ResearchSpace

Optimum sampling scheme for characterization of mine tailings

Show simple item record

dc.contributor.author Debba, Pravesh
dc.contributor.author Carranza, EJM
dc.contributor.author Stein, A
dc.contributor.author Van der Meer, FD
dc.date.accessioned 2010-04-13T07:17:25Z
dc.date.available 2010-04-13T07:17:25Z
dc.date.issued 2009-07
dc.identifier.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 en
dc.identifier.isbn 978-1-4244-3395-7
dc.identifier.uri http://hdl.handle.net/10204/4016
dc.description Copyright: 2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009 en
dc.description.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. en
dc.language.iso en en
dc.publisher IEEE en
dc.subject Geoscience en
dc.subject Mine tailings en
dc.subject Remote sensing en
dc.subject Hyperspectral en
dc.subject External drift kriging en
dc.subject Variogram en
dc.subject Spectral unmixing en
dc.subject Airborne hyperspectral data en
dc.subject Variogram model en
dc.subject Optimum sampling en
dc.title Optimum sampling scheme for characterization of mine tailings en
dc.type Conference Presentation en
dc.identifier.apacitation Debba, P., Carranza, E., Stein, A., & Van der Meer, F. (2009). Optimum sampling scheme for characterization of mine tailings. IEEE. http://hdl.handle.net/10204/4016 en_ZA
dc.identifier.chicagocitation Debba, Pravesh, EJM Carranza, A Stein, and FD Van der Meer. "Optimum sampling scheme for characterization of mine tailings." (2009): http://hdl.handle.net/10204/4016 en_ZA
dc.identifier.vancouvercitation Debba P, Carranza E, Stein A, Van der Meer F, Optimum sampling scheme for characterization of mine tailings; IEEE; 2009. http://hdl.handle.net/10204/4016 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Debba, Pravesh AU - Carranza, EJM AU - Stein, A AU - Van der Meer, FD AB - 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. DA - 2009-07 DB - ResearchSpace DP - CSIR KW - Geoscience KW - Mine tailings KW - Remote sensing KW - Hyperspectral KW - External drift kriging KW - Variogram KW - Spectral unmixing KW - Airborne hyperspectral data KW - Variogram model KW - Optimum sampling LK - https://researchspace.csir.co.za PY - 2009 SM - 978-1-4244-3395-7 T1 - Optimum sampling scheme for characterization of mine tailings TI - Optimum sampling scheme for characterization of mine tailings UR - http://hdl.handle.net/10204/4016 ER - en_ZA


Files in this item

Thumbnail
Name: Debba1_2009.pdf
Size: 427.2Kb
Format: PDF
View/Open

This item appears in the following Collection(s)

Show simple item record