Countries citing papers authored by James G. Bellingham
Since
Specialization
Citations
This map shows the geographic impact of James G. Bellingham'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 James G. Bellingham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James G. Bellingham more than expected).
Fields of papers citing papers by James G. Bellingham
This network shows the impact of papers produced by James G. Bellingham. 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 James G. Bellingham. The network helps show where James G. Bellingham may publish in the future.
Co-authorship network of co-authors of James G. Bellingham
This figure shows the co-authorship network connecting the top 25 collaborators of James G. Bellingham.
A scholar is included among the top collaborators of James G. Bellingham 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 James G. Bellingham. James G. Bellingham is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Yanwu, et al.. (2013). Two-dimensional mapping and tracking of a coastal upwelling front by an autonomous underwater vehicle. 2013 OCEANS - San Diego. 1–4.15 indexed citations
4.
Ryan, John P., et al.. (2012). Observing Coastal Upwelling Front Dynamics by AUV Tracking, Remote Sensing, and Mooring Measurements. AGU Fall Meeting Abstracts. 2012.2 indexed citations
5.
Godin, M. A., et al.. (2012). Localization and Tracking of Submerged Phytoplankton Bloom Patches by an Autonomous Underwater Vehicle. AGUFM. 2012.1 indexed citations
6.
Glickson, D., E. J. Barron, Rana A. Fine, et al.. (2011). Critical Infrastructure for Ocean Research and Societal Needs in 2030. AGUFM. 2011.1 indexed citations
7.
Ryan, John P., James G. Bellingham, Julio B.J. Harvey, et al.. (2011). Classification of Water Masses and Targeted Sampling of Ocean Plankton Populations by an Autonomous Underwater Vehicle. AGUFM. 2011.5 indexed citations
McEwen, R., et al.. (2010). Acquiring Peak Samples from Phytoplankton Thin Layers and Intermediate Nepheloid Layers by an Autonomous Underwater Vehicle with Adaptive Triggering. AGUFM. 2010.1 indexed citations
Bellingham, James G., et al.. (2006). Error Analysis and Sampling Design for Ocean Flux Estimation. AGU Fall Meeting Abstracts. 2006.1 indexed citations
15.
Godin, M. A. & James G. Bellingham. (2005). The Metadata Oriented Query Assistant (MOQuA): a Web Tool for Finding Data in Heterogeneous, Multi-Platform Data Collections by Simultaneously Pivoting on Multiple Metadata Hierarchies.. AGU Fall Meeting Abstracts. 2005.1 indexed citations
16.
Bellingham, James G., et al.. (2005). Optimizing Autonomous Underwater Vehicles' Survey for Reconstruction of an Ocean Field that Varies in Space and Time. AGU Fall Meeting Abstracts. 2005.4 indexed citations
Bellingham, James G., William Kirkwood, Edward D. Cokelet, et al.. (2002). Field Results for an Arctic AUV Designed for Characterizing Circulation and Ice Thickness. AGU Fall Meeting Abstracts. 2002.2 indexed citations
19.
Bellingham, James G., et al.. (1993). Demonstration of a high-performance, low-cost autonomous underwater vehicle.3 indexed citations
20.
Bellingham, James G., Clifford A. Goudey, Thomas R. Consi, & Chryssostomos Chryssostomidis. (1992). A Small, Long-Range Autonomous Vehicle For Deep Ocean Exploration.12 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.