Echelon approach to areas of concern in synoptic regional monitoring

Wayne Myers; Ganapati P. Patil; Kyle Joly

doi:10.1023/a:1018518327329

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Echelon approach to areas of concern in synoptic regional monitoring

Wayne Myers·Ganapati P. Patil·Kyle Joly

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Abstract

Echelons provide an objective approach to prospecting for areas of potential concern in synoptic regional monitoring of a surface variable. Echelons can be regarded informally as stacked hill forms. The strategy is to identify regions of the surface which are elevated relative to surroundings ( R elative ELEVATIONS or RELEVATIONS ). These are areas which would continue to expand as islands with receding (virtual) floodwaters. Levels where islands would merge are critical elevations which delimit echelons in the vertical dimension. Families of echelons consist of surface sectors constituting separate islands for deeper waters that merge as water level declines. Pits which would hold water are disregarded in such a progression, but a complementary analysis of pits is obtained using the surface as a virtual mould to cast a counter-surface (bathymetric analysis). An echelon tree is a family tree of echelons with peaks as terminals and the lowest level as root. An echelon tree thus provides a dendrogram representation of surface topology which enables graph theoretic analysis and comparison of surface structures. Echelon top view maps show echelon cover sectors on the base plane. An echelon table summarizes characteristics of echelons as instances or cases of hill form surface structure. Determination of echelons requires only ordinal strength for the surface variable, and is thus appropriate for environmental indices as well as measurements. Since echelons are inherent in a surface rather than perceptual, they provide a basis for computer-intelligent understanding of surfaces. Echelons are given for broad-scale mammalian species richness in Pennsylvania.

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Wayne Myers, Ganapati P. Patil, Kyle Joly. 1997. Echelon approach to areas of concern in synoptic regional monitoring. https://doi.org/10.1023/a%3A1018518327329

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