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Matthew J. Cracknell
Matthew J. Cracknell
Senior Lecturer @ Centre for Ore Deposit and Earth Sciences, University of Tasmania
Verified email at utas.edu.au - Homepage
Title
Cited by
Cited by
Year
Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of training data and …
MJ Cracknell, AM Reading
Computers & Geosciences 63, 22-33, 2014
5802014
The upside of uncertainty: Identification of lithology contact zones from airborne geophysics and satellite data using random forests and support vector machines
MJ Cracknell, AM Reading
Geophysics 78 (3), WB113-WB126, 2013
982013
Distinguishing ore deposit type and barren sedimentary pyrite using laser ablation-inductively coupled plasma-mass spectrometry trace element data and statistical analysis of …
DD Gregory, MJ Cracknell, RR Large, P McGoldrick, S Kuhn, ...
Economic Geology 114 (4), 771-786, 2019
962019
Mapping geology and volcanic-hosted massive sulfide alteration in the Hellyer–Mt Charter region, Tasmania, using Random Forests™ and Self-Organising Maps
MJ Cracknell, AM Reading, AW McNeill
Australian Journal of Earth Sciences 61 (2), 287-304, 2014
842014
Lithologic mapping using Random Forests applied to geophysical and remote-sensing data: A demonstration study from the Eastern Goldfields of Australia
S Kuhn, MJ Cracknell, AM Reading
Geophysics 83 (4), B183-B193, 2018
832018
Geological mapping in Western Tasmania using radar and random forests
DDG Radford, MJ Cracknell, MJ Roach, GV Cumming
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018
452018
Lithological mapping in the Central African Copper Belt using Random Forests and clustering: Strategies for optimised results
S Kuhn, MJ Cracknell, AM Reading
Ore Geology Reviews 112, 103015, 2019
322019
Revealing the multi-stage ore-forming history of a mineral deposit using pyrite geochemistry and machine learning-based data interpretation
R Zhong, Y Deng, W Li, LV Danyushevsky, MJ Cracknell, I Belousov, ...
Ore Geology Reviews 133, 104079, 2021
252021
Automated core logging technology for geotechnical assessment: A study on core from the Cadia East porphyry deposit
CL Harraden, MJ Cracknell, J Lett, RF Berry, R Carey, AC Harris
Economic Geology 114 (8), 1495-1511, 2019
242019
Linking protolith rocks to altered equivalents by combining unsupervised and supervised machine learning
SB Hood, MJ Cracknell, MF Gazley
Journal of Geochemical Exploration 186, 270-280, 2018
232018
Multiple influences on regolith characteristics from continental-scale geophysical and mineralogical remote sensing data using Self-Organizing Maps
MJ Cracknell, AM Reading, P De Caritat
Remote Sensing of Environment 165, 86-99, 2015
232015
Machine learning for geological mapping: Algorithms and applications
MJ Cracknell
University of Tasmania, 2014
232014
Estimating bedding orientation from high-resolution digital elevation models
MJ Cracknell, M Roach, D Green, A Lucieer
IEEE Transactions on Geoscience and Remote Sensing 51 (5), 2949-2959, 2012
222012
Quantitative mineral mapping of drill core surfaces II: Long-wave infrared mineral characterization using μXRF and machine learning
RD Barker, SLL Barker, MJ Cracknell, ED Stock, G Holmes
Economic Geology 116 (4), 821-836, 2021
182021
Combining machine learning and geophysical inversion for applied geophysics
AM Reading, MJ Cracknell, DJ Bombardieri, T Chalke
ASEG Extended Abstracts 2015 (1), 1-5, 2015
182015
Element mobility and spatial zonation associated with the Archean Hamlet orogenic Au deposit, Western Australia: Implications for fluid pathways in shear zones
SB Hood, MJ Cracknell, MF Gazley, AM Reading
Chemical Geology 514, 10-26, 2019
172019
Sampling forest canopy arthropod biodiversity with three novel minimal‐cost trap designs
YD Bar‐Ness, PB McQuillan, M Whitman, RR Junker, M Cracknell, ...
Australian Journal of Entomology 51 (1), 12-21, 2012
172012
Identification of intrusive lithologies in volcanic terrains in British Columbia by machine learning using random forests: The value of using a soft classifier
S Kuhn, MJ Cracknell, AM Reading, S Sykora
Geophysics 85 (6), B249-B258, 2020
162020
National virtual core library HyLogging data and Ni–Co laterites: A mineralogical model for resource exploration, extraction and remediation
MJ Cracknell, NH Jansen
Australian Journal of Earth Sciences 63 (8), 1053-1067, 2016
152016
Height, crime and colonial history
H Maxwell-Stewart, M Cracknell, K Inwood
Law, Crime & Hist. 5, 25, 2015
152015
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Articles 1–20