期刊
ENVIRONMETRICS
卷 20, 期 2, 页码 206-220出版社
WILEY
DOI: 10.1002/env.924
关键词
complete randomness versus regularity; modeling of nearest-neighbor distance distributions; polygonal terrain landforms; randomization testing procedures; spatial point patterns
资金
- NSERC
- Canadian Space Agency's Analogue Research Network (CARN)
- Arctic Net [2.4]
In this paper, we explain the successive steps by which spatial point pattern analysis (SPPA) can be used to describe the variety of polygonal terrain morphologies observed both on Earth and on Mars. In this context, a point is defined as a polygon trough intersection with identifiable spatial coordinates. This definition corresponds to a key step in our approach: obtaining observed 2-D spatial point patterns from digitized images. The distribution of nearest-neighbor (NN) distances provides the quantitative basis Sought to characterize objectively the overall polygonal network geometry as completely random, regular, or intermediate. In the cases of regular geometry, the distribution of NN distances can be advantageously modeled, which completes the effectiveness of the statistical approach and method based on SPPA. Copyright (C) 2008 John Wiley & Sons, Ltd.
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