Optimum Sampling Scheme for Characterization of Mine Tailings

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.

• Type: Journal
• Year: 2009
• Where: IGARSS
• Authors: Pravesh Debba, Emmanuel John M. Carranza, Alfred Stein, Freek D. van der Meer
• Keywords: Airborne Hyperspectral Data, IGARSS 2009, Optimal Prospective Sampling, Remote Sensing, Secondary Iron-bearing Minerals