Chongya Jiang

6.3k total citations · 1 hit paper
72 papers, 3.1k citations indexed

About

Chongya Jiang is a scholar working on Ecology, Global and Planetary Change and Plant Science. According to data from OpenAlex, Chongya Jiang has authored 72 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Ecology, 45 papers in Global and Planetary Change and 27 papers in Plant Science. Recurrent topics in Chongya Jiang's work include Remote Sensing in Agriculture (46 papers), Plant Water Relations and Carbon Dynamics (34 papers) and Leaf Properties and Growth Measurement (12 papers). Chongya Jiang is often cited by papers focused on Remote Sensing in Agriculture (46 papers), Plant Water Relations and Carbon Dynamics (34 papers) and Leaf Properties and Growth Measurement (12 papers). Chongya Jiang collaborates with scholars based in United States, China and South Korea. Chongya Jiang's co-authors include Youngryel Ryu, Hongliang Fang, Kaiyu Guan, Bin Peng, Shanshan Wei, Hyungsuk Kimm, Sheng Wang, Hideki Kobayashi, Matteo Detto and Wenjuan Li and has published in prestigious journals such as Nature Communications, Environmental Science & Technology and The Science of The Total Environment.

In The Last Decade

Chongya Jiang

68 papers receiving 3.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems

2024 60 citations Licheng Liu, Wang Zhou et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chongya Jiang United States	33	1.9k	1.6k	823	774	432	72	3.1k
Xiufang Zhu China	30	1.7k 0.9×	1.1k 0.7×	624 0.8×	441 0.6×	580 1.3×	92	3.0k
Éric Ceschia France	26	1.6k 0.8×	1.1k 0.7×	678 0.8×	806 1.0×	696 1.6×	60	2.9k
Martin Claverie United States	18	1.9k 1.0×	2.3k 1.5×	458 0.6×	1.3k 1.7×	720 1.7×	37	3.6k
D. Drewry United States	20	1.7k 0.9×	821 0.5×	526 0.6×	369 0.5×	422 1.0×	43	2.2k
Guido D’Urso Italy	31	1.7k 0.9×	1.4k 0.9×	758 0.9×	1.2k 1.5×	484 1.1×	113	3.2k
Thomas R. Clarke United States	20	1.3k 0.7×	1.2k 0.7×	756 0.9×	907 1.2×	385 0.9×	35	2.3k
Holly Croft Canada	32	1.4k 0.7×	1.5k 0.9×	1.1k 1.4×	571 0.7×	316 0.7×	59	2.6k
Toshihiro Sakamoto Japan	25	1.4k 0.7×	2.2k 1.4×	1.1k 1.3×	887 1.1×	636 1.5×	61	3.3k

Countries citing papers authored by Chongya Jiang

Since Specialization

Citations

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

Fields of papers citing papers by Chongya Jiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chongya Jiang

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

All Works

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20 of 20 papers shown

Sun, Haoran, Weiguo Yu, Hengbiao Zheng, et al.. (2025). SIDEST: A sample-free framework for crop field boundary delineation by integrating super-resolution image reconstruction and dual edge-corrected Segment Anything model. Computers and Electronics in Agriculture. 230. 109897–109897. 7 indexed citations

Wang, Weiwei, Elena Blanc‐Betes, Madhu Khanna, et al.. (2025). Land conversion to energy crops for sustainable aviation fuel production reduces greenhouse gas emissions in the United States. Communications Earth & Environment. 6(1). 1 indexed citations

Yan, Yulin, Bolun Li, Benjamin Dechant, et al.. (2025). Plant traits shape global spatiotemporal variations in photosynthetic efficiency. Nature Plants. 11(4). 924–934. 2 indexed citations

Zhou, Meng, Timothy A. Warner, Hengbiao Zheng, et al.. (2025). A in-seasonal phenology monitoring approach for wheat breeding accessions with time-series RGB imagery by using a combination KNN-CNN-RF model. ISPRS Journal of Photogrammetry and Remote Sensing. 227. 297–315.

Xue, Bowen, Long Tian, Pablo J. Zarco‐Tejada, et al.. (2025). A two-step approach to mitigating phenological influences on spectroscopic detection of rice blast and removing pseudo severity estimates in healthy plants. Computers and Electronics in Agriculture. 236. 110458–110458.

Xu, Lian, et al.. (2025). A long-term reconstruction of a global photosynthesis proxy over 1982–2023. Scientific Data. 12(1). 372–372. 5 indexed citations

Wu, Yapeng, Weiguo Yu, Qi Zhang, et al.. (2024). Accurate estimation of grain number per panicle in winter wheat by synergistic use of UAV imagery and meteorological data. International Journal of Applied Earth Observation and Geoinformation. 136. 104320–104320. 1 indexed citations

Gao, Lun, Kaiyu Guan, Liyin He, et al.. (2024). Tropospheric ozone pollution increases the sensitivity of plant production to vapor pressure deficit across diverse ecosystems in the Northern Hemisphere. The Science of The Total Environment. 951. 175748–175748. 3 indexed citations

Gao, Lun, Kaiyu Guan, Chongya Jiang, et al.. (2024). Incorporating environmental stress improves estimation of photosynthesis from NIRvP in US Great Plains pasturelands and Midwest croplands. Remote Sensing of Environment. 316. 114516–114516. 3 indexed citations

10.

Liu, Licheng, Wang Zhou, Kaiyu Guan, et al.. (2024). Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems. Nature Communications. 15(1). 357–357. 60 indexed citations breakdown →

11.

Wang, Yongxian, Mingchao Shao, Xia Yao, et al.. (2024). Design and implementation of a portable snapshot multispectral imaging crop-growth sensor. Frontiers in Plant Science. 15. 1416221–1416221.

12.

Zhang, Jinhan, Xiaomao Lin, Chongya Jiang, et al.. (2024). Predicting rice phenology across China by integrating crop phenology model and machine learning. The Science of The Total Environment. 951. 175585–175585. 12 indexed citations

13.

Jiang, Chongya, et al.. (2023). A vehicle imaging approach to acquire ground truth data for upscaling to satellite data: A case study for estimating harvesting dates. Remote Sensing of Environment. 300. 113894–113894. 9 indexed citations

14.

Zhou, Junxiong, Qi Yang, Licheng Liu, et al.. (2023). A deep transfer learning framework for mapping high spatiotemporal resolution LAI. ISPRS Journal of Photogrammetry and Remote Sensing. 206. 30–48. 17 indexed citations

15.

Wang, Sheng, Kaiyu Guan, Chenhui Zhang, et al.. (2022). Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data. Remote Sensing of Environment. 285. 113366–113366. 45 indexed citations

16.

Zhou, Qu, Kaiyu Guan, Sheng Wang, et al.. (2022). Recent Rapid Increase of Cover Crop Adoption Across the U.S. Midwest Detected by Fusing Multi‐Source Satellite Data. Geophysical Research Letters. 49(22). 39 indexed citations

17.

Kimm, Hyungsuk, Kaiyu Guan, Chongya Jiang, et al.. (2021). A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt. Environmental Research Letters. 16(12). 124051–124051. 41 indexed citations

18.

Wu, Genghong, Kaiyu Guan, Chongya Jiang, et al.. (2019). Radiance-based NIR_v as a proxy for GPP of corn and soybean. Environmental Research Letters. 15(3). 34009–34009. 79 indexed citations

19.

Ryu, Youngryel, Benjamin Dechant, Joseph A. Berry, et al.. (2018). Sun-induced chlorophyll fluorescence is more strongly related to absorbed light than to photosynthesis at half-hourly resolution in a rice paddy. Remote Sensing of Environment. 216. 658–673. 182 indexed citations

20.

Jiang, Chongya & Hua Fang. (2012). Soil Reflectance Modeling With A Global Spectral Library: Refinement of The Price Soil Reflectance Model. AGU Fall Meeting Abstracts. 2012. 1 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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