Catchment basin modelling of stream sediment anomalies revisited: incorporation of EDA and fractal analysis

被引:104
作者
Carranza, Emmanuel John M. [1 ]
机构
[1] Int Inst Geoinformat Sci & Earth Observat ITC, Dept Earth Syst Anal, NL-7500 AA Enschede, Netherlands
关键词
local background; geochemical residuals; downstream dilution; exploratory data analysis; concentration-area fractal analysis; spatial data integration; GIS; Aroroy (Philippines); EXPLORATION GEOCHEMISTRY; THRESHOLD ESTIMATION; DOWNSTREAM DILUTION; DISTRIBUTIONS; DRAINAGE;
D O I
10.1144/1467-7873/09-224
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
This paper revisits catchment basin modelling of stream sediment geochemical anomalies with regard to two aspects: (1) standardization of uni-element residuals derived from analysis of a number of subsets of stream sediment geochemical data in order to obtain a single set of uni-element residuals for classification of anomalies; and (2) objective classification of anomalies in dilution-corrected uni-element residuals and in derivative scores representing multi-element associations. These two aspects of catchment basin modelling of stream sediment geochemical anomalies were examined in the Aroroy epithermal-Au district (Philippines). For the first aspect, the results of the case study show that, for the standardization of dilution-corrected uni-element residuals per data subset in order to derive a single set of dilution-corrected uni-element residuals for classification of anomalies, the application of robust statistics in exploratory data analysis is preferable to the application of classical statistics in confirmatory data analysis. For the second aspect, the results of the case study show that anomalies in standardized dilution-corrected uni-element residuals and in derivative scores representing multi-element associations can be identified objectively by application of the concentration-area fractal analysis. The results of the case study further show that the area of individual sample catchment basins is useful in GIS-based screening of significant anomalies by integrating derivative geochemical variables with fault/fracture density, which was estimated as the ratio of number of pixels representing faults/fractures in a sample catchment basin to number of pixels in the same sample catchment basin.
引用
收藏
页码:365 / 381
页数:17
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