@article{fdi:010094171,
  title = {{D}oes foreshock identification depend on seismic monitoring capability ?},
  author = {{C}ui, {X}. and {L}i, {Z}. {F}. and {A}mpuero, {J}ean-{P}aul and {D}e {B}arros, {L}.},
  editor = {},
  language = {{ENG}},
  abstract = {{F}oreshocks, though well-documented phenomena preceding many large earthquakes, have limited forecasting utility due to their non-pervasive occurrence and non-distinctive characteristics. {U}sing {C}alifornia as an example, we investigate how seismic monitoring capability, particularly the completeness magnitude ({M}-c), influences the inferred proportion of mainshocks with foreshocks ({P}-f). {W}e test four foreshock identification methods, namely the fixed-window, nearest neighbor clustering, empirical statistical ({ES}) methods and the epidemic-type aftershock sequence ({ETAS}) model. {T}he fixed-window method shows {P}-f decreasing with higher {M}-c due to the misclassification of background events as foreshocks. {I}n contrast, clustering and {ES} methods yield relatively stable {P}(f )across different {M}-c values. {T}he {ETAS} model suggests that many foreshocks in {C}alifornia are associated with aseismic driving processes, but the identification of the processes diminishes at high {M}-c. {T}hese results show that improved seismic monitoring capability does not significantly increase {PP}f but is crucial for distinguishing processes driving foreshocks.},
  keywords = {foreshock identificaiton ; earthquake sequence ; statistical seismology ; {ETATS} {UNIS} ; {CALIFORNIE}},
  booktitle = {},
  journal = {{G}eophysical {R}esearch {L}etters},
  volume = {52},
  numero = {11},
  pages = {e2025{GL}115394 [11 p.]},
  ISSN = {0094-8276},
  year = {2025},
  DOI = {10.1029/2025gl115394},
  URL = {https://www.documentation.ird.fr/hor/fdi:010094171},
}