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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:

Predicting Canopy Chlorophyll Content in Sugarcane Crops Using Machine Learning Algorithms and Spectral Vegetation Indices Derived from UAV Multispectral Imagery
A. Narmilan, Felipé Gonzalez, Arachchige Surantha Ashan Salgadoe, et al.
Remote Sensing (2022) Vol. 14, Iss. 5, pp. 1140-1140
Open Access | Times Cited: 82

Showing 1-25 of 82 citing articles:

Detection of White Leaf Disease in Sugarcane Using Machine Learning Techniques over UAV Multispectral Images
A. Narmilan, Felipé Gonzalez, Arachchige Surantha Ashan Salgadoe, et al.
Drones (2022) Vol. 6, Iss. 9, pp. 230-230
Open Access | Times Cited: 58
High-Throughput Analysis of Leaf Chlorophyll Content in Aquaponically Grown Lettuce Using Hyperspectral Reflectance and RGB Images
Mohamed Farag Taha, Hanping Mao, Yafei Wang, et al.
Plants (2024) Vol. 13, Iss. 3, pp. 392-392
Open Access | Times Cited: 10
Monitoring Maize Canopy Chlorophyll Content throughout the Growth Stages Based on UAV MS and RGB Feature Fusion
Wenfeng Li, Kun Pan, Wenrong Liu, et al.
Agriculture (2024) Vol. 14, Iss. 8, pp. 1265-1265
Open Access | Times Cited: 9
Enhancing in-season yield forecast accuracy for film-mulched wheat: A hybrid approach coupling crop model and UAV remote-sensing data by ensemble learning technique
Zhikai Cheng, Xiaobo Gu, Zhihui Zhou, et al.
European Journal of Agronomy (2024) Vol. 156, pp. 127174-127174
Closed Access | Times Cited: 7
Machine learning assisted remote forestry health assessment: a comprehensive state of the art review
Juan Sebastián Estrada, Andrés Fuentes, Pedro Reszka, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 16
A Survey on Applications of Unmanned Aerial Vehicles Using Machine Learning
Karolayne Teixeira, Geovane Miguel, Hugerles S. Silva, et al.
IEEE Access (2023) Vol. 11, pp. 117582-117621
Open Access | Times Cited: 16
Digital Insights into Plant Health: Exploring Vegetation Indices Through Computer Vision
Manojit Chowdhury, Rohit Anand, Tushar Dhar, et al.
(2024), pp. 7-30
Closed Access | Times Cited: 6
Enhancing phenotyping efficiency in faba bean breeding: integrating UAV imaging and machine learning
Shirin Mohammadi, Anne Kjersti Uhlen, Morten Lillemo, et al.
Precision Agriculture (2024) Vol. 25, Iss. 3, pp. 1502-1528
Open Access | Times Cited: 5
Crop aboveground biomass monitoring model based on UAV spectral index reconstruction and Bayesian model averaging: A case study of film-mulched wheat and maize
Zhikai Cheng, Xiaobo Gu, Zhihui Zhou, et al.
Computers and Electronics in Agriculture (2024) Vol. 224, pp. 109190-109190
Closed Access | Times Cited: 5
Estimating Leaf Chlorophyll Content of Winter Wheat from UAV Multispectral Images Using Machine Learning Algorithms under Different Species, Growth Stages, and Nitrogen Stress Conditions
Liyuan Zhang, Aichen Wang, Huiyue Zhang, et al.
Agriculture (2024) Vol. 14, Iss. 7, pp. 1064-1064
Open Access | Times Cited: 5
Smart Agriculture Based on Artificial Intelligence and Drones Through a Systematic Review
Ali Mhaned, Mouatassim Salma, Mounia El Haji, et al.
IGI Global eBooks (2025), pp. 213-266
Closed Access
Improving potato leaf chlorophyll content prediction using a machine learning model with a hybrid dataset
Haibo Yang, Yuncai Hu, Hang Yin, et al.
International Journal of Remote Sensing (2025), pp. 1-25
Closed Access
Predicting Olive Tree Chlorophyll Fluorescence Using Explainable AI with Sentinel-2 Imagery in Mediterranean Environment
Leonardo Costanza, Beatriz Lorente, Francisco Pedrero Salcedo, et al.
Applied Sciences (2025) Vol. 15, Iss. 5, pp. 2746-2746
Open Access
Automatic optimization of regions of interest in hyperspectral images for detecting vegetative indices in soybeans
Sangyeab Lee, Amit Ghimire, Yoon-Ha Kim, et al.
Frontiers in Plant Science (2025) Vol. 16
Open Access
Evaluating the Canopy Chlorophyll Density of Maize at the Whole Growth Stage Based on Multi-Scale UAV Image Feature Fusion and Machine Learning Methods
Lili Zhou, Chenwei Nie, Tao Su, et al.
Agriculture (2023) Vol. 13, Iss. 4, pp. 895-895
Open Access | Times Cited: 15
Estimation of Winter Wheat Plant Nitrogen Concentration from UAV Hyperspectral Remote Sensing Combined with Machine Learning Methods
Xiaokai Chen, Fenling Li, Botai Shi, et al.
Remote Sensing (2023) Vol. 15, Iss. 11, pp. 2831-2831
Open Access | Times Cited: 15
Autonomous Detection of Mouse-Ear Hawkweed Using Drones, Multispectral Imagery and Supervised Machine Learning
A. Narmilan, Mark Hamilton, J. Kelly, et al.
Remote Sensing (2023) Vol. 15, Iss. 6, pp. 1633-1633
Open Access | Times Cited: 13
Estimation of Plant Height and Biomass of Rice Using Unmanned Aerial Vehicle
Enze Song, Guangcheng Shao, Xueying Zhu, et al.
Agronomy (2024) Vol. 14, Iss. 1, pp. 145-145
Open Access | Times Cited: 4
Use of a UAV for statistical-spectral analysis of vegetation indices in sugarcane plants in the Eastern Amazon
Luiz Antonio Soares Cardoso, Paulo Roberto Silva Farias, João Almiro Corrêa Soares, et al.
International Journal of Environmental Science and Technology (2024) Vol. 21, Iss. 10, pp. 6947-6964
Closed Access | Times Cited: 4
An Estimation of the Leaf Nitrogen Content of Apple Tree Canopies Based on Multispectral Unmanned Aerial Vehicle Imagery and Machine Learning Methods
Xin Zhao, Zeyi Zhao, Fengnian Zhao, et al.
Agronomy (2024) Vol. 14, Iss. 3, pp. 552-552
Open Access | Times Cited: 4
Assessing Drought Stress of Sugarcane Cultivars Using Unmanned Vehicle System (UAS)-Based Vegetation Indices and Physiological Parameters
Ittipon Khuimphukhieo, Mahendra Bhandari, Juan Enciso, et al.
Remote Sensing (2024) Vol. 16, Iss. 8, pp. 1433-1433
Open Access | Times Cited: 4
Multi-modal fusion and multi-task deep learning for monitoring the growth of film-mulched winter wheat
Zhikai Cheng, Xiaobo Gu, Yadan Du, et al.
Precision Agriculture (2024) Vol. 25, Iss. 4, pp. 1933-1957
Closed Access | Times Cited: 4
UAS-based remote sensing for agricultural Monitoring: Current status and perspectives
Jingzhe Wang, Silu Zhang, Iván Lizaga, et al.
Computers and Electronics in Agriculture (2024) Vol. 227, pp. 109501-109501
Closed Access | Times Cited: 4
Mapping Spatial Variability of Sugarcane Foliar Nitrogen, Phosphorus, Potassium and Chlorophyll Concentrations Using Remote Sensing
Ericka Picado Mora, Kerin F. Romero, Muditha K. Heenkenda
Geomatics (2025) Vol. 5, Iss. 1, pp. 3-3
Open Access
A multi-spectral and hyperspectral image dataset for evaluating chemical traits and the water status of avocado, olive and grape through leaf dehydration under laboratory conditions
Juan Sebastian Estrada, Rodrigo Demarco, Ciaran Johnson, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
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