GEOSCAN, résultats de la recherche


TitreA method for detecting glacial dispersal trains in till geochemical data
AuteurHarris, J R; Bonham-Carter, G F
SourceGeochemistry: Exploration, Environment, Analysis 3, 2, 2003 p. 133-155,
Séries alt.Commission géologique du Canada, Contributions aux publications extérieures 2002046
ÉditeurGeological Society of London
Documentpublication en série
Mediapapier; en ligne; numérique
Sujetsprofils de dispersion; dépôts glaciaires; tills; analyses de till; géochimie du till; prospection minière; analyses géochimiques; applications par ordinateur; système d'information géographique; traînées de dispersion; géomathématique; géologie économique
Illustrationsgraphs; sketch maps; tables
Diffusé2003 05 01
Résumé(disponible en anglais seulement)
A new algorithm for identifying potential glacial dispersal trains in till geochemical data is introduced. The algorithm, referred to as the dispersal train identification algorithm (DTIA), requires a set of user input parameters used for simulating dispersal train characteristics. The algorithm employs a succession of wedge-shaped search regions (each one shaped like an isosceles triangle with the search point at the principal vertex) to "look" in user-specified directions from a set of search points that may be mineral prospects, geochemical anomalies in rock or a homogeneous grid of points. The values of the till sample points occurring within the wedge are analysed as candidates for a dispersal train using a set of criteria. The geologist specifies the length and angle of the wedge, where the length reflects the distance of down-ice dispersal and the angle is used to model a ribbon or fan-shaped dispersal train. For each search position, DTIA calculates the average of the values within the wedge (pmed), the difference between wedge average and the local average (diff), and fits an exponential model to the within-wedge points (geochemical value as a function of distance from the search point). Candidate search points for the heads of dispersal trains are selected based on high values of pmed and diff, as well as best fit lines (fitted to the natural logarithms of geochemical values) that show high negative slopes (b), significant values of a test statistic for the slope magnitude (ts), and large negative correlation coefficients (R). The slope statistic, ts, is particularly useful in identifying candidate trains, but care must be taken to eliminate situations where the closest sample point is relatively far from the search point.
DTIA was tested on two datasets: a dataset in Cape Breton where documented till dispersal trains exist and in the Swayze greenstone belt where no documented trains are known. The effects of varying the input parameters (e.g. length, angle and direction of wedge) were studied as well as different search strategies with the objective of identifying the most appropriate parameters for successfully identifying points that represent the heads (or source zones) of potential till dispersal trains.
The algorithm performed well with the Cape Breton data. The results are particularly sensitive to both direction of search and the wedge angle. By systematically searching from a set of grid points, then screening out search points (and associated directions) that have (1) pmed values less than a threshold, (2) diff values less than a threshold, (3) distance of point closest to search point less than a threshold, (4) slope values less than zero and (5) ts values usually less than -2.0,a suite of candidate search points can be plotted on the till geochemical map, colour coded by search direction. These candidate points (and associated wedges) can then be visually appraised as potential dispersal trains.
Application to the Swayze data revealed candidate trains whose directions are consistent with glacial transport directions known from data on glacial striations. Although this method shows promise as a data exploration tool, more work is needed to improve the algorithm and to test it under a greater range of conditions.