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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:

UAV Hyperspectral Data Combined with Machine Learning for Winter Wheat Canopy SPAD Values Estimation
Qi Wang, Xiaokai Chen, Huayi Meng, et al.
Remote Sensing (2023) Vol. 15, Iss. 19, pp. 4658-4658
Open Access | Times Cited: 11

Showing 11 citing articles:

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: 10
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
UAV-assisted method for dynamic monitoring of wheat uniformity toward yield and biomass estimation
Yandong Yang, Qing Li, Yue Mu, et al.
Plant Phenomics (2024) Vol. 6
Open Access | Times Cited: 5
Ground-Based Hyperspectral Estimation of Maize Leaf Chlorophyll Content Considering Phenological Characteristics
Yiming Guo, Shiyu Jiang, Huiling Miao, et al.
Remote Sensing (2024) Vol. 16, Iss. 12, pp. 2133-2133
Open Access | Times Cited: 4
Deep Feature-Based Hyperspectral Object Tracking: An Experimental Survey and Outlook
Yuchao Wang, Xu Li, Xinyan Yang, et al.
Remote Sensing (2025) Vol. 17, Iss. 4, pp. 645-645
Open Access
Field-Scale Winter Wheat Growth Prediction Applying Machine Learning Methods with Unmanned Aerial Vehicle Imagery and Soil Properties
Lwandile Nduku, Cilence Munghemezulu, Zinhle Mashaba-Munghemezulu, et al.
Land (2024) Vol. 13, Iss. 3, pp. 299-299
Open Access | Times Cited: 3
Retrieval of Crop Canopy Chlorophyll: Machine Learning vs. Radiative Transfer Model
Mir Md Tasnim Alam, Anita Šimić Milas, Mateo Gašparović, et al.
Remote Sensing (2024) Vol. 16, Iss. 12, pp. 2058-2058
Open Access | Times Cited: 3
Enhancing Winter Wheat Soil–Plant Analysis Development Value Prediction through Evaluating Unmanned Aerial Vehicle Flight Altitudes, Predictor Variable Combinations, and Machine Learning Algorithms
Jianjun Wang, Yin Quan, Lige Cao, et al.
Plants (2024) Vol. 13, Iss. 14, pp. 1926-1926
Open Access | Times Cited: 3
Inversion of Glycyrrhiza Chlorophyll Content Based on Hyperspectral Imagery
Miaomiao Xu, Jian‐Guo Dai, Guoshun Zhang, et al.
Agronomy (2024) Vol. 14, Iss. 6, pp. 1163-1163
Open Access | Times Cited: 2
Non-destructive chlorophyll prediction by machine learning techniques using RGB-based vegetation indices in wheat
Biswabiplab Singh, Allimuthu Elangovan, Sudhir Kumar, et al.
Plant Physiology Reports (2024)
Closed Access | Times Cited: 2
Retrieval of the Crop Canopy Chlorophyll: Machine Learning vs. Radiative Transfer Model
Mir Md Tasnim Alam, Anita Šimić Milas, Mateo Gašparović, et al.
(2024)
Open Access | Times Cited: 1
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