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.
California’s methane super-emitters
2019252 citationsRiley Duren, Andrew K. Thorpe et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Brian Bue'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 Brian Bue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Bue more than expected).
This network shows the impact of papers produced by Brian Bue. 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 Brian Bue. The network helps show where Brian Bue may publish in the future.
Co-authorship network of co-authors of Brian Bue
This figure shows the co-authorship network connecting the top 25 collaborators of Brian Bue.
A scholar is included among the top collaborators of Brian Bue 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 Brian Bue. Brian Bue is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Duren, Riley, Andrew K. Thorpe, Daniel Cusworth, et al.. (2020). Methane point-source emissions from oil, gas, and coal operations. AGU Fall Meeting Abstracts. 2020.1 indexed citations
Foster, Kelsey, Andrew K. Thorpe, K. R. Verhulst, et al.. (2019). Detecting and Quantifying Methane Emissions from Oil Refineries in California. AGU Fall Meeting Abstracts. 2019.1 indexed citations
7.
Hua, Hook, S. E. Owen, Sang‐Ho Yun, et al.. (2017). Large-Scale Sentinel-1 Processing for Solid Earth Science and Urgent Response using Cloud Computing and Machine Learning. AGU Fall Meeting Abstracts. 2017.1 indexed citations
8.
Duren, Riley, Andrew K. Thorpe, F. M. Hopkins, et al.. (2017). The California Baseline Methane Survey. AGUFM. 2017.1 indexed citations
9.
Bue, Brian, Kiri L. Wagstaff, & D. E. Stillman. (2017). Automated Mapping and Characterization of RSL from HiRISE data with MAARSL. DPS.1 indexed citations
Agram, P. S., S. E. Owen, G. Manipon, et al.. (2016). ARIA: delivering state-of-the-art InSAR products for end users. AGUFM. 2016.1 indexed citations
12.
Rebbapragada, Umaa, Brian Bue, & P. R. Woźniak. (2015). Time-domain Surveys and Data Shift: Case Study at the intermediate Palomar Transient Factory. 225.1 indexed citations
Thorpe, Andrew K., David R. Thompson, Christian Frankenberg, et al.. (2015). Directly attributing methane emissions to point source locations using the next generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG). 2015 AGU Fall Meeting. 2015.1 indexed citations
15.
Bue, Brian, Umaa Rebbapragada, Kiri L. Wagstaff, & David R. Thompson. (2014). Using Machine Learning to Enable Big Data Analysis within Human Review Time Budgets. AGUFM. 2014.
16.
Bue, Brian & David R. Thompson. (2011). Multiclass Continuous Correspondence Learning. neural information processing systems.
17.
Stepinski, T. F., M. P. Mendenhall, & Brian Bue. (2007). Robust Automated Identification of Martian Impact Craters. Lunar and Planetary Science Conference. 1202.6 indexed citations
18.
Bue, Brian, et al.. (2007). Automatic Onboard Detection of Planetary Volcanism from Images. Lunar and Planetary Science Conference. 1717.4 indexed citations
Bue, Brian & T. F. Stepinski. (2006). Machine Detection of Martian Craters from Digital Topography. LPI. 1178.1 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.