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Point Pattern Analysis: A Quantitative Geographical Approach to the Understanding of Landform Distributions

Wednesday, March 7, 2007
Bishop (PSI and University of South Australia)

Landform analysis within a geographical information system (GIS) is an abstract concept. In the case of point pattern analysis (ppa) this abstraction involves the representation of 4-D features as events with zero dimensionality. Such abstract recognition may be useful in landscape interpretation where time coupled with degradation, erosion and burial takes a significant toll on the geometry, relief and identity of landforms, and where landscape is inaccessible as with extra-terrestrial surfaces. Thus regional interpretation and the spatial statistical methods used to describe landform dispersion, orientation, and pattern are often most reliant on point data. For example, the geographic signature of Martian dune distribution and self- organization as measured by the R-statistic offers a viewpoint on the geography of crescentic eolian systems and proposes an index from which to determine the degree of self-organization across a variety of spatial scales. Fields of simple dunes (dome, barchan, barchan-seif) are comparatively less regular in distribution than are those fields, or part thereof, that consist of compound (barchanoid) morphologies whose patterns are more highly dispersed (regular). Likewise, spatial analysis has shown the distribution and pattern of a sample of terrestrial volcanic fields to be heterogeneous, anisotropic and not completely spatially random, and offers through the exploration of point dispersion, orientation, and pattern, a viewpoint on the geography of low-volume, basaltic monogenetic volcanic systems. Geographic point signatures, therefore, are in themselves a tool that can further interpret and understand regional landscapes across a variety of scales, and which may offer a parameter that is useful in the identification of like-structures and process mechanisms within a comparative planetary context.

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