Wei Fu
Impact in
- Plant Science top 5%
- Smart Agriculture and AI
- Plant Surface Properties and Treatments
- Leaf Properties and Growth Measurement
- Analytical Chemistry top 10%
- Spectroscopy and Chemometric Analyses
Papers in
-
- Smart Agriculture and AI 13
- Plant Surface Properties and Treatments 6
- Ecology 7
- Remote Sensing in Agriculture 6
- Co-authors
- Yubin Lan (3 shared papers)Xin Fang (3 shared papers)Xiaoqiang Han (4 shared papers)Guobin Wang (3 shared papers)Huiming Zhang (2 shared papers)Yuan Li (3 shared papers)Xirui Zhang (3 shared papers)Huiming Zhang (3 shared papers)
- Journals
- Agronomy (5 papers)International journal of agricultural and biological engineering (3 papers)Frontiers in Plant Science (2 papers)Applied Sciences (2 papers)Computers and Electronics in Agriculture (2 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Wei Fu
30 papers receiving 482 citations
Peers
Comparison fields: 5 of 62
- Plant Science 369
- Analytical Chemistry 49
- Environmental Engineering 55
- Ecology 96
- Earth-Surface Processes 23
Countries citing papers authored by Wei Fu
This map shows the geographic impact of Wei Fu'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 Wei Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Fu more than expected).
Fields of papers citing papers by Wei Fu
This network shows the impact of papers produced by Wei Fu. 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 Wei Fu. The network helps show where Wei Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Fu, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 108 | |
| 2 | 2019 | 47 | |
| 3 | 2018 | 47 | |
| 4 | 2022 | 36 | |
| 5 | 2024 | 34 | |
| 6 | 2022 | 28 | |
| 7 | 2022 | 23 | |
| 8 | 2023 | 19 | |
| 9 | 2022 | 17 | |
| 10 | 2018 | 16 | |
| 11 | 2024 | 16 | |
| 12 | 2022 | 12 | |
| 13 | 2024 | 12 | |
| 14 | 2023 | 12 | |
| 15 | 2023 | 11 | |
| 16 | 2022 | 8 | |
| 17 | 2022 | 8 | |
| 18 | 2020 | 5 | |
| 19 | 2024 | 5 | |
| 20 | 2025 | 4 |
About Wei Fu
Wei Fu is a scholar working on Plant Science, Ecology, Mechanical Engineering, Atmospheric Science and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 487 indexed citations. Recurring topics across this work include Smart Agriculture and AI (13 papers), Plant Surface Properties and Treatments (6 papers), Remote Sensing in Agriculture (6 papers), Tree Root and Stability Studies (5 papers), Remote Sensing and LiDAR Applications (4 papers), Robotic Path Planning Algorithms (3 papers), Remote Sensing and Land Use (3 papers) and Aeolian processes and effects (3 papers). The work is most often cited by research in Plant Science (369 citations), Analytical Chemistry (49 citations), Environmental Engineering (55 citations), Ecology (96 citations) and Earth-Surface Processes (23 citations). Wei Fu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Yubin Lan, Xin Fang, Xiaoqiang Han, Guobin Wang, Huiming Zhang, Yuan Li, Xirui Zhang, Huiming Zhang, Xirui Zhang and Juan Wang. Their work appears in journals such as Agronomy, International journal of agricultural and biological engineering, Frontiers in Plant Science, Applied Sciences and Computers and Electronics in 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.