class covers 15.2% of GAAR (Table 9), and is found in all three ecoregions 

(Figures 3a and 3b). The average site size is 22.5 acres and includes huge expanses of 

tundra ranging up to 47,603 acres (Table 12). 

Shrub species commonly found within this mapping class include Betula nana (dwarf 

arctic birch) or Betula glandulosa (resin birch), Vaccinium uliginosum (bog 

blueberry), Ledum palustre (Labrador tea), Andromeda polifolia (bog rosemary), 

Vaccinium vitis-idaea, Empetrum nigrum (crowberry), Salix planifolia subspecies

pulchra (diamondleaf willow), and Loiseleuria procumbens (alpine azalea). Some 

sites are dominated by willow, primarily Salix planifolia subspecies pulchra

(diamondleaf willow), Salix lanata subspecies richardsonii (Richardson willow), 

Salix brachycarpa (barren-ground willow), and Salix myrtillifolia (low blueberry 

willow). Herbaceous species include Eriophorum species, Calamagrostis canadensis

(bluejoint grass), Carex bigelowii (Bigelow sedge), and Carex aquatilis (water 

sedge). Lichen and mosses also commonly occur. 

Plant associations. Plant associations within the shrub birch-ericaceous-willow

landcover class are Betula glandulosa, Lichen-Betula glandulosa, Vaccinium 

uliginosum-Ledum palustre/Sphagnum, Vaccinium uliginosum-Ledum palustre, and 

Salix planifolia subspecies pulchra (open). 

Interpretation key. The overall low shrub category is slightly different than the 

Alaska Vegetation Classification level II low scrub category. We used 0.3 to 3.5 feet 

in height as the defining characteristic, whereas the Alaska Vegetation Classification 

used 0.3 to 4.5 feet. The shrub birch-ericaceous-willow and open low willow classes 

used for mapping in the field were collapsed into the shrub birch-ericaceous-willow

class because each class could not be separated spectrally. The shrub birchericaceous-willow map class is not defined in the Alaska Vegetation Classification. 

Accuracy assessment and mapping issues. The producer’s accuracy for the shrub 

birch-ericaceous-willow class was 75%, with a user’s accuracy of 74% (Table 10b). 

Errors of commission and omission were due primarily to confusion with the shrub 

birch-willow-tussock tundra class and to a lesser extent with the mesic herbaceous

(with a relatively large low shrub component) and the spruce woodland class (also 

with a relatively large low shrub component). Mapping of this class was based 

primarily on the quantitative spectral characteristics (training signatures statistics) for 
117 

176 sites within GAAR. Because of the high number of training signatures for shrub 

birch-ericaceous-willow, shrub birch-willow-tussock tundra , and mesic herbaceous

classes, the spectral based classification was relied on as the primary discriminator 

between these classes. Modeling with NDVI was effective at reducing the 

commission errors with the prostrate shrub classes. Manual editing based on review 

of the FirePro and 1998 field data, image annotations, and image interpretation was 

marginally successful and implemented on a limited scale. However, manual edits 

were limited to ensure map consistency. There were also some commission errors 

with the open spruce and woodland classes. Part of this confusion was due to partial 

terrain shadow altering the signatures for shrub birch-ericaceous-willow for sites 

sampled in these terrain conditions. Another factor believed to contribute to 

commission errors in woodland areas is relatively low spruce cover (10-15%) with 

understory dominated by low shrub. Models using winter imagery were less effective 

at reducing this error (because the shrub birch-ericaceous-willow can realistically 

occur intermixed with open spruce or woodland mapping areas). Landsat TM 4,5,3 

(RGB) signatures for this class were quite variable and include a dull orange-red, 

medium red, and whitish-orange colors. The variation in response was typically due 

to the variations in site moisture (generally more water results in a darker/grayer the 

signatures), herbaceous component (generally more herbaceous vegetation increases 

red tones in the signatures) and lichen or moss understory (generally more lichen or 

moss results in whitening/lightening of signatures). Partially senesced herbaceous or 

willow components of the shrub birch-ericaceous-willow class in the Arctic Foothills 

are also believed to contribute to the “bleaching” of sites in this region. When 

considering the shrub birch-willow-tussock tundra, shrub birch-ericaceous-willow, 

and closed low willow shrub classes a single low shrub mapping class, the producer’s 

accuracy is 82%, while the user’s accuracy is 87%. 

 

Closed low willow (II.C.2.B.) 

Classification. Shrub height is 0.3 to 3.5 feet with total low shrub cover between 75 

to 100% (Figures 36a and b). Less than 25% of the site is covered by tussocks and 

greater than 2/3 of the total low shrub cover is willow. Tree canopy cover is less than 

10% or absent. 
118 

Figure 36a. Closed low willow (75% willow) 

 Figure 36b. Closed low willow (75% willow) 

Class description. This is a common map class located in the northern half of GAAR. 

 It is found on the edge of small streams, and the water tracks of tussock tundra 

hillsides. Many of the small streams have terrace formation. The streams and water 
119 

tracks occur on slopes ranging from 00 to 100. Elevations for sites sampled range 

from approximately 1,200 to 3,420 feet (Appendix 2).Hummocks often form due to 

the presence of Eriophorum angustifolium (tall cottongrass) and Carex aquatilis 

(water sedge). The map class covers 0.18% of GAAR (Table 9). The average site 

size is 5.2 acres and rnages up to 172 acres (Table 12). 

Salix planifolia subspecies pulchra (diamondleaf willow) is the most frequently 

found willow in low closed willow mapping class. It generally grows 2 feet in height 

although it can reach 6 feet (Viereck 1972). Species commonly found in the map 

class include Calamagrostis canadensis, Equisetum (horsetail) species, Betula nana

(dwarf arctic birch) or Betula glandulosa (resin birch), Eriophorum species, and 

Petasites frigidus (frigid coltsfoot). Mosses associated with this class are Sphagnum

(peat moss) species and Hylocomium splendens (feather moss). 

Plant associations. Only one plant association is described for the closed low willow

landcover class, Salix planifolia subspecies pulchra (closed). Other observed plant 

associations, but not described, include Salix planifolia subspecies pulchra

(diamondleaf willow) with an understory of Calamagrostis canadensis (bluejoint 

grass) (Kobuk Boot region), and, possibly, low growing Salix alaxensis (feltleaf 

willow) and Salix lanata subspecies richardsonii (Richardson willow) along 

floodplains on the northern edge of GAAR. 

Interpretation key. The overall low shrub category is slightly different than the 

Alaska Vegetation Classification level II low scrub category. We used 0.3 to 3.5 feet 

in height as the defining characteristic, whereas the Alaska Vegetation Classification 

used 0.3 to 4.5 feet. The closed low willow class has a corresponding class of the 

same name in the Alaska Vegetation Classification. 

Accuracy assessment and mapping issues. The producer’s accuracy for the closed 

low willow class was 78%, with a user’s accuracy of 58% (Table 10b). Nearly all 

errors of commission and omission were due to to confusion between the low shrub 

classes shrub birch-willow-tussock tundra class and shrub birch-ericaceous-willow, 

and to a lesser extent with the prostrate shrub (with a relatively large herbaceous 

component) or the mesic herbaceous (with a relatively large shrub component). 

Modeling with NDVI was effective at reducing the commission errors with the 

prostrate shrub class. Mapping of this class was based primarily on the quantitative 

spectral characteristics (training signatures statistics) for 11 sites within GAAR. 

Manual editing based on review of the FirePro and 1998 field data, image 

annotations, and image interpretation was effective as the closed low willow class was 

usually identifiable in the field data and imagery at the river/stream confluences and 

along riparian areas. Landsat TM 4,5,3 (RGB) signatures for this class were typically 

medium red to magenta. The variation in response was typically due to the variations 

in site moisture (generally more water results in darkening these signatures) and 

exposed rock/gravel (generally more exposed sand/gravel bars results in increased 

white tones and bluish-magenta tones in these signatures). When considering the 

shrub birch-willow-tussock tundra, shrub birch-ericaceous-willow, and closed low 
120 

willow shrub classes a single low shrub mapping class, the producer’s accuracy is 

82%, while the user’s accuracy is 87%. 

Prostrate shrub-rock (II.D.Y.) 

Classification. Shrub height is less than 0.3 feet with total prostrate shrub cover 

greater than 25% (Figures 37a and b). Bare-ground comprises 33 to 74% of the total 

cover. The sites contain less than 25% cover of tussocks. Tree canopy is less than 

10% or absent. 

 Figure 37a. Prostrate shrub-rock in arctic foothills (45% dryas, 40% bare rock) 

 Figure 37b. Prostrate shrub-rock in arctic foothills (45% dryas, 40% bare rock) 
121 

Class description. This is a major type—6.1% of GAAR—located throughout the 

Park on unstable surfaces such as talus slopes, slopes below bedrock outcrops, frost 

boils on river terraces, areas of intense frost action in high mountain valley floors, 

rounded mountain ridges (exposed bedrock) with intense frost action, and sorted 

patterned ground (Table 9). This map class contains sites with a fellfield appearance 

(broken rock/rubble mixed with prostrate shrubs), as well as areas on steep sideslopes 

that contain uneven strips of rubble and prostrate vegetation. Soils are a thin layer of 

dry to mesic sand, litter, or organic mat interspersed with exposed rock. Rock and 

bare-ground cover ranges from 33 to 74%, while prostrate shrubs, lichens and forbs 

comprise the remainder. Slopes range from 00 to 500. Elevation of sites sampled 

ranged from 1,030 to 5,423 feet (Appendix 2). The average site size is 15.3 acres and 

includes large areas ranging up to 8,065 acres (Table 12). 

Characteristic vegetation includes Dryas octopetala (white mountain avens), Salix 

phlebophylla (skeletonleaf willow), Salix reticulata (netleaf willow), Silene acaulis

(moss campion), Pedicularis species, Diapensia lapponica (Lapland diapensia), 

Loiseleuria procumbens (alpine azalea), and Arctostaphylos alpina (alpine 

bearberry). Both crustose and fruticose lichens are present, however crustose lichens 

dominate the lichen flora. Primarily Cladina species, Cetraria species, and 

occasionally Stereocaulon species are present. 

Plant associations. Dryas octopetala-rock is the only plant association described for 

the prostrate shrub-rock map class. 

Interpretation key. The overall prostrate shrub class is the same as the Alaska 

Vegetation Classification level II category dwarf scrub. Both use 0.3 feet as the 

defining height characteristic. For the final map, the fellfield class used for field work 

was renamed prostrate shrub-rock. 

Accuracy assessment and mapping issues. The producer’s accuracy for the prostrate 

shrub-rock was 88%, with a user’s accuracy of 93% (Table 10b). Nearly all errors of 

commission and omission were due to to confusion between the prostrate shrub and 

prostrate shrub-lichen, and the sparsely vegetated class. Models utilizing NDVI 

were effective at reducing confusion with all of these classes. This class was based 

primarily on the quantitative spectral characteristics (training signatures statistics) for 

45 sites in GAAR. Landsat TM 4,5,3 (RGB) signatures for this class typically were 

greenish red or greenish red speckled with orange or brighter red. When considering 

the prostrate shrub-rock, prostrate shrub-lichen, and prostrate shrub classes a single 

prostrate shrub mapping class, the producer’s accuracy becomes 84%, while the 

user’s accuracy changes to 79%. 

Prostrate shrub-lichen (II.D.X.C.) 

Classification. Shrub height is less than 0.3 feet with total prostrate shrub cover 

greater than 25% (Figures 38a and b). Less than 33% of the total cover is bare-
122 

ground and greater than or equal to 25% of total cover is fruticose lichen. These sites 

contain less than 25% tussocks. Tree cover is less than 10% or absent. 

 Figure 38a. Prostrate shrub-lichen (30% prostrate shrub, 25% bare rock, 30% 

lichen) 

 Figure 38b. Prostrate shrub-lichen (30% prostrate shrub, 25% bare rock, 30% 

lichen) 

Class description. The high lichen cover (up to 65% of the total cover) differentiates 
123 

this class from other prostrate shrub types. This is a minor type covering 1.2% of 

GAAR located throughout the Park on relatively stable surfaces including mountain 

valleys, mountain slopes, rounded mountain ridges (exposed bedrock) and alluvial 

fans (Table 9). Slopes range from 00

 to 250. Elevations of sites sampled ranged from 

about 1,550 to 4,160 feet (Appendix 2). The soils are a thin duff layer over dry to 

mesic silt, sand and cobble. Soils are typically dry to slightly mesic. The average 

site size is 7.6 acres—based on sampled polygons—and ranges up to 787 acres (Table 

12). 

Vascular plant cover includes prostrate height shrubs such as Vaccinium uliginosum 

(bog blueberry), Vaccinium vitis-idaea (low bush cranberry), Dryas octopetala (white 

mountain avens), Ledum palustre (Labrador tea), Loiseleuria procumbens (alpine 

azalea), and Arctostaphylos rubra (red-fruit bearberry). Betula nana (dwarf arctic 

birch) or Betula glandulosa (resin birch) may also be present and generally grows to a 

height of 6 to 8 inches. Fruticose lichen genera are Cladonia, Cetraria, and 

Alectoria. 

Plant associations. The prostrate shrub-lichen class is comprised of one plant 

association, Vaccinium uliginosum/fruticose lichen. 

Interpretation key. The overall prostrate shrub class is the same as the Alaska 

Vegetation Classification level II category dwarf scrub. Both use 0.3 feet as the 

defining height characteristic. For the final map, the prostrate-lichen class used for 

field mapping was renamed prostrate shrub-lichen. This class is comparable to the 

Alaska Vegetation Classification level IV class dryas-lichen tundra. 

Accuracy assessment and mapping issues. The producer’s accuracy for the prostrate 

shrub-lichen class was 85%, with a user’s accuracy of 93% (Table 10b). Nearly all 

errors of commission and omission were due to confusion between the prostrate 

shrub class. This class also showed significant confusion with the sparsely vegetated

class and the bare-ground class. This class was based primarily on the quantitative 

spectral characteristics (training signatures statistics) for 11 sites in GAAR. Models 

utilizing NDVI were effective at reducing confusion among the confused prostrate 

shrub classes and sparsely vegetated and bare-ground classes. Landsat TM 4,5,3 

(RGB) signatures for this class typically were white with light reddish orange tones, 

and was generally fairly unique. However, prostrate shrub sites with relatively high 

lichen content (20-25%), and relatively low prostrate shrub content (approximately 

25-40%) are likely to be misclassified as prostrate shrub-lichen. When considering 

the prostrate shrub-rock, prostrate shrub-lichen, and prostrate shrub classes as a single 

prostrate shrub mapping class, the producer’s accuracy is 84%, while the user’s 

accuracy is 79%. 

Prostrate shrub (II.D.X.) 

Classification. Shrub height is less than 0.3 feet with total prostrate shrub cover 

greater than 25% (Figures 39a and b). Less than 33% of the total cover is bare-
124 

ground, less than 25% of the total cover is fruticose lichen, and less than 25% 

tussocks. Tree canopy is less than 10% or absent. 

Figure 39a. Prostrate shrub (55% prostrate shrub, 25% herbaceous, 10% 

 bare rock, 5% water, 5% moss) 

 Figure 39b. Prostrate shrub (50%prostrate shrub, 15% herbaceous, 15% 

 lichen, and 5% bare rock) 

Class description. Prostrate shrub is the predominant shrub type found within alpine 
125 

areas of GAAR. It is concentrated within the Brooks Range ecoregion (Figures 3a

and 3b), and covers 17.2% of GAAR (Table 9). The map class is found on unstable 

to stable surfaces such as mountain slopes, high mountain valley floors, rounded 

mountain ridges (exposed bedrock), the riverside edge of river terraces, and on sorted 

patterned ground. Slopes range from 00 to 550, and the elevation typically exceeds 

1,600 feet (Appendix 2). The soils are a thin layer of dry to mesic sand, litter or 

organic mat interspersed with exposed rock. This class often grades into the sparse 

vegetation landcover class and, on more stable sites and downslope, the prostratelichen, closed low willow, open tall shrub, and closed tall shrub landcover classes. 

Site size is large averaging 28 acres and ranging up to 16,354 acres (Table 12). 

The prostrate shrub map class is comprised of vegetation that generally reaches a 

height of 4 inches or less. The dominant shrub is Dryas octopetala (white mountain 

avens). Other strong associates are Dryas integrifolia (entire-leaf mountain-avens), 

Salix reticulata (netleaf willow), Salix arctica (arctic willow), Salix phlebophylla

(skeletonleaf willow), Cassiope tetragona (four-angled cassiope), Vaccinium 

uliginosum (bog blueberry), Arctostaphylos rubra (red-fruit bearberry), and 

Arctostaphylos alpina (alpine bearberry). Herbaceous vegetation often has high 

cover values and includes Carex bigelowii (Bigelow sedge), Silene acaulis (moss 

campion), Minuartia species, Pedicularis species, Boykinia richardsonii, and 

Anemone narcissiflora (narcissus-flowered anemone). Multiple species of fruticose 

lichens also occur. 

Plant associations. The described plant associations within the prostrate landcover 

class are Dryas octopetala/Carex species, Dryas octopetala, Dryas octopetalaCassiope tetragona, Dryas integrifolia, and Salix reticulata. 

Interpretation key. The overall prostrate shrub class is the same as the Alaska 

Vegetation Classification level II category dwarf scrub. Both use 0.3 feet as the 

defining height characteristic. Two classes, prostrate-herbaceous and prostrate, were

used for field mapping, and were collapsed into one class—prostrate shrub—after the 

field season because they could not be separated spectrally. 

Accuracy assessment and mapping issues. The producer’s accuracy for the prostrate 

shrub class was 77%, with a user’s accuracy of 67% (Table 10b). Errors of 

commission and omission were due to confusion among the prostrate shrub-rock and 

prostrate shrub-lichen classes. This class also shows significant confusion mesic 

herbaceous. This class was based primarily on the quantitative spectral 

characteristics (training signatures statistics) for 127 sites in GAAR. Because of the 

large number of training samples (signatures) for all of the prostrate classes as well as 

the mesic herbaceous class, the spectral classification was relied on heavily for class 

discrimination. Models utilizing NDVI were effective at reducing confusion among 

the confused prostrate shrub classes, and between the prostrate shrub and sparsely 

vegetated or bare-ground classes. In the higher elevation valleys, mesic herbaceous

areas were found adjacent to prostrate shrub areas. This confusion was particularly 

problematic when the herbaceous content of the prostrate shrub areas were close to 
126 

the 25% upper threshold for the prostrate shrub mapping class. Manual editing was 

for the most part ineffective due to the difficulty of determining shrub/herbaceous 

components from image interpretation. Based on the Landsat TM 4,5,3 (RGB) 

signatures for this class typically are orange-red, but may vary considerably. When 

considering the prostrate shrub-rock, prostrate shrub-lichen, and prostrate shrub

classes as a single prostrate shrub mapping class, the producer’s accuracy is 84%, 

while the user’s accuracy is 79%. 

Dry herbaceous (III.X.1.) 

Classification. The dominant vegetation is growing on well drained, dry sites 

(Figures 40a and b). Herbaceous cover is greater than 25%, tree canopy is less than 

10% or absent, and shrub cover is less than 25%. 

 Figure 40a. Dry herbaceous (clumps of graminoid grasses) on lateral sand 

dunes along the Killik River 
127 

 Figure 40b. Dry herbaceous (clumps of grasses) on lateral sand dunes 

along the Killik River 

Class description. The dry herbaceous map class is found on well-drained sites with 

no standing water. It is extremely limited within GAAR found primarily on sand 

dunes along the Killik River in the north central region of the park. The map class 

covers <0.01% of GAAR. 

Plant associations. No plant associations were described for this class. 

Interpretation key. Within the general herbaceous category, graminoids and forbs 

were combined and the environmental modifiers (dry, mesic, wet and aquatic) were 

maintained as per the Alaska Vegetation Classification. The GAAR class dry 

herbaceous equals the combined Alaska Vegetation Classification classes dry 

graminoid herbaceous and dry forb herbaceous. 

Accuracy assessment and mapping issues. This class was not found in sufficient 

quantities to map. It was only observed intermixed with mesic herbaceous and low 

shrub classes on partially stabilized sand dunes along the Killik River north of the 

Brooks Range. 

Mesic herbaceous (III.X.2.) 

Classification. The sites are moist and tussocks may dominate (Figures 41). 

Permanent standing water is not present. Herbaceous cover is greater than 25%, tree 

canopy is less than 10% or absent, and shrub cover is less than 25%. 
128 

 Figure 41. Mesic herbaceous (70% herbaceous, 25% moss, 5% dwarf shrub, 

 80% tussocks) 

Class description. The mesic herbaceous map class most primarily occurs in the 

north half of GAAR on rolling hills, valley bottoms, terraces, and floodplains. It 

covers 6.2% of the Park (Table 9), and is a diverse grouping of plant associations that 

range from Calamagrostis canadensis (bluejoint grass) to Eriophorum russeolum

(russett cottongrass). Upland herbaceous meadows as well as tussock tundra are 

included in this class. The majority of mesic herbaceous sites contain some tussocks. 

 Standing water may be present in small amounts and is frequently a result of 

seasonal precipitation fluctuations. These small pools of water are most commonly 

found within the tussock types. The elevation ranges from 505 to 4,682 feet, and the 

slope ranges from 00

 to 200 (Appendix 2). The average site size is 11.4 acres—based 

on sampled polygons—and it often cover huge areas ranging up to 33,393 acres 

(Table 12). 

The dominant graminoid species include Carex membranacea (fragile sedge), Carex 

lugens, Carex bigelowii (Bigelow sedge), Calamagrostis canadensis (bluejoint 

grass), Eriophorum russeolum (russett cottongrass), and Eriophorum vaginatum

(tussock cottongrass). Ledum palustre (Labrador tea), Vaccinium uliginosum (bog 

blueberry), and Dryas octopetala (white mountain avens) are common. Other species 

include Salix reticulata (netleaf willow), Pedicularis species, and Polygonum bistorta

(pink plume). Mosses are also commonly found in tussock dominated sites and 

include Sphagnum (peat moss) species and Hylocomium splendens (feather moss). 

Plant associations. The following plant associations were defined: Calamagrostis 
129 

canadensis, Carex bigelowii, Carex lugens, Carex membrancea, Eriophorum 

russeolum, and Eriophorum vaginatum.

Interpretation key. Within the general herbaceous category, graminoids and forbs 

were combined and the environmental modifiers (dry, mesic, wet and aquatic) were 

maintained as per the Alaska Vegetation Classification. The GAAR class mesic 

herbaceous equals the combined Alaska Vegetation Classification classes mesic 

graminoid herbaceous and mesic forb herbaceous. 

Accuracy assessment and mapping issues. The producer’s accuracy for the mesic 

herbaceous class was 79%, with a user’s accuracy of 67% (Table 10b). Errors of 

commission and omission were due primarily to confusion between the shrub birchwillow-tussock tundra and shrub birch-ericaceous-willow, as well as some confusion 

with the wet herbaceous classes. This class was based primarily on the quantitative 

spectral characteristics (training signatures statistics) for 85 sites in GAAR. Because 

of the large number of training samples (signatures) for the mesic herbaceous class, 

as well as the shrub birch-willow-tussock tundra and shrub birch-ericaceous-willow, 

the spectral classification was relied on heavily for class discrimination. However, 

reducing confusion between these classes was problematic because many of the shrub 

birch-willow-tussock tundra and shrub birch-ericaceous-willow sites had a large 

herbaceous component. Conversely, many of the mesic herbaceous sites have a 

relatively high shrub component (15-25%). To maintain consistency, manual editing 

was limited to those areas that could be definitively corroborated in the FirePro, 1998 

field data, or image annotations as classes mesic herbaceous, shrub birch-willowtussock tundra, and shrub birch-ericaceous-willow. Based on the Landsat TM 4,5,3 

(RGB) signatures for this class typically were orange-red, but can vary considerably. 

Signatures for sites in early or late season (when minimal active biomass covers the 

site) often appeared darker due to the spectral absorption characteristics of the 

seasonally wet site. Confusion with the prostrate shrub class was reduced through 

the implementation of modeling with NDVI. When considering the mesic 

herbaceous, wet herbaceous classes, and the aquatic herbaceous mapping classes as 

a single herbaceous mapping class, the producer’s accuracy is 79%, while the user’s 

accuracy is 72%. 

Wet herbaceous (III.X.3.) 

Classification. The dominant vegetation is emergent—not submerged or floating—

and semi-permanent or standing water is present (Figures 42). Herbaceous cover is 

greater than 25%, tree canopy is less than 10% or absent, and shrub cover is less than 

25%. 
130 

Figure 42. Wet Herbaceous area on edge of lake 

Class description. The wet herbaceous map class occurs on sites that have semipermanent or standing water and hydrophilic vegetation. It occurs on low centered 

polygons, saturated river terraces, the edge of ponds, lakes, sloughs, on dune slacks, 

the edge of small streams, and in water tracks. Water tracks generally occur adjacent 

to tussock tundra (mesic herbaceous map class), but contain more standing water and 

different sedge species. Wet herbaceous plant associations that occur on the edges of 

thaw lakes and ponds are typically dominated by Arctophila fulva mixed with 

Hippuris vulgaris (mare’s tail), or Carex aquatilis (water sedge). Relative to the 

other herbaceous map classes, wet herbaceous is generally small in size and patchy in 

distribution. It covers 0.26% of GAAR (Table 9). Elevations for sampled sites 

ranged from about 900 to 3,500 feet (Appendix 2) and typically occurred on low 

slope areas. 

Frequently found species include Carex aquatilis (water sedge), Arctophila fulva, 

Equisetum fluviatile, Menyanthes trifoliata (buckbean), and Eriophorum 

angustifolium (tall cottongrass). Hippuris vulgaris (mare’s tail), Sphagnum (peat 

moss) species, and Potentilla palustris (marsh fivefinger) may also occur. 

Plant associations. The following plant associations were defined for the wet 

herbaceous mapping class: Arctophila fulva, Carex aquatilis, Carex 

aquatilis/Sphagnum, Carex limosa, Carex rostrata, Carex saxatilis, Eriophorum 

angustifolium, and Equisetum fluviatile. 
131 

Interpretation key. Within the general herbaceous category, graminoids and forbs 

were combined and the environmental modifiers (dry, mesic, wet and aquatic) were 

maintained as per the Alaska Vegetation Classification. The GAAR class wet 

herbaceous equals the combined Alaska Vegetation Classification classes wet 

graminoid herbaceous and wet forb herbaceous. 

Accuracy assessment and mapping issues. The producer’s accuracy for the wet 

herbaceous class was 60%, with a user’s accuracy of 98% (Table 10b). Errors of 

commission and omission were due primarily to confusion between the shrub birchwillow-tussock tundra and mesic herbaceous classes, as well as some confusion with 

the silty water and mosaic/patterned vegetation classes. This class was based 

primarily on the quantitative spectral characteristics (training signatures statistics) for 

37 sites in GAAR. Based on the Landsat TM 4,5,3 (RGB), signatures for this class 

typically are darker grey to blue with red tones. Signatures for sites in early or later 

season (when minimal active vegetation covers the site) often appear even darker due 

to the spectral absorption characteristics of the seasonally wet site. There were also 

significant commission errors with the open spruce forest classes. Modeling with 

winter imagery (Landsat MSS Band 4) resulted in some reduction in these errors. 

Modeling with TM Band 5 (which is highly sensitive to water/moisture) was effective 

at separating the wet herbaceous sites. When considering the mesic herbaceous, wet 

herbaceous classes, and the aquatic herbaceous mapping classes as a single 

herbaceous mapping class, the producer’s accuracy is 79%, while the user’s accuracy 

is 72%. 

Aquatic herbaceous (III.D.X) 

Classification. Vegetation is submerged, floating, or growing in permanent water. 

Herbaceous cover is greater than 25%, tree canopy is less than 10% or absent, and 

shrub cover is less than 25%. 

Class description. This class includes aquatic communities in fresh water dominated 

by pondlilies (Nuphar species), Sparganium species, aquatic buttercups (Ranunculus

species), water milfoil (Myriophyllum spicatum) and pondweed (Potamogeton

species). 

Interpretation key. Within the general herbaceous category, graminoids and forbs 

were combined and the environmental modifiers (dry, mesic, wet and aquatic) were 

maintained as per the Alaska Vegetation Classification. The aquatic herbaceous map 

class is comparable to the Viereck et al (1992) class of the same name. 

Accuracy assessment and mapping issues. Although not indicated in the confusion 

matrices, this class was typically confused with the silty water class and occasionally 

with the wet herbaceous class. This site was based on a very small sample, and was 

therefore inappropriate for evaluating accuracy. To supplement the spectral 

classification, manual editing based on review of the FirePro and 1998 field data, 
132 

image annotations, and image interpretation. However, identification of lakes where 

this class occurred was still difficult other than where found in large, dense 

populations. Based on the Landsat TM 4,5,3 (RGB) signatures for this class typically 

are very dark maroon or blackish-red, but can vary considerably. When considering 

the mesic herbaceous, wet herbaceous classes, and the aquatic herbaceous mapping 

classes as a single herbaceous mapping class, the producer’s accuracy is 79%, while 

the user’s accuracy is 72% (Table 10b). 

Sparsely vegetated (IV.X) 

Classification. Total vegetation cover is 15 to 25% (Figures 43a and b). 

Figure 43a. Sparsely vegetated steep rock and talus slope (~15% dryas/moss) 
133 

 Figure 43b. Sparsely vegetated steep rock and talus slope (~15% dryas/moss) 

Class description. The sparsely vegetated map class most often occurs at the upper 

elevational limit of plant growth in the mountains, between 1,762 and 5,430 feet 

(Appendix 2). Below the elevational limit of plant growth, it commonly occurs on 

talus slopes, areas of intense frost action in high mountain valley floors, fellfield, and 

rounded mountain ridges (exposed bedrock) with intense frost action. It occurs 

occasionally on slopes below bedrock outcrops, frost boils on river terraces, and on 

sorted patterned ground. Included in the sparsely vegetated landcover class is high 

elevation sites below bare ground. Frequently, the vegetation is clumped, rather than 

a uniform distribution on bare-ground. The soils are a thin layer of dry to mesic sand, 

litter or organic mat interspersed with exposed rock. Slopes range from 00

 to 500. 

The map class covers 7.3 of GAAR, and the average site size is 16 acres based on 

sampled polygons (Table 9 and 11). 

The map class is characterized by prostrate shrubs, and 75 to 85% cover of sand, silt 

and rocks. The dominant species are Dryas octopetala (white mountain avens), Salix 

reticulata (netleaf willow), Salix arctica (arctic willow), Salix phlebophylla

(skeletonleaf willow), Cassiope tetragona (four-angled cassiope), Vaccinium 

uliginosum (bog blueberry), Arctostaphylos rubra (red-fruit bearberry), 

Arctostaphylos alpina (alpine bearberry), Carex bigelowii (Bigelow sedge), Silene 

acaulis (moss campion), and Pedicularis species. Moss and fruticose lichens occur, 

and rocks may be covered with crustose lichen. This map class typically grades into 

the bare-ground landcover class and, on more stable sites, prostrate shrub landcover 

classes. 

Accuracy assessment and mapping issues. The producer’s accuracy for the sparsely 
134 

vegetated class was 91%, with a user’s accuracy of 85% (Table 10b). Errors of 

omission and commission for this class were primarily due to confusion with the

bare-ground and prostrate shrub-rock class. NDVI was used to separate the 

prostrate rock/sparsely vegetated/bare-ground classes. This layer was particularly 

useful because of partial penetration of terrain shadow, where much of the sparsely 

vegetated areas are found. This class was based primarily on the quantitative spectral 

characteristics (training signatures statistics) for 22 sites in GAAR. Based on the 

Landsat TM 4,5,3 (RGB) signatures for this class typically appeared white, green, or 

blue with very light pink tone. 

Bare-ground (V.X.1.) 

Classification. Bare-ground represents areas with less than 15% vegetation cover 

(Figure 44). 

Figure 44. Bedrock interspersed with a sparse covering of prostrate shrub 

Class description. The bare-ground map class is one of the most common map class 

in GAAR covering 8.9% of the Park (Table 9), and is concentrated in the Brooks 

Range ecoregion (Figures 3a and 3b). The average site size is 33 acres—based on 

sampled polygons—although it typically occurs as huge expanses up to 32,040 acres 

(Table 12). It occurs in the mountains above the elevational limit of plant growth 

(average 3,241 feet; Appendix 2). Below the elevational limit of plant growth, it 
135 

occurs on talus slopes, floodplains and outwash plains, and areas of intense frost 

action in high mountain valley floors. Slopes range from 00 to 900. This type 

typically grades into the sparsely vegetated landcover class and, on more stable sites, 

prostrate shrub landcover classes. 

Accuracy assessment and mapping issues. The producer’s accuracy for the bareground class was 91%, with a user’s accuracy of 87% (Table 10b). This class was 

primarily confused with the sparsely vegetated mapping class, and was also 

misclassified occasionally in areas of the terrain shadow (shadow/indeterminate

class) . Models utilizing NDVI, slope, and illumination were applied to correct thes 

problems. Based on the Landsat TM 4,5,3 (RGB) signatures for this class typically 

appeared white, green, or blue based on color of bare–ground (or crustose lichen 

cover for rock). 

Clear water (V.X.2.) 

Clear water indicates water with little to no sediment or glacial silt (Figure 45). It 

includes lakes with productive communities of fish and aquatic vegetation. They do 

not freeze completely in the winter and are generally greater than one meter in depth. 

 Large, slow moving, deep rivers were also mapped as clear water. This type covers 

0.6% of GAAR (Table 9). 

 Figure 45. Landsat image that has silty water (blue color), clear water (black and 

 dark blue) and an area mapped as mosaic/patterned vegetation outlined by the 

 polygon 
136 

Lakes mapped as clear water include Walker Lake, Chandler Lake, and Nutuvukti 

Lake. Rivers mapped as clear water include the Noatak, Alatna, and John Rivers. 

Accuracy assessment and mapping issues. The producer’s accuracy for the clear 

water class was 99%, with a user’s accuracy of 100% (Table 10b). This class was 

typically confused with the silty water class. It was also confused with the 

shadow/indeterminate class. In areas of high terrain and extensive terrain shadows, 

erroneous water often appears in areas of shadow or partial shadow. A combination 

of illumination, slope, and the preliminary classification (ISODATA) was used to 

ensure that overclassified water areas were recoded to shadow based on the principal 

that mappable water bodies only occur on low slope areas, and not in typically high 

slope terrain shadow areas. In the spectral based ML classification and initial 

modeling for each TM scene, the continuity of the water class in a number of 

primary/secondary rivers required improvement. Also, the distinction between silty

and clear water classes was inconsistent. Changes in water levels between the 

multiple dates of scenes also resulted in problems in maintaining continuity of rivers 

at TM scene boundaries. Also, small ponds (less than 4 pixels) appeared to be 

underrepresented. To correct these problems, an additional modeling step was added 

during the interactive raster editing process. This involved first creating a clear 

water/silty water/shadow “candidate” layer by establishing thresholds in TM Band 5 

through interactive interpretation. This layer was then raster edited simultaneously 

with the complete landcover database using the TM imagery and selected airphotos as 

a guide. Areas in the water candidate layer that were visually interpreted as “true” 

water were maintained as water classes, while shadow areas were eliminated from 

further consideration as water types. Following completion of raster editing, this 

“corrected” water layer was mosaicked into the landcover database. Based on the 

Landsat TM 4,5,3 (RGB), signatures for this class typically appeared as grey to black. 

Silty water (V.X.3.) 

Silty water referred to water containing moderate to high levels of glacial silt or areas 

not deep enough to support aquatic species diversity (Figure 45). Shallow lakes, less 

than one meter in depth, and most small rivers were mapped as silty water. Many 

lakes within the mapping area are products of thermokarst, the thawing of permafrost 

which produces shallow depressions in the landscape. Many of these small lakes 

were mapped as silty water. Smaller rivers tend to have high turbidity with many 

suspended particles. This type covers 0.5% of GAAR (Table 9). 

Accuracy assessment and mapping issues. The accuracy for the silty water class 

could not be effectively estimated due to the small size and narrow linear shape of 

these areas (generally swift moving rivers). Errors in this class are primarily due to 

confusion with the clear water class. In addition, lake areas mapped as silty water

were typically either very shallow (1 meter or less) or in some cases may represent 
137 

aquatic or wet herbaceous classes. Therefore, the silty water class often is found 

along the banks of lakes, and along fast flowing riverbanks. Based on the Landsat 

TM 4,5,3 (RGB) signatures for this class typically appeared light grey to dark 

grey/black. 

Snow/ice (V.X.4.) 

This class referred to areas covered with ice or late lying snow. The expansive 

mountain range within the study area formed a wide central band, covering much of 

the park and contains large areas of both the bare-ground and snow/ice mapping 

classes. North facing slopes typically have more snow and ice present than south 

facing slopes. The mean elevation for the occurrence of the snow/ice class is 5,536 

feet (Appendix 2). It covers 0.4% of GAAR and is concentrated in the Brooks Range 

ecoregion (Figures 3a and 3b). 

Accuracy assessment and mapping issues. The producer’s accuracy for the snow/ice 

class was 99%, with a user’s accuracy of 100% (Table 10b). The preliminary 

(ISODATA derived) classification was used to develop a snow/ice layer. Particular 

clusters corresponding with snow and ice were selected from the ISODATA 

classification, and used in the final landcover database. Based on the Landsat TM 

4,5,3 (RGB) signatures for this class typically appear as bright magenta to purple. 

Mosaic/Pattern Vegetation (V.X.5.) 

This class includes patterned ground that could not be reliably mapped due to the 

highly variable, sub-pixel patterns of vegetation, water, or bare ground (Figure 45). 

Sorted polygons and ice wedge polygons dominate the type. The class covers 0.2% 

of GAAR (Table 9), however, the actual cover of polygonal ground in GAAR is 

much higher and is a common component of other classes. 

Sorted polygons range up to 30 feet in diameter and occur on glacial drift on rounded 

foothills and mountain slopes on the north edge of GAAR. Vegetation ranges from 

absent on the rims with prostrate shrubs in the center, to shrubs on the edge with no 

vegetation in the polygon center. 

Ice wedge polygons are typically connected in a polygonal pattern that is similar to 

the pattern produced by mud cracks. Their diameter ranges from 20 to 100 feet. 

These polygons are a common feature on level ground of glacial drift, lacustrine and 

floodplain surficial geology deposits of the arctic foothills and the interior forested 

lowlands and uplands ecoregions. They also occur in the larger mountain valley 

bottoms of the Brooks Range ecoregion on glacial drift and lacustrine deposits. 

Vegetation of ice wedge polygons is dependent on surface elevation and soil 

moisture. Low-center polygons have centers often with standing water and support 
138 

emergent or tussock vegetation. Low shrubs often dominate their edges. High-center 

polygons have centers dominated by prostrate shrubs and their edges by low shrubs. 

A more exhaustive description of all types of patterned ground is given in the section 

“Patterned Ground.” 

Interpretation key. These areas were primarily identified through image annotations 

and 1998 field data, and review of CIR photography. 

Accuracy assessment and mapping issues. Because of the sub-pixel (less than 28.5m) 

nature of this mapping class, it was largely delineated through manual editing. These 

areas were primarily identified through image annotations and 1998 field data, and 

review of CIR photography. All suitable training areas were therefore incorporated as 

manual edits. 

Shadow/Indeterminate (V.X.6.) 

This mapping class included areas of severe terrain shadow where landcover could 

not be reliably identified. It also included cloud or cloud shadowed areas primarily in 

the Northeast corner of GAAR. It covers 4.5% of the Park (Table 9). 

Accuracy assessment and mapping issues. The producer’s accuracy for the 

shadow/indeterminate class was 100%, with a user’s accuracy of 99% (Table 10b). 

This class was effectively modeled using illumination, slope, and the preliminary 

(pre-field) landcover database. Based on the Landsat TM 4,5,3 (RGB), signatures for 

this class typically appeared as black. 

Sand Dunes (V.X.7.) 

This class occurred very rarely (total of 173 acres) in GAAR, primarily along the 

Killik River north of the Brooks Range (Figure 46). However, large deposits were 

common in the Kobuk Valley region southwest of the GAAR project area (in 

particular, the Kobuk Dunes). Vegetation included alder and moist to dry grass/forb 

sites on the dunes, and ponds and wet herbaceous plant associations in the slacks 

(depressions). Blowouts, with exposed sand, were also common. 
139 

 Figure 46 Partially stabilized sand dunes along the Killik River 

 

Accuracy assessment and mapping issues. This class was extremely rare and was 

only observed intermixed with dry herbaceous, mesic herbaceous and low shrub 

classes on partially stabilized sand dunes along the Killik River north of the Brooks 

Range. Manual edits were implemented to include this very limited area. 
140 

3.7 PLANT ASSOCIATION DESCRIPTIONS 

The plant associations found in the GAAR project area are listed below, and 

described in full. This part of the document is intended to help users to understand the 

distribution of species and community structure across the GAAR landscapeand to 

provide a link between the mapped landcover classes and species information. Plant 

associations were classified by qualitatively grouping similar sites based primarily on 

the dominant and subdominant species. Species composition, species cover, and 

vegetation height were also considerations. A description based on vegetation and 

physical site variables was then written for each plant association. Forested and 

woodland plant associations and most tall shrub plant associations are not described 

because too few ground samples were collected in these landcover classes to provide an 

accurate description. 

Salix alaxensis 

Salix lanata subspecies richardsonii

Salix lanata subspecies richardsonii/Carex membranacea

Betula glandulosa/Carex bigelowii

Betula glandulosa/Carex aquatilis

Betula glandulosa/Eriophorum russeolum

Vaccinium uliginosum-Ledum palustre/Carex bigelowii

Vaccinium uliginosum-Ledum palustre/Eriophorum russeolum

Vaccinium uliginosum-Ledum palustre/Eriophorum vaginatum

Salix lanata subspecies richardsonii /Carex bigelowii

Salix planifolia subspecies pulchra/Carex bigelowii

Salix planifolia subspecies pulchra/Eriophorum russeolum

Salix planifolia subspecies pulchra/Carex aquatilis

Vaccinium uliginosum-Ledum palustre/Sphagnum

Vaccinium uliginosum-Ledum palustre

Betula glandulosa

Lichen-Betula glandulosa 

Salix planifolia subspecies pulchra (open) 

Salix planifolia subspecies pulchra (closed) 

Dryas octopetala-rock

Vaccinium uliginosum/fruticose lichen

Dryas octopetala/Carex species

Dryas octopetala-Cassiope tetragona

Dryas octopetala

Dryas integrifolia

Salix reticulata 

Calamagrostis canadensis 

Carex bigelowii

Carex lugens

Carex membrancea

Eriophorum russeolum
141 

Eriophorum vaginatum

Arctophila fulva

Carex aquatilis

Carex aquatilis/Sphagnum

Carex limosa

Carex rostrata

Carex saxatilis

Eriophorum angustifolium subspecies subarcticum

Equisetum fluviatile

 

CLOSED TALL SHRUB AND OPEN TALL SHRUB PLANT ASSOCIATIONS 

Salix alaxensis plant association 

Feltleaf willow 

10 sites 

 Figure 47. Salix Alaxensis plant association 

Vegetation. Salix alaxensis (feltleaf willow) is typically the only species in the low 

to tall shrub layer ranging from 2 to 6 feet in height (Figure 47). The height of Salix 

alaxensis (feltleaf willow) is lower—often only 2 feet tall—on the north edge of 

GAAR. Its cover varies from 15 to 80%. Associate species include Betula nana

(dwarf arctic birch), Empetrum nigrum (crowberry), Arctostaphylos alpina (alpine 

bearberry), Dryas octopetala subspecies alaskensis (white mountain avens), and Salix 

planifolia subspecies pulchra (diamondleaf willow), Epilobium latifolium (dwarf 
142 

fireweed), and Equisetum arvense (common horsetail). Bare-ground, rock and litter 

often have high cover. 

Environmental characteristics. This is a minor type found throughout GAAR on 

newly deposited stream and river deposits. It typically occurs as stringers or patches 

amongst open forest map classes or tussock tundra and low shrub. The small streams 

typically are rocky and receive flash floods partially due to high stream gradients (up 

to 100 slope). The Salix alaxensis (feltleaf willow) type is also found on the major 

rivers on new alluvial deposits, such as point bars. The soil surface is either bare 

alluvium or a thin layer of dry to mesic organic matter—up to 1 inches thick—over 

silt, sand and rocks. Permafrost, if present, is typically deep (10+ inches). The sites 

are relatively dry except during flooding, and the pH varies from 5.1 to 7.6 

Salix lanata subspecies richardsonii plant association 

Richardson willow 

5 sites 

Figure 48. Salix lanata subspecies richardsonii plant association 

Vegetation. Salix lanata subspecies richardsonii is the dominant shrub species, 

ranging in height from 2 to 6 feet (Figure 48). Other low to tall shrubs occur—

sometimes codominating—and include Salix arbusculoides (littletree willow), Salix 

brachycarpa (barren-ground willow), Salix alaxensis (feltleaf willow), Salix novae-
143 

angliae (tall blueberry willow) and Salix planifolia subspecies pulchra (diamondleaf 

willow). Total low to tall shrub cover is often low, ranging from 25 to 63%. 

Understory species include Vaccinium uliginosum (bog blueberry), Arctostaphylos 

rubra (red-fruit bearberry), Empetrum nigrum (crowberry), Dryas octopetala (white 

mountain avens), Calamagrostis purpurascens, Lupinus arcticus (arctic lupine), 

Equisetum variegatum (small horsetail) and Hylocomium splendens (feather moss). 

Bare-ground, rock and bryophyte cover is typically low. 

 

Environmental characteristics. This is a minor type found in the north half of GAAR 

on unstable surfaces including newly deposited stream and river deposits, the base of 

solifluction lobes, and active dunes. It occurs as stringers or patches amongst tussock 

tundra and low shrub. The dune sites are relatively dry, as are floodplain sites except 

during flooding. The small streams are typically rocky and receive flash floods 

partially due to high stream gradients (up to 100 slope). On the major rivers the Salix 

lanata subspecies richardsonii (Richardson willow) plant association occurs on new 

alluvial deposits such as point bars. Permafrost, if present, is typically deep (10+ 

inches). On solifluction lobes the sites are moist to wet, and prostrate shrubs occupy 

the upslope and downslope positions. 

Salix lanata subspecies richardsonii/Carex membranacea plant association 

Richardson willow/fragile sedge 

1 site 

Figure 49. Salix lanata subspecies richardsonii/Carex membranacea plant 

association 
144 

Salix lanata subspecies richardsonii (Richardson willow) dominates the shrub 

layer—ranging up to 5 feet in height—and the tussock forming Carex membranacea

(fragile sedge) dominates the herbaceous layer with at least 25% cover (Figure 49). 

Associate species include Salix reticulata (netleaf willow), Cassiope tetragona (fourangled cassiope), Dryas octopetala (white mountain avens) and moss species. The 

plant association appears to be uncommon in GAAR on moderate slopes. The one 

soil profile sampled had 1 foot of peat at which permafrost was encountered, the peat 

was moist to wet, and the pH 7.5. 

SHRUB BIRCH-WILLOW-TUSSOCK TUNDRA PLANT ASSOCIATIONS 

Betula glandulosa/Carex bigelowii plant association 

Resin birch/Bigelow sedge 

3 sites 

Figure 50. Betula glandulosa/Carex bigelowii plant association 

Vegetation. This plant association is dominated by Betula glandulosa (resin birch) or 

Betula nana (dwarf arctic birch) with at least 25% cover and at least 25% Carex 

bigelowii (Bigelow sedge) cover (Figure 50). Salix glauca (grayleaf willow) is 

sometimes a strong codominant, and other species include Empetrum nigrum 

(crowberry), Ledum palustre subspecies decumbens (narrow leaf Labrador tea), 

Vaccinium vitis-idaea (low bush cranberry) and Arctostaphylos alpina (alpine 
145 

bearberry). Moss and lichen cover are both less than 5%. The plant association often 

grades into various prostrate shrub and low shrub landcover classes. 

Environmental characteristics. The distribution of the plant association is not clear, 

but appears to be more common in areas dominated by tussock tundra on the north 

half of GAAR. Slopes range from 00

 to 250 in moist-wet valley bottoms and on 

rolling hills. The sites are dominated by tussocks ranging in height up to 8 inches 

with water sometimes in the hollows. The tussocks overlay silt or sand. Permafrost 

was encountered at 7 inches at one site, and bedrock was reached at 12 inches on 

another. 

Betula glandulosa/Carex aquatilis plant association 

Resin birch/water sedge 

4 sites 

Vegetation. This plant association is dominated by Betula glandulosa (resin birch) or 

Betula nana (dwarf arctic birch) and at least 25% cover of Carex aquatilis (water 

sedge). Other species include Vaccinium uliginosum (bog blueberry), Salix planifolia 

subspecies pulchra (diamondleaf willow), Ledum palustre (Labrador tea), 

Andromeda polifolia (bog rosemary), Calamagrostis canadensis (bluejoint grass) and 

Sphagnum (peat moss) species. The plant association often grades into herbaceous 

and low shrub landcover classes. Its distribution is not clear, but appears to be more 

common in the south half of GAAR on moist to wet valley sites. 

Betula glandulosa/Eriophorum russeolum plant association 

Resin birch/russett cottongrass 

2 sites 

Vegetation. This plant association is dominated by Betula glandulosa (resin birch) or 

Betula nana (dwarf arctic birch) with at least 25% cover of Eriophorum russeolum

(russett cottongrass). Other species include Picea mariana (black spruce), Potentilla 

fruticosa (shrubby cinquefoil), Vaccinium uliginosum (bog blueberry), Ledum 

palustre subspecies groenlandicum (Labrador tea), Carex vaginata, Carex bigelowii

(Bigelow sedge), and Hylocomium splendens (feather moss). Moss and lichen cover 

are both less than 20%. The plant association is similar to the Betula 

glandulosa/Carex bigelowii plant association. 

Environmental characteristics. The distribution of the plant association is not clear. 

Slopes range up to 50 in moist-wet valley bottoms and on rolling hills. Tussocks 

dominate the sites and overlay peat up to 1 foot deep over silt or sand. Permafrost 

was encountered at 12 and 20 inches. 

Vaccinium uliginosum-Ledum palustre/Carex bigelowii plant association 

Bog blueberry-Labrador tea/Bigelow sedge 

9 sites 
146 

Vaccinium uliginosum (bog blueberry) in combination with Ledum palustre

(primarily subspecies decumbens [narrow-leaf Labrador-tea]) dominates the shrub 

layer, and Carex bigelowii (Bigelow sedge) dominates the herbaceous layer with at 

least 25% cover. Associate species include Betula glandulosa (resin birch), 

Empetrum nigrum (crowberry), Vaccinium vitis-idaea (low bush cranberry), 

Eriophorum vaginatum and Hylocomium splendens (feather moss). The distribution 

of the plant association is not clear but is likely more common in the south half of 

GAAR. The composition, structure and physical characteristics of the Vaccinium 

uliginosum-Ledum palustre/Carex bigelowii plant association are similar to the 

Betula glandulosa/Carex bigelowii plant association, the primary difference being 

Betula glandulosa (resin birch) is not the dominant shrub. 

Vaccinium uliginosum-Ledum palustre/Eriophorum russeolum plant association 

Bog blueberry-Labrador tea/russett cottongrass 

2 sites 

Vaccinium uliginosum (bog blueberry) in combination with Ledum palustre

(primarily subspecies decumbens, narrow-leaf Labrador-tea) dominates the shrub 

layer, and Eriophorum russeolum (russett cottongrass) dominates the herbaceous 

layer with at least 25% cover. Associate species include Picea glauca (white spruce), 

Betula glandulosa (resin birch), Arctostaphylos alpina (alpine bearberry), Carex 

bigelowii (Bigelow sedge) and Hylocomium splendens (feather moss). The plant 

association’s distribution in GAAR is not clear. The composition, structure and 

physical characteristics of the Vaccinium uliginosum-Ledum palustre/Eriophorum 

russeolum plant association are similar to the Betula glandulosa/Eriophorum 

russeolum plant association, the primary difference being Betula glandulosa (resin 

birch) is not the dominant shrub. Tussocks dominate the sites and overlay peat up to 

1 foot deep over silt or sand. 

Vaccinium uliginosum-Ledum palustre/Eriophorum vaginatum plant association 

Bog blueberry-Labrador tea/tussock cottongrass 

1 site 

Vaccinium uliginosum (bog blueberry) in combination with Ledum palustre

(primarily subspecies decumbens [narrow-leaf Labrador-tea]) dominates the shrub 

layer, and Eriophorum vaginatum (tussock cottongrass) dominates the herbaceous 

layer with at least 25% cover. Associate species include Betula glandulosa (resin 

birch), Salix planifolia subspecies pulchra (diamondleaf willow), Carex bigelowii

(Bigelow sedge) and Sphagnum (peat moss). The plant association appears to be 

common in the south half of GAAR. The composition, structure and physical 

characteristics of the plant association are similar to that of the Vaccinium 

uliginosum-Ledum palustre/Eriophorum russeolum plant association, the principal 

difference being that Eriophorum vaginatum (tussock cottongrass) is the dominant 

herbaceous species. 
147 

Salix lanata subspecies richardsonii/Carex bigelowii plant association 

Richardson willow/Bigelow sedge 

1 site 

Figure 51. Salix lanata subspecies richardsonii/Carex bigelowii plant association 

Vegetation. This plant association is dominated by Salix lanata subspecies 

richardsonii (Richardson willow) with at least 25% cover, and at least 25% cover of 

Carex bigelowii (Bigelow sedge; Figure 51). Salix lanata subspecies richardsonii is 

approximately 16 inches in height. Other species include Vaccinium uliginosum (bog 

blueberry), Salix reticulata (netleaf willow), Equisetum arvense (common horsetail), 

Arctostaphylos rubra (red-fruit bearberry), and Eriophorum vaginatum (tussock 

cottongrass). Moss cover is high. The plant association often grades into various 

prostrate shrub landcover classes and plant associations such as Betula 

glandulosa/Carex bigelowii. 

Environmental characteristics. This is an incidental plant association occurring on 

moderate slopes in moist-wet valley bottoms and on rolling hills. Its distribution is 

not clear, but occurs in areas dominated by tussock tundra on the north half of 

GAAR. The tussocks range in height up to 8 inches with water sometimes in the 

hollows. The tussocks overlay peat over silt or sand. Bedrock was reached at 18 

inches and the pH of the peat was 6.2. 
148 

Salix planifolia subspecies pulchra/Carex bigelowii plant association 

Diamondleaf willow/Bigelow sedge 

3 sites 

Figure 52. Salix planifolia subspecies pulchra/Carex bigelowii plant association

Vegetation. This plant association is dominated by Salix planifolia subspecies

pulchra (diamondleaf willow) with at least 25% cover, and at least 25% cover of 

Carex bigelowii (Bigelow sedge; Figure 52). Other shrub species include Betula 

nana (dwarf arctic birch), Ledum palustre subspecies decumbens (narrow leaf 

Labrador tea) and Salix reticulata (netleaf willow). Eriophorum russeolum (russett 

cottongrass) and Eriophorum vaginatum (tussock cottongrass) are often codominant 

tussock forming species, and other herbaceous species include Pedicularis lanata and 

Hierochloe alpina (alpine holy grass). Moss cover ranges up to 60% and includes 

Hylocomium splendens (feather moss) and Sphagnum (peat moss) species. The plant 

association often grades into prostrate shrub landcover classes and plant associations 

such as Betula glandulosa/Carex bigelowii. 

Environmental characteristics. This is a common type in areas dominated by tussock 

tundra on the north half of GAAR. It occurs on moderate slopes—up to 100

—in 

moist-wet valley bottoms and at the base of hills and mountains. The sites are 

dominated by tussocks ranging in height up to 8 inches with water sometimes in the 

hollows. The tussocks overlay peat up to 10 inches thick over silt or sand. 
149 

Permafrost was reached at 7 to 12 inches deep, and the pH of the peat ranged from 

4.7 to 6.3. The water table was at the soil surface to 9 inches below the soil surface. 

Salix planifolia subspecies pulchra/Eriophorum russeolum plant association 

Diamondleaf willow/russett cottongrass 

1 site 

Figure 53. Salix planifolia subspecies pulchra/Carex aquatilis plant association 

Vegetation. This plant association is dominated by Salix planifolia subspecies

pulchra (diamondleaf willow) with at least 25% cover, and at least 25% cover of 

Eriophorum russeolum (russett cottongrass). Other shrub species include Betula 

nana (dwarf arctic birch), Ledum palustre subspecies decumbens (narrow leaf 

Labrador tea) and Vaccinium uliginosum (bog blueberry). Other herbaceous species 

include Carex bigelowii (Bigelow sedge) and Saxifraga nelsoniana. Moss cover 

ranges up to 40% and includes Sphagnum (peat moss) species. The plant association 

often grades into prostrate shrub landcover classes and plant associations such as 

Betula glandulosa/Carex bigelowii. 

Environmental characteristics. The distribution of the plant association is not clear, 

but it is likely a common type in areas dominated by tussock tundra in the north half 

of GAAR. It occurs on moderate slopes—up to 100

—in moist-wet valley bottoms 

and on hillsides. The sites are dominated by tussocks ranging in height up to 10 

inches with water sometimes in the hollows. The tussocks overlay peat over silt or 

sand. Permafrost was reached at 6 inches deep, and the pH of the peat was 5.3. 
150 

Salix planifolia subspecies pulchra/Carex aquatilis plant association 

Diamondleaf willow/water sedge 

1 site 

Vegetation. This plant association is dominated by Salix planifolia subspecies

pulchra (diamondleaf willow) with at least 25% cover, and at least 25% cover of 

Carex aquatilis (water sedge; Figure 53). Other shrub species include Betula nana

(dwarf arctic birch), Ledum palustre subspecies decumbens (narrow leaf Labrador 

tea), Empetrum nigrum (crowberry), Vaccinium uliginosum (bog blueberry) and Salix 

fuscescens. Other herbaceous species include Bistorta vivipara, Potentilla palustris

(marsh fivefinger) and Pedicularis lanata. Moss cover was 40% and included 

Sphagnum (peat moss) species. The plant association often grades into pure sites of 

Carex aquatilis (water sedge) and low shrub plant associations such as Betula 

glandulosa/Carex bigelowii. 

Environmental characteristics. The distribution of the plant association is not clear, 

but it is likely a common type in areas dominated by tussock tundra on the north half 

of GAAR. It occurs on level areas in moist-wet valley bottoms. The sites are 

dominated by poorly formed tussocks of Carex aquatilis (water sedge) ranging in 

height up to 8 inches with water sometimes in the hollows. The tussocks overlay peat 

over silt or sand. Permafrost was reached at 20 inches in depth. 

SHRUB BIRCH-ERICACEOUS-WILLOW PLANT ASSOCIATIONS 

Vaccinium uliginosum-Ledum palustre/Sphagnum plant association 

Bog blueberry-Labrador tea/peat moss 

1 site 

Vaccinium uliginosum (bog blueberry) in combination with Ledum palustre

(primarily subspecies decumbens) dominates the shrub layer, and Sphagnum (peat 

moss) species dominate the bryophyte layer with at least 35% cover. Associate 

species include Empetrum nigrum (crowberry), Vaccinium vitis-idaea (low bush 

cranberry), Betula glandulosa (resin birch), Salix planifolia subspecies pulchra 

(diamondleaf willow), Eriophorum vaginatum (tussock cottongrass), and Carex 

bigelowii (Bigelow sedge). The plant association appears to be common in the south 

half of GAAR. 

Vaccinium uliginosum-Ledum palustre plant association 

Bog blueberry-Labrador tea 

7 sites 

Vaccinium uliginosum (bog blueberry) in combination with Ledum palustre

(primarily subspecies decumbens) dominates the plant association. Associate species 

include Betula glandulosa (resin birch), Vaccinium vitis-idaea (low bush cranberry), 
151 

Empetrum nigrum (crowberry) and Carex bigelowii (Bigelow sedge). Moss species 

dominate the understory and include Pleurozium schreberi, Polytrichum commune

and Hylocomium splendens (feather moss). The plant association often grades into 

various prostrate shrub (upslope), low shrub and tall shrub (downslope) landcover 

classes. The plant association may be common in the Kobuk Boot region of GAAR. 

The composition, structure and physical characteristics of the Vaccinium uliginosumLedum palustre plant association are similar to the Betula glandulosa plant 

association, the primary difference being Betula glandulosa is not the dominant 

shrub. 

Betula glandulosa plant association 

Resin birch 

7 sites 

Figure 54. Betula Glandulosa plant association 

Vegetation. Betula glandulosa or Betula nana dominate the plant association and no 

codominants occur (Figure 54). Associate species include Salix planifolia subspecies

pulchra (diamondleaf willow), Salix phlebophylla (skeletonleaf willow), Vaccinium 

vitis-idaea (low bush cranberry), Vaccinium uliginosum (bog blueberry), Empetrum 

nigrum (crowberry), Dryas octopetala (white mountain avens), Rhododendron 

lapponicum (lapland rosebay) and Hierochloe alpina (alpine holy grass). Moss and 

fruticose lichen cover range up to 20 and 40%, respectively. This plant association 

often grades into various prostrate shrub (upslope), low shrub and tall shrub 

(downslope) landcover classes. 

Environmental characteristics. This is a major type located throughout GAAR on 
152 

stable surfaces on mountain slopes, rounded mountain ridges (exposed bedrock), hill 

tops, and the river-side edge of river and stream terraces—terrace edges tend to be 

drier than sites further removed from the river. The Betula glandulosa plant 

association is common on slopes ranging from 00 to 450. The soils are a thin layer of 

dry to dry-mesic organic matter—up to 10 inches thick—over silt, sand and rocks. 

Permafrost is typically deep (10+ inches), and pH varies from 4.9 to 5.9 (one site with 

a pH of 8.0). 

Lichen-Betula glandulosa plant association 

Lichen-resin birch 

10 sites 

 Figure 55. Lichen-Betula Glandulosa plant association 

Vegetation. This plant association is dominated by Betula glandulosa (resin birch) or 

Betula nana (dwarf arctic birch) with at least 25% cover, and an understory of greater 

than 40% fruticose lichen (Figure 55). Other shrub species may have high cover 

including Ledum palustre subspecies decumbens (narrow leaf Labrador tea), 

Vaccinium uliginosum (bog blueberry), Vaccinium vitis-idaea (low bush cranberry), 

Loiseleuria procumbens (alpine azalea) and Empetrum nigrum (crowberry). 

Fruticose lichens include Cladina rangiferina, Cladina stellaris, Cetraria islandica,

and other Cetraria species. This plant association often grades into spruce-lichen 

woodland, and prostrate shrub map classes and various low shrub and tall shrub 

classes. 

 

Environmental characteristics. This is a major plant association located on the south 
153 

half of GAAR on relatively stable surfaces in mountain valleys, mountain slopes, 

rounded mountain ridges (exposed bedrock) and alluvial fans. Slopes range from 00

to 300. The soils are sand and sand mixed with cobble, and a thin peat layer may 

occur. The pH varies from 4.7 to 5.0. 

Salix planifolia subspecies pulchra (open) plant association 

Diamondleaf willow (open) 

3 sites 

Figure 56. Salix planifolia subspecies pulchra (open) plant association 

Vegetation. Salix planifolia subspecies pulchra (diamondleaf willow) dominates or 

codominates the plant association along with Salix glauca (grayleaf willow) or Salix 

alaxensis (feltleaf willow; Figure 56). Associate species include Vaccinium 

uliginosum (bog blueberry), Betula glandulosa (resin birch), Potentilla fruticosa

(shrubby cinquefoil), Bromus pumpellianus, Festuca altaica, Equisetum arvense 

(common horsetail) and Hierochloe alpina (alpine holy grass). Moss cover reaches 

70% dominated by Sphagnum (peat moss) species or Hylocomium splendens (feather 

moss). 

Environmental characteristics. This is a minor plant association found on recently 

deposited floodplain sites located throughout GAAR. The sites are typically level, 

dry to mesic, and subjected to periodic flooding. The soils are a thin layer of dry to 

dry-mesic organic matter over silt, sand and rocks. Permafrost was not encountered. 

The pH varies from 6.6 to 8.8. 
154 

CLOSED LOW WILLOW PLANT ASSOCIATIONS 

Salix planifolia subspecies pulchra (closed) plant association 

Diamondleaf willow (closed) 

7 sites 

Vegetation. Salix planifolia subspecies pulchra (diamondleaf willow) dominates the 

plant association, and no codominants occur although Betula glandulosa and 

Vaccinium uliginosum (bog blueberry) often have high cover values. Associate 

understory species include Equisetum arvense (common horsetail), Equisetum 

pratense, Eriophorum angustifolium (tall cottongrass), Petasites frigidus (frigid 

coltsfoot) and Salix reticulata (netleaf willow). Moss cover reaches 90% and is 

dominated by Sphagnum (peat moss) species and Hylocomium splendens (feather 

moss). 

 

Environmental characteristics. This is a common type located in the north half of 

GAAR. It is found on the edge of small streams, and on water tracks found on 

tussock tundra hillsides. Many of the small streams have terrace formation. The 

streams and water tracks occur on slopes ranging from 00

 to 100. Hummocks often 

form due to the presence of Eriophorum angustifolium (tall cottongrass) and Carex 

aquatilis (water sedge). The tussocks overlay a thin (0 to 9 inches) layer of peat over 

silt, sand and rocks. Permafrost is common, often at less than 10 inches deep. The 

soil pH varies from 5.4 to 7.0. 

PROSTRATE SHRUB-ROCK PLANT ASSOCIATION 

Dryas octopetala-rock plant association 

White mountain avens-rock 

6 sites 

Vegetation. This plant association is characterized by prostrate shrubs and 25 to 75% 

cover of rocks typically 0.5 to 8 inches in size that are often covered with crustose 

lichen (Figure 57). Dryas octopetala subspecies alaskensis (white mountain avens) 

dominates the plant association and no codominants occur. Other species include 

Arctostaphylos alpina (alpine bearberry), Salix phlebophylla (skeletonleaf willow), 

Loiseleuria procumbens (alpine azalea), Carex scirpoidea, Carex microchaeta, 

Minuartia arctica and Epilobium latifolium (fireweed). Moss and fruticose lichen 

cover ranges from 1 to 40%. The plant association often grades into the sparse 

vegetation landcover class and, on more stable sites, the prostrate shrub-lichen, and 

prostrate shrub landcover classes. 
155 

 Figure 57. Dryas octopetala-rock plant association 

Environmental characteristics. This is a major type located throughout GAAR on 

unstable surfaces such as talus slopes, slopes below bedrock outcrops, fellfield, frost 

boils on river terraces, areas of intense frost action in high mountain valley floors, 

rounded mountain ridges (exposed bedrock) with intense frost action, and sorted 

patterned ground. Slopes range from 00

 to 500. The soils are a thin layer of dry to 

mesic sand, litter or organic mat interspersed with exposed rock. The pH varies from 

5.8 to 7.9. 
156 

PROSTRATE SHRUB-LICHEN PLANT ASSOCIATIONS 

Vaccinium uliginosum/fruticose lichen plant association 

Bog blueberry/fruticose lichen 

5 sites 

 Figure 58. Vaccinium uliginosum/fructicose lichen plant association 

Vegetation. Fruticose lichen in combination with greater than 25% prostrate shrub 

cover dominate this plant association (Figure 58). Shrub species include various 

combinations of Vaccinium uliginosum (bog blueberry), Vaccinium vitis-idaea (low 

bush cranberry), Ledum palustre subspecies decumbens (narrow leaf Labrador tea), 

Betula nana (dwarf arctic birch), Loiseleuria procumbens (alpine azalea), Dryas 

octopetala (white mountain avens) and Arctostaphylos rubra (red-fruit bearberry). 

Lichens include Cladina rangiferina, Stereocaulon species, Cetraria species and

Alectoria species. The plant association often grades into spruce-lichen woodland, 

prostrate shrub, and various low shrub and tall shrub landcover classes. 
157 

 

Environmental characteristics. This is a minor type located primarily in the south 

half of GAAR on relatively stable surfaces in mountain valleys, mountain slopes, 

rounded mountain ridges (exposed bedrock) and alluvial fans. Slopes range from 00

to 250

. The soils are a thin duff layer over dry to mesic silt, sand and cobble. The pH 

varies from 4.0 to 5.9. 

PROSTRATE SHRUB PLANT ASSOCIATIONS 

Dryas octopetala-Carex species plant association 

White mountain avens-sedge species 

5 sites 

Vegetation. This plant association is characterized by at least 25% cover of prostrate 

shrubs and 25% cover of herbaceous vegetation. The dominant prostrate shrubs 

include Dryas octopetala (white mountain avens), Ledum palustre subspecies

decumbens (narrow leaf Labrador tea), Salix arctica (arctic willow), Salix reticulata

(netleaf willow) and Vaccinium uliginosum (bog blueberry). The dominant 

herbaceous species are Carex bigelowii (Bigelow sedge) and Equisetum arvense 

(common horsetail). Other species include Arctostaphylos alpina (alpine bearberry), 

Cassiope tetragona (four-angled cassiope), Salix phlebophylla (skeletonleaf willow) 

and Diapensia lapponica (Lapland diapensia). Moss and lichen cover ranges from 5 

to 30%. The plant association often grades into the prostrate shrub landcover class, 

or low shrub landcover classes. 

Environmental characteristics. This is a minor type located throughout GAAR on 

unstable to stable surfaces such as mountain slopes, high mountain valley floors, 

rounded mountain ridges (exposed bedrock), and sorted patterned ground. Slopes 

range from 00

 to 100. The soils are a thin layer of dry to mesic sand, litter or organic 

mat interspersed with exposed rock. 

Dryas octopetala-Cassiope tetragona plant association 

White mountain avens–four angled cassiope 

10 sites 

Vegetation. This plant association is characterized by Dryas octopetala (white 

mountain avens) in combination with other prostrate shrub species, and less than 25% 

cover of herbaceous species (Figure 59). Various combinations of Cassiope 

tetragona (four-angled cassiope), Dryas octopetala (white mountain avens), Salix 

arctica (arctic willow), Salix reticulata (netleaf willow), Salix rotundifolia, 

Arctostaphylos rubra (red-fruit bearberry), Vaccinium uliginosum (bog blueberry), 

Diapensia lapponica (Lapland diapensia) and Empetrum nigrum (crowberry) 

dominate the type. Other species include Carex bigelowii (Bigelow sedge), Carex 

scirpoidea, Carex misandra and Equisetum arvense (common horsetail). Moss cover 

ranges from 2 to 50%. The plant association often grades into various prostrate shrub 
158 

and low shrub landcover classes. 

Environmental characteristics. This is a minor plant association located primarily on 

the north half of the Brooks Range and in the Noatak River Valley. It typically 

occurs as small patches on northerly facing hillside and mountain slopes. These 

slopes are often unstable with significant exposed rock. Slopes range from 150

 to 550. 

 The soils are a thin layer of peat (1 to 6 inches) over silt, sand or rock. Tussock 

formation is uncommon. Most sites are dry to mesic, and a minority of sites had 

water tables between 4 and 18 inches deep. The pH varies from 4.4 to 6.8. 

Figure 59. Dryas octopetala-Cassiope tetragona plant association 
159 

Dryas octopetala plant association 

White mountain avens 

4 sites 

Figure 60. Dryas Octopetala plant association 

Vegetation. Dryas octopetala (white mountain avens) dominates the plant 

association and no codominants occur (Figure 60). Other species include Salix 

planifolia subspecies pulchra (diamondleaf willow), Salix reticulata (netleaf willow) 

and Epilobium latifolium (fireweed). Moss and fruticose lichen cover ranges from 10 

to 20%. It is similar to the Dryas octopetala-rock type but with less exposed rock. 

The plant association often grades into the sparse vegetation landcover class and, on 

more stable sites, the prostrate shrub-lichen landcover class and other low shrub and 

tall shrub landcover classes. 

 

Environmental characteristics. This is a major plant association located throughout 

GAAR on unstable to stable surfaces such as mountain slopes, high mountain valley 

floors, rounded mountain ridges (exposed bedrock), the river-side edge of river 

terraces, and sorted patterned ground. Slopes range from 00

 to 300. The soils are a 

thin layer of dry to mesic sand, litter or organic mat interspersed with exposed rock. 

The pH varies from 4.7 to 6.9. 
160 

Dryas integrifolia plant association 

Entire-leaf mountain avens 

2 sites 

Vegetation. The Dryas integrifolia (entire-leaf mountain-avens) plant association is 

characterized by Dryas integrifolia in combination with other prostrate shrub species 

including Vaccinium uliginosum (bog blueberry), Arctostaphylos rubra (red-fruit 

bearberry), Salix arctica (arctic willow), Cassiope tetragona (four-angled cassiope)

and Salix reticulata (netleaf willow). Herbaceous species are common—greater than 

25% cover—and include Carex scirpoidea, Carex filifolia, Carex membranacea, 

Equisetum arvense (common horsetail) and Eriophorum russeolum (russett 

cottongrass). Moss cover ranges up to 10%. The plant association often grades into 

various herbaceous, prostrate shrub and low shrub landcover classes. 

 

Environmental characteristics. This is an incidental plant association located 

primarily on the north half of the Brooks Range. It typically occurs as small patches 

or strips on patterned ground. Slopes range from 00

 to 20. The soils are a thin layer 

of peat (1 to 2 inches) over silt, sand or gravel. Most sites are mesic and tussocks 

occur on the moister sites. No permafrost was encountered to 2 feet. 

Salix reticulata plant association 

Netleaf willow 

1 site 

Figure 61. Salix Reticulata plant association 
161 

Vegetation. Salix reticulata (netleaf willow) dominates the plant association and no 

codominants occur (Figure 61). Other species include Salix arctica (arctic willow), 

Dryas octopetala (white mountain avens), Salix planifolia subspecies pulchra

(diamondleaf willow) and Carex capillaris. Moss cover is 30% and bare-ground is 

common. 

 

Environmental characteristics. The distribution of the plant association is not clear 

but appears to be an incidental type throughout GAAR on newly colonized floodplain 

deposits. The soils are a thin layer of moss over sand and silt, and no horizon 

development was evident. The pH is 6.8. 

MESIC HERBACEOUS PLANT ASSOCIATIONS 

Calamagrostis canadensis plant association 

Bluejoint 

1 site 

Vegetation. Calamagrostis canadensis (bluejoint grass) dominates the plant 

association (63% cover), and ranges up to 5 feet in height. Other vegetation includes 

minor cover of Carex and Salix planifolia subspecies pulchra (diamondleaf willow), 

and bryophyte cover at 88%. 

Environmental characteristics. This is an incidental plant association found on moist 

sites on the south edge of the Brooks Range. 

Carex bigelowii plant association 

Bigelow sedge 

1 site 

Vegetation. The Carex bigelowii (Bigelow sedge) plant association is dominated by 

tussocks of Carex bigelowii (Figure 62). Salix lanata subspecies richardsonii

(Richardson willow), Vaccinium uliginosum (bog blueberry) and other low shrubs are 

present. The tussocks are approximately 12 inches tall with water, litter or moss 

often in the hollows. Height of Carex bigelowii is 6 inches. 

Environmental characteristics. The distribution and patch size of the plant 

association is unclear. It probably is common on the north side of GAAR and in the 

Noatak Valley where tussock tundra dominates. The site sampled was on a colluvial 

slope (200

). During spring runoff and periods of high summer precipitation the sites 

are relatively wet with water often occupying the hollows. It may be mesic during 

drier periods and as the soil active layer increases in depth allowing better drainage. 

The hummocks rest on organic matter, rock or mineral soil. The pH is 6.7. 
162 

Figure 62. Carex Bigelowii plant association 

Carex lugens plant association 

1 site 

Vegetation. Carex lugens is the dominant species and Salix reticulata (netleaf 

willow), Eriophorum vaginatum (tussock cottongrass) and Vaccinium uliginosum 

(bog blueberry) are common associates. Hylocomium splendens (feather moss) 

carpets the ground layer. Tussock formation (30%) was less common than in other 

mesic herbaceous types. 

Environmental characteristics. The distribution and patch size of the plant 

association is unclear. It probably is common on the north side of GAAR and in the 

Noatak Valley where tussock tundra dominates. The site sampled was on a 50 

colluvial slope. During spring runoff and periods of high summer precipitation the 

sites are relatively wet with water often occupying the hollows. It may be mesic 

during drier periods and as the soil active layer increases in depth allowing better 

drainage. 

Carex membranacea plant association 

Fragile sedge plant association 

2 sites 

Vegetation. Sites are dominated by tussocks of Carex membranacea (fragile sedge; 
163 

Figure 63). Dryas integrifolia (entire-leaf mountain-avens), Arctostaphylos rubra

(red-fruit bearberry) and Vaccinium uliginosum (bog blueberry) are also commonly 

present. The tussocks range up to 8 inches tall with water, litter or moss often in the 

hollows. Height of Carex membranacea is 6 inches. 

Environmental characteristics. The distribution and patch size of the plant 

association is unclear. It probably is common on the north side of GAAR and in the 

Noatak Valley where tussock tundra dominates. The sites sampled are on glacial drift 

covered slopes (180

) and floodplain surfaces. During spring runoff and periods of 

high summer precipitation they are relatively wet with water often occupying the 

hollows. It may be mesic during drier periods and as the soil active layer increases in 

depth allowing better drainage. The hummocks rest on organic matter 2 to 12 inches 

deep over sand. Permafrost is at 8 to 14 inches, and pH ranges from 7.1 to 7.2. 

Figure 63. Carex Membrancea plant association 

Eriophorum russeolum plant association 

Russett cottongrass 

2 sites 

Vegetation. Sites are dominated by tussocks of Eriophorum russeolum (russett 

cottongrass; Figure 64). Vaccinium uliginosum (bog blueberry) and Carex aquatilis 

(water sedge) are often strong codominants. The tussocks range up to 12 inches tall 

with water, litter or moss commonly in the hollows. Height of Eriophorum 

russeolum averages 1 foot. 
164 

Environmental characteristics. The plant association is common on the north side of 

the Brooks Range and in the Noatak River valley. It occurs as large contiguous 

patches that often grade into the shrub birch-willow-tussock tundra landcover class. 

During spring runoff and periods of high summer precipitation the sites are relatively 

wet with water often occupying the hollows. It is mesic during drier periods and as 

the soil active layer increases in depth allowing better drainage. Slopes ranged from 

00 to100. The hummocks rest on organic matter or mineral soil that is often saturated. 

 The one pH value recorded was 6.4. 

Figure 64. Eriophorum Russeolum plant association 

Eriophorum vaginatum plant association 

Tussock cottongrass 

3 sites 

Vegetation. Sites are dominated by tussocks of Eriophorum vaginatum (tussock 

cottongrass). Low shrubs are typically strongly represented including Ledum 

palustre (Labrador tea), Vaccinium uliginosum (bog blueberry) and Betula nana

(dwarf arctic birch). Sphagnum (peat moss) species and Polytrichum species are 

common mosses. 

Environmental characteristics. The distribution and patch size of the plant 

association is unclear. It probably is common on the north side of GAAR and in the 
165 

Noatak Valley where tussock tundra dominates. The sites sampled were below 1,000 

feet in elevation. 

WET HERBACEOUS PLANT ASSOCIATIONS 

Arctophila fulva plant association 

Pendent grass 

3 sites 

Figure 65. Arctophilia Fulva plant association 

Vegetation. Arctophila fulva (pendent grass) dominates the plant association, and no 

codominants were observed (Figure 65). Arctophila fulva height reaches 2 feet, 

however, it is often prostrate and less than 8 inches in height. The only other 

emergent species recorded was Hippuris vulgaris (mare’s tail). 

Environmental characteristics. This is a minor type located on sites with permanent 

to semi-permanent standing water such as the edge of ponds, lakes, sloughs, streams 

and even dune slacks. Water depth varies depending on flooding and precipitation, 

ranging up to 18 inches above the soil surface. The soils are typically silt or sand 

with no horizon development. The one pH value recorded was 6.7. 

Carex aquatilis plant association 

Water sedge 

3 sites 
166 

Vegetation. Carex aquatilis (water sedge) dominates the plant association, and no 

codominants occur (Figure 66). Species diversity varies from nearly pure Carex 

aquatilis to sites with a variety of low and prostrate shrubs, graminoids and forbs. 

These include Salix planifolia subspecies pulchra (diamondleaf willow), Salix 

reticulata (netleaf willow), Betula glandulosa (resin birch), Potentilla palustris

(marsh fivefinger), Menyanthes trifoliata (buckbean), Eriophorum angustifolium (tall 

cottongrass) and Carex lugens. Sites with greater species diversity typically have 

tussock formation. Moss cover increases on drier sites. 

Environmental characteristics. This is a major type located throughout GAAR on 

relatively level sites with permanent to semi-permanent standing water. These 

include low centered polygons, saturated river terraces, the edge of ponds, lakes, 

sloughs, streams and dune slacks (sampled at the mouth of the Killik River), and even 

water tracks on hillsides on the north slope of the Brooks Range. Water depth varies 

depending on flooding and precipitation, ranging up to 6 inches above the soil surface 

to 10 inches below. Approximately 50% of the sample sites are dominated by 

tussocks ranging up to 10 inches in height. The soils are typically organic matter and 

roots 1 to 20 inches over sand, silt and rock. Some sites have permafrost near the 

surface (8+ inches deep). The pH varies from 5.8 to 6.3. 

Figure 66. Carex Aquatilis plant association 

Carex aquatilis/Sphagnum species plant association 

Water sedge/peat moss species 

2 sites 
167 

Vegetation. Carex aquatilis (water sedge) dominates the sites, often with high 

canopy cover of Eriophorum species, Potentilla palustris (marsh fivefinger) and 

Equisetum fluviatile (swamp horsetail). Sphagnum (peat moss) species are diagnostic 

in the moss layer. 

Environmental characteristics. This plant association is found in the south half of 

GAAR in small patches. It is typically located on sites with permanent to semipermanent standing water such as peatlands or as floating mats in shallow ponds. 

Carex limosa plant association 

Shore sedge 

3 sites 

Vegetation. Sites are dominated by Carex limosa (shore sedge) and Sphagnum (peat 

moss). Eriophorum russeolum (russett cottongrass) was also common. 

Environmental characteristics. The distribution and patch size of the plant 

association is unclear. It probably is common on the south side of GAAR where 

peatlands are common. 

Carex rostrata plant association 

Beaked sedge 

1 site 

Vegetation. Carex rostrata (beaked sedge) codominates with Equisetum fluviatile 

(swamp horsetail)in the site sampled. 

Environmental characteristics. The site sampled was in the Kobuk Boot region on a 

floodplain, however, the distribution and patch size of the plant association is unclear. 
168 

Carex saxatilis plant association 

1 site 

Vegetation. Carex saxatilis dominates the plant association (Figure 67). Other 

species that occur include Eriophorum angustifolium (tall cottongrass) and Salix 

planifolia subspecies pulchra (diamondleaf willow). 

Environmental characteristics. The distribution and patch size of the plant 

association is unclear. It probably is more common on the north side of GAAR and 

in the Noatak Valley where tussock tundra dominates. It is typically located on sites 

with permanent to semi-permanent standing water, such as the edge of ponds, lakes, 

and sloughs. 

Figure 67. Carex Saxatilis plant association 
169 

Eriophorum angustifolium subspecies subarcticum plant association 

Tall cottongrass 

2 sites 

Vegetation. Eriophorum angustifolium subspecies subarcticum (tall cottongrass) 

dominates the sites, often with high canopy cover of Carex podocarpa, Eriophorum 

russeolum (russett cottongrass) and Equisetum fluviatile (swamp horsetail; Figure 

68). Shrubs have low cover values and include Salix reticulata (netleaf willow), 

Salix planifolia subspecies pulchra (diamondleaf willow) and Betula glandulosa 

(resin birch). Tussock formation was minor. 

Environmental characteristics. This plant association is found throughout GAAR in 

small patches. It is typically located on sites with permanent to semi-permanent 

standing water such as pond and lake edges, patterned fens and sloughs. Water depth 

ranges from 1 inch below the surface to 8 inches above and varies depending on 

flooding, runoff, active layer depth and precipitation. Permafrost was encountered at 

one site at 10 inches. Acidity ranges from 6.2 to 6.5. 

 Figure 68. Eriophorum Angustifolium plant association 
170 

Equisetum fluviatile plant association 

Swamp Horsetail 

1 site 

Vegetation. Equisetum fluviatile (swamp horsetail) dominates the plant association 

but typically has low cover. Potentilla palustris (marsh fivefinger) and Carex 

aquatilis (water sedge) may be found as codominants. Equisetum fluviatile often 

reaches 2 feet in height. 

Environmental characteristics. The Equisetum fluviatile (swamp horsetail)plant 

association is found throughout GAAR in small patches. It is typically located on 

sites with permanent to semi-permanent standing water, such as the edge of ponds, 

lakes, and sloughs. Water depth was 8 inches and varies depending on flooding and 

precipitation. 
171 

3.8 SURFICIAL GEOLOGY INFLUENCES ON LANDCOVER 

Surficial geology units—as defined and mapped by Hamilton (1999c)—were 

considered in developing the classification system because some units strongly affect 

the distribution and pattern of landcover on a time and space scale pertinent to the 

products being produced. For example, the floodplain surficial geology unit is 

strongly influences the type of vegetation and the pattern of landcover classes on 

floodplains exist at a spatial scale that can be recognized using Landsat imagery. 

This is not to imply that all surficial geology units delineated by Hamilton (1999c) 

strongly influence or reflect vegetation distribution. 

However, in order to link the surficial geology units to landcover classes the units 

needed to be aggregated. For example, the aggregated unit termed floodplain is 

actually a combination of the alluvium, undifferentiated, modern alluvium, low 

alluvial-terrace deposits, alluvium, sand facies, and neoglacial outwash surficial units. 

 This aggregated unit of floodplain is a better reflection of vegetation than each of its 

individual components. This aggregated surficial geology data layer included in the 

Interactive Map and the GAAR Landcover ArcView 3.1 product (Table1). 

The aggregated surficial geology units are described below, and a list of the original 

and aggregated units is given in Appendix 3. Several surficial geology units and 

landforms that are described in this report but not defined by Hamilton (1999c) 

include patterned ground (sorted polygons, frost boils and ice wedge polygons), 

thermokarst, water tract, and frost scar. They reflect previously described Alaskan 

landscapes (Davidson 1996, Walker and Webber 1979, Krieg and Reger 1982, 

Embleton and King 1975). 

Bedrock 

Bedrock occurs at higher elevations and includes all the jagged rocky ridges, peaks, 

cirque headwalls and cirque basins in the Brooks Range (Figure 69, 44 and the 

landcover map). Bedrock has little or no soil development, and colluvium, alluvial 

fans and glacial drift all occur downslope. Glaciation has shaped and exposed the 

bedrock, although presently only small headwater glaciers exist in GAAR. Frost 

action and weathering continue to fracture rock, causing continued rock fall and 

erosional landforms such as altiplanation terraces (mountain terraces), scarps, cliffs, 

and tors. Most precipitation runs off the surface because of shallow soils or a lack of 

soils, and relatively steep slopes. Bedrock was the only surficial geology unit from 

Hamilton (1999c) used to delineate this type, and covers 58% of GAAR’s landmass 

(Appendix 6). 
172 

Figure 69. Landsat image of bedrock showing covering of prostrate shrub 

[Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Bedrock vegetation. Vegetation is generally absent in the higher elevations or is 

sparse due to the harsh climatic conditions, and shallow or no soils (see the landcover 

map). On stable areas the vegetation often forms continuous mats of low growing 

vegetation (lichen, prostrate shrub), and, moving downslope, shrubs and trees occur. 

For all bedrock in GAAR, forests cover 11.7%, tall or low shrubs 24.0%, prostrate 

shrubs 29.8%, herbaceous vegetation 4.7%, and bare-ground, sparsely vegetated and 

water 24.7%, and mosaic/patterned vegetation and shadow indeterminate 5.0% 

(Table 13). 
173 

Colluvium

Colluvial deposits are unconsolidated surface materials that have been transported 

downslope and deposited on the lower slopes (Figures 70 and 71). Colluvium is 

moved by landslides, flow slides, talus rubble, rock-glaciers, solifluction and 

unconsolidated runoff. Solifluction and rock-glaciers are described below. It covers 

6.8% of the land within GAAR (Appendix 6). 
174 

Figure 70. Landsat image of colluvial slope in arctic foothills ecoregion 

[Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 71. Colluvial slope in the arctic foothills ecoregion 
175 

Figure 72. Solifluction Lobes 

Solifluction. Solifluction (or gelifluction) is the flow of soil in association with 

frozen ground, and is a type of colluvium (Ritter 1986; Figure 72). During the spring 

and summer thaw, water in the active layer cannot penetrate below the permafrost 

table. Soils are often saturated, and the loss of friction and cohesion causes them to 

behave like viscous fluids. The soil thus slowly ‘flows.’ The downslope fronts of the 

solifluction lobes are marked by near-vertical scarps as high as six feet (Figure 73). 

This form of mass wasting commonly occurs on slopes between 50 and 200. Steeper 

slopes tend to drain off excess water. Silty soils are the most susceptible to 

solifluction, whereas gravelly and sandy soils are so permeable and easily drained 

that they rarely flow. Solifluction was commonly observed on various colluvial and 

glacial drift deposits. 
176 

 

 Figure 73. Idealized cross-section of a sollifluction lobe 

In GAAR, it is likely that solifluction deposits are actively forming over a wide area. 

Well-formed lobes are an easily recognizable indication of the process; however, 

solifluction may be active and important at altitudes lower than where such lobes 

occur. We observed stands of willows growing on many of the advancing fronts, and 

prostrate shrubs on the upper portions of the lobes. Occasionally, the upper portions 

were marked by tension cracks in the vegetation and organic soil layer. 

Rock Glacier. Rock glaciers are tongue-shaped or lobate masses of unsorted, angular 

frost-rived material with interstitial ice (Figure 74). They are another type of 

colluvium and a distinctive feature in the high mountains. They typically originate in 

cirques or in high, steep-walled recesses. All the rock glaciers observed were free of 

vegetation. 
177 

Figure 74. Rock glacier in the Brooks Range ecoregion

Colluvium vegetation. For all colluvium in GAAR, forests cover 18.4%, tall or low 

shrubs 31.2%, prostrate shrubs 19.7%, herbaceous vegetation 11.4%, and bare 

ground, sparsely vegetated, and water 15.3% and mosaic/patterned vegetation and 

shadow indeterminate 3.77% (Table 13). 

Alluvial Fans 

Alluvial fans are common throughout the mountainous ecoregion of GAAR, covering 

1.5 of its landmass (Figure 75, Appendix 6). Alluvial fans are an erosionaldepositional system in which rock and sediment are transported down-valley and 

deposited where it emerges from the confines of a narrow valley into a larger valley 

or plain. They tend to be fan-shaped in plan view; a segment of a cone radiating 

away from a single point source. The point of deposition can shift away from the 

mountain front to well down the original fan surface if the stream has become 

entrenched. The stream emerges down-fan and deposits its material forming a new 

fan on top of the older deposits. On an alluvial fan, some areas are actively forming 

whereas other areas are inactive. 
178 

Figure 75. Landsat image of an alluvial fan north of treeline 

[Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Slushflows and flooding in side-canyons can add significant debris to alluvial fans. 

In winter, snow avalanches strip the frost-loosened bedrock from the valley walls and 

deposits it on valley bottoms. Both slushflow and flooding remove this debris and 

deposit it on alluvial fans. Slushflows occur when rapid snowmelt during May and 

June causes wet-snow avalanches that flush the debris out of the canyons onto the 

alluvial fans. Flooding may occur if late summer heavy rains funnel water into steep 

channels. The flooding picks up soil, rocks, and vegetation, and scours out the 

channels. The debris is then deposited in fans at the base of the mountain. 

Fan morphology is relatively consistent. The slope of an alluvial fan decreases as 

you move downfan. Near the mountain front, fans are relatively steep although rarely 

exceeding 100

 (Ritter 1986). They gradually flatten at their lower extremity. The 

steepest gradients are usually associated with coarse-grained materials. The presence 

of boulders strewn across fan surfaces suggests periodic slushflow activity. 

Alluvial fan vegetation. Vegetation reflects the differences in active versus inactive 

fan areas, and different vegetation successional stages are evident. Disturbance 

species—such as willows (Salix species) and alder (Alnus species)—prefer the active 

areas, just as they colonize recently deposited floodplain materials. The inactive 
179 

older deposits tend to reflect the vegetation found on stable surfaces adjacent to the 

fans such as on colluvium and glacial drift. On the south half of GAAR, for example, 

spruce forests are common on both fans and glacial drift (Figure 76, Appendix 4). 

Figure 76. Alluvial fan in the South half of GAAR 

 Some fans have a high cover of the landcover classes prostrate shrub-lichen and 

spruce-lichen woodland. North of treeline, low shrubs and tussock tundra are 

common on fans (Figure 77). Tall shrubs rarely occurred on other surficial geology 

units north of treeline except for floodplains type. For all alluvial fans in GAAR, 

forests cover 23.6%, tall or low shrubs 34.4%, prostrate shrubs 20.7%, herbaceous 

vegetation 11.8%, and bare ground, sparsely vegetated, water, 7.9% and 

mosaic/patterned vegetation and shadow indeterminate 1.7% (Table 13). 
180 

Figure 77. Alluvial fan North of treeline 

Glacial Drift, Terraces, and Sand-Silt Deposits

Glacial drift, terraces and sand-silt deposits were aggregated into a single group. This 

was due to—in general—sharing similar landcover classes and the units were often 

intermixed with each other. 

Glacial Drift. This surficial geology type is somewhat of an agglomeration of 

different deposits that dominate the valley bottoms and mountain sideslopes (Figure 

78). It covers 27% of GAAR (Table 13). Glacial drift is defined as material 

transported by a glacier and then deposited either directly from the ice or from the 

melt water. In GAAR, these deposits are predominantly of late Pleistocene age, 

however, older (Miocene) and younger (Holocene) deposits can be found. Numerous 

types of glacial drift occur including moraines, kettle-kame topography, eskers, 

drumlins, glacial till and outwash. Glacial till is the dominant feature and is formed 

by sediment originating directly from glacial ice and typically has no discernible 

sediment stratification. Inactive glacial outwash is included in this section—active

outwash is placed in the floodplain surficial geology unit. 
181 

 Figure 78. Landsat image of glacial till in the south half of GAAR 

 [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Various processes and other surficial geology types occur on the glacial drift type. 

These include thermokarst, frost scaring, polygonal ground, pingos and water tracks. 

Alluvial fans and colluvial slopes often cover glacial drift, and glacial drift is 

subjected to solifluction—a type of colluvial process. Rivers can also rework glacial 

deposits forming floodplains. 

Terraces. Terraces are floodplains and outwash plains that have been horizontally 

and vertically removed from the regular flooding of a river. The ultimate cause of 

this removal from the river’s influence is down-cutting by the river. These surfaces 

are typically gravel and sandy gravel, capped by floodplain deposits of silt, sand, or 

peat up to 3 to 6 feet thick. Older surfaces may be also covered by thicker eolian silt, 

peatland, and thaw-lake deposits. 

Sand-Silt deposits. Sand and silt occur in a variety of forms within GAAR, and a few 

examples follow.. Some silt and sand is deposited initially by slow-moving streams 

within basins partly dammed by end moraines. These deposits commonly grade 

downward into lacustrine deposits and are often dissected by postglacial streams. 

Other sand-silt deposits are formed by loess, and now are poorly stratified sandy silt, 

organic silt, and silty peat. Abundant ice often occurs in the form of lenses, wedges, 
182 

and interstitial grains. Another example is upland silt deposits formed from loess and 

the layers are subsequently mixed by frost action with local organic matter and 

weathering products (Hamilton, 1999c). 

Active dunes and inactive dunes both occur within GAAR (Figures 40a and b). The 

most extensive dunes observed were parabolic and longitudinal dunes along the 

Killik River near the north flank of the Brooks Range (Killik River quadrangle) and a 

series of subparallel ridges on the Alatna River floodplain near the south margin of 

the range (Survey Pass quadrangle, Hamilton 1999c). The location and formation of 

dunes depend primarily on the availability of sand, and wind direction. The main 

source of sand and silt is the sediment load delivered by the various rivers and 

deposited on outwash plains, floodplains or deltas. Once the sediment is deposited, 

winds form the dunes. The eventual quasi-equilibrium in sand dunes represents a 

balance between erosion and deposition, and requires the forward movement of the 

entire feature. 

Glacial drift vegetation. For all of the glacial drift in GAAR, forests cover 26.3%, 

tall or low shrubs 38.1%, prostrate shrubs 16.5%, herbaceous vegetation 13.9%, and 

bare ground, sparsely vegetated, water 3.8% mosaic/patterned vegetation and shadow 

indeterminate 1.2% (Table 13). On glacial drift in the south half of GAAR, the 

vegetation generally changes, moving downslope, from prostrate shrubs to either low 

or tall shrubs, then to open forest (Figure 78). On the relatively level valley bottoms 

lichen-woodland is common on drier sites, and woodlands and peatlands occupy the 

wetter sites. 

On the north half of GAAR—north of treeline—the vegetation generally changes, 

moving downslope, from prostrate shrubs to either low shrubs or tussock tundra 

(Figure 79). On level valley bottoms wet-herbaceous vegetation or tussock tundra 

will dominate. Small but consistent pockets of well drained river bluffs and frost 

boils—areas of bare soil caused by frost action—also occur and are dominated by 

prostrate shrubs or resin birch (Betula glandulosa). 
183 

Figure 79. Landsat image of glacial till north of treeline 

[Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 
184 

Lacustrine Deposits 

Lacustrine deposits occupy the valley bottoms, as do glacial drift and floodplains 

(Figure 80). This deposit is derived from materials deposited in lake water and 

exposed when the water level is lowered or the land is raised. Lacustrine deposits 

have a high percentage of thermokarst formed lakes and covers 1.2% of GAAR. 

For all of the lacustrine deposits in GAAR, forests cover 53.7%, tall or low shrubs 

19.9%, prostrate shrubs 7.4%, herbaceous vegetation 10.4%, and bare ground 5.5% 

and mosaic/patterned vegetation and shadow indeterminate 2.8% (Table 13). 

 

Figure 80. Landsat image of lacustrine deposits 

 [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Floodplain

Floodplains are composed of glacial and non-glacial rivers, sandbars and low terraces 

that are still actively flooded. The soils include both poorly-drained permafrost rich 

soils, lake silts and clays, and well-drained alluvial loams, sands and gravels. 

Surficial geology deposits included in this type are ‘modern alluvium’ and 

‘undifferentiated alluvium.’ Floodplains are widely distributed and cover 4% of the 

landmass of GAAR (Appendix 6). 
185 

Active glacial outwash plain is included in this section due to its similarity to 

floodplains—inactive glacial outwash is included in the glacial drift description. Glacial 

outwash forms when glacially fed rivers deposit their sediment in stream channels and 

the associated plain. Due to continual channel shifting the sediment is spread across an 

area called an outwash plain. Outwash plains typically have braided rivers consisting of 

multiple, wide, shallow channels characterized by rapid erosion, deposition and channel 

shifts. Many of the drainage systems in GAAR have small headwater glaciers but the 

influence of these glaciers on the drainages appears to be minor and, consequently, 

outwash plains are uncommon in GAAR. 

Floodplains are formed by non-glacial fed rivers. In GAAR, they often rework 

lacustrine and glacial drift deposits. The formation of new land on floodplains is well 

documented. Along a meandering river—meandering rivers have one or two main 

channels—alluvium is deposited on convex curves in the river channel (Figure 81). The 

opposing concave bank is cut, providing sediment for deposition on convex curves 

downstream and creating a series of similar bands of alluvial deposits. The channel thus 

meanders laterally across the floodplain. Vegetation growing on new deposits near the 

river may be contrasted with that on older deposits inland to recognize and measure 

successional processes. Alluvium is also deposited on the soil surface during flooding 

further raising the soil surface height, but because surface height is a function of 

floodwater height it eventually stabilizes. 

 Figure 81. Idealized cross-section of geomorphic and vegetation succession on a 

flood- plain (adapted from Krieg and Reger 1982) 

Terraces play a major role in plant community structure and composition. Deposits with 

high permeability become progressively drier as they are vertically and horizontally 

removed from the active channels. This is due to decreased soil water recharge from 

channel seepage. Vegetation responds to these gradients in soil moisture with changes in 

composition and structure. On older terraces, in contrast, permafrost forms and creates 

an impermeable layer that, in turn, leads to a wetter environment. Ponds, such as 

meander scrolls and oxbows, are common on floodplains (Figure 82). A meander scroll 

is formed on the convex side of river bends by alluvial deposition. As alluvium is 

deposited, it forms point bars and further inland an undulating topography of levees and 

depressions. The meander scroll depressions are often filled with standing water or act 
186 

as overflow channels during high flows. Oxbows are formed when a river abruptly 

changes course cutting off a stream segment. Typically, the oxbow will partially fill with 

water. The effect of permafrost on ponds is not clear, but it appears the formation of 

ground ice alters pond shape and depth. 

Figure 82. Oxbows on floodplain altered by ground ice 

Floodplain vegetation. On forested floodplains and outwash plains on the south-half of 

GAAR, new alluvial bars or abandoned stream channels are invaded by sapling balsam 

poplar (Populus balsamifera), white spruce (Picea glauca), willow (Salix species) and 

alder (Alnus species) species (Figure 83). In time, balsam poplar and white spruce 

dominate the sites and form sparse to dense forests. If the soils remain well drained then 

white spruce will eventually dominate as balsam poplar reaches senescence. However, if 

ground ice forms, leading to poorly-drained soils, then black spruce (Picea mariana) will 

invade along with other moisture tolerant species such as peat moss (Sphagnum [peat 

moss] species). The balsam poplar map class was not observed on other surficial 

geology types except in the Kobuk Boot area on uplands. 
187 

Figure 83. Landsat image of floodplain surficial geology type in the south half of 

GAAR [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 

Figure 84. Landsat image of the floodplain surficial geology type in the north 

half of GAAR [Scale = 1:63,360, Landsat TM bands 4,5,3 (RGB)] 
188 

Figure 85. River floodplain north of treeline dominated by willows (Salix) 

and tussock tundra 

North of treeline, new alluvial bars or abandoned stream channels are invaded by river 

beauty (Epilobium latifolium, dwarf fireweed), arctic wormwood (Artemisia arctica) and 

shrub species such as feltleaf willow (Salix alaxensis) and grayleaf willow (Salix glauca) 

(Figures 84 and 85). If the soils remain well drained, then willows may continue to 

dominate. However, if ground ice forms, leading to poorly-drained soils, then tussock 

tundra and wet herbaceous meadows form. Tall shrubs rarely occur north of treeline 

except on recently disturbed portions of floodplains and alluvial fans. Small streams are 

common in GAAR, but were usually not captured by either the Landsat imagery or the 

surficial geology maps due to their narrow widths. On small streams in the south half of 

GAAR, willow and alder species dominate the narrow floodplains and stream banks 

(Figure 86). On small streams in the north half of GAAR the narrow floodplains are 

dominated by open and closed shrub stands composed of Salix planifolia subspecies

pulchra, and Betula glandulosa (resin birch), and herbaceous vegetation (Figure 87). 

For floodplains large enough—greater than 90 feet width—to be captured by Landsat 

imagery, forests covered 35.1%, tall or low shrubs 26.8%, prostrate shrubs 9.2%, 

herbaceous vegetation 9.5%, and bare ground, sparsely vegetated, water and 

patterned ground 19.5% (Table 13). 
189 

Figure 87. Stream in the north half of GAAR whose floodplain is dominated 

by willow (Salix) 

Figure 88. Pingo (~40 m diameter) in alluvial valley 

Organic Deposits

Organic deposits (i.e., peatlands, muskeg) are composed of three to six feet of 

accumulated peat in areas of restricted drainage with water tables at or close to the 

peat surface. The peat generally grades laterally into organic silt and silty peat near 

the bases of solifluction slopes (Hamilton 1999c). Organic deposits are generally 
190 

restricted to forested areas beyond the south flank of the Brooks Range. They occupy 

former lake basins and other closed depressions, alluvium along some valley floors, 

and are abundant on older glacial drift deposits within the boreal forest. These 

deposits cover 0.7% of GAAR (Table 13). 

The gradient of nutrient availability and water sources for organic deposits is 

typically divided into nutrient rich (fen) and nutrient poor (bog) peatlands. Fens are 

wetlands with wet organic soils, dominated by aquatic, emergent, and dwarf shrubs, 

or raised peat dominated by shrubs and trees. Ground water, the primary water 

source in a fen, is nutrient rich because of its contact with mineral soils. Waters may 

be acidic or basic, but typically with a pH above 4.7. Water is lost through 

evapotranspiration, seepage (infiltration through the soil), and surface outflow. 

Bogs are wetlands with organic soils, typically dominated by Sphagnum (peat moss) 

species, sedges, grasses, or reeds. Bogs require depressions (ponds) in level areas 

where precipitation exceeds evapotranspiration. Precipitation is the primary water 

source in a bog, with little or no ground-water flow. Consequently the sites are 

nutrient-poor and acidic, commonly with a pH less than 4.7. The water table is at or 

close to the surface most of the year. Because of the continuum of site and vegetation 

change within a peatland, it is often difficult to clearly separate a fen from a bog in 

the field. 

Peatland Vegetation. In level areas, bogs and fens generally exhibit recognizable 

and consistent vegetation zonation patterns that are directly associated with different 

water depths. The vegetation, on a wet to dry moisture gradient, typically changes 

from aquatic (pond), to emergent, to mesic herbaceous, to carr (shrub-dominated 

wetland), to dwarf tree. Not all the vegetation zones are always expressed, and the 

zonation may change abruptly, such as from a pond to a carr. Beavers typically have 

a major effect on the development and maintenance of fens by creating pools, 

forming hummocks with their dams, and consuming woody vegetation. Fens on 

ground with a slight gradient and with heavy subsurface and surface waterflow often 

develop a patterned ground of vegetated ridges, and vegetated or unvegetated hollows 

filled with water. The major vegetation cover observed during the 1998 field season 

was peat moss (Sphagnum) and stunted black spruce. For all of the lacustrine 

deposits in GAAR, forests cover 53.7%, tall or low shrubs 19.9%, prostrate shrubs 

7.4%, herbaceous vegetation 10.4%, and bare ground sparsely vegetated, water 5.5% 

and mosaic/patterned vegetation and shadow indeterminate 2.8% (Table 13). 

Pingo. Pingos are uncommon yet widespread throughout GAAR (Figure 88). They 

are ice-filled conical hills or mounds, 20 to 400 m in diameter and 10 to 70 m high. 

Closed-system pingos form in nearly level areas when unfrozen ground water 

migrates under hydrostatic pressure to a site where the permafrost is domed up to 

form a mound. An open-system type is generally smaller and forms on sloping 

ground where water beneath or within the permafrost penetrates the permafrost under 

high hydraulic pressure, which heaves the overlying material to form a mound. 

Radiometric dating indicates that most pingos in Alaska are less than 4,000 to 7,000 
191 

years old, however, many are less than 1,000 and even 100 years old. Vegetation on 

pingos is not described in this report. 

 Figure 89. Idealized representation of the formation of an ice wedge polygon 

 according to the contraction crack theory (Lachenbruch 1962) 
192 

Other Surficial Geology Types Not Listed on the Surficial Geology Map. Several 

surficial geology types that strongly influence vegetation are described but were not 

listed by Hamilton (1999c) including patterned ground, thermokarst and water tracts. 

Patterned Ground. Regions with perennially frozen ground often have their surface 

materials arranged into distinct geometric shapes. The features, collectively known 

as patterned ground, include polygons, nets, circles and stripes (Washburn 1956). In 

general, the geometric pattern changes with increasing slope from polygons and 

circles on level ground, to nets and then stripes on steeper surfaces. Whether the 

geometric shape was formed by sorting or not has an effect on the type and size of 

patterned ground and its vegetation (Ritter 1986). Three types of patterned ground 

are described below: sorted polygons, ice wedge polygons, and frost boils. These 

units were not mapped by Hamilton (1999c). 

For sorted polygons, sorting separates the coarse from the fine soil particles, and 

typically produces a surface feature of fine materials bordered by stones in a variety 

of geometric shapes; polygons, circles, nets and stripes. Sorted polygons are bounded 

by straight segments composed of stones that surround a central core of finer 

material. They range up to 10 m in diameter. One general theory behind the 

formation of sorted polygons is that soil heaving separates the coarse and fine 

sediments, and repeated freezing and thawing moves the stones upward and outward. 

 The smaller grains with greater cohesion contract farther inward and downward 

during thawing. The process continues until the adjacent polygons meet. The coarse 

materials form circular or polygonal rims with finer materials in the center (Ballard 

1973). 

Sorted circles are similar to sorted polygons but circular in outline. Sorted stripes are 

linear alignments of soil, vegetation and stones on slopes. They are strips of stone 

separated by broad zones of finer sediment and vegetation. The strips are up to 

several meters in width and 100 m in length. 

Sorted polygons and circles were observed on glacial drift on rounded foothills and 

mountain slopes on the north edge of GAAR. Vegetation ranged from absent on the 

rims with prostrate shrubs in the center, to shrubs on the edge with no vegetation in 

the polygon center. 

Ice wedge polygons are typically connected in a polygonal pattern that is similar to 

the pattern produced by mud cracks. They are formed by large masses of ice—called 

ice wedges—which grow in thermal contraction cracks in permafrost (Figure 89). 

Thermal tension on the ground surface leads to frost fractures only millimeters wide 

that penetrate the active layer and permafrost. The ground cracking typically occurs 

in winter when ground temperatures reach their annual minimum. In spring, water 

from melting snow freezes in these cracks and produces a vertical vein of ice. During 

the summer months the permafrost warms and horizontal compression caused by reexpansion of the permafrost results in the upturning of permafrost, forming elevated 

perimeters of the polygon. In winter, renewed thermal tension reopens the vertical 
193 

crack that is presumed to be a zone of weakness. Another sliver of ice is added when 

the spring meltwater enters the renewed crack and freezes. Over the centuries, these 

incremental cracks produce ice wedges that may be 2 m wide at the top. Troughs 

often form the boundaries between polygons and generally indicate ice wedges that 

are 1 to 2 m wide at the top. The diameter of ice wedge polygons ranges from several 

to more than 30 meters. 

Ice wedge polygons are a common feature on level ground of glacial drift, lacustrine 

and floodplain surficial geology deposits of the arctic foothills and the interior 

forested lowlands and uplands ecoregions. They also occur in the larger mountain 

valley bottoms of the Brooks Range ecoregion on glacial drift and lacustrine deposits. 

 

Vegetation of ice wedge polygons is dependent on surface elevation and soil 

moisture. Some polygons have perimeters that are elevated relative to the center of 

the polygon and are termed low-center polygons. These polygon centers often have 

standing water and support emergent or tussock vegetation. Low shrubs often 

dominate their edges. Other polygons have depressed perimeters relative to the 

center of the polygon and are termed high-center polygons. Their centers do not have 

standing water and may be dominated by prostrate shrubs and their edges by low 

shrubs. Low center polygons indicate that ice wedges are actually growing and that 

sediments are being actively upturned. High center polygons indicate that erosion, 

deposition, or thawing is more prevalent than the up-pushing of the sediments along 

the sides of the wedge. 

Frost boils are areas of bare soil, which are sufficiently disturbed by frost action to 

prevent plant colonization. On slopes, fine material in unsorted circles moves slowly 

downslope producing banked or “stepped” frost boils (from Gabriel and Talbot, 

1984). Frost boils were observed on river terraces and on low angle hills on the north 

edge of the Brooks Range. 
194 

Figure 90. Landsat image of thermokarst [Scale = 1:63,360, Landsat TM bands 4,5,3 

(RGB)] 

 Figure 91. Thermokarst north of Anaktuvuk Pass 
195 

Thermokarst. Thermokarst is the collapse of the soil surface due to the thawing of 

ice rich permafrost (Figures 90 and 91). The ground around thermokarst is 

supersaturated—often with ice lenses and layers—because it contains more water in 

the solid state than the ground could possibly hold if the water were in the liquid 

state. The melting of ground ice is due to either vertical soil degradation when the 

surface thermal properties are altered, or lateral degradation such as where lake water 

laterally erodes its banks, including ground ice. Many of the processes that lead to 

thermokarst are initiated by broad climate changes, but minor events such as fires, 

clearing of forest vegetation, shifting stream channels, and removal of the peat 

surface will upset the thermal balance and produce thermokarst. 

Thermokarst is a common feature in areas with low relief and level land such as in 

mountain valleys and the regions north and south of the Brooks Range. It occurs on a 

variety of surficial geology deposits—sand, lacustrine, glacial drift, and floodplain—

throughout GAAR. Most thermokarst ponds have steep banks and consequently 

support little emergent vegetation. 

Water Tract. Many of the rolling hills and mountain sideslopes covered by tussock 

tundra have narrow water tracks running downslope (Figure 92). Water tracks are 

shallow depressions that have significantly greater water flow than the adjacent 

tussock tundra. They also commonly have horizontal soil ridges that pool the water. 

These ridges suggest some mass movement of the soil. The water tracks are 

commonly dominated by open water, diamondleafed willow (Salix planifolia 

subspecies pulchra) and sedges (Carex species). 

 

Figure 92. Water tracts on a loess covered bedrock outcrop in the arctic 

foothills ecoregion 
196 

LITERATURE CITED 

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203 

GLOSSARY 

Most of the ecological terms below are from Hamilton (1999c), Gallant et al. (1995), 

Anderson et al. (1998), Viereck et al. (1992) and Gabriel and Talbot (1984). 

Albedo—Same as reflectivity. The percentage of incoming radiation that is reflected 

by a natural surface such as a ground, ice, snow, water, clouds, or particulates in the 

atmosphere. 

Albers equal area projection—the Albers Equal Area projection is a method of 

projection on which the areas of all regions are shown in the same proportion of their 

true areas. The meridians are equally spaced straight lines converging at a common 

point, which is normally beyond the pole. The angles between them are less than the 

true angles. The parallels are unequally spaced concentric circular arcs centered on 

the point of convergence of the meridians. The poles are normally circular arcs 

enclosing the same angle as that enclosed by the other parallels of latitude for a given 

range of longitude. Albers Equal Area is frequently used in the ellipsoidal form for 

maps of the United States in the National Atlas of the United States, for thematic 

maps, and for world atlases. It is also used and recommended for equal-area maps of 

regions that are predominantly east-west in extent. 

Alliance—A physiognomically uniform group of plant associations sharing one or 

more dominant or diagnostic species, which as a rule are found in the uppermost 

stratum of the vegetation (Grossman et al. 1998). 

Alluvial fans—Erosional-depositional system in which rock and sediment are 

transported down-valley and deposited where it emerges from the confines of the 

valley into a larger valley or plain. They tend to be fan-shaped in plan view; a 

segment of a cone radiating away from a single point source. 

Alluvial—Characterized by the deposition of sediment by a stream or other running 

water at any point along its course. 

Alpine—The zone on mountain tops between permanent snow and the cold limits of 

trees. 

Annual—Plant species that complete their life-cycle within a single growing season. 

Aquatic—Refers to sites with vegetation that is submerged, floating, or growing in 

permanent water. 

Attributes—Attributes, also called feature codes or classification attributes, are used 

to describe map information represented by a node, line, or area. For example, an 

attribute code for an area might identify it to be a lake or swamp; an attribute code for 

a line might identify a road, railroad, stream, or shoreline. 
204 

Bare-ground—Refers to (1) a landcover class with less than 15% vegetation cover, 

and (2) a soil surface devoid of vegetation. 

Bedrock—Refers to exposed rock typically at higher elevations and includes all the 

jagged rocky ridges, peaks, cirque headwalls and cirque basins in the Brooks Range. 

It has little or no soil development. 

Biennial—Plant species that complete their life-cycles within two growing seasons. 

Binary—Numerical system using the base 2. 

Bit—Contraction of binary digit, which in digital computing represents an exponent 

of the base 2. 

Boreal—Northern biogeographical region typically referring to subpolar and cold 

temperate areas. 

Brackish—Tidal water with a salinity of 0.5-30 parts per thousand. 

Brightness—Magnitude of the response produced in the eye by light. 

Broad-leaved—Describes a plant with leaves that have well-defined leaf blades and 

are relatively wide in outline (shape) as opposed to needle-like or linear; leaf area is 

typically greater than 500 square millimeters or 1 square inch. 

Bryophyte—Nonvascular, terrestrial green plant, including mosses, hornworts, and 

liverworts. 

Bunch grass—Multi-stemmed (Caespitose) life form of grasses characterized by 

clumps of erect shoots that slowly spread horizontally by tillers, generally creating 

distinct individual plants spaced across the ground; often applied to sedges and other 

graminoids with similar life forms. 

Byte—A group of eight bits of digital data. 

Caespitose (cespitose) —Describes a low branching pattern from near the base that 

forms a multi-stemmed or a bunched appearance. 

Canopy cover—The% of the ground in the polygon covered by the gross outline of 

an individual plant's foliage (canopy), or the outline collectively covered by all 

individuals of a species or life-form within the polygon (Daubenmire 1959). 

Classification—Process of assigning individual pixels of an image to categories, 

generally on the basis of spectral reflectance characteristics. 

Cliff—Any high, very steep to perpendicular, or overhanging face of a rock outcrop. 
205 

Cold-deciduous—Describes a plant that sheds its leaves as a strategy to avoid 

seasonal periods of low temperature, often initiated by photoperiod; applied to 

vegetation adapted to seasonal cold season influences (temperate). 

Colluvium—Unconsolidated surface materials that have been transported downslope 

and deposited on the lower slopes. Colluvium is moved by landslides, flow slides, 

talus rubble, rock-glaciers, solifluction and unconsolidated runoff. 

Contrast—The ratio between the energy emitted or reflected by an object and its 

immediate surroundings. 

Contrast stretching—Expanding a measured range of digital numbers in an image to 

a larger range, to improve the contrast of the image and its component parts. 

Creeping—Describes the pattern of stems growing at or just beneath the surface of 

the ground and usually producing roots at nodes. 

Crustose lichen—Lichen life form that grows in intimate contact with its substrate, 

lacks a lower cortex and rhizoids (root-like structures), and is impossible to separate 

from the substrate without destroying the thallus; lichen with an unlobed, flattened 

thallus, growing adnate to the substrate. 

Cubic convolution—A high order resampling technique in which the brightness 

value of a pixel in a corrected image is interpolated from the brightness values of the 

16 nearest pixels around the location of the corrected pixel. 

Cushion plant—A low, woody, plant life form so densely branched that it forms a 

compact canopy that is pad- or bolster-like in appearance; usually with microphyllous 

foliage; characteristic of alpine and tundra plants. 

Datum—In surveying, a reference system for computing or correlating the results of 

surveys. There are two principal types of datums: vertical and horizontal. A vertical 

datum is a level surface to which heights are referred. In the United States, the 

generally adopted vertical datum for leveling operations is the national geodetic 

vertical datums of 1929 (differing slightly from mean sea level). The horizontal 

datum, used as a reference for position, is defined by: the latitude and longitude of an 

initial point, the direction of a line between this point and a specified second point, 

and two dimensions which define the spheroid. In the United States, the initial point 

for the horizontal datum is location at Meades Ranch in Kansas. 

Deciduous—Describes a woody plant that seasonally loses all of its leaves and 

becomes temporarily bare-stemmed. 

DEM–Digital Elevation Models—The U.S. Geological Survey produces five primary 

types of digital elevation model data: they are: 
206 

7.5-minute DEM (30- x 30-m data spacing, cast on Universal Transverse Mercator 

(UTM) projection or 1- x 1-arc-second data spacing). Provides coverage in 7.5- x 

7.5-minute blocks. Each product provides the same coverage as a standard USGS 

7.5-minute map series quadrangle. Coverage: Contiguous United States, Hawaii, and 

Puerto Rico. 

1-degree DEM (3- x 3-arc second data spacing). Provides coverage in 1- x 1-degree 

blocks. Two products (three in some regions of Alaska) provide the same coverage 

as a standard USGS 1- x 2-degree map series quadrangle. The basic elevation model 

is produced by or for the Defense Mapping Agency (DMA), but is distributed by 

USGS in the DEM data record format. Coverage: United States. 

30-minute DEM (2- x 2-arc-second data spacing). Consists of four 15- x 15-minute 

DEM blocks. Two 30-minute DEMs provide the same coverage as a standard USGS 

30- x 60-minute map series quadrangle. Saleable units will be 30- x 30-minute 

blocks, that is, four 15- x 15-minute DEMs representing one half of a 1:100,000-scale 

map. Coverage: Contiguous United States, Hawaii. 

15-minute Alaska DEM (2- x 3-arc-second data spacing, latitude by longitude). 

Provides coverage similar to a 15-minute DEM, except that the longitudinal cell 

limits vary from 20 minutes at the southernmost latitude of Alaska to 36 minutes at 

the northern most latitude limits of Alaska. Coverage of one DEM will generally 

correspond to a 1:63,360-scale quadrangle. 

7.5-minute Alaska DEM (1- x 2-arc-second data spacing, latitude by longitude). 

Provides coverage similar to a 7.5-minute DEM, except that the longitudinal cell 

limits vary from 10 minutes at the southernmost latitude of Alaska to 18 minutes at 

the northernmost latitude limits of Alaska. 

Detector—Component of a remote sensing system that converts electromagnetic 

radiation into a recorded signal. 

Digital image processing—computer manipulation of the digital-number values of 

an image. 

Digital image—an image where the property being measured has been converted 

from a continuous range of analogue values to a range expressed by a finite number 

of integers, usually recorded as binary codes from 0 to 255, or as one byte. 

Digital number (DN)—Value assigned to a pixel in a digital image. 

Digitization—Process of converting an analog display into a digital display. 

Digitizer—Device for scanning an image and converting it into numerical format. 
207 

Dominant—An organism, group of organisms, or taxon that by its size, abundance, 

or coverage exerts considerable influence upon an association's biotic (such as 

structure and function) and abiotic (such as shade and relative humidity) conditions. 

DTM-Digital Terrain Model—A DTM is a land surface represented in digital form 

by an elevation grid or lists of three-dimensional coordinates. 

Ecoregions—Landscape units defined based on similar patterns in potential natural 

communities, soils, hydrologic function, landform, topography, lithology, climate, 

and natural processes such as nutrient cycling, productivity, succession, and natural 

disturbance regimes associated with flooding, wind, or fire. Climate, as modified by 

topography, is the dominant criterion at the scale mapped for GAAR. 

Edge enhancement—Image-processing technique that emphasizes the appearance of 

edges and lines. 

Edge—A boundary in an image between areas with different tones. 

Electromagnetic radiation—Energy propagated in the form of and advancing 

interaction between electric and magnetic fields. All electromagnetic radiation 

moves at the speed of light. 

Electromagnetic spectrum—Continuous sequence of electromagnetic energy 

arranged according to wavelength or frequency. 

Enhancement—Process of altering the appearance of an image so that the interpreter 

can extract more information. 

Eolian—Wind blown sand and silt deposits. 

Ephemeral forb vegetation—Annual associations or synusiae that, during favorable 

periods, dominate areas that are usually sparsely vegetated or unvegetated for most of 

the year. 

Epiphyte—Vascular plant that grows by germinating and rooting on other plants or 

other perched structures; sometimes called "air plants." 

Evergreen—Describes a plant that has green leaves all year round. 

False-color image—A color image where parts of the non-visible EM spectrum are 

expressed as one or more of the red, green, and blue components, so that the colors 

produced by the Earth’s surface do not correspond to normal visual experience. Also 

called a false-color composite (FCC). The most commonly seen false color images 

display the very-near infrared as red, red as green, and green as blue. 

False-color photograph—Another term for IR color photograph. 
208 

Field of View—Essentially the synthesis of the IFOV from the scanning process of 

the radiometer. 

Field Verification Area—An area sampled during the field season composed of 

multiple polygons. 

Floodplain—A fluvial plain formed by non-glacial fed rivers. Along a meandering 

river—meandering rivers have one or two main channels—alluvium is deposited on 

convex curves in the river channel. The opposing concave bank is cut, providing 

sediment for deposition on convex curves downstream and creating a series of similar 

bands of alluvial deposits. The channel thus meanders laterally across the floodplain. 

Foliose lichen—Lichen life form that is leafy in appearance and loosely attached to 

its substrate; lichen with a lobed, flattened thallus growing loosely attached to the 

substrate, the lobes flattened or inflated with distinctly differentiated upper and lower 

surfaces; umbilicate lichens are included. 

Forb—A broad-leaved herbaceous plant. 

Fresh water—Water with a salinity of less than 0.5 parts per thousand. 

Frost boils—These are areas of bare soil which are sufficiently disturbed by frost 

action to prevent plant colonization. On slopes, fine material in unsorted circles 

moves slowly downslope producing banked or “stepped” frost boils (from Gabriel 

and Talbot. 1984). 

Frost Scar—These are exposed bare mineral soil formed by frost action in the soil. 

Fruticose lichen—Lichen life form that is bunched, shrubby or "hairy" in appearance 

and loosely attached to its substrate; lichen with the thallus branched, the branches 

solid, or hollow and round, or flattened without distinctly differentiated upper and 

lower surfaces; squamulose lichens are included. 

GCP—Ground-control point. 

Geographic information system (GIS)—A data-handling and analysis system based 

on sets of data distributed spatially in two dimensions. The data sets may be map 

oriented, when they comprise qualitative attributes of an area recorded as lines, 

points, and areas often in vector format, or image oriented, when the data are 

quantitative attributes referring to cells in a rectangular grid usually in raster format. 

It is also known as a geobased or geocoded information system. 

Geometric correction—Image-processing procedure that corrects spatial distortions 

in an image. 
209 

Geomorphic process—Refers to the mechanical transport of organic and inorganic 

material such as mass movement, surface erosion, the transport of material (silt) by 

water, and biogenic soil movement by root throw and animals. 

Glacial drift—the material transported by a glacier and then deposited either directly 

from the ice or from the melt water. Numerous types of glacial drift occur including 

moraines, kettle-kame topography, eskers, drumlins, glacial till and outwash. 

Glacial outwash—Fluvial plains formed when glacially fed rivers deposit their sediment 

in stream channels and the associated plain. Due to continual channel shifting the 

sediment is spread across an area called an outwash plain. Outwash plains typically have 

braided rivers consisting of multiple, wide, shallow channels characterized by rapid 

erosion, deposition and channel shifts. 

Glacial till—A surface formed by sediment originating directly from glacial ice and 

typically has no discernible sediment stratification. 

GPS–Global Positioning System—The GPS is a worldwide satellite navigation 

system that is funded and supervised by the U.S. Department of Defense. GPS 

satellites transmit specially coded signals. These signals are processed by a GPS 

receiver that computes extremely accurate measurements, including 3-dimensional 

position, velocity, and time on a continuous basis. 

Graminoid—Grasses and grass-like plants, including sedges and rushes. 

Grassland—Vegetation dominated by perennial graminoid plants. 

Ground layer—Applies to the herbaceous layer. 

Ground receiving station—Facility that records data transmitted by a satellite, such 

as Landsat. 

Ground-control point—A geographic feature of known location that is recognizable 

on images and can be used to determine geometric corrections. 

Growth form—The shape or appearance of a plant; it primarily reflects the influence 

of growing conditions. 

Herbaceous—A vascular plant without significant woody tissue above or at the 

ground; an annual, biennial, or perennial plant lacking significant thickening by 

secondary woody growth, with perennating buds borne at or below the ground surface 

(hemicryophytes, geophytes, helophytes, and therophytes of Raunkier). 

High-pass filter—A spatial filter which selectively enhances contrast variations with 

high spatial frequencies in an image. It improves the sharpness of images and is a 

method of edge enhancement. 
210 

Hypertext—The use of links between related words, graphics, or documents that 

allow the user to jump to associated topics or definitions when reading menus or help 

files. 

Ice wedge polygons—Refers to patterned ground with polygons typically connected 

in a polygonal pattern that is similar to the pattern produced by mud cracks. They are 

formed by large masses of ice—called ice wedges—that grow in thermal contraction 

cracks in permafrost. 

IFOV—Instantaneous Field of View. The solid angle through which a detector is 

sensitive to radiation. It forms one limit to the resolution of an imaging system. 

Image—pictorial representation of a scene recorded by a remote sensing system. 

Although image is a general term, it is commonly restricted to representations 

acquired by non-photographic methods. 

Interactive processing—Method of image processing in which the operator views 

preliminary results and can alter the instructions to the computer to achieve desired 

results. 

Interpretation key—Characteristic or combination of characteristics that enable an 

interpreter to identify an object on an image. 

Interpretation—The process in which a person extracts information from an image. 

IR color photograph—Color photograph in which the red-imaging layer is sensitive 

to photographic IR wavelengths, the green-imaging layer is sensitive to red light, and 

the blue-imaging layer is sensitive to green light. Also known as camouflage 

detection photographs and false-color photographs. 

Kernel—Two-dimensional array of digital numbers used in digital filtering. 

Krummholz—Growth form assumed by tree species at the upper treeline or in the 

alpine zone; characterized by a creeping and multi-stemmed growth pattern due to 

desiccation and physical damage caused by wind and blowing ice crystals near the 

upper treeline; the same species grows as an erect, single-stemmed tree at lower 

elevation. 

Lacustrine deposits—derived from materials deposited in lake water and exposed 

when the water level is lowered or the land is raised. 
211 

Landsat (formerly ERTS)—The Landsat program, first known as the Earth 

Resources Technology Satellite (ERTS) Program, is a development of the National 

Aeronautics and Space Administration (NASA) in association with NOAA, USGS, 

and the Space Imaging. The activities of these combined groups led to the concept of 

dedicated Earth-orbiting satellites, the defining of spectral and spatial requirements 

for their instruments, and the fostering of research to determine the best means of 

extracting and using information from the data. The first satellite, ERTS 1, was 

launched on July 23, 1972. The second satellite was launched on January 22, 1975. 

Concurrently, the name of the satellites and program was changed to emphasize its 

prime area of interest (land resources). The first two satellites were designated as 

Landsats 1 and 2. Landsat 3 was launched on March 5, 1978. Landsat 4 was 

launched on July 16, 1982. Landsat 5 (launched March 1, 1984) is currently in 

service providing selected data to worldwide researchers. Both Landsat 4 and 5 are 

carry the Thematic Mapper (TM) sensor. 

Lichen—An organism generally recognized as a single plant that consists of a fungus 

and an alga or cyanobacterium living in symbiotic association. 

Life form—The shape or appearance of a plant that mostly reflects inherited or 

genetic influences. 

Light—Electromagnetic radiation ranging from 0.4 to 0.7Fm in wavelength that is 

detectable by the human eye. 

Line drop out—The loss of data from a scan line caused by malfunction of one of 

the detectors in a line scanner. 

Low shrub—Low-growing shrub life form between 0.3 and 3.5 feet tall. 

Matted—Describes a creeping plant that by reiterative growth has overlapping stems 

and forms a low, dense ground cover. 

Mesic—Sites are moist and tussocks may dominate. Permanent standing water is not 

present. 

Mid-infrared (MIR)—The range of EM wavelengths from 8 to 14 Fm dominated by 

emission of thermally generated radiation from materials; also known as thermal 

infrared. 

Mixed forest—Describes vegetation in which evergreen and deciduous species each 

generally contribute 25-75% to the total canopy cover. 

Mixed pixel—A pixel whose DN represents the average energy reflected or emitted 

by several types of surface present within the area that it represents on the ground; 

sometimes called a mixel. 
212 

Montane—Describes the zone in mountainous regions where the influence of 

altitude (vertical relief) results in local climatic regimes that are sufficiently different 

from those in the adjacent lowlands as to cause a complex vertical climatevegetation-soil zonation; includes vegetation at the base of a mountain when it is 

different from lowland vegetation. 

Mosaic—Composite image or photograph made by piecing together individual 

images or photographs covering adjacent areas. 

MSS—Refers to the Landsat Multispectral Scanner System (MSS) satellite based 

imaging sensor. The MSS simultaneously senses radiation using an array of six 

detectors in each of four spectral bands from 0.5 to 1.1 micrometers (visible to near 

infrared region of the electromagnetic spectrum. This system was a precursor to the 

higher spatial(geometric) and spectral (7 bands) Landsat TM system. 

Multispectral classification—Identification of terrain categories by digital 

processing of data acquired by multispectral scanners. 

Multispectral scanner—Scanner system that simultaneously acquires images of the 

same scene at different wavelengths. 

Nadir—The point on the ground vertically beneath the satellite. 

NDVI-Normalized Difference Vegetation Index—The NDVI is computed by 

calculating the ratio of the VI (vegetation index, i.e., the difference between Channel 

2 and 1) and the sum of Channels 2 and 1. Thus NDVI = (channel 2 - channel 1) / 

(channel 2 + channel 1). 

Near-infrared (NIR)—the shorter wavelength range of the infrared region of the EM 

spectrum, from 0.7 to 2.5 Fm. It is often divided into very-near infrared (VNIR) 

covering the range accessible to photographic emulsions (0.7 to 1.0 m), and the shortwavelength infrared (SWIR) covering the remainder of the NOR atmospheric window 

from 1.0 to 2.5m. 

NN-Nearest Neighbor Resampling—When correcting image data points, the nearest 

neighbor technique assigns for each new pixel that pixel value which is closest in 

relative location to the newly computed pixel location. 

Nonvascular plant—A plant without specialized water or fluid conductive tissue 

(xylem and phloem); includes bryophytes, lichens, and algae. 

Orbit—Path of a satellite around a body such as the earth, under the influence of 

gravity. 

Ortho-Correction—Correction applied to satellite imagery to account for terraininduced distortion. 
213 

Path and row index—System for locating Landsat MSS and TM images. 

Patterned ground—Refers to regions with perennially frozen ground that often have 

their surface materials arranged into distinct geometric shapes. The features, 

collectively known as patterned ground, include polygons, nets, circles and stripes. 

Pavement—A relatively flat surface of consolidated material, generally exposed 

bedrock. 

Perennial—Plant species with a life-cycle that characteristically lasts more than two 

growing seasons and persists for several years. 

Picture element—In a digitized image, the area on the ground represented by each 

digital number. Commonly contracted to pixel. 

Pingo—These are ice-filled conical hills or mounds, 20 to 400 m in diameter and 10 

to 70 m high. 

Pixel—Contraction of picture element. 

Plant association—The finest level of both the Viereck et al. (1992) and National 

Vegetation Classification System (Grossman et al. 1998) classifications. It is defined 

as “a plant community type of definite floristic composition, uniform habitat 

conditions, and uniform physiognomy” (Flahault and Schroter 1910). 

Prostrate shrub—Shrub life form growing less than 0.3 feet tall. 

Pulvinate mosses—Mosses growing in cushion-like mats or clumps. 

Raster format—A means of representing spatial data in the form of a grid of DN, 

each line of which can be used to modulate the lines of a video raster. 

Raster—A raster image is a matrix of row and column data points whose values 

represent energy being reflected or emitted from the object being viewed. These 

values, or pixels, can be viewed on a display monitor as a black-and-white or color 

image. The scanned and illuminated area of a video display, produced by a 

modulated beam of electrons sweeping the phosphorescent screen line by line from 

top to bottom at a regular rate of repetition. 

Ratio image—An image prepared by processing digital multi-spectral data as 

follows: for each pixel, the value for one band is divided by that of another. The 

resulting digital values are displayed as an image. 

Registration—Process of superposing two or more images or photographs so that 

equivalent geographic points coincide. 
214 

Remote sensing—Collection and interpretation of information about an object 

without being in physical contact with the object. 

Resampling—The calculation of new DN for pixels created during geometric 

correction of a digital scene, based on the values in the local area around the 

uncorrected pixels. 

Resolution—Ability to separate closely spaced objects on an image or photograph. 

Resolution is commonly expressed as the most closely spaced line-pairs per unit 

distance that can be distinguished. Also called spatial resolution. 

RMSE-Root Mean Square Error—The RMSE statistic is used to describe accuracy 

encompassing both random and systematic errors. The square of the difference 

between a true test point and an interpolated test point divided by the total number of 

test points in the arithmetic mean. The square root of this value is the root mean 

square error. 

Rock Glacier—Tongue-shaped or lobate masses of unsorted, angular frost-rived 

material with interstitial ice. They typically originate in cirques or in high, steepwalled recesses. 

Saltwater—Water with a salinity of greater than 30 parts per thousand. 

Satellite—An object in orbit around a celestial body. 

Saturation—In the IHS system, represents the purity of color. Saturation is also the 

condition where energy flux exceeds the sensitivity range of a detector. 

Scale—Ratio of distance on an image to the equivalent distance on the ground. 

Scene—Area on the ground that is covered by an image or photograph. 

Scree—A sheet of coarse rock debris covering a mountain slope without an adjacent 

cliff. 

Scrub—Vegetation dominated by shrubs, including thickets. 

Seasonal—Showing periodicity related to the seasons; applied to vegetation 

exhibiting pronounced seasonal periodicity marked by conspicuous physiognomic 

changes. 

Sensor—Device that receives electromagnetic radiation and converts it into a signal 

that can be recorded and displayed as either numerical data or an image. 
215 

Shaded Relief—Shading added to an image that makes the image appear to have 

three dimensional aspects. This type of enhancement is commonly done to satellite 

images and thematic maps utilizing digital topographic data to provide the 

appearance of terrain relief within the image. 

Shrub—A perennial woody species with a life form that is usually less than 4 to 5 

meters or 13 to 16 feet in height; typically, plants have several stems arising from or 

near the ground, but this term includes short tuft-tree, bamboo, and woody vine 

species; length of vine may exceed 5 meters; shrub species growth form may be taller 

than 5 meters or single-stemmed under certain environmental conditions. 

Signal to noise radio (S/N)—the ratio of the level of the signal carrying real 

information to that carrying spurious information as a result of defects in the system. 

Signal—Information recorded by a remote sensing system. 

Solifluction (or gelifluction)—The flow of soil in association with frozen ground. 

During the spring and summer thaw, water in the active layer cannot penetrate below 

the permafrost table. Soils are often saturated, and the loss of friction and cohesion 

causes them to behave like viscous fluids. The soil thus slowly ‘flows. ’ The 

downslope fronts of the solifluction lobes are marked by near-vertical scarps as high 

as 2 m. 

Sorted circles—Similar to sorted polygons but circular in outline. 

Sorted polygons—Refers to patterned ground where sorting separates the coarse 

from the fine soil particles, and typically produces a surface feature of fine materials 

bordered by stones in a variety of geometric shapes; polygons, circles, nets and 

stripes. 

Sorted stripes—Refers to patterned ground that consists of linear alignments of soil, 

vegetation and stones on slopes. They are strips of stone separated by broad zones of 

finer sediment and vegetation. The strips are up to several meters in width and 100 m 

in length. 

Sparsely vegetated—Describes vegetation with low total plant cover (between 15 

and 25%) that is scattered; areas with high cover of crustose lichen and no other 

vegetation are included here. 

Spectral reflectance—Reflectance of electromagnetic energy at specified 

wavelength intervals. 
216 

Spheroid—Mathematical figure closely approaching the geoid in form and size and 

used as a surface of reference for geodetic surveys. A reference spheroid or ellipsoid 

is a spheroid determined by revolving an ellipse about its shorter (polar) axis and 

used as a base for geodetic surveys of a large section of the Earth (such as the Clarke 

spheroid of 1866 which is used for geodetic surveys in the United States). 

Stomata—Pores or openings for gas exchange that are generally concentrated on leaf 

surfaces. 

Subalpine—Upper mountain vegetation immediately below the cold limits of tree 

and tall shrub growth. 

Sun-synchronous orbit—A polar orbit where the satellite always crosses the 

Equator at the same local solar time. 

Sun-synchronous—Earth Satellite orbit in which the orbit plane is nearly polar and 

the altitude is such that the satellite passes over all places on earth having the same 

latitude twice daily at the same local sun time. 

Supervised classification—Digital-information extraction technique in which the 

operator provides training-site information that the computer uses to assign pixels to 

categories. 

Tall shrub—Tall-growing shrub life form greater than 3.5 feet tall. 

Talus—A sloping accumulation of coarse rock fragments at the base of a cliff. 

Temperate—Geographically, the region between the polar and tropical regions; 

climatically, the region is moderate with distinct seasons of alternating long, warm 

summers and short, cold winters. 

Terraces—Floodplains and outwash plains removed from frequent flooding due to 

down-cutting of the river. 

Texture—Frequency of change and arrangement of tones on an image. 

Thematic Data—Thematic data layers in a data set are layers of information that 

deal with a particular theme. These layers are typically related information that 

logically go together. Examples of thematic data would include a data layer whose 

contents are roads, railways, and river navigation routes. 

Thematic Mapper (TM)—A cross-track scanner deployed on Landsat that records 

seven bands of data from the visible through the thermal IR regions. 
217 

Thermal Infrared—Phase used to describe the middle wavelength ranges in the 

infrared portion of the electromagnetic spectrum. Ranging between 3 microns and 20 

microns, most remote sensing applications utilize the 8- to 13-micron range. This is 

emitted energy whereas other infrared (near infrared) is reflected energy. 

Thermokarst—Refers to the collapse of the soil surface due to the thawing of ice 

rich permafrost, resulting in ponds and hills. 

TM—Thematic mapper. 

Topographic Map—Map that presents the horizontal and vertical positions of the 

features represented; distinguished from a plainimetric map by the addition of relief 

in measurable form. 

Topography—Configuration (relief) of the land surface; the graphic delineation or 

portrayal of that configuration in map form, as by contour lines; in oceanography the 

term is applied to a surface such as the sea bottom or a surface of given 

characteristics within the water mass. 

Training area—A sample of the Earth’s surface with known properties; the statistics 

of the imaged data within the area are used to determine decision boundaries in 

classification. 

Training site—Area of terrain with known properties or characteristics that is used in 

supervised classification. 

Treeline—A zone where the normal growth of trees is limited; cold temperatures 

often combined with drought form the upper or arctic treeline, and drought combined 

with hot temperatures form lower or arid treeline. 

Tundra—The treeless region north of the Arctic Circle (arctic tundra) or above the 

treeline of high mountains (alpine tundra) and on some sub-Antarctic islands; 

characterized by very low winter temperatures, short cool summers, permafrost below 

a surface layer subject to summer melt, short growing season, and low precipitation. 

Tussock—Graminoid life form consisting of bunch-like tufts, sometimes more than 1 

meter or 3 feet tall, in which the hard, old, withered leaves are intermingled with the 

fresh, young, green leaves. 

Type—A general term used in place of “vegetation type” or “alliance”. Plant 

associations are often referred to as “types”, but the term generally is not applied to 

alliances, and needs to be corrected in descriptions where it’s used. 
218 

Understory—General term that in these descriptions applies to the shrub and 

herbaceous layers of a vegetation type, as well as the tree regeneration layer. We have 

tried to use “shrub layer” or “herbaceous layer” in most cases, but understory is used 

in some places. “Undergrowth” is the more specific term used for shrub and 

herbaceous layers in forests or woodland vegetation types, and has been little used in 

these descriptions. 

Unsupervised classification—digital information extraction technique in which the 

computer assigns pixels to categories with no instructions from the operator. 

UV—Ultraviolet region of the electromagnetic spectrum ranging in wavelengths from 

0.01 to 0.4m. 

Vascular plant—Plant with water and fluid conductive tissue (xylem and phloem); 

includes seed plants, ferns, and fern allies. 

Water Tract—Many of the rolling hills and mountain sideslopes covered by tussock 

tundra have narrow water tracks running downslope. Water tracks are shallow 

depressions that have significantly greater water flow than the adjacent tussock 

tundra. 

Wet—Refers to sites where the dominant vegetation is emergent—not submerged or 

floating—and semi-permanent or standing water is present. 

Woody plant—Plant species life form with woody tissue and buds on that woody 

tissue near or at the ground surface or above; plants with limited to extensive 

thickening by secondary woody growth and with perennating buds; includes 

phanerophytes and chamaephytes of Raunkier. 

Woody—Containing lignified plant tissue. 

WRS-Worldwide Reference System—The WRS is a global indexing scheme 

designed for the Landsat program based on nominal scene centers defined by path 

and row coordinates. 

Xeromorphic—Describes plants with morphological and physiological characters 

that tolerate persistently low water availability, such as succulence, specialized leaf 

surfaces for light reflectance or water retention, opportunistic leaf growth, leaf-size 

reduction with increased thickness and sunken stomata, revolute margins, or stem and 

leaf modification to form thorns or spines. 



Appendix 2. The mean and range in elevation for field sampled polygons based on 

comparison with digital elevation model 

Landcover classes # of samples Mean Elev (ft) Min Elev (ft) Max Elev 

(ft) 

Dense-open white spruce forest 2 1,190 896 1,391 

Open spruce forest, unknown 15 0 0 0 

Open black spruce-like forest 16 1,284 322 2,743 

Open white spruce-like forest 27 1,568 466 2,822 

Spruce woodland 34 1,871 679 2,897 

Spruce-lichen woodland 11 1,773 735 2,759 

Closed paper birch-aspen forest 5 1,454 906 2,244 

Closed balsam poplar forest 4 910 804 1,168 

Open paper birch-aspen forest 3 1,209 787 1,604 

Open balsam poplar forest 4 1,525 801 1,801 

Closed spruce-broadleaf forest 7 1,343 302 2,225 

Open spruce-broadleaf forest 9 1,458 840 2,139 

Closed tall shrub 34 2,074 896 3,534 

Open tall shrub 45 2,103 653 4,029 

Shrub birch-willow-tussock 

tundra 52 2,310 610 3,363 

Shrub birch-ericaceous-willow 176 2,495 302 4,797 

Closed low willow 11 2,227 1,201 3,422 

Prostrate shrub-rock 45 3,569 1,030 5,423 

Prostrate shrub-lichen 10 3,062 1,549 4,157 

Prostrate shrub 127 2,975 1,604 5,030 

Dry herbaceous 0 0 0 0 

Mesic herbaceous 85 2,517 505 4,682 

Wet herbaceous 37 2,252 899 3,501 

Aquatic herbaceous 2 804 804 804 

Sparsely vegetated 22 4,068 1,762 5,430 

Bare-ground 24 3,241 607 5,985 

Silty water 7 1,580 577 1,703 

Clear water 15 1,446 679 3,248 

Snow/Ice 12 5,536 1,946 7,149 

Sand dunes 0 0 0 0 

Mosaic/patterned vegetation 0 0 0 0 

Shadow/indeterminate 0 0 0 0 

 A-4 











 






Appendix 9. List of plant species identified during ground sampling, 1998

Scientific Binomial Six Letter Code

Trees

Betula papyrifera BETPAP

Picea glauca PICGLA

Picea mariana PICMAR

Picea species PICEAX

Populus balsamifera POPBAL

Shrubs

Alnus crispa ALNCRI

Alnus incana ALNINC

Andromeda polifolia ANDPOL

Androsace chamaejasme ANDCHA

Arctostaphylos alpina ARCALP

Arctostaphylos rubra ARCRUB

Arctostaphylos uva-ursi ARCUVA

Artemisia alaskana ARTALA

Artemisia arctica ARTARC

Artemisia borealis ARTBOR

Artemisia glomerata ARTGLO

Betula glandulosa BETGLA

Betula nana BETNAN

Cassiope tetragona CASTET

Chamaedaphne calyculata CHACAL

Dryas integrifolia DRYINT

Dryas octopetala subspecies alaskensis DRYOCTALA

Empetrum nigrum EMPNIG

Ledum decumbens LEDDEC

Ledum groenlandicum LEDGRO

Loiseleuria procumbens LOUPRO

Oxycoccus species OXYCOC

Potentilla fruticosa POTFRU

Pyrola minor PYRMIN

Rhododendron lapponicum RHOLAP

Ribes triste RIBTRI

Rosa acicularis ROSACI

Rubus arcticus RUBARC

Salix myrtillifolia SALMYR

Salix species SALIXX

Salix alaxensis SALALA

Salix arbusculoides SALARB

A-23
Salix arctica SALARC

Salix barclayi SALBAR

Salix brachycarpa SALBRA

Salix chamissonis SALCHA

Salix fuscescens SALFUS

Salix glauca SALGLA

Salix lanata subspecies richardsonii SALLANRIC

Salix monticola SALMON

Salix novae-angliae SALNOV

Salix phlebophylla SALPHL

Salix planifolia subspecies pulchra SALPLAPUL

Salix reticulata SALRET

Salix rotundifolia SALROT

Shepherdia canadensis SHECAN

Spiraea beauverdiana SPIBEA

Vaccinium uliginosum VACULI

Vaccinium vitis-idaea VACVIT

Graminoids

Arctagrostis latifolia ARCLAT

Arctophila fulva ARCFUL

Bromus pumpellianus var. arcticus BROPUM

Bromus species BROMUS

Calamagrostis canadensis CALCAN

Calamagrostis lapponica CALLAP

Calamagrostis purpurascens CALPUR

Calamagrostis species CALAMA

Carex aquatilis CARAQU

Carex bigelowii CARBIG

Carex capillaris CARCAP

Carex dioica subspecies gynocrates CARDIOGYN

Carex filifolia CARFIL

Carex krausei CARKRA

Carex limosa CARLIM

Carex lugens CARLUG

Carex membranacea CARMEM

Carex microchaeta CARMIC

Carex misandra CARMIS

Carex obtusata CAROBT

Carex podocarpa CARPOD

Carex rariflora CARRAR

Carex rostrata CARROS

A-24
Carex rupestris CARRUP

Carex saxatilis CARSAX

Carex scirpoidea CARSCI

Carex species CAREXX

Carex tenuiflora CARTEN

Carex vaginata CARVAG

Elymus innovatus ELYINO

Eriophorum angustifolium ERIANG

Eriophorum russeolum ERIRUS

Eriophorum species ERIOPH

Eriophorum vaginatum ERIVAG

Festuca altaica FESALT

Festuca baffinensis FESBAF

Festuca brachyphylla FESBRA

Festuca rubra FESRUB

Festuca species FESTUC

Hierochloe alpina HIEALP

Juncus species JUNCUS

Juncus triglumis JUNTRI

Kobresia myosuroides KOBMYO

Luzula confusa LUZCON

Luzula groenlandica LUZGRO

Luzula multiflora LUZMUL

Luzula kjellmaniana LUZKJE

Luzula species LUZULA

Luzula tundricola LUZTUN

Poa arctica POAARC

Poa glauca POAGLA

Poa leptocoma POALEP

Poa pratensis POAPRA

Poa species POAXXX

Scirpus species SCIRPU

Trisetum spicatum TRISPI

Forbs

Aconitum delphinifolium ACODEL

Anemone drummondii ANEDRU

Anemone narcissiflora ANENAR

Anemone parviflora ANEPAR

Anemone richardsonii ANERIC

Anemone species ANEMON

Antennaria friesiana ANTFRI

A-25
Antennaria monocephala ANTMON

Arenaria capillaris ARECAP

Arnica alpina ARNALP

Arnica frigida ARNFRI

Artemisia tilesii ARTTIL

Aster sibiricus ASTSIB

Aster species ASTERX

Astragalus alpinus ASTALP

Astragalus species ASTRAG

Astragalus umbellatus ASTUMB

Bistorta plumosa BISPLU

Bistorta vivipara BISVIV

Boschniakia rossica BOSROS

Boykinia richardsonii BOYRIC

Boykinia species BOYKIN

Bupleurum americanum BUPAME

Bupleurum triradiatum subspecies arcticum BUPTRIARC

Caltha palustris CALPAL

Cardamine bellidifolia CARBEL

Cardamine digitata CARDIG

Cardamine hyperborea CARHYP

Caryophyllaceae family CARYOP

Castilleja species CASTIL

Castilleja elegans CASELE

Castilleja hyperborea CASHYP

Cerastium species CERAST

Chrysanthemum integrifolium CHRINT

Diapensia lapponica DIALAP

Dodecatheon frigidum DODFRI

Dodecatheon species DODECA

Draba alpina DRAALP

Epilobium angustifolium EPIANG

Epilobium latifolium EPILAT

Equisetum arvense EQUARV

Equisetum fluviatile EQUFLU

Equisetum pratense EQUPRA

Equisetum scirpoides EQUSCI

Equisetum species EQUISE

Equisetum variegatum EQUVAR

Eutrema edwardsii EUTEDW

Galium boreale GALBOR

Gentiana propinqua GENPRO

A-26
Geum glaciale GEUGLA

Geum species GEUMXX

Hedysarum alpinum HEDALP

Hedysarum hedysaroides HEDHED

Hippurus vulgaris HIPVUL

Lagotis glauca LAGGLA

Linnaea borealis LINBOR

Lomatogonium rotatum LOMROT

Lupinus arcticus LUPARC

Lupinus species LUPINU

Lycopodium alpinum LYCALP

Lycopodium annotinum LYCANO

Lycopodium selago LYCSEL

Melandrium apetalum MELAPE

Menyanthes trifoliata MENTRI

Mertensia paniculata MERPAN

Minuartia arctica MINARC

Minuartia elegans MINELE

Minuartia macrocarpa MINMAC

Minuartia obtusiloba MINOBT

Myosotis alpestris MYOALP

Oxytropis bryophila OXYBRY

Oxytropis campestris OXYCAM

Oxytropis koyukukensis OXYKOK

Oxytropis maydelliana OXYMAY

Oxytropis maydelliana OXYMAY

Oxytropis nigrescens OXYNIG

Oxytropis species OXYTRO

Oxytropis varians OXYVAR

Oxytropis viscida OXYVIS

Oxytropix scammaniana OXYSCA

Papaver macounii PAPMAC

Papaver macounii PAPMAC

Papaver radicatum PAPRAD

Papaver species PAPAVE

Parnassia kotzebuei PARKOT

Parnassia palustris PARPAL

Parrya nudicaulis PARNUD

Parrya species PARRYA

Pedicularis capitata PEDCAP

Pedicularis kanei PEDKAN

Pedicularis labradorica PEDLAB

A-27
Pedicularis lanata PEDLAN

Pedicularis lapponica PEDLAP

Pedicularis species PEDICU

Pedicularis sudetica PEDSUD

Pedicularis verticillata PEDVER

Petasites frigidus PETFRI

Petasites hyperboreus PETHYP

Phlox alaskensis PHLALA

Polemonium acutiflorum POLACU

Polemonium boreale POLBOR

Polemonium species POLEMO

Polygonum bistorta POLBIS

Polygonum species POLYGO

Potentill biflora POTBIF

Potentilla palustris POTPAL

Potentilla uniflora POTUNI

Pyrola asarifolia PYRASA

Pyrola grandiflora PYRGRA

Ranunculus species RANUNC

Ranunculus sulphureus RANSUL

Rumex arcticus SALARC

Saussurea angustifolia SAUANG

Saxifraga bracteata SAXBRA

Saxifraga bronchialis subspecies funstonii SAXBROFUN

Saxifraga calycina SAXCAL

Saxifraga davurica SAXDAV

Saxifraga eschscholtzii SAXESC

Saxifraga flagellaris SAXFLA

Saxifraga hieracifolia SAXHIE

Saxifraga hirculus SAXHIR

Saxifraga nelsoniana SAXNEL

Saxifraga nivalis SAXNIV

Saxifraga oppositifolia SAXOPP

Saxifraga punctata SAXPUN

Saxifraga punctata subspecies nelsoniana SAXPUNNEL

Saxifraga reflexa SAXREF

Saxifraga species SAXIFR

Saxifraga tricuspidata SAXTRI

Selaginella sibirica SELSIB

Senecia fuscatus SENFUS

Senecio atropurpureus SENATR 

Senecio lugens SENLUG

A-28
Senecio resedifolius SENRES

Senecio tundricola SENTUN

Silene acaulis SILACA

Silene acaullis SILACA

Smelowskia calycina SMECOL

Solidago multiradiata SOLMUL

Stellaria longipes STELON

Stellaria species STELLA

Thalictrum alpinum THAALP

Tofieldia coccinea TOFCOC

Tofieldia pusilla TOFPUL

Tofieldia species TOFIEL

Valeriana capitata VALCAP

Mosses

Calliergon stramineum CALSTR

Dicranum species DICRAN

Hylocomium splendens HYLSPL

Polytrichum species POLYTR

Sphagnum species SPHAGN

Lichens

Alectoria species ALECTO

Cetraria species CETRAR

Cladina rangiferina CLARAN

Cladina species CLADIN

Cladonia species CLADON

Coelocaulon species COELOC

Dactylina species DACTYL

Masonhalea richardsonii MASRIC

Nephroma species NEPHRO

Peltigera species PELTIG

Stereocaulon species STEREO

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Appendix 10b. Administrative Park Boundaries in the GAAR Study Area 
The Department of the Interior protects and manages the nation’s natural resources and cultural heritage; provides scientific and 

other information about those resources; and honors its special responsibilities to American Indians, Alaska Natives, and 

affiliated Island Communities. 

NPS D-48, October 1999
National Park Service 

U.S. Department of the Interior 

Natural Resource Program Center 

1201 Oakridge Drive, Suite 150 

Fort Collins, CO 80525 

www.nature.nps.gov 

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