  We introduce the Anisotropic Clustering of Location Uncertainty Distributions
(ACLUD) method to reconstruct active fault networks on the basis of both
earthquake locations and their estimated individual uncertainties. After a
massive search through the large solution space of possible reconstructed fault
networks, we apply six different validation procedures in order to select the
corresponding best fault network. Two of the validation steps (cross-validation
and Bayesian Information Criterion (BIC) process the fit residuals, while the
four others look for solutions that provide the best agreement with
independently observed focal mechanisms. Tests on synthetic catalogs allow us
to qualify the performance of the fitting method and of the various validation
procedures. The ACLUD method is able to provide solutions that are close to the
expected ones, especially for the BIC and focal mechanismbased techniques. The
clustering method complemented by the validation step based on focal mechanisms
provides good solutions even in the presence of a significant spatial
background seismicity rate. Our new fault reconstruction method is then applied
to the Landers area in Southern California and compared with previous
clustering methods. The results stress the importance of taking into account
undersampled sub-fault structures as well as of the spatially inhomogeneous
location uncertainties.
