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Inadequacies of indices

Redundancy
Transfer of indices
Indeterminate boundaries

Many indices may be necessary to cope with the different data types and formats that are commonly used in landscape studies but there are still inadequacies.


Redundancy

Riitters et al. (1995) show that a lot of the indices are highly intercorrelated. This is because there are basically only a few measures that can be made from land cover maps, so what we end up with is redundancy and replication in some landscape indices.

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Transfer of indices

Most of the indices widely used today were developed on, and applied to data sets in North America and there are problems in applying them to other areas.

Hulsoff (1995) looked at pattern indices such as land use type, patch number, mean patch size, patch shape and dominance, and change indices. She found that not all the indices widely used in North America were suitable for application in Dutch landscapes.

This means that different indices or measures may be necessary for different landscape types.


Indeterminate boundaries

Most of the indices so far are assessments of patch geometry. These are useful metrics of landscape structure provided boundaries between landscape elements can be clearly identified, like Kellerberrin. Problems arise however, when the landscape takes the form of a continuum with landscape features grading into one another, eg in the New England tablelands.

Defining objects in this situation is difficult. One solution is to treat the landscape as a series of gradients rather than discrete objects and to apply a range of texture measures derived from image processing. These can be used with remotely sensed data or data that exists as surfaces. This constitutes a move away from patch theory and could be a good way of measuring landscape structure in landscapes, such as those found in Northern Australia.

Texture refers to 'the spatial variation in brightness values within a region of an image' (Haines-Young and Chopping, 1996). Descriptors of texture include properties such as:

Other measures that could be used are ones based on spatial statistical analysis, for example spatial autocorrelation (Pearson, 1998).

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Do this - Identify appropriate measures - Why?
Would the same measures be appropriate in studying Kellerberrin and New England? Identify what would be best in each location.

More?
A good article providing more information on indices is Reading 1.5 written by Haines-Young and Chopping.

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