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.
Reference:
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
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
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
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 .
