Kun Tan
Impact in
- Media Technology top 0.05%
- Remote-Sensing Image Classification
- Environmental Engineering top 2%
- Soil Geostatistics and Mapping
Papers in
-
- Remote-Sensing Image Classification 83
-
- Spectroscopy and Chemometric Analyses 17
- Co-authors
- Peijun Du (57 shared papers)Qian Du (22 shared papers)Xue Wang (38 shared papers)Yu Chen (30 shared papers)Junshi Xia (8 shared papers)Xiuping Jia (8 shared papers)Jianwei Ding (21 shared papers)Sicong Liu (4 shared papers)
- Journals
- Remote Sensing (13 papers)International Journal of Applied Earth Observation and Geoinformation (12 papers)IEEE Transactions on Geoscience and Remote Sensing (12 papers)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (9 papers)Geoderma (4 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Kun Tan
126 papers receiving 4k citations
Peers
Comparison fields: 5 of 103
- Media Technology 2.2k
- Environmental Engineering 481
- Analytical Chemistry 429
- Pollution 430
- Ecology 299
Countries citing papers authored by Kun Tan
This map shows the geographic impact of Kun Tan'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 Kun Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Tan more than expected).
Fields of papers citing papers by Kun Tan
This network shows the impact of papers produced by Kun Tan. 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 Kun Tan. The network helps show where Kun Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Tan, 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 136 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 256 | |
| 2 | 2019 | 196 | |
| 3 | 2020 | 188 | |
| 4 | 2020 | 166 | |
| 5 | 2012 | 147 | |
| 6 | 2019 | 133 | |
| 7 | 2021 | 132 | |
| 8 | 2021 | 125 | |
| 9 | 2020 | 102 | |
| 10 | 2015 | 83 | |
| 11 | 2019 | 83 | |
| 12 | 2019 | 81 | |
| 13 | 2021 | 77 | |
| 14 | 2020 | 76 | |
| 15 | 2022 | 74 | |
| 16 | 2016 | 73 | |
| 17 | 2013 | 72 | |
| 18 | 2016 | 61 | |
| 19 | 2019 | 61 | |
| 20 | 2020 | 61 |
About Kun Tan
Kun Tan is a scholar working on Media Technology, Analytical Chemistry, Environmental Engineering, Pollution and Ecology, having authored 136 papers that have together received 4.1k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (83 papers), Spectroscopy and Chemometric Analyses (17 papers), Soil Geostatistics and Mapping (12 papers), Heavy metals in environment (11 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (9 papers), Remote Sensing in Agriculture (8 papers), Environmental Quality and Pollution (7 papers) and Environmental Changes in China (6 papers). The work is most often cited by research in Media Technology (2.2k citations), Environmental Engineering (481 citations), Analytical Chemistry (429 citations), Pollution (430 citations) and Ecology (299 citations). Kun Tan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Peijun Du, Qian Du, Xue Wang, Yu Chen, Junshi Xia, Xiuping Jia, Jianwei Ding, Sicong Liu, Lihan Chen and Erzhu Li. Their work appears in journals such as Remote Sensing, International Journal of Applied Earth Observation and Geoinformation, IEEE Transactions on Geoscience and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and Geoderma.
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.