Haikuan Feng

8.7k total citations · 9 hit papers
193 papers, 6.9k citations indexed

About

Haikuan Feng is a scholar working on Ecology, Plant Science and Environmental Engineering. According to data from OpenAlex, Haikuan Feng has authored 193 papers receiving a total of 6.9k indexed citations (citations by other indexed papers that have themselves been cited), including 153 papers in Ecology, 100 papers in Plant Science and 75 papers in Environmental Engineering. Recurrent topics in Haikuan Feng's work include Remote Sensing in Agriculture (153 papers), Remote Sensing and LiDAR Applications (65 papers) and Leaf Properties and Growth Measurement (58 papers). Haikuan Feng is often cited by papers focused on Remote Sensing in Agriculture (153 papers), Remote Sensing and LiDAR Applications (65 papers) and Leaf Properties and Growth Measurement (58 papers). Haikuan Feng collaborates with scholars based in China, United States and United Kingdom. Haikuan Feng's co-authors include Guijun Yang, Zhenhai Li, Jibo Yue, Bo Xu, Xingang Xu, Hao Yang, Xiaodong Yang, Xiuliang Jin, Chunjiang Zhao and Chengquan Zhou and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Remote Sensing of Environment.

In The Last Decade

Haikuan Feng

183 papers receiving 6.8k citations

Hit Papers

Unmanned Aerial Vehicle Remote Sensing for Field-Based Cr... 2017 2026 2020 2023 2017 2017 2019 2019 2024 100 200 300 400 500
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.

  1. Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives
    2017 561 citations Guijun Yang, Chunjiang Zhao et al. profile →
  2. A review of data assimilation of remote sensing and crop models
    2017 387 citations Xiuliang Jin, Zhenhai Li et al. profile →
  3. Estimate of winter-wheat above-ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices
    2019 336 citations Jibo Yue, Guijun Yang et al. profile →
  4. Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
    2019 324 citations Guijun Yang, Huayang Dai et al. profile →
  5. 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 →
  6. 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 →
  7. 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 →
  8. 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 →
  9. 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 — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haikuan Feng China 45 5.2k 3.5k 2.6k 1.5k 1.3k 193 6.9k
Yongchao Tian China 51 5.8k 1.1× 4.9k 1.4× 2.6k 1.0× 1.5k 1.0× 1.6k 1.2× 219 8.1k
Xia Yao China 48 5.4k 1.0× 4.4k 1.3× 2.4k 0.9× 1.4k 0.9× 1.6k 1.3× 218 7.5k
Wenjiang Huang China 50 6.0k 1.1× 4.9k 1.4× 2.3k 0.9× 1.9k 1.3× 2.2k 1.7× 348 9.4k
Yanbo Huang United States 37 2.7k 0.5× 3.0k 0.9× 1.1k 0.4× 989 0.7× 803 0.6× 166 5.7k
Yoshio Inoue Japan 36 3.4k 0.6× 2.3k 0.7× 2.2k 0.9× 2.2k 1.5× 647 0.5× 111 6.9k
Georg Bareth Germany 35 4.3k 0.8× 2.2k 0.6× 3.0k 1.2× 1.2k 0.8× 579 0.4× 131 5.8k
Mirco Boschetti Italy 39 3.0k 0.6× 2.0k 0.6× 1.4k 0.5× 1.7k 1.2× 474 0.4× 156 5.1k
Jiali Shang Canada 43 3.3k 0.6× 1.8k 0.5× 2.8k 1.1× 1.4k 1.0× 578 0.4× 181 6.7k
Timothy J. Arkebauer United States 38 4.6k 0.9× 3.4k 1.0× 1.9k 0.7× 3.2k 2.2× 479 0.4× 95 7.3k
Prasad S. Thenkabail United States 47 6.1k 1.2× 2.0k 0.6× 2.3k 0.9× 3.8k 2.6× 842 0.7× 125 8.6k

Countries citing papers authored by Haikuan Feng

Since Specialization
Citations

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

Fields of papers citing papers by Haikuan Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haikuan Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Haikuan Feng. A scholar is included among the top collaborators of Haikuan Feng 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 Haikuan Feng. Haikuan Feng 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.
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 →
2.
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 →
3.
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
4.
Chen, Yang, et al.. (2025). Identifying Key Traits for Screening High-Yield Soybean Varieties by Combining UAV-Based and Field Phenotyping. Remote Sensing. 17(4). 690–690. 2 indexed citations
5.
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
6.
Zhang, Chengjian, Haikuan Feng, Huiling Long, et al.. (2024). Real-time monitoring of maize phenology with the VI-RGS composite index using time-series UAV remote sensing images and meteorological data. Computers and Electronics in Agriculture. 224. 109212–109212. 17 indexed citations
7.
Yue, Jibo, Guijun Yang, Changchun Li, et al.. (2024). Analyzing winter-wheat biochemical traits using hyperspectral remote sensing and deep learning. Computers and Electronics in Agriculture. 222. 109026–109026. 16 indexed citations
8.
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
9.
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
10.
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
11.
Yue, Jibo, Qingjiu Tian, Yang Liu, et al.. (2023). Mapping cropland rice residue cover using a radiative transfer model and deep learning. Computers and Electronics in Agriculture. 215. 108421–108421. 15 indexed citations
12.
Li, Heli, Guijun Yang, Huiling Long, et al.. (2023). Estimating characteristic coefficient of vertical leaf nitrogen profile within wheat canopy from spectral reflectance. Computers and Electronics in Agriculture. 206. 107652–107652. 8 indexed citations
13.
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
14.
Liu, Yang, Haikuan Feng, Jibo Yue, et al.. (2023). Estimating potato above-ground biomass by using integrated unmanned aerial system-based optical, structural, and textural canopy measurements. Computers and Electronics in Agriculture. 213. 108229–108229. 75 indexed citations
15.
Yue, Jibo, Jia Tian, William Philpot, et al.. (2023). VNAI-NDVI-space and polar coordinate method for assessing crop leaf chlorophyll content and fractional cover. Computers and Electronics in Agriculture. 207. 107758–107758. 33 indexed citations
16.
Liu, Yang, Haikuan Feng, Jibo Yue, et al.. (2022). Estimation of Potato Above-Ground Biomass Based on Vegetation Indices and Green-Edge Parameters Obtained from UAVs. Remote Sensing. 14(21). 5323–5323. 18 indexed citations
17.
Liu, Yang, Haikuan Feng, Jibo Yue, et al.. (2022). Estimation of Potato Above-Ground Biomass Using UAV-Based Hyperspectral images and Machine-Learning Regression. Remote Sensing. 14(21). 5449–5449. 28 indexed citations
18.
Zhang, Jie, et al.. (2022). Remote Sensing Monitoring of Rice Grain Protein Content Based on a Multidimensional Euclidean Distance Method. Remote Sensing. 14(16). 3989–3989. 5 indexed citations
19.
Dai, Huayang, et al.. (2016). Hyperspectral estimation of plant nitrogen content based on Akaike's information criterion. Nongye Gongcheng Xuebao. 32(23). 167. 1 indexed citations
20.
Feng, Haikuan, et al.. (2016). Hyperspectral estimation of leaf area index for winter wheat based on Akaike's information criterion.. Nongye gongcheng xuebao. 32(3). 163–168. 7 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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