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.
ICESat's laser measurements of polar ice, atmosphere, ocean, and land
2002786 citationsH. Jay Zwally, James B. Abshire 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 Stephen P. Palm
Since
Specialization
Citations
This map shows the geographic impact of Stephen P. Palm'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 Stephen P. Palm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen P. Palm more than expected).
This network shows the impact of papers produced by Stephen P. Palm. 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 Stephen P. Palm. The network helps show where Stephen P. Palm may publish in the future.
Co-authorship network of co-authors of Stephen P. Palm
This figure shows the co-authorship network connecting the top 25 collaborators of Stephen P. Palm.
A scholar is included among the top collaborators of Stephen P. Palm 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 Stephen P. Palm. Stephen P. Palm is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yorks, John E., Matthew J. McGill, Stephen P. Palm, et al.. (2015). The Cloud-Aerosol Transport System (CATS): Demonstrating New Techniques for Cloud and Aerosol Measurements. AGU Fall Meeting Abstracts. 2015.1 indexed citations
14.
Yorks, John E., Matthew J. McGill, Dennis L. Hlavka, et al.. (2013). New capabilities for space-based cloud and aerosols measurements: The Cloud-Aerosol Transport System (CATS). AGU Fall Meeting Abstracts. 2013.2 indexed citations
15.
Hart, William D., James D. Spinhirne, Stephen P. Palm, & Dennis L. Hlavka. (2006). GLAS Spaceborne Lidar Observations of Clouds and Aerosols. Optica Pura y Aplicada. 39(1). 117–123.1 indexed citations
16.
Spinhirne, James D., Stephen P. Palm, Dennis L. Hlavka, William D. Hart, & Ashwin Mahesh. (2004). Global and Polar Cloud Cover from the Geoscience Laser Altimeter System, Observations and Implications. AGU Fall Meeting Abstracts. 2004.2 indexed citations
17.
Spinhirne, James D., Ellsworth J. Welton, Stephen P. Palm, et al.. (2004). The Glas Polar Orbiting LIDAR Experiment: First Year Results and Available Data. NASA STI Repository (National Aeronautics and Space Administration). 561. 949.1 indexed citations
18.
Sun, Xiaoli, James B. Abshire, Michael A. Krainak, et al.. (2004). Cloud and aerosol lidar channel design and performance of the Geoscience Laser Altimeter System on the ICESat mission. Conference on Lasers and Electro-Optics. 2.4 indexed citations
19.
Palm, Stephen P., Dennis L. Hlavka, William D. Hart, James D. Spinhirne, & Matthew J. McGill. (2003). Calibration of the Geoscience Laser Altimeter System (glas) Atmospheric Channels. 561. 1003.2 indexed citations
20.
Marquis, Melinda, Anita C. Brenner, D. W. Hancock, et al.. (2001). Geoscience Laser Altimeter System (GLAS) Data Products from the Ice, Cloud, and land Elevation Satellite (ICESat) Mission. AGUFM. 2001.2 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.