DSpace
 

Researchspace >
General science, engineering & technology >
General science, engineering & technology >
General science, engineering & technology >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/4016

Title: Optimum sampling scheme for characterization of mine tailings
Authors: Debba, P
Carranza, EJM
Stein, A
Van der Meer, FD
Keywords: Geoscience
Mine tailings
Remote sensing
Hyperspectral
External drift kriging
Variogram
Spectral unmixing
Airborne hyperspectral data
Variogram model
Optimum sampling
Issue Date: Jul-2009
Publisher: IEEE
Citation: Debba, P, Carranza, EJM et al 2009. Optimum sampling scheme for characterization of mine tailings. IEEE. International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009, pp 1-4
Abstract: The paper describes a novice method for sampling geochemicals to characterize mine tailings. The author’s 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.
Description: Copyright: 2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009
URI: http://hdl.handle.net/10204/4016
ISBN: 978-1-4244-3395-7
Appears in Collections:Pollution and waste
Mining and geoscience
Logistics and quantitative methods
General science, engineering & technology

Files in This Item:

File Description SizeFormat
Debba1_2009.pdf427.26 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback