Chi Chen

8.4k total citations · 3 hit papers
42 papers, 6.2k citations indexed

About

Chi Chen is a scholar working on Global and Planetary Change, Ecology and Environmental Engineering. According to data from OpenAlex, Chi Chen has authored 42 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Global and Planetary Change, 23 papers in Ecology and 20 papers in Environmental Engineering. Recurrent topics in Chi Chen's work include Remote Sensing in Agriculture (20 papers), Plant Water Relations and Carbon Dynamics (13 papers) and Remote Sensing and LiDAR Applications (10 papers). Chi Chen is often cited by papers focused on Remote Sensing in Agriculture (20 papers), Plant Water Relations and Carbon Dynamics (13 papers) and Remote Sensing and LiDAR Applications (10 papers). Chi Chen collaborates with scholars based in China, United States and Germany. Chi Chen's co-authors include Ranga B. Myneni, Taejin Park, Ramakrishna Nemani, Shilong Piao, Xuhui Wang, Philippe Ciais, Hans Tømmervik, Rasmus Fensholt, Baodong Xu and Victor Brovkin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Renewable and Sustainable Energy Reviews.

In The Last Decade

Chi Chen

40 papers receiving 6.1k citations

Hit Papers

China and India lead in greening of the world through lan... 2018 2026 2020 2023 2019 2019 2018 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chi Chen China 25 4.4k 2.7k 1.5k 1.3k 721 42 6.2k
Taejin Park United States 24 3.9k 0.9× 2.6k 0.9× 1.3k 0.9× 1.2k 0.9× 698 1.0× 64 5.5k
Zaichun Zhu China 34 5.0k 1.1× 2.8k 1.0× 1.5k 1.0× 928 0.7× 675 0.9× 79 6.5k
Xu Lian China 31 5.5k 1.2× 2.6k 0.9× 2.1k 1.4× 925 0.7× 993 1.4× 57 7.4k
William K. Smith United States 43 4.5k 1.0× 2.4k 0.9× 1.6k 1.1× 633 0.5× 1.2k 1.7× 117 6.8k
Mingguo Ma China 44 4.1k 0.9× 2.3k 0.8× 2.0k 1.4× 2.0k 1.6× 289 0.4× 202 6.4k
Matthias Forkel Germany 32 3.5k 0.8× 1.8k 0.6× 1.5k 1.0× 824 0.6× 539 0.7× 72 5.0k
Paul V. Bolstad United States 44 3.7k 0.8× 2.5k 0.9× 1.1k 0.8× 1.3k 1.0× 1.5k 2.1× 103 6.2k
Bin Zhao China 40 2.7k 0.6× 3.4k 1.2× 849 0.6× 1.2k 0.9× 481 0.7× 143 5.9k
Zongming Wang China 52 4.3k 1.0× 4.8k 1.8× 1.1k 0.7× 1.9k 1.4× 548 0.8× 286 8.6k
Conghe Song United States 47 5.5k 1.2× 3.7k 1.3× 1.7k 1.2× 3.2k 2.5× 884 1.2× 132 8.6k

Countries citing papers authored by Chi Chen

Since Specialization
Citations

This map shows the geographic impact of Chi Chen'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 Chi Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi Chen more than expected).

Fields of papers citing papers by Chi Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chi Chen. 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 Chi Chen. The network helps show where Chi Chen may publish in the future.

Co-authorship network of co-authors of Chi Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Chi Chen. A scholar is included among the top collaborators of Chi Chen 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 Chi Chen. Chi Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhou, Jian, et al.. (2025). BEVFix: Deep feature enhancement for robust 3D object detection. Neural Networks. 190. 107675–107675.
2.
Chen, Chi, et al.. (2024). Automated segmentation of individual leafy potato stems after canopy consolidation using YOLOv8x with spatial and spectral features for UAV-based dense crop identification. Computers and Electronics in Agriculture. 219. 108795–108795. 10 indexed citations
3.
Chen, Chi, Yang Li, Xuhui Wang, et al.. (2024). Biophysical effects of croplands on land surface temperature. Nature Communications. 15(1). 10901–10901. 7 indexed citations
5.
Zhao, Ruiying, et al.. (2024). Cropland expansion drives vegetation greenness decline in Southeast Asia. Biogeosciences. 21(23). 5393–5406. 2 indexed citations
6.
Wu, Weitong, Jianping Li, Chi Chen, et al.. (2023). AFLI-Calib: Robust LiDAR-IMU extrinsic self-calibration based on adaptive frame length LiDAR odometry. ISPRS Journal of Photogrammetry and Remote Sensing. 199. 157–181. 18 indexed citations
7.
Chen, Chi. (2023). Global Carbon Neutral Pathways and China's Strategies under Paris Agreement Climate Goals. Highlights in Business Economics and Management. 3. 86–94.
9.
Li, Jun, Emanuele Bevacqua, Chi Chen, et al.. (2022). Regional asymmetry in the response of global vegetation growth to springtime compound climate events. Communications Earth & Environment. 3(1). 41 indexed citations
10.
Cortés, José, Miguel D. Mahecha, Markus Reichstein, et al.. (2021). Where Are Global Vegetation Greening and Browning Trends Significant?. Geophysical Research Letters. 48(6). 100 indexed citations
11.
Yang, Bisheng, et al.. (2021). Automated 3D Road Boundary Extraction and Vectorization Using MLS Point Clouds. IEEE Transactions on Intelligent Transportation Systems. 23(6). 5287–5297. 36 indexed citations
12.
Fan, Lei, Jean‐Pierre Wigneron, Philippe Ciais, et al.. (2019). Satellite-observed pantropical carbon dynamics. Nature Plants. 5(9). 944–951. 160 indexed citations
13.
Song, Wanjuan, Yuri Knyazikhin, Guoyong Wen, et al.. (2018). Implications of Whole-Disc DSCOVR EPIC Spectral Observations for Estimating Earth’s Spectral Reflectivity Based on Low-Earth-Orbiting and Geostationary Observations. Remote Sensing. 10(10). 1594–1594. 18 indexed citations
14.
Li, Wei, Philippe Ciais, Yilong Wang, et al.. (2018). Recent Changes in Global Photosynthesis and Terrestrial Ecosystem Respiration Constrained From Multiple Observations. Geophysical Research Letters. 45(2). 1058–1068. 21 indexed citations
15.
Yan, Kai, Taejin Park, Chi Chen, et al.. (2018). Generating Global Products of LAI and FPAR From SNPP-VIIRS Data: Theoretical Background and Implementation. IEEE Transactions on Geoscience and Remote Sensing. 56(4). 2119–2137. 92 indexed citations
16.
Tian, Feng, Jean‐Pierre Wigneron, Philippe Ciais, et al.. (2018). Coupling of ecosystem-scale plant water storage and leaf phenology observed by satellite. Nature Ecology & Evolution. 2(9). 1428–1435. 141 indexed citations
17.
Song, Wanjuan, Guoyong Wen, Alexander Marshak, et al.. (2017). Earth reflectivity from Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Camera (EPIC). OpenBU/Boston University Institutional Repository (Boston University). 2017. 1 indexed citations
18.
Yang, Bin, Yuri Knyazikhin, Matti Mõttus, et al.. (2017). Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data: Theoretical basis. Remote Sensing of Environment. 198. 69–84. 55 indexed citations
19.
Yan, Kai, Taejin Park, Guangjian Yan, et al.. (2016). Evaluation of MODIS LAI/FPAR Product Collection 6. Part 1: Consistency and Improvements. Remote Sensing. 8(5). 359–359. 179 indexed citations
20.
Yan, Kai, Taejin Park, Guangjian Yan, et al.. (2016). Evaluation of MODIS LAI/FPAR Product Collection 6. Part 2: Validation and Intercomparison. Remote Sensing. 8(6). 460–460. 239 indexed citations

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.

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