This map shows the geographic impact of D. Ravat'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 D. Ravat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Ravat more than expected).
This network shows the impact of papers produced by D. Ravat. 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 D. Ravat. The network helps show where D. Ravat may publish in the future.
Co-authorship network of co-authors of D. Ravat
This figure shows the co-authorship network connecting the top 25 collaborators of D. Ravat.
A scholar is included among the top collaborators of D. Ravat 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 D. Ravat. D. Ravat is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ravat, D.. (2019). The Moho is Not the Magnetization Limit: Evidence from North American Magnetic Anomalies from the Spectral Multi-Defractal Method. AGU Fall Meeting Abstracts. 2019.1 indexed citations
Ravat, D.. (2012). North American Magnetic Bottom/Curie Depth estimates and their significance for lithospheric temperatures and magnetization. AGUFM. 2012.1 indexed citations
6.
Ravat, D. & Juha Korhonen. (2010). A Preliminary, Full Spectrum, Magnetic Anomaly Grid of the United States with Improved Long Wavelengths for Studying Continental Dynamics. EGUGA. 15500.1 indexed citations
7.
Ravat, D., Terence J. Sabaka, Eslam Elawadi, et al.. (2008). A Preliminary Full Spectrum Magnetic Anomaly Database of the United States With Improved Long Wavelengths for Studying Continental Dynamics. AGU Fall Meeting Abstracts. 2008.2 indexed citations
8.
Ravat, D.. (2006). Uncertainty in magnetization directions derived from planetary magnetic anomalies in view of numerical experiments with coalesced anomalies from Earth. AGU Fall Meeting Abstracts. 2006.4 indexed citations
9.
Hinze, William J., Bernard Coakley, Thomas G. Hildenbrand, et al.. (2006). Reply to the discussion. Geophysics. 71(6). X32–X33.1 indexed citations
10.
Hemant, K., Erwan Thébault, Mioara Mandéa, D. Ravat, & S. Maus. (2005). Merging airborne, marine and ground-based magnetic anomaly maps with satellite derived lithospheric field models. AGU Fall Meeting Abstracts. 2005.
11.
Ravat, D., et al.. (2005). Why meaningful paleopoles can't be determined without special assumptions from Mars Global Surveyor data?. 2005.2 indexed citations
12.
Ravat, D., Alessandro Pignatelli, Iacopo Nicolosi, & M. Chiappini. (2005). Comparison of Methods of Mapping the Depth to the Top and the Bottom of Magnetic Sources Using Layered and Random Synthetic Magnetic Models. AGU Spring Meeting Abstracts. 2005.4 indexed citations
13.
Ravat, D.. (2005). Deconstructing a Few Myths in the Interpretation of Satellite-Altitude Crustal Magnetic Field: Examples from Mars Global Surveyor. LPI. 2114.1 indexed citations
14.
Ravat, D., et al.. (2004). Magnetic Depth Estimates and Their Potential for Constraining Crustal Composition and Heat Flow in Antarctica. AGUFM. 2004.19 indexed citations
Ravat, D., et al.. (2002). The Large Meteorite Impact Origin of the Satellite Altitude Bangui Magnetic Anomaly: Additional Evidence.. AGU Spring Meeting Abstracts. 2002.1 indexed citations
Zatman, Stephen, D. R. Stegman, D. Ravat, Patrick Taylor, & J. J. Frawley. (2001). Geodynamic constraints on the age of Martian magnetic anomaly construction. AGUSM. 2001.1 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.