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\DOI{10.5802/crgeos.281}
\datereceived{2024-11-06}
\dateaccepted{2024-11-19}
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%\makeatletter
%\def\TITREspecial{\relax}
%\def\cdr@specialtitle@english{New Developments in Passive Seismic Imaging and Monitoring}
%\def\cdr@specialtitle@french{Nouveaux d\'eveloppements en mati\`ere d'imagerie sismique passive et de surveillance}
%\makeatother

\CDRsetmeta{articletype}{foreword}

\title{Foreword to New developments in passive seismic imaging and
monitoring}

\alttitle{Nouveaux d\'{e}veloppements dans le domaine de l'imagerie
et de la surveillance sismique passive}

\author{\firstname{Nikolai M.} \lastname{Shapiro}\CDRorcid{0000-0002-0144-723X}}
\address{Institut des Sciences de la Terre, University Grenoble Alpes,
CNRS, University Savoie Mont Blanc, IRD, University Gustave Eiffel,
Grenoble, France}
\email[N. M. Shapiro]{nikolai.shapiro@univ-grenoble-alpes.fr}

\author{\firstname{Michel} \lastname{Campillo}\CDRorcid{0000-0001-6971-4499}}
\addressSameAs{1}{Institut des Sciences de la Terre, University Grenoble Alpes,
CNRS, University Savoie Mont Blanc, IRD, University Gustave Eiffel,
Grenoble, France}
\email[M. Campillo]{michel.campillo@univ-grenoble-alpes.fr}

\author{\firstname{Anne} \lastname{Obermann}\CDRorcid{0000-0001-6933-6301}}
\address{Swiss Seismological Service, ETH Zurich, Switzerland}
\email[A. Obermann]{anne.obermann@sed.ethz.ch}

\author{\firstname{Andrew} \lastname{Curtis}\CDRorcid{0000-0003-1222-1583}}
\address{School of GeoSciences, University of Edinburgh, Edinburgh EH9
3FE, UK}
\email[A. Curtis]{andrew.curtis@ed.ac.uk}

\thanks{ERC Advanced Grants F-Image, SEISMAZE, FaultScan}

\shortrunauthors

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\xsection{}
During the last two decades, 
imaging and monitoring methods based on
cross-correlations of ambient seismic noise have been extensively
developed and have become widely used at different scales and in different
natural and human-controlled environments. Application of these methods
has been facilitated by improved availability of data from large and
dense seismic networks and by several open software packages. At the
same time, noise-based imaging and monitoring is far from becoming just
a set of ``standard'' and ``routine'' methods. As discussed in this
special issue, the origin and nature of the seismic noise wavefields,
their correlation properties as well as their sensitivity to the medium
structure and changes, remain areas of active study. Improving their
understanding is necessary in order to refine the existing methods and
to develop new approaches for imaging and monitoring. Therefore,
noise-based passive seismology remains a dynamic field of research with
some first-order problems yet to be solved. In this context, 13 years
after the first thematic issue of Comptes Rendus G\'{e}oscience on
passive seismic noise-based imaging and monitoring 
\citep[e.g.,][]{Campilloetal2011} we introduce a new special issue
devoted to this topic.

Most passive noise-based seismic imaging and monitoring methods are
based on the so-called ``noise cross-correlation theorem''  
\citep[e.g.,][]{LobkisWeaver2001,Wapenaar2004,Rouxetal2005,
Campillo2006,Gouedardetal2008} 
which states that the time derivative
of cross-correlation of an ideal fully diffuse wavefield converge to
the Green's function of the medium in which the waves are propagating.
The fully diffuse wavefield can be defined either as being composed of
all possible medium vibration modes with equally partitioned energy, or
locally as composed of isotropic combination of plane waves,
or as generated by homogenously distributed random sources.
Neither of these definitions applies to the real Earth's seismic noise
whose main sources are inhomogeneously distributed over the surface.
This makes direct application of the ``full'' cross-correlation theorem
to real seismological data questionable, and requires that we further
improve our understanding of seismic noise cross-correlations to
develop accurate methods.\looseness=-1

So far, the surface wave part of Green's functions has been most
reliably reconstructed from the correlations of the ambient seismic
noise. Since initial demonstration of this possibility 
\citep[e.g.,][]{ShapiroCampillo2004,Shapiroetal2005,Sabraetal2005a,Sabraetal2005b}
a family of methods known as Ambient Noise
Surface Wave Tomography (ANSWT) has been developed and successfully
applied in many studies 
\citep[e.g.,][]{Ritzwolleretal2011,Shapiro2018}.  A systematic
application of this approach to image the European Alps is presented by
\citet{Pauletal2024}. The authors show how methodological advances of
this approach evolving from simple isotropic group velocity tomography
to wave-equation based inversions, and those based on trans-dimensional
Bayesian formalism and including anisotropy, significantly improved
knowledge of the structure of the crust and shallow mantle beneath the
Alps-Apennines system. 

\citet{Giammarinaroetal2024} use two-dimensional simulations of wave
propagation to investigate the lateral resolution power of an
alternative approach to ANSWT: seismic Rayleigh wave focal spot
imaging. They demonstrate that the station configuration can be tuned
to improve image quality and properties, and that high-quality data
from dense networks can result in super-resolution.

\citet{Lavoueetal2024} investigate the applicability of the ANSWT at
small scales, i.e., those of a single sedimentary basin, to resolve the
near-surface structure for estimation of site amplifications required
for seismic hazard models. They show that, while ANSWT results
reproduce well the main geological structures of the basin, they have
limited capability to accurately predict the numerical amplification
near the basin edges and other locations with significant 3D wave
propagation effects. This allows the authors to suggest perspectives
for future improvement of ANSWT, that shows promise for site effect
assessment in low- to moderate-seismicity contexts. 

\citet{BoueTomasetto2024} investigate how the teleseismic body waves
are generated by oceanic forcing on the Earth's surface, resulting in a
spatially inhomogeneous distribution of microseismic sources. The
authors show that, despite the inherent complexity of these noise
sources, cross-correlation based methods applied to properly selected
pairs of stations result in the isolation of coherent waves for imaging
applications and propose a workflow based on ocean sea state models to
extract robust interferences.\looseness=-1 

Influence of the heterogeneous distribution of noise sources on the
accuracy of noise-based seismic monitoring is studied by 
\citet{Stehlyetal2024} who perform a single station analysis at all available
European broadband stations. They show that at short periods (${<}$3~s),
the noise field in Europe is dominated by surface waves coming from two
sources: (1) the north Atlantic Ocean dominating during winters, and
(2)~the Adriatic and Aegean Seas increasing in summer. The interplay of
these two source regions leads to time and space dependent convergence
of the coda part of cross-correlations, and thus in across-Europe
variations of the accuracy and temporal resolution of detected seismic
velocity changes. 

Other important aspects of the noise-based seismic monitoring are
addressed by \citet{Caneletal2024} who investigate the physical
mechanisms that could explain the seismic velocity changes measured
from the noise cross-correlations in the vicinity of active fault
zones. The authors perform a set of numerical experiments to test a
simple model of a cohesive granular medium and to study the
relationship between the damage and velocity of elastic waves.  They
show that the microscopic deformation of cohesive discrete media
quickly becomes very heterogeneous with a small amount of damage
inducing a strong decrease in the elastic velocity. As a consequence,
they suggest that monitoring the wave velocities in such media could
measure subtle transient deformation processes, such as earthquake
initiation phases. 

\section*{Acknowledgments}
The content of the present thematic Issue was discussed during the~6th
edition of the school on Passive Imaging and Monitoring in Wave
Physics: From Seismology to Ultrasound, that was held on April 18--22,
2022~at the~Institut d'\'{E}tudes Scientifiques de Carg\`{e}se in
Corsica, France. We thank the contributors of the special issue and the
participants to the workshop as well as all people who contributed to its
logistics. The workshop and the organization of this issue were made
possible by the support of CNRS (France), and Universit\'{e} Grenoble
Alpes (Grenoble, France). The authors acknowledge support from the ERC
Advanced Grants F-Image, SEISMAZE, and FaultScan. 

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