Riqiang Chen

1.3k total citations · 6 hit papers
44 papers, 951 citations indexed

About

Riqiang Chen is a scholar working on Ecology, Plant Science and Environmental Engineering. According to data from OpenAlex, Riqiang Chen has authored 44 papers receiving a total of 951 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Ecology, 23 papers in Plant Science and 18 papers in Environmental Engineering. Recurrent topics in Riqiang Chen's work include Remote Sensing in Agriculture (40 papers), Remote Sensing and LiDAR Applications (17 papers) and Spectroscopy and Chemometric Analyses (11 papers). Riqiang Chen is often cited by papers focused on Remote Sensing in Agriculture (40 papers), Remote Sensing and LiDAR Applications (17 papers) and Spectroscopy and Chemometric Analyses (11 papers). Riqiang Chen collaborates with scholars based in China and Germany. Riqiang Chen's co-authors include Guijun Yang, Haikuan Feng, Mingbo Bian, Yiguang Fan, Yanpeng Ma, Jibo Yue, Hao Yang, Yang Liu, Chengjian Zhang and Muhammad Adeel Hassan and has published in prestigious journals such as Remote Sensing of Environment, IEEE Transactions on Geoscience and Remote Sensing and Frontiers in Plant Science.

In The Last Decade

Riqiang Chen

40 papers receiving 930 citations

Hit Papers

5 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.

UAV-based multi-sensor data fusion and machine learning algorithm for yield prediction in wheat

2022 191 citations Riqiang Chen et al. profile →
Estimating potato above-ground biomass based on vegetation indices and texture features constructed from sensitive bands of UAV hyperspectral imagery

2024 65 citations Yang Liu, Yiguang Fan et al. Computers and Electronics in Agriculture profile →
Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data

2024 57 citations Yang Liu, Haikuan Feng et al. Computers and Electronics in Agriculture profile →
Improving potato above ground biomass estimation combining hyperspectral data and harmonic decomposition techniques

2024 53 citations Yang Liu, Haikuan Feng et al. Computers and Electronics in Agriculture profile →
Utilizing UAV-based hyperspectral remote sensing combined with various agronomic traits to monitor potato growth and estimate yield

2025 30 citations Yang Liu, Haikuan Feng et al. Computers and Electronics in Agriculture profile →
Estimation of potato above-ground biomass based on the VGC-AGB model and deep learning

2025 15 citations Haikuan Feng, Yiguang Fan et al. Computers and Electronics in Agriculture profile →

Peers

Riqiang Chen

ECOLO

Yiguang Fan China

Heli Li China

Fábio Henrique Rojo Baio Brazil

Xiaoqing Zhao China

Yanpeng Ma China

Reddy Pullanagari New Zealand

Ittai Herrmann Israel

Xiaohe Gu China

Liang Wan China

Anna Chlingaryan Australia

Yiguang Fan China

Riqiang Chen

545 ×0.9

ECOLO

325 ×0.7

237 ×0.7

200 ×0.9

160 ×0.9

Citations per year, relative to Riqiang Chen Riqiang Chen (= 1×) peers Yiguang Fan

Countries citing papers authored by Riqiang Chen

Since Specialization

Citations

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

Fields of papers citing papers by Riqiang Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Riqiang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Riqiang Chen. A scholar is included among the top collaborators of Riqiang 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 Riqiang Chen. Riqiang Chen 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

Feng, Haikuan, Yiguang Fan, Jibo Yue, et al.. (2025). Estimation of potato above-ground biomass based on the VGC-AGB model and deep learning. Computers and Electronics in Agriculture. 232. 110122–110122. 15 indexed citations breakdown →

Liu, Yang, Haikuan Feng, Yiguang Fan, et al.. (2025). Utilizing UAV-based hyperspectral remote sensing combined with various agronomic traits to monitor potato growth and estimate yield. Computers and Electronics in Agriculture. 231. 109984–109984. 30 indexed citations breakdown →

Zhang, Chengjian, Zhibo Chen, Riqiang Chen, et al.. (2025). Retrieving the chlorophyll content of individual apple trees by reducing canopy shadow impact via a 3D radiative transfer model and UAV multispectral imagery. Plant Phenomics. 7(1). 100015–100015. 3 indexed citations

Feng, Haikuan, Yiguang Fan, Jibo Yue, et al.. (2025). Enhancing potato leaf protein content, carbon-based constituents, and leaf area index monitoring using radiative transfer model and deep learning. European Journal of Agronomy. 166. 127580–127580. 5 indexed citations

Zhang, Wenjie, Chengjian Zhang, Riqiang Chen, et al.. (2025). Quantifying the severity of Marssonina blotch on apple leaves: development and validation of a novel spectral index. Plant Methods. 21(1). 102–102. 1 indexed citations

Chen, Riqiang, et al.. (2024). Automatic Rice Early-Season Mapping Based on Simple Non-Iterative Clustering and Multi-Source Remote Sensing Images. Remote Sensing. 16(2). 277–277. 8 indexed citations

Chen, Riqiang, Wenping Liu, Hao Yang, et al.. (2024). A novel framework to assess apple leaf nitrogen content: Fusion of hyperspectral reflectance and phenology information through deep learning. Computers and Electronics in Agriculture. 219. 108816–108816. 14 indexed citations

Liu, Yang, Yiguang Fan, Jibo Yue, et al.. (2024). A model suitable for estimating above-ground biomass of potatoes at different regional levels. Computers and Electronics in Agriculture. 222. 109081–109081. 38 indexed citations

Chen, Riqiang, Hao Yang, Wenping Liu, et al.. (2024). An orchard mapping index and mapping algorithm coupling orchard phenology and green-holding characteristics from time-series sentinel-2 images. Computers and Electronics in Agriculture. 226. 109437–109437. 3 indexed citations

10.

Zhang, Chengjian, Zhibo Chen, Guijun Yang, et al.. (2024). Removal of canopy shadows improved retrieval accuracy of individual apple tree crowns LAI and chlorophyll content using UAV multispectral imagery and PROSAIL model. Computers and Electronics in Agriculture. 221. 108959–108959. 19 indexed citations

11.

Liu, Yang, Haikuan Feng, Jibo Yue, et al.. (2024). Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data. Computers and Electronics in Agriculture. 219. 108808–108808. 57 indexed citations breakdown →

12.

Liu, Yang, Jibo Yue, Wanxue Zhu, et al.. (2024). Crop canopy volume weighted by color parameters from UAV-based RGB imagery to estimate above-ground biomass of potatoes. Computers and Electronics in Agriculture. 227. 109678–109678. 31 indexed citations

13.

Liu, Yang, Yiguang Fan, Yihan Yao, et al.. (2024). Estimation of potato leaf area index based on spectral information and Haralick textures from UAV hyperspectral images. Frontiers in Plant Science. 15. 1492372–1492372. 3 indexed citations

14.

Fan, Yiguang, Yang Liu, Jibo Yue, et al.. (2024). Estimation of potato yield using a semi-mechanistic model developed by proximal remote sensing and environmental variables. Computers and Electronics in Agriculture. 223. 109117–109117. 18 indexed citations

15.

Zhao, Dan, Hao Yang, Guijun Yang, et al.. (2024). Estimation of Maize Biomass at Multi-Growing Stage Using Stem and Leaf Separation Strategies with 3D Radiative Transfer Model and CNN Transfer Learning. Remote Sensing. 16(16). 3000–3000. 7 indexed citations

16.

Yang, Guijun, Hao Yang, Haikuan Feng, et al.. (2023). Orchard classification based on super-pixels and deep learning with sparse optical images. Computers and Electronics in Agriculture. 215. 108379–108379. 6 indexed citations

17.

Chen, Riqiang, Hao Yang, Guijun Yang, et al.. (2023). Land-Use Mapping with Multi-Temporal Sentinel Images Based on Google Earth Engine in Southern Xinjiang Uygur Autonomous Region, China. Remote Sensing. 15(16). 3958–3958. 9 indexed citations

18.

Bian, Mingbo, Zhichao Chen, Yiguang Fan, et al.. (2023). Integrating Spectral, Textural, and Morphological Data for Potato LAI Estimation from UAV Images. Agronomy. 13(12). 3070–3070. 9 indexed citations

19.

Wang, Han, Wangfei Zhang, Guijun Yang, et al.. (2023). Maize Ear Height and Ear–Plant Height Ratio Estimation with LiDAR Data and Vertical Leaf Area Profile. Remote Sensing. 15(4). 964–964. 12 indexed citations

20.

Li, Heli, Shaoyu Han, Riqiang Chen, et al.. (2023). Estimation of Soybean Yield by Combining Maturity Group Information and Unmanned Aerial Vehicle Multi-Sensor Data Using Machine Learning. Remote Sensing. 15(17). 4286–4286. 23 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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