Huiren Tian

643 total citations · 1 hit paper
12 papers, 439 citations indexed

About

Huiren Tian is a scholar working on Ecology, Plant Science and Environmental Engineering. According to data from OpenAlex, Huiren Tian has authored 12 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Ecology, 10 papers in Plant Science and 3 papers in Environmental Engineering. Recurrent topics in Huiren Tian's work include Remote Sensing in Agriculture (11 papers), Smart Agriculture and AI (7 papers) and Greenhouse Technology and Climate Control (6 papers). Huiren Tian is often cited by papers focused on Remote Sensing in Agriculture (11 papers), Smart Agriculture and AI (7 papers) and Greenhouse Technology and Climate Control (6 papers). Huiren Tian collaborates with scholars based in China, United Kingdom and Belgium. Huiren Tian's co-authors include Kevin Tansey, Pengxin Wang, Shuyu Zhang, Jingqi Zhang, Hongmei Li, Dong Han, Junming Liu, Wenting Quan, Jie Wang and Hongmei Li and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Agricultural and Forest Meteorology and Computers and Electronics in Agriculture.

In The Last Decade

Huiren Tian

10 papers receiving 430 citations

Hit Papers

1 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.

A deep learning framework combining CNN and GRU for improving wheat yield estimates using time series remotely sensed multi-variables

2023 77 citations Jie Wang, Pengxin Wang et al. Computers and Electronics in Agriculture profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Huiren Tian China	10	244	227	116	82	60	12	439
Luan Pierre Pott Brazil	8	242 1.0×	298 1.3×	79 0.7×	60 0.7×	41 0.7×	17	478
Tiecheng Bai China	15	174 0.7×	195 0.9×	109 0.9×	108 1.3×	80 1.3×	45	526
Benson Kipkemboi Kenduiywo Kenya	10	189 0.8×	154 0.7×	98 0.8×	95 1.2×	47 0.8×	34	439
Sumanta Das India	13	181 0.7×	153 0.7×	215 1.9×	81 1.0×	62 1.0×	49	506
Wenxuan Guo United States	13	224 0.9×	288 1.3×	147 1.3×	71 0.9×	24 0.4×	39	535
Geomar Mateus Corassa Brazil	11	311 1.3×	445 2.0×	107 0.9×	84 1.0×	47 0.8×	23	671
Ma. Luisa Buchaillot Spain	8	331 1.4×	316 1.4×	144 1.2×	102 1.2×	46 0.8×	22	588
Yi Bai China	12	359 1.5×	294 1.3×	205 1.8×	73 0.9×	74 1.2×	21	527
Xun Yu China	12	314 1.3×	290 1.3×	202 1.7×	105 1.3×	60 1.0×	34	583

Countries citing papers authored by Huiren Tian

Since Specialization

Citations

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

Fields of papers citing papers by Huiren Tian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huiren Tian

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

All Works

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12 of 12 papers shown

Zeng, Yelu, Anne Gobin, Jianxi Huang, et al.. (2025). Normalized Solar-Induced Fluorescence Responds Earlier Than Vegetation Indices to the 2019 North China Plain Drought. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–13.

Tian, Huiren, Pengxin Wang, Kevin Tansey, & Shuyu Zhang. (2025). A Knowledge-Guided Deep Learning Framework With Remotely Sensed Variables and Meteorological Variables for Improving Wheat Yield Estimation. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–13.

Tian, Huiren, Pengxin Wang, Kevin Tansey, et al.. (2024). Attention mechanism-based deep learning approach for wheat yield estimation and uncertainty analysis from remotely sensed variables. Agricultural and Forest Meteorology. 356. 110183–110183. 10 indexed citations

Wang, Jie, Pengxin Wang, Huiren Tian, et al.. (2023). A deep learning framework combining CNN and GRU for improving wheat yield estimates using time series remotely sensed multi-variables. Computers and Electronics in Agriculture. 206. 107705–107705. 77 indexed citations breakdown →

Han, Dong, Pengxin Wang, Kevin Tansey, et al.. (2022). Integrating an attention-based deep learning framework and the SAFY-V model for winter wheat yield estimation using time series SAR and optical data. Computers and Electronics in Agriculture. 201. 107334–107334. 11 indexed citations

Zhang, Jingqi, Huiren Tian, Pengxin Wang, et al.. (2021). Improving wheat yield estimates using data augmentation models and remotely sensed biophysical indices within deep neural networks in the Guanzhong Plain, PR China. Computers and Electronics in Agriculture. 192. 106616–106616. 27 indexed citations

Tian, Huiren, Pengxin Wang, Kevin Tansey, et al.. (2021). An LSTM neural network for improving wheat yield estimates by integrating remote sensing data and meteorological data in the Guanzhong Plain, PR China. Agricultural and Forest Meteorology. 310. 108629–108629. 123 indexed citations

Tian, Huiren, Pengxin Wang, Kevin Tansey, et al.. (2021). A deep learning framework under attention mechanism for wheat yield estimation using remotely sensed indices in the Guanzhong Plain, PR China. International Journal of Applied Earth Observation and Geoinformation. 102. 102375–102375. 72 indexed citations

Han, Dong, Pengxin Wang, Kevin Tansey, et al.. (2021). Improving Wheat Yield Estimates by Integrating a Remotely Sensed Drought Monitoring Index Into the Simple Algorithm for Yield Estimate Model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 10383–10394. 12 indexed citations

10.

Wang, Pengxin, et al.. (2020). Reconstruction of time series leaf area index for improving wheat yield estimates at field scales by fusion of Sentinel-2, -3 and MODIS imagery. Computers and Electronics in Agriculture. 177. 105692–105692. 34 indexed citations

11.

Tian, Huiren, Pengxin Wang, Kevin Tansey, et al.. (2020). An IPSO-BP neural network for estimating wheat yield using two remotely sensed variables in the Guanzhong Plain, PR China. Computers and Electronics in Agriculture. 169. 105180–105180. 55 indexed citations

12.

Han, Dong, Pengxin Wang, Kevin Tansey, et al.. (2020). Linking an agro-meteorological model and a water cloud model for estimating soil water content over wheat fields. Computers and Electronics in Agriculture. 179. 105833–105833. 18 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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