National Wilderness Inventory
Australia: Our national stories
Australian Heritage Commission, 2003
ISBN 0 642 23561 9
4. Creating The Wilderness Database (continued)
4.2 Distance-based Indicators
(Remoteness from Access, Remoteness from Settlement, and Apparent Naturalness)
As discussed in Section 2.1, wilderness survey work is implemented by measuring variation in wilderness quality across the landscape using four wilderness quality 'indicators' that represent the two essential attributes of wilderness: remoteness and naturalness.
Three of these 'indicators' are derived in a similar manner and get their collective name, distance-based 'indicators', from the process used to derive them.
These indicators are:
- Remoteness from Settlement
remoteness from places of permanent occupation;
- Remoteness from Access
remoteness from established access routes;
- Apparent Naturalness
the degree to which the landscape is free from the presence of permanent structures associated with modern technological society;
This section of the handbook describes the processes used to create the results for these three distance-based indicators used in the wilderness analysis. The process of creating these results are similar, and standardised across Australia. Because of this, any variation in the quality and consistency of results for these indicators generally relates back to characteristics of the primary data which are described more fully in other parts of this handbook.
For each of the distance-based indicators primary data is graded according to its associated amount of impact. Remoteness from Access and Remoteness from Settlement take into account four grades of impact whilst three grades are used in determining Apparent Naturalness. Descriptions of these grades are presented in Table 4.1. The primary data codes and associated grouped feature coverages are detailed in Section 3.4.
|Grade||Primary data description||Grouped Primary Data Coverage|
|Remoteness from Access||Major||Major two-wheel drive roads: generally sealed or at least surfaced to ensure regular and continuous public use||ACC1|
|Medium||Minor roads: generally unsurfaced, or, if surfaced, then irregularly used and maintained. Also included are constructed and maintained airstrips and operating railways.||ACC2
|Low||LowVehicle tracks (usually four-wheel drive).||ACC3|
|Very Low||Established but unconstructed vehicle access routes (e.g. beach access) and cleared lines; established walking tracks; cleared land.||ACC4
|Remoteness from Settlement||Major||Built-up areas and commercial and/or service location with 100 permanent residents or more.||SET1
|Intermediate||Commercial and/or service location with more than ten but fewer than 100 permanent residents.||SET2|
|Minor||Commercial and/or service location with ten permanent residents or fewer.||SET3|
|Residential||Residential location only.||SET4|
|Apparent Naturalness||Major||Intrusive infrastructure (including medium and high grade access routes) and cleared land boundaries||AES1LN
|Medum||Small-scale infrastructure (including four-wheel drive||AES2LN
The analysis process for deriving the three distance-based indicators is outlined below, as a sequence of four steps.
i) Grading primary feature impacts:
Point, line and polygon primary data features are drawn from the appropriate layer in the library manager and grouped in coverages according to feature type and indicator impact grade (outlined in Table 3.6). The association between these grouped coverages and each indicator grade is outlined in Table 4.1.
ii) Distance Calculation:
Euclidean distance (in metres) is calculated from each sample point to the nearest feature within each grouped feature coverage. The nearest distance, in each case, is assigned to each sample point in the database as a permanent attribute.
iii) Minimum Weighted Distance Calculation:
Raw distance values are processed to produce a single indicator distance measure for each sample point. This distance is calculated by weighting the distance values for each grouped feature according to its associated grade of impact so that all distances are represented in units equivalent to a high grade feature. The equation for determining high grade equivalence takes the form:
Note: refer to Table 4.2
|Feature Grade||Weighting Factor|
|Remoteness from Settlement
|Remoteness from Access
Very Low Access
The minimum value for each indicator (mHGE) is recorded for each sample point and recorded as permanent attributes in the wilderness database (refer to Table 4.9).
iv) Indicator Classification:
Minimum high grade feature distances are classified to produce a standardised Remoteness from Settlement, Remoteness from Access, and Apparent Naturalness class according to the following equation:
The resultant classification of the three indicators is shown in Figure 4.3. These distance-based classifications are recorded as continuous floating point variables thus showing variation within class groupings as well as class values beyond the class 5 notional maximum. Remoteness from Settlement, Remoteness from Access, and Apparent Naturalness index values are assigned to sample points in the database as permanent attributes (refer to Table 4.9).