Jun Li
- Media Technology top 0.01%
- Remote-Sensing Image Classification 278
- Advanced Image Fusion Techniques 130
- Atmospheric Science top 0.1%
- Remote Sensing and Land Use 148
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- Advanced Image and Video Retrieval Techniques 52
- Image Retrieval and Classification Techniques 37
- Computational Mathematics top 1%
- Analytical Chemistry top 0.2%
- Spectroscopy and Chemometric Analyses 33
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- Remote Sensing in Agriculture 59
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- Advanced Chemical Sensor Technologies 32
- Co-authors
- Antonio PlazaJosé M. Bioucas‐DiasJavier PlazaLin HeJón Atli BenediktssonShutao LiPedram GhamisiZebin Wu
- Journals
- IEEE Transactions on Geoscience and Remote Sensing (106 papers)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (42 papers)IEEE Geoscience and Remote Sensing Letters (16 papers)
- Partner nations
- ChinaSpainUnited States
In The Last Decade
Jun Li
647 papers receiving 19.4k citations
Hit Papers
Peers
Comparison fields: 5 of 220
- Media Technology 12.5k
- Atmospheric Science 7.2k
- Computer Vision and Pattern Recognition 5.5k
- Computational Mathematics 82
- Analytical Chemistry 1.1k
Countries citing papers authored by Jun Li
This map shows the geographic impact of Jun Li'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 Jun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Li more than expected).
Fields of papers citing papers by Jun Li
This network shows the impact of papers produced by Jun Li. 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 Jun Li. The network helps show where Jun Li may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 4 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 0 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 32 | |
| 13 | 2024 | 1 | |
| 14 | 2024 | 1 | |
| 15 | 2024 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2023 | 5 | |
| 18 | 2019 | 57 | |
| 19 | 2017 | 12 | |
| 20 | 2013 | 0 |
About Jun Li
Jun Li is a scholar working on Media Technology, Atmospheric Science and Computer Vision and Pattern Recognition, having authored 737 papers that have together received 19.9k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (278 papers), Remote Sensing and Land Use (148 papers), Advanced Image Fusion Techniques (130 papers), Remote Sensing in Agriculture (59 papers), Advanced Image and Video Retrieval Techniques (52 papers), Image Retrieval and Classification Techniques (37 papers), Spectroscopy and Chemometric Analyses (33 papers) and Advanced Chemical Sensor Technologies (32 papers). The work is most often cited by research in Media Technology (12.5k citations), Atmospheric Science (7.2k citations) and Computer Vision and Pattern Recognition (5.5k citations). Jun Li has collaborated with scholars based in China, Spain and United States. Frequent co-authors include Antonio Plaza, José M. Bioucas‐Dias, Javier Plaza, Lin He, Jón Atli Benediktsson, Shutao Li, Pedram Ghamisi, Zebin Wu, Chenying Liu and Juan M. Haut. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Geoscience and Remote Sensing Letters, Remote Sensing and International Journal of Applied Earth Observation and Geoinformation.
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.