Paul Bodesheim
- Global and Planetary Change top 10%
- Artificial Intelligence top 10%
- Atmospheric Science
- Ecology
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Miguel D. MahechaJoachim DenzlerErik RodnerFabian GansMarkus ReichsteinAlexander FreytagMartin JungFlurin Babst
- Topics
- Anomaly Detection Techniques and Applications (6 papers)Remote Sensing in Agriculture (4 papers)Plant Water Relations and Carbon Dynamics (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEInternational Journal of Computer Vision
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Paul Bodesheim
22 papers receiving 468 citations
Peers
Comparison fields: 5 of 81
- Global and Planetary Change 228
- Artificial Intelligence 132
- Atmospheric Science 102
- Ecology 86
- Computer Vision and Pattern Recognition 66
Countries citing papers authored by Paul Bodesheim
This map shows the geographic impact of Paul Bodesheim'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 Paul Bodesheim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Bodesheim more than expected).
Fields of papers citing papers by Paul Bodesheim
This network shows the impact of papers produced by Paul Bodesheim. 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 Paul Bodesheim. The network helps show where Paul Bodesheim may publish in the future.
Co-authorship network of co-authors of Paul Bodesheim
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Bodesheim. A scholar is included among the top collaborators of Paul Bodesheim 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 Paul Bodesheim. Paul Bodesheim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 8 | |
| 4 | 10 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 8 | |
| 8 | 3 | |
| 9 | 65 | |
| 10 | 102 | |
| 11 | 1 | |
| 12 | 32 | |
| 13 | 70 | |
| 14 | Potential of new machine learning methods for understanding long-term interannual variability of carbon and energy fluxes and states from site to global scale | 1 |
| 15 | 19 | |
| 16 | 4 | |
| 17 | 24 | |
| 18 | 30 | |
| 19 | 67 | |
| 20 | 3 |
About Paul Bodesheim
Paul Bodesheim is a scholar working on Ecological Modeling, Artificial Intelligence and Global and Planetary Change, having authored 24 papers that have together received 474 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (6 papers), Remote Sensing in Agriculture (4 papers) and Plant Water Relations and Carbon Dynamics (4 papers). The work is most often cited by research in Global and Planetary Change (228 citations), Ecological Modeling (29 citations) and Atmospheric Science (102 citations). Paul Bodesheim has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Miguel D. Mahecha, Joachim Denzler, Erik Rodner, Fabian Gans, Markus Reichstein, Alexander Freytag, Martin Jung, Flurin Babst, David Frank and Benjamin Poulter. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and International Journal of Computer Vision.
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.