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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Estimating the maize biomass by crop height and narrowband vegetation indices derived from UAV-based hyperspectral images
Yue Zhang, Chenzhen Xia, Xingyu Zhang, et al.
Ecological Indicators (2021) Vol. 129, pp. 107985-107985
Open Access | Times Cited: 124

Showing 1-25 of 124 citing articles:

UAV-based chlorophyll content estimation by evaluating vegetation index responses under different crop coverages
Lang Qiao, Weijie Tang, Dehua Gao, et al.
Computers and Electronics in Agriculture (2022) Vol. 196, pp. 106775-106775
Closed Access | Times Cited: 144
Remote Sensing in Field Crop Monitoring: A Comprehensive Review of Sensor Systems, Data Analyses and Recent Advances
Emmanuel Omia, Hyungjin Bae, Eunsung Park, et al.
Remote Sensing (2023) Vol. 15, Iss. 2, pp. 354-354
Open Access | Times Cited: 120
Comparison of different machine learning algorithms for predicting maize grain yield using UAV-based hyperspectral images
Yahui Guo, Yi Xiao, Fanghua Hao, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 124, pp. 103528-103528
Open Access | Times Cited: 68
Estimating potato above-ground biomass based on vegetation indices and texture features constructed from sensitive bands of UAV hyperspectral imagery
Yang Liu, Yiguang Fan, Haikuan Feng, et al.
Computers and Electronics in Agriculture (2024) Vol. 220, pp. 108918-108918
Closed Access | Times Cited: 55
Improving potato above ground biomass estimation combining hyperspectral data and harmonic decomposition techniques
Yang Liu, Haikuan Feng, Yiguang Fan, et al.
Computers and Electronics in Agriculture (2024) Vol. 218, pp. 108699-108699
Closed Access | Times Cited: 50
Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data
Yang Liu, Haikuan Feng, Jibo Yue, et al.
Computers and Electronics in Agriculture (2024) Vol. 219, pp. 108808-108808
Closed Access | Times Cited: 48
Hyperspectral Image Analysis and Machine Learning Techniques for Crop Disease Detection and Identification: A Review
Yimy Edisson García Vera, Mauricio Andrés Polochè Arango, Camilo A. Mendivelso-Fajardo, et al.
Sustainability (2024) Vol. 16, Iss. 14, pp. 6064-6064
Open Access | Times Cited: 20
Utilizing UAV-based hyperspectral remote sensing combined with various agronomic traits to monitor potato growth and estimate yield
Yang Liu, Haikuan Feng, Yiguang Fan, et al.
Computers and Electronics in Agriculture (2025) Vol. 231, pp. 109984-109984
Closed Access | Times Cited: 10
Improved Estimation of Aboveground Biomass in Rubber Plantations Using Deep Learning on UAV Multispectral Imagery
Hongjian Tan, Weili Kou, Weiheng Xu, et al.
Drones (2025) Vol. 9, Iss. 1, pp. 32-32
Open Access | Times Cited: 2
Estimation of Above-Ground Biomass of Winter Wheat Based on Consumer-Grade Multi-Spectral UAV
Falv Wang, Mao Yang, Longfei Ma, et al.
Remote Sensing (2022) Vol. 14, Iss. 5, pp. 1251-1251
Open Access | Times Cited: 60
Estimating the maize above-ground biomass by constructing the tridimensional concept model based on UAV-based digital and multi-spectral images
Meiyan Shu, Mengyuan Shen, Dong Qizhou, et al.
Field Crops Research (2022) Vol. 282, pp. 108491-108491
Closed Access | Times Cited: 58
Application of UAV Multisensor Data and Ensemble Approach for High-Throughput Estimation of Maize Phenotyping Traits
Meiyan Shu, Shuaipeng Fei, Bingyu Zhang, et al.
Plant Phenomics (2022) Vol. 2022
Open Access | Times Cited: 57
Retrieving SPAD Values of Summer Maize Using UAV Hyperspectral Data Based on Multiple Machine Learning Algorithm
Bilige Sudu, Guangzhi Rong, Suri Guga, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5407-5407
Open Access | Times Cited: 47
Improved estimation of aboveground biomass in rubber plantations by fusing spectral and textural information from UAV-based RGB imagery
Yuying Liang, Weili Kou, Hongyan Lai, et al.
Ecological Indicators (2022) Vol. 142, pp. 109286-109286
Closed Access | Times Cited: 46
Prediction of soil salinity parameters using machine learning models in an arid region of northwest China
Chao Xiao, Qingyuan Ji, Junqing Chen, et al.
Computers and Electronics in Agriculture (2022) Vol. 204, pp. 107512-107512
Closed Access | Times Cited: 42
Using the plant height and canopy coverage to estimation maize aboveground biomass with UAV digital images
Meiyan Shu, Qing Li, Abu Zar Ghafoor, et al.
European Journal of Agronomy (2023) Vol. 151, pp. 126957-126957
Closed Access | Times Cited: 39
Taking Artificial Intelligence Into Space Through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “brain” close to the “eyes” of satellite missions
Agata M. Wijata, M.F. Foulon, Yves Bobichon, et al.
IEEE Geoscience and Remote Sensing Magazine (2023) Vol. 11, Iss. 2, pp. 10-39
Closed Access | Times Cited: 26
UAV-borne hyperspectral estimation of nitrogen content in tobacco leaves based on ensemble learning methods
Mingzheng Zhang, Tianen Chen, Xiaohe Gu, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 108008-108008
Closed Access | Times Cited: 24
Are unmanned aerial vehicle-based hyperspectral imaging and machine learning advancing crop science?
Alessandro Matese, Joby M. Prince Czarnecki, Sathishkumar Samiappan, et al.
Trends in Plant Science (2023) Vol. 29, Iss. 2, pp. 196-209
Open Access | Times Cited: 24
Combining spectral and texture feature of UAV image with plant height to improve LAI estimation of winter wheat at jointing stage
Mengxi Zou, Yu Liu, Maodong Fu, et al.
Frontiers in Plant Science (2024) Vol. 14
Open Access | Times Cited: 14
UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs
Ocident Bongomin, Jimmy Lamo, Joshua Mugeziaubwa Guina, et al.
The Plant Phenome Journal (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 12
Estimation Model for Cotton Canopy Structure Parameters Based on Spectral Vegetation Index
Yaqin Qi, Xi Chen, Zhengchao Chen, et al.
Life (2025) Vol. 15, Iss. 1, pp. 62-62
Open Access | Times Cited: 1
Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground”
Wu Nile, Rina Su, Na Mula, et al.
Remote Sensing (2025) Vol. 17, Iss. 4, pp. 572-572
Open Access | Times Cited: 1
Estimation of Cotton Leaf Area Index (LAI) Based on Spectral Transformation and Vegetation Index
Yiru Ma, Qiang Zhang, Yi Xiang, et al.
Remote Sensing (2021) Vol. 14, Iss. 1, pp. 136-136
Open Access | Times Cited: 52
UAV-based indicators of crop growth are robust for distinct water and nutrient management but vary between crop development phases
Wanxue Zhu, Ehsan Eyshi Rezaei, Hamideh Nouri, et al.
Field Crops Research (2022) Vol. 284, pp. 108582-108582
Closed Access | Times Cited: 38
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