Bei Cui
Impact in
- Ecology top 10%
- Remote Sensing in Agriculture
- Analytical Chemistry top 5%
- Spectroscopy and Chemometric Analyses
Papers in
- Ecology 13
- Remote Sensing in Agriculture 13
-
- Leaf Properties and Growth Measurement 6
- Smart Agriculture and AI 5
- Date Palm Research Studies 3
- Co-authors
- Huichun Ye (12 shared papers)Wenjiang Huang (9 shared papers)Yingying Dong (5 shared papers)Shanyu Huang (4 shared papers)Xiaoyu Song (4 shared papers)Yu Ren (4 shared papers)Yu Jin (3 shared papers)Anting Guo (4 shared papers)
In The Last Decade
Bei Cui
20 papers receiving 363 citations
Peers
Comparison fields: 5 of 63
- Ecology 261
- Analytical Chemistry 76
- Environmental Engineering 93
- Plant Science 243
- Global and Planetary Change 57
Countries citing papers authored by Bei Cui
This map shows the geographic impact of Bei Cui'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 Bei Cui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bei Cui more than expected).
Fields of papers citing papers by Bei Cui
This network shows the impact of papers produced by Bei Cui. 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 Bei Cui. The network helps show where Bei Cui may publish in the future.
Co-authors
The 25 scholars most cited alongside Bei Cui, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 97 | |
| 2 | 2019 | 82 | |
| 3 | 2020 | 40 | |
| 4 | 2018 | 30 | |
| 5 | 2019 | 23 | |
| 6 | 2017 | 23 | |
| 7 | 2022 | 16 | |
| 8 | 2019 | 15 | |
| 9 | 2021 | 15 | |
| 10 | 2021 | 7 | |
| 11 | 2020 | 6 | |
| 12 | 2020 | 4 | |
| 13 | [Winter wheat GPC estimation based on leaf and canopy chlorophyll parameters]. | 2014 | 3 |
| 14 | 2022 | 2 | |
| 15 | 2017 | 2 | |
| 16 | 2016 | 2 | |
| 17 | 2021 | 2 | |
| 18 | 2012 | 2 | |
| 19 | 2022 | 1 | |
| 20 | 2014 | 1 |
About Bei Cui
Bei Cui is a scholar working on Ecology, Plant Science, Environmental Engineering, Atmospheric Science and Information Systems, having authored 24 papers that have together received 374 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (13 papers), Leaf Properties and Growth Measurement (6 papers), Smart Agriculture and AI (5 papers), Remote Sensing and Land Use (4 papers), Remote Sensing and LiDAR Applications (3 papers), Date Palm Research Studies (3 papers), Spectroscopy and Chemometric Analyses (2 papers) and Land Use and Ecosystem Services (2 papers). The work is most often cited by research in Ecology (261 citations), Analytical Chemistry (76 citations), Environmental Engineering (93 citations), Plant Science (243 citations) and Global and Planetary Change (57 citations). Bei Cui has collaborated with scholars based in China, Australia and Germany. Frequent co-authors include Huichun Ye, Wenjiang Huang, Yingying Dong, Shanyu Huang, Xiaoyu Song, Yu Ren, Yu Jin, Anting Guo, Qianjun Zhao and Xianfeng Zhou. Their work appears in journals such as Remote Sensing, International journal of agricultural and biological engineering, Agronomy, International Review of Finance and Journal of Integrative Agriculture.
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.