Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 biomass of winter oilseed rape using vegetation indices and texture metrics derived from UAV multispectral images
Yinuo Liu, Shishi Liu, Jing Li, et al.
Computers and Electronics in Agriculture (2019) Vol. 166, pp. 105026-105026
Closed Access | Times Cited: 117

Showing 1-25 of 117 citing articles:

UAV-based multi-sensor data fusion and machine learning algorithm for yield prediction in wheat
Shuaipeng Fei, Muhammad Adeel Hassan, Yonggui Xiao, et al.
Precision Agriculture (2022) Vol. 24, Iss. 1, pp. 187-212
Open Access | Times Cited: 170
A comprehensive review on recent applications of unmanned aerial vehicle remote sensing with various sensors for high-throughput plant phenotyping
Lei Feng, Shuangshuang Chen, Chu Zhang, et al.
Computers and Electronics in Agriculture (2021) Vol. 182, pp. 106033-106033
Closed Access | Times Cited: 156
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
Predicting Canopy Chlorophyll Content in Sugarcane Crops Using Machine Learning Algorithms and Spectral Vegetation Indices Derived from UAV Multispectral Imagery
A. Narmilan, Felipe González, Arachchige Surantha Ashan Salgadoe, et al.
Remote Sensing (2022) Vol. 14, Iss. 5, pp. 1140-1140
Open Access | Times Cited: 83
Estimating potato above-ground biomass by using integrated unmanned aerial system-based optical, structural, and textural canopy measurements
Yang Liu, Haikuan Feng, Jibo Yue, et al.
Computers and Electronics in Agriculture (2023) Vol. 213, pp. 108229-108229
Closed Access | Times Cited: 64
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
A model suitable for estimating above-ground biomass of potatoes at different regional levels
Yang Liu, Yiguang Fan, Jibo Yue, et al.
Computers and Electronics in Agriculture (2024) Vol. 222, pp. 109081-109081
Closed Access | Times Cited: 34
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
Crop rotation history constrains soil biodiversity and multifunctionality relationships
Minghui Li, Junjie Guo, Tao Ren, et al.
Agriculture Ecosystems & Environment (2021) Vol. 319, pp. 107550-107550
Closed Access | Times Cited: 90
Monitoring of sugar beet growth indicators using wide-dynamic-range vegetation index (WDRVI) derived from UAV multispectral images
Yang Cao, Guo Long Li, Yuan Kai Luo, et al.
Computers and Electronics in Agriculture (2020) Vol. 171, pp. 105331-105331
Closed Access | Times Cited: 73
Combining UAV multispectral imagery and ecological factors to estimate leaf nitrogen and grain protein content of wheat
Zhaopeng Fu, Shanshan Yu, Jiayi Zhang, et al.
European Journal of Agronomy (2021) Vol. 132, pp. 126405-126405
Closed Access | Times Cited: 67
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: 61
Above-Ground Biomass Estimation in Oats Using UAV Remote Sensing and Machine Learning
Prakriti Sharma, Larry Leigh, Jiyul Chang, et al.
Sensors (2022) Vol. 22, Iss. 2, pp. 601-601
Open Access | Times Cited: 59
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
An improved approach to estimate ratoon rice aboveground biomass by integrating UAV-based spectral, textural and structural features
Le Xu, Longfei Zhou, Ran Meng, et al.
Precision Agriculture (2022) Vol. 23, Iss. 4, pp. 1276-1301
Closed Access | Times Cited: 52
Integrating the Textural and Spectral Information of UAV Hyperspectral Images for the Improved Estimation of Rice Aboveground Biomass
Tianyue Xu, Fumin Wang, Lili Xie, et al.
Remote Sensing (2022) Vol. 14, Iss. 11, pp. 2534-2534
Open Access | Times Cited: 49
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
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: 41
Crop rotation-driven change in physicochemical properties regulates microbial diversity, dominant components, and community complexity in paddy soils
Hanfeng Zhang, Gongwen Luo, Yizhe Wang, et al.
Agriculture Ecosystems & Environment (2022) Vol. 343, pp. 108278-108278
Closed Access | Times Cited: 40
Improving estimation of maize leaf area index by combining of UAV-based multispectral and thermal infrared data: The potential of new texture index
Ning Yang, Zhitao Zhang, Junrui Zhang, et al.
Computers and Electronics in Agriculture (2023) Vol. 214, pp. 108294-108294
Closed Access | Times Cited: 33
Prediction of cotton FPAR and construction of defoliation spraying prescription map based on multi-source UAV images
Lechun Zhang, Binshu Sun, Denan Zhao, et al.
Computers and Electronics in Agriculture (2024) Vol. 220, pp. 108897-108897
Closed Access | Times Cited: 9
Improving Wheat Leaf Nitrogen Concentration (LNC) Estimation across Multiple Growth Stages Using Feature Combination Indices (FCIs) from UAV Multispectral Imagery
Xiangxiang Su, 櫻井 克年, Yue Hu, et al.
Agronomy (2024) Vol. 14, Iss. 5, pp. 1052-1052
Open Access | Times Cited: 9
Enhancing the accuracy of monitoring effective tiller counts of wheat using multi-source data and machine learning derived from consumer drones
Ziheng Feng, Jiaxiang Cai, Ke Wu, et al.
Computers and Electronics in Agriculture (2025) Vol. 232, pp. 110120-110120
Closed Access | Times Cited: 2
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
Page 1 - Next Page

Scroll to top