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DECEMBER 2015 • VOLUME 21, NUMBER 3 International Journal of Wilderness 35
Assessing Wilderness Values
The Tasmanian
Wilderness World Heritage Area, Australia
BY MARTIN HAWES, ROGER LING, and GRANT DIXON
INTERNATIONAL PERSPECTIVES
Introduction
e values associated with wilderness are diverse and
sometimes subtle, and cannot be fully accounted for in
quantitative terms (Landres et al. 2008). For example,
no amount of data can fully convey the ecological signif-
icance of a pristine landscape, nor can one measure the
sense of awe that a visitor might feel when standing in its
midst. It is nevertheless possible to identify some of the
key physical and geographical attributes that are necessary
and sucient for an area to qualify as wilderness, and to
a large extent it is possible to quantify these attributes.
Assessments based on such measurements can be used to
estimate the extent and quality of existing or potential
wilderness across a given region and can be a useful tool
for protecting, maintaining, and enhancing wilderness
values. In this article, the term wilderness value will be used
to denote the extent to which a place or region exhibits
key physical and geographical attributes that may dene
it as wilderness.
A number of wilderness-assessment methodologies
have been developed, ranging from simple area-counts
to complex algorithms that take a wide range of factors
into account. In the United States, for example, map-
ping methodologies have been developed to monitor and
manage wilderness character, based on indicators such as
untrammeled quality and remoteness from occupied areas
(Landres et al. 2008; Tricker et al. 2013). While some
methodologies take account only of geographical condi-
tions such as the location of roads, others incorporate
subjective assessments contributed by wilderness users
and/or the general public (Kliskey and Kearsley 1993;
Carver et al. 2002).
In the mid-1980s the Australian Heritage Commis-
sion developed a wilderness-assessment methodology as
the basis for a nationwide wilderness inventory (Lesslie
and Maslen 1995). e National Wilderness Inventory
(NWI) methodology identies remoteness and natural-
ness as the key components of wilderness value, dening
Martin Hawes. Grant Dixon.
Roger Ling.
36 International Journal of Wilderness DECEMBER 2015 • VOLUME 21, NUMBER 3
remoteness as distance from human
structures and disturbances such
as buildings, dams, and logging
areas. Rather than attempting to
distinguish wilderness from nonwil-
derness, the methodology assesses
wilderness value as a continuum
ranging from urban to pristine. e
methodology was used to assess wil-
derness value across Tasmania and
other parts of Australia in the late
1980s and 1990s, and it has since
formed the basis for several studies
in Europe (Henry and Husby 1995;
Carver et al. 2002).
Although the NWI method-
ology is the most comprehensive
wilderness-assessment methodology
yet developed in Australia, it has
some deciencies. In particular, it
takes no account of the inuence
of terrain and vegetation on access
remoteness. In an attempt to address
this deciency, British researchers
Fritz and Carver (1998) developed an
algorithm for taking walking times
into account, based on assumptions
about walking speeds across dif-
ferent gradients of terrain. Similar
algorithms have been employed in
subsequent wilderness-value surveys
(e.g., Tricker et al. 2013).
e current study focused on
the Tasmanian Wilderness World
Heritage Area (TWWHA) – a
1.4-million hectare (3.5 million
acre) region (expanded to 1.6 mil-
lion hectares in 2013 since this
study was undertaken) that encom-
passes one of the last great tracts
of temperate wilderness on Earth
(Parks and Wildlife Service 1999).
It is a wild and largely undeveloped
(i.e., free of the impacts and infra-
structure of modern civilization)
part of Tasmania, Australia’s island
state, containing a range of natural
and indigenous cultural values that
led to the listing as a World Heri-
tage Area in 1982. e landscape
includes formerly glaciated moun-
tain ranges, thickly forested valleys,
open plains, and an extensive rug-
ged coastline. While it contains in
excess of 1,300 kilometers (808
miles) of mostly rough walking
tracks (trails), much of the coun-
try is untracked. e area hence
provides some of the best opportu-
nities for self-reliant recreation in
the Australasian region.
Prior to the NWI assessment, at
least two attempts had been made
to assess the wilderness values of the
region that is now the TWWHA.
Kirkpatrick and Haney (1980)
calculated wilderness values across
a 4 kilometer x 4 kilometer (2.49
mile x 2.49 mile) grid (rened to 2
km x 2 km [1.24 mile x 1.24 mile]
where boundaries were complex).
ey dened wilderness value as
a function of the remoteness and
biophysical primitiveness of each
square, and dened remoteness as
the time required to access the loca-
tion on foot. Hawes and Heatley
(1985) took a simpler approach,
dening wilderness as land more
than eight kilometers (4.97 miles)
(nominally a half walking day) from
the nearest roads, dams, and similar
disturbances. Using this denition
they assessed the potential impact
on wilderness of projected logging
operations in areas adjacent to the
then recently listed TWWHA. e
NWI approach was applied state-
wide in 1995 as part of a process
(the Regional Forest Agreement)
to identify areas that qualied for
reservation from future industrial-
scale logging. is 1995 assessment
formed the comparative baseline for
the current study.
e rst objective of the current
study was to assess the changes in
wilderness value that had occurred
across the TWWHA since 1995 by
reapplying the NWI methodology
(as described below) to the region
using updated geodata. e second
objective was to repeat the assess-
ment of current wilderness value
using a revised methodology that
was designed to address some of the
deciencies mentioned earlier.
No attempt was made in this
study to assess the impact of view-
eld disturbances, although it was
acknowledged that development
of such a technique could enhance
future wilderness-value mapping.
Measuring Wilderness Values
Using the NWI Methodology
Component Variables of Wilder-
ness Value
In the NWI methodology, the
variable Wilderness Value (WV)
is assigned to each square in a grid
covering the region of interest. e
grid resolution can be selected to
suit the size of the region and the
resources available for the analysis. A
1 kilometer (0.62 mile) grid was used
for this study (see Map 1).
Wilderness Value was mea-
sured as the sum of four variables:
Remoteness from Settlement (RS),
Remoteness from Access (RA),
Apparent Naturalness (AN), and
Biophysical Naturalness (BN). e
rst three of these variables are
distance based, the value assigned
The NWI methodology
remains the most
comprehensive system
yet employed for
quantitatively assessing
wilderness value in
Australia.
DECEMBER 2015 • VOLUME 21, NUMBER 3 International Journal of Wilderness 37
to each grid square depending
on the remoteness of the square’s
center from specied types of geo-
graphical features. Each category
of geographical feature is assigned
a weighting to reect its relative
impact on wilderness values. For
example, it is assumed that roads
have substantially greater impact
on wilderness values than walking
tracks (trails). In the formula for
calculating Remoteness from Access
(RA), walking tracks and roads are
weighted so that the impact of a
walking track one kilometer (.62
mile) distant is equivalent to that
of a major road 9 kilometers (5.59
miles) distant.
e relationship is illustrated
in Figure 1; the curves illustrate the
formulas used to calculate Remote-
ness from Access as a function of
distance from various geographic
features. For example, a location 5
kilometers (3.11 miles) from a walk-
ing track would have an RA value of
approximately 7. If the point were
also 10 kilometers (6.21 miles) from
a major road, its RA value would be
reduced to 4.
Remoteness from Settlement
is a function of the minimum map
distance from towns and smaller
settlements, weighted according to
population. Apparent Naturalness,
which is a measure of how “wild” or
“undeveloped” an area might seem to
a visitor, is a function of the distance
from the nearest nonnatural features
such as roads, impoundments, and
transmission lines.
Biophysical Naturalness values
are determined by environmental
conditions (such as logging and graz-
ing history) within each square and
measured on a scale of 1–5 with val-
ues determined by a list of condition
classes.
e study area encompassed the
entire TWWHA (as per its 2005
boundaries), together with adjacent
areas that were largely free of major
development features such as dams
or roads. Wilderness values within
the study area were calculated using
data on geographical features located
within a 30-kilometer (18.6 mile)
radius of the area.
Data Sources
e primary data source for the
study was the Tasmanian govern-
ment’s GIS database, which contains
geodata on roads, impoundments,
vegetation types, and a wide range
of other geographical features.
ese data were supplemented
by information from a variety of
sources, including satellite imagery
and local knowledge. For example,
some clearfelled (clear-cut) areas
that were visible on satellite images
but not recorded on available GIS
layers were manually traced from
georeferenced satellite imagery using
Map 1 – Distribution of wilderness values in 2005 calculated using the National Wilderness Inventory
(1995) methodology; 1-kilometer (.62 mile) grid. The maps show the TWWHA boundary in 2005, at the
time the study was undertaken. As noted in the text, the reserve was expanded somewhat in 2013.
38 International Journal of Wilderness DECEMBER 2015 • VOLUME 21, NUMBER 3
the MapInfo polygonal drawing
tool. Most of the data sources were
known to have been current in 2002
or later.
e analysis was undertaken
using MapInfo Professional software
and the scripting language MapBa-
sic. e latter was used to calculate
the minimum distance from the
centroid of each grid square in the
study area to the nearest relevant
point, polyline, or polygonal distur-
bance feature (such as a road or an
area of logged forest). e calcula-
tion was made by creating a small
circular search zone around each
centroid, and progressively increas-
ing the radius of the zone until the
relevant feature was found.
e authors had access to the
output data from the 1995 analysis,
but not to the geodata on which this
analysis was based. Hence it was pos-
sible to compare the wilderness value
measured in 1995 and 2005, but it
was not possible to explain all the
observed dierences.
Developing a Modified
Wilderness-Assessment
Methodology
Rationale for Modifying the
Methodology
As noted earlier, the NWI methodology
has a number of shortcomings. e
principle shortcomings are:
1. Remoteness of Access as dened
under the NWI system is not
a reliable indicator of the time
required to access o-road areas
because it takes no account
of terrain, vegetation, or the
standard of walking tracks. For
example, two locations 5 kilo-
meters (3.11 miles) from the
nearest road can have the same
RA rating, even though one
may be accessed in a couple of
hours across open country and
the other may take days to reach
through Tasmania’s notoriously
dense vegetation.
2. e weightings assigned to some
categories of geographical feature
under the NWI methodology
are arguably inappropriate. For
example, a walkers’ hut (cabin)
has the same impact locally on
wilderness value as a major road
or hydroelectric impoundment.
Details of the Modifications
e primary modication was to
replace the variable Remoteness of
Access with a new variable, Time
Remoteness (TR), dened as the
shortest nonmechanized traveling
time from points and corridors of
mechanized access. It is possible to
write computer algorithms to calculate
Time Remoteness using GIS data on
vegetation types, terrain slopes, and
typical walking speeds (e.g., Tricker et
al. 2013). However such algorithms
can never be entirely reliable because
they cannot take account of local
(unmapped) factors such as variations
in the density of forest understory
and the impassability or otherwise
of steep terrain. ey also require
computing resources beyond those
available for the current study (Fritz
and Carver 1998).
Time Remoteness was therefore
assessed manually by the authors,
using map-based information sup-
plemented by their own rsthand
knowledge of the TWWHA. e
risk of bias in this approach was con-
sidered to be adequately minimized
by the fact that each of the authors
had walked extensively throughout
the region over a period of 40 years.
Specically, the authors identied
“contours” of access remoteness that
were respectively half a day, one day,
and two days remote by foot or raft
from the nearest point of mechanized
access, thereby dividing the region
into four zones that were subsequently
assigned numerical TR values.
Changes were also made to the
weighting conventions for RS and
AN to correct the anomalies noted
Figure 1 – Remoteness from Access varies according to the map remoteness from different types of
geographic features. For example, a location 15 kilometers (9.32 miles) from a helipad (indicated by
the red dot) would have an RA rating of approximately 7.
DECEMBER 2015 • VOLUME 21, NUMBER 3 International Journal of Wilderness 39
Map 2 – Change in wilderness values that have occurred between 1995 and 2005, calculated using the National Wilderness Inventory (1995)
methodology; 1 kilometer (.62 mile) grid.
40 International Journal of Wilderness DECEMBER 2015 • VOLUME 21, NUMBER 3
in (2), earlier. For example, small
settlements were given slightly lower
weightings relative to large towns.
e variables Remoteness from
Settlement and Apparent Natural-
ness were redened as functions
that increase asymptotically to 5
as remoteness increases. Using this
approach, changes in wilderness
value can be analyzed even in very
remote areas because the “perfect”
value of 20 can never be reached.
Results
Assessment of Current (2005)
Wilderness Values Using the NWI
Methodology
Map 1 shows the distribution of
current wilderness values using the
NWI methodology. For the sake of
simplicity, Maps 1–3 show only major
roads and towns. Wilderness Values of
less than 10 have been combined as a
single group because they correspond
to areas of low to very low wilderness
value and are of less interest in terms
of wilderness management.
Map 1 reveals that a substantial
part of the entire region has wilder-
ness value in the range of 18–20,
the highest category under the NWI
system. Areas with lower wilderness
value are located mainly around the
fringes of the region.
Note the dramatic impact of
hydroelectric impoundments, such
as the two large impoundments near
the center of the map, and of the
Lyell Highway, which dissects the
region along an east-west axis. Note
also the impact of walking tracks,
which account for the corridors of
lighter shading in some of the more
remote areas.
e isolated but substantial
“holes” in regions of high wilderness
value are mainly due to the presence
of remote buildings. e large area of
low wilderness value in the southwest
corner of the region is due to the
presence of a settlement that includes
buildings, a mine, and an airstrip.
Comparison of Wilderness Values,
1995–2005
Map 2 shows the changes in wilderness
value that occurred between 1995
and 2005. No signicant losses
or gains in Wilderness Value were
recorded in areas shaded with neutral
gray. e darker red areas recorded a
reduction in WV of at least 5, and
the darker green areas recorded an
increase of at least 5.
Most of the wilderness losses cor-
respond to known developments such
as recent tourist infrastructure or the
expansion of walking tracks. Some
apparent losses appear to be explained
by the omission of features such as
vehicle tracks from the original 1995
dataset. (Since the dataset is unavail-
able, this cannot be conrmed.)
Most of the gains in Wilderness
Value can be explained by the closure,
Map 3 – Distribution of wilderness values in 2005 using the revised methodology described herein; 1
kilometer (.62 mile) grid. Note the zones in this map cannot be directly compared to those in Map 1, as
they have been derived by a different methodology.
DECEMBER 2015 • VOLUME 21, NUMBER 3 International Journal of Wilderness 41
removal, or natural reclamation of
features such as vehicle tracks, air-
strips, and huts.
Assessment of Current (2005) Wil-
derness Values Using the Revised
Methodology
Map 3 shows the current distri-
bution of Wilderness Values across
the TWWHA as measured by the
revised methodology. Note that
because they were derived by a
dierent methodology, the zones in
this map cannot be directly compared
to those in Map 1. While the overall
picture is not greatly dierent from
that obtained using the original
NWI methodology, closer inspection
reveals signicant dierences.
One dierence is that the revised
methodology indicates higher impacts
due to major articial features such
as roads and impoundments, and
lower impacts due to buildings and
low-grade walking tracks. Also in the
revised methodology, powered-boat
access has a major impact on wilder-
ness values on the west and southwest
coast because points on coastlines
where powered boats can easily put
ashore are assigned a Time Remote-
ness value of zero.
In some areas, signicant changes
in the distribution of Wilderness
Value are evident as a result of the
inclusion of vegetation and terrain in
the calculation of Time Remoteness.
e greatest disparity between Time
Remoteness and Remoteness from
Access occurs in the northeast of the
study area, where walking speeds are
generally quite fast (due to the rela-
tive openness of country in this area).
Discussion
e NWI methodology remains
the most comprehensive system yet
employed for quantitatively assessing
wilderness value in Australia.
e main advantage of using the
methodology in its original form
is that this allows comparison with
studies that have used the same
methodology, either in other areas or
in the same area at a dierent time.
e revised methodology pro-
posed in this article corrects several
shortcomings of the NWI method-
ology. In particular, the replacement
of Access Remoteness with Time
Remoteness highlighted the impact
of mechanized boat access and
deemphasized the impact of minor
walking tracks on Wilderness Value.
If sucient resources were avail-
able, automating the assessment of
Time Remoteness would increase
the reproducibility of this variable.
is approach has been adopted, for
example, by Tricker et al. (2013) and
Carver et al. (2013). However, the
accuracy and reliability of automated
calculations will depend on the
extent to which available data such
as vegetation type and terrain maps
can be interpreted to estimate typical
walking speeds.
An important caution for any
approach to wilderness mapping
utilizing spatial data, highlighted by
Tricker et al. (2013), is to be mind-
ful of the source data (e.g., accuracy,
completeness, and scale of any GIS
layer) when considering any resul-
tant wilderness quality maps. It is
also important to note that maps
such as those derived in this study
do not necessarily represent the less
tangible or more personal qualities of
wilderness, the perception of which
inevitably varies with the individual.
e NWI and revised methodol-
ogies are based solely on geographical
data. However, both methodologies
inevitably involve subjective deci-
sions about the inuence of factors
such as accessibility and naturalness.
In future studies it may be pos-
sible to make this subjectivity more
explicit by allowing wilderness users
and other interested parties to assign
their own weightings to identied
components of wilderness value
(such as the impact of huts, tracks,
or roads), as proposed by Carver et
al. (2002) and other researchers, but
this approach does not yet seem to
have been pursued.
e wilderness concept, and wil-
derness-value mapping in particular,
has to some extent fallen out of favor
in Australia in recent years. Sawyer
(2015) postulates various reasons for
this, ranging from a narrowing view
of the rationale for conservation by
ecologists to its inconvenience for
various political agendas. Neverthe-
less public concern for wilderness
remains strong, as shown by the
controversy generated by the 2014
release of a draft management plan
for the TWWHA (ABC News 2015)
that deemphasizes wilderness and
greenlights mechanized access and
tourism development in remote areas
(DPIPWE 2014). Perhaps partly
in response to this controversy, the
Tasmanian government has now
embarked on a program to remap the
wilderness values of the TWWHA.
In a global context the impor-
tance of wilderness remains widely
recognized. Wilderness has been
assigned its own category under
IUCN’s classication system for pro-
tected areas (Dudley et al. 2012), and
wilderness preservation is an explicit
management objective for many
national parks and similar reserves
around the world (Suh and Harrison
2005). As a tool for objectively assess-
ing the likely impact of proposed
developments on wilderness quality,
and for determining the extent and
condition of the planet’s remaining
Continued on page 48
48 International Journal of Wilderness DECEMBER 2015 • VOLUME 21, NUMBER 3
wilderness areas, wilderness mapping
has the potential to play an impor-
tant role in achieving this objective.
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MARTIN HAWES is a Tasmanian-based
wilderness and walking tracks (trails)
management consultant, who spends
much of his spare time walking off-track;
email martin@twelveprinciples.net.
ROGER LING is a spatial analyst at the
Parks and Wildlife Service, enjoying the
geochallenges of the Tasmanian bush;
email roger.ling@parks.tas.gov.au.
GRANT DIXON has worked on
backcountry management issues for the
Tasmania Parks and Wildlife Service for
more than 26 years but is embarking on
a new life and spending more time in
the wilderness; email grantdixon@iinet.
net.au.
