A
Andy Green
Researcher at Commonwealth Scientific and Industrial Research Organisation
Publications - 32
Citations - 3247
Andy Green is an academic researcher from Commonwealth Scientific and Industrial Research Organisation. The author has contributed to research in topics: Hydrogeology & Groundwater recharge. The author has an hindex of 12, co-authored 32 publications receiving 3041 citations. Previous affiliations of Andy Green include Cooperative Research Centre.
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Streamed data - a source of insight and improvement for time domain airborne EM
TL;DR: Streamed data reveals that only the high amplitude, high frequency components of these signals are significant in the context of the present QUESTEM 450 system, and resulted in an improvement to the method of suppression applied in real time on-board the aircraft.
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A reference library of thermal infrared mineral reflectance spectra for the HyLogger-3 drill core logging system
TL;DR: A reference library of thermal infrared spectral reflectance measurements of the major rock-forming and alteration minerals has been compiled to support and enhance analysis of data acquired using the CSIRO HyLogger-3 drill-core logging system.
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Altitude correction of time domain AEM data for image display and geological mapping using the Apparent Dipole Depth (ADD) method
TL;DR: In this paper, a procedure called the Apparent Dipole Depth (ADD) method for simple correction of airborne TEM data for the effects of changing aircraft altitude is described, which uses the receding image concept of Maxwell and assumes that the earth is horizontally layered.
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The use of multivariate statistical techniques for the analysis and display of AEM data
TL;DR: In this paper, non-linear rescaling on the AEM data to take into consideration the inherent nonlinear relationships arising from the physics of the EM diffusion process is proposed. But the rescaling technique is not suitable for high-dimensional data, as it is difficult to relate to geophysical parameters such as conductivity and depth.
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A Comparison Between Three Sparse Unmixing Algorithms Using a Large Library of Shortwave Infrared Mineral Spectra
TL;DR: Two novel aspects are introduced: the simultaneous fitting of the low frequency background with mineral identification and the combined fitting being carried out using a suitably defined Mahalanobis distance; this has certain optimality properties under an idealized model.