Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
High-Resolution Surface-Wave Tomography from Ambient Seismic Noise
20051.7k citationsН. М. Шапиро, Michel Campillo et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Laurent Stehly
Since
Specialization
Citations
This map shows the geographic impact of Laurent Stehly's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Laurent Stehly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laurent Stehly more than expected).
This network shows the impact of papers produced by Laurent Stehly. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Laurent Stehly. The network helps show where Laurent Stehly may publish in the future.
Co-authorship network of co-authors of Laurent Stehly
This figure shows the co-authorship network connecting the top 25 collaborators of Laurent Stehly.
A scholar is included among the top collaborators of Laurent Stehly based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Laurent Stehly. Laurent Stehly is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Boué, Pierre, et al.. (2019). Local ambient noise tomography using a dense array : the MAUPASACQ experiment. EGU General Assembly Conference Abstracts. 8644.2 indexed citations
12.
Stehly, Laurent, et al.. (2019). Regional ambient noise tomography of the Pyrenees using correlation of correlation. EGUGA. 7914.1 indexed citations
13.
Villaseñor, Antonio, Sébastien Chevrot, Matthieu Sylvander, et al.. (2019). Crustal architecture of the Mauléon Basin (Western Pyrenees) from high resolution local earthquake tomography using the large-N Maupasacq experiment. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 10657.3 indexed citations
14.
Retailleau, Lise, et al.. (2016). Core Mantle Boundary Imaging underneath the North Atlantic ocean using teleseismic noise correlations. AGU Fall Meeting Abstracts. 2016.1 indexed citations
15.
Barnoud, Anne, Olivier Coutant, C. Bouligand, Frédérick Massin, & Laurent Stehly. (2015). Seismic tomography of Basse-Terre volcanic island, Guadeloupe, Lesser Antilles, using earthquake travel times and noise correlations. EGUGA. 11015.1 indexed citations
16.
Campillo, Michel & Laurent Stehly. (2007). Using coda waves extracted from microseisms to construct direct arrivals.. AGU Fall Meeting Abstracts. 2007.1 indexed citations
17.
Larose, Éric, et al.. (2006). Correlation of random wave fields; an interdisciplinary review. Geophysics.18 indexed citations
Fry, Bill, Laurent Stehly, Michel Campillo, Lapo Boschi, & Domenico Giardini. (2005). Surface Wave Tomography of the Central Alps: Merging Traditional Source and Non-traditional Noise Dispersion Measurements. AGU Fall Meeting Abstracts. 2005.1 indexed citations
20.
Stehly, Laurent, Н. М. Шапиро, Michel Campillo, & M. H. Ritzwoller. (2004). Correlation of oceanic microseisms at Californian seismic stations. AGUFM. 2004.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.