TY  - JOUR
A1  - von Specht, Sebastian
A1  - Heidbach, Oliver
A1  - Cotton, Fabrice Pierre
A1  - Zang, Arno
T1  - Uncertainty reduction of stress tensor inversion with data-driven catalogue selection
JF  - Geophysical journal international
N2  - The selection of earthquake focal mechanisms (FMs) for stress tensor inversion (STI) is commonly done on a spatial basis, that is, hypocentres. However, this selection approach may include data that are undesired, for example, by mixing events that are caused by different stress tensors when for the STI a single stress tensor is assumed. Due to the significant increase of FM data in the past decades, objective data-driven data selection is feasible, allowing more refined FM catalogues that avoid these issues and provide data weights for the STI routines. We present the application of angular classification with expectation-maximization (ACE) as a tool for data selection. ACE identifies clusters of FM without a priori information. The identified clusters can be used for the classification of the style-of-faulting and as weights of the FM data. We demonstrate that ACE effectively selects data that can be associated with a single stress tensor. Two application examples are given for weighted STI from South America. We use the resulting clusters and weights as a priori information for an STI for these regions and show that uncertainties of the stress tensor estimates are reduced significantly.
KW  - Inverse Theory
KW  - Statistical Methods
KW  - Seismicity
KW  - tectonics
KW  - Kinematics of crustal
KW  - mantle deformation
Y1  - 2018
U6  - https://doi.org/10.1093/gji/ggy240
SN  - 0956-540X
SN  - 1365-246X
VL  - 214
IS  - 3
SP  - 2250
EP  - 2263
PB  - Oxford Univ. Press
CY  - Oxford
ER  -