Optimum sampling scheme for characterization of mine tailings

Author

Debba, P. ; Carranza, E.J.M. ; Stein, A. ; Van Der Mee, F.D.

Author_Institution

Council for Sci. & Ind. Res., CSIR Built Environ., South Africa

Volume

4

fYear

2009

fDate

12-17 July 2009

Abstract

The paper describes a novice method for sampling geochemicals to characterize mine tailings. We model the spatial relationships between a multi-element signature and, as covariates, abundance estimates of secondary iron-bearing minerals in mine tailings dumps. The covariates of interest, are readily, but less accurately obtainable by using airborne hyperspectral data and estimated through spectral unmixing. Via simulated annealing an optimal prospective sampling scheme for a new unvisited area is derived based on the variogram model of a previously sampled area.

Keywords

geochemistry; geophysical techniques; minerals; remote sensing; sampling methods; Hungary; Recsk-Lahoca copper mining area; airborne hyperspectral data; external drift kriging; geochemical characterization; iron-bearing minerals; mine tailings dumps; multi-element signature; optimum sampling scheme; remote sensing; variogram model; Copper; Councils; Hyperspectral imaging; Hyperspectral sensors; Industrial relations; Minerals; Remote sensing; Sampling methods; Spectroscopy; Tail; Sampling; external drift kriging; hyper-spectral; mine tailings; remote sensing; unmixing; variogram;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009

Conference_Location

Cape Town

Print_ISBN

978-1-4244-3394-0

Electronic_ISBN

978-1-4244-3395-7

Type

conf

DOI

10.1109/IGARSS.2009.5417522

Filename

5417522