David Fee
- Geophysics top 0.5%
- Seismic Waves and Analysis 104
- Earthquake Detection and Analysis 48
- Seismic Imaging and Inversion Techniques 27
- earthquake and tectonic studies 21
- Atmospheric Science top 5%
- Meteorological Phenomena and Simulations 14
- Artificial Intelligence top 1%
- Seismology and Earthquake Studies 44
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- Landslides and related hazards 12
- Oceanography top 5%
- Underwater Acoustics Research 16
- Co-authors
- Robin S. MatozaMilton GarcésM. M. HaneyJ. J. LyonsAndrea SteffkeAlexandra M. IezziD. J. SchneiderKeehoon Kim
- Journals
- Geophysical Research Letters (19 papers)Bulletin of Volcanology (15 papers)Journal of Volcanology and Geothermal Research (14 papers)
- Partner nations
- United StatesUnited KingdomNew Zealand
In The Last Decade
David Fee
125 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 70
- Geophysics 2.6k
- Atmospheric Science 598
- Artificial Intelligence 941
- Management, Monitoring, Policy and Law 313
- Oceanography 229
Countries citing papers authored by David Fee
This map shows the geographic impact of David Fee'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 David Fee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Fee more than expected).
Fields of papers citing papers by David Fee
This network shows the impact of papers produced by David Fee. 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 David Fee. The network helps show where David Fee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David Fee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2023 | 4 | |
| 3 | 2022 | 5 | |
| 4 | 2022 | 7 | |
| 5 | 2022 | 10 | |
| 6 | 2022 | 2 | |
| 7 | 2022 | 7 | |
| 8 | 2022 | 2 | |
| 9 | 2021 | 4 | |
| 10 | 2021 | 17 | |
| 11 | 2021 | 7 | |
| 12 | 2021 | 14 | |
| 13 | 2020 | 14 | |
| 14 | 2020 | 46 | |
| 15 | 2020 | 11 | |
| 16 | 2019 | 38 | |
| 17 | Multiplet and particle motion analysis of very-long-period (VLP) events at Stromboli Volcano, Italy, during a period of low surface activity in 2018 | 2019 | 1 |
| 18 | 2019 | 4 | |
| 19 | 2018 | 30 | |
| 20 | Gas-Pistoning Associated With the 2008 Summit Eruption of Kilauea Volcano, Hawai'i | 2008 | 3 |
About David Fee
David Fee is a scholar working on Geophysics, Atmospheric Science and Artificial Intelligence, having authored 132 papers that have together received 3.0k indexed citations. Recurring topics across this work include Seismic Waves and Analysis (104 papers), Earthquake Detection and Analysis (48 papers), Seismology and Earthquake Studies (44 papers), Seismic Imaging and Inversion Techniques (27 papers), earthquake and tectonic studies (21 papers), Underwater Acoustics Research (16 papers), Meteorological Phenomena and Simulations (14 papers) and Landslides and related hazards (12 papers). The work is most often cited by research in Geophysics (2.6k citations), Atmospheric Science (598 citations) and Artificial Intelligence (941 citations). David Fee has collaborated with scholars based in United States, United Kingdom and New Zealand. Frequent co-authors include Robin S. Matoza, Milton Garcés, M. M. Haney, J. J. Lyons, Andrea Steffke, Alexandra M. Iezzi, D. J. Schneider, Keehoon Kim, T. M. Lopez and Akihiko Yokoo. Their work appears in journals such as Geophysical Research Letters, Bulletin of Volcanology, Journal of Volcanology and Geothermal Research, Journal of Geophysical Research Solid Earth and Seismological Research Letters.
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.