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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:

Detection of rice phenology through time series analysis of ground-based spectral index data
Hengbiao Zheng, Tao Cheng, Xia Yao, et al.
Field Crops Research (2016) Vol. 198, pp. 131-139
Closed Access | Times Cited: 102

Showing 1-25 of 102 citing articles:

Drones in agriculture: A review and bibliometric analysis
Abderahman Rejeb, Alireza Abdollahi, Karim Rejeb, et al.
Computers and Electronics in Agriculture (2022) Vol. 198, pp. 107017-107017
Open Access | Times Cited: 372
Deep convolutional neural networks for rice grain yield estimation at the ripening stage using UAV-based remotely sensed images
Qi Yang, Liangsheng Shi, Jingye Han, et al.
Field Crops Research (2019) Vol. 235, pp. 142-153
Closed Access | Times Cited: 311
ChinaCropPhen1km: a high-resolution crop phenological dataset for three staple crops in China during 2000–2015 based on leaf area index (LAI) products
Yuchuan Luo, Zhao Zhang, Yi Chen, et al.
Earth system science data (2020) Vol. 12, Iss. 1, pp. 197-214
Open Access | Times Cited: 216
Evaluation of RGB, Color-Infrared and Multispectral Images Acquired from Unmanned Aerial Systems for the Estimation of Nitrogen Accumulation in Rice
Hengbiao Zheng, Tao Cheng, Dong Li, et al.
Remote Sensing (2018) Vol. 10, Iss. 6, pp. 824-824
Open Access | Times Cited: 180
Combining UAV-based hyperspectral imagery and machine learning algorithms for soil moisture content monitoring
Xiangyu Ge, Jingzhe Wang, Jianli Ding, et al.
PeerJ (2019) Vol. 7, pp. e6926-e6926
Open Access | Times Cited: 172
Integrating spectral and textural information for identifying the tasseling date of summer maize using UAV based RGB images
Yahui Guo, Yongshuo H. Fu, Shouzhi Chen, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102435-102435
Open Access | Times Cited: 71
A systematic method for spatio-temporal phenology estimation of paddy rice using time series Sentinel-1 images
Huijin Yang, Bin Pan, Ning Li, et al.
Remote Sensing of Environment (2021) Vol. 259, pp. 112394-112394
Closed Access | Times Cited: 69
Monitoring rice crop and yield estimation with Sentinel-2 data
Jesús Soriano-González, Eduard Angelats, Maite Martínez‐Eixarch, et al.
Field Crops Research (2022) Vol. 281, pp. 108507-108507
Closed Access | Times Cited: 49
Remote Sensing Monitoring of Rice and Wheat Canopy Nitrogen: A Review
Jie Zheng, Xiaoyu Song, Guijun Yang, et al.
Remote Sensing (2022) Vol. 14, Iss. 22, pp. 5712-5712
Open Access | Times Cited: 40
Wheat phenology detection with the methodology of classification based on the time-series UAV images
Meng Zhou, Hengbiao Zheng, Can He, et al.
Field Crops Research (2023) Vol. 292, pp. 108798-108798
Closed Access | Times Cited: 24
Automatic Rice Early-Season Mapping Based on Simple Non-Iterative Clustering and Multi-Source Remote Sensing Images
G. Wang, Di Meng, Riqiang Chen, et al.
Remote Sensing (2024) Vol. 16, Iss. 2, pp. 277-277
Open Access | Times Cited: 10
WREP: A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops
Dong Li, Tao Cheng, Kai Zhou, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2017) Vol. 129, pp. 103-117
Closed Access | Times Cited: 84
Using hyperspectral analysis as a potential high throughput phenotyping tool in GWAS for protein content of rice quality
Dawei Sun, Haiyan Cen, Haiyong Weng, et al.
Plant Methods (2019) Vol. 15, Iss. 1
Open Access | Times Cited: 71
Establishment of Plot-Yield Prediction Models in Soybean Breeding Programs Using UAV-Based Hyperspectral Remote Sensing
Xiaoyan Zhang, Jin-Ming Zhao, Guijun Yang, et al.
Remote Sensing (2019) Vol. 11, Iss. 23, pp. 2752-2752
Open Access | Times Cited: 57
Detection of phenology using an improved shape model on time-series vegetation index in wheat
Meng Zhou, Xue Ma, Kangkang Wang, et al.
Computers and Electronics in Agriculture (2020) Vol. 173, pp. 105398-105398
Closed Access | Times Cited: 51
Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data
Yanjun Yang, Wei Ren, Bo Tao, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 170, pp. 156-173
Closed Access | Times Cited: 50
Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System
Jun Ni, Lili Yao, Zhang JingChao, et al.
Sensors (2017) Vol. 17, Iss. 3, pp. 502-502
Open Access | Times Cited: 49
Assessing the Effect of Real Spatial Resolution of In Situ UAV Multispectral Images on Seedling Rapeseed Growth Monitoring
Jian Zhang, Chufeng Wang, Chenghai Yang, et al.
Remote Sensing (2020) Vol. 12, Iss. 7, pp. 1207-1207
Open Access | Times Cited: 43
Crop growth monitoring through Sentinel and Landsat data based NDVI time-series
Mukesh Singh Boori, Komal Choudhary, Alexander Kupriyanov
Computer Optics (2020) Vol. 44, Iss. 3
Open Access | Times Cited: 43
Performances of Vegetation Indices on Paddy Rice at Elevated Air Temperature, Heat Stress, and Herbicide Damage
Jae-Hyun Ryu, Hoejeong Jeong, Jaeil Cho
Remote Sensing (2020) Vol. 12, Iss. 16, pp. 2654-2654
Open Access | Times Cited: 43
Real-time detection of rice phenology through convolutional neural network using handheld camera images
Jingye Han, Liangsheng Shi, Qi Yang, et al.
Precision Agriculture (2020) Vol. 22, Iss. 1, pp. 154-178
Closed Access | Times Cited: 42
Estimation and Forecasting of Rice Yield Using Phenology-Based Algorithm and Linear Regression Model on Sentinel-II Satellite Data
Abid Nazir, Saleem Ullah, Zulfiqar Ahmad Saqib, et al.
Agriculture (2021) Vol. 11, Iss. 10, pp. 1026-1026
Open Access | Times Cited: 40
Improving extraction phenology accuracy using SIF coupled with the vegetation index and mapping the spatiotemporal pattern of bamboo forest phenology
Yanxin Xu, Xuejian Li, Huaqiang Du, et al.
Remote Sensing of Environment (2023) Vol. 297, pp. 113785-113785
Open Access | Times Cited: 16
Estimating wheat grain yield by assimilating phenology and LAI with the WheatGrow model based on theoretical uncertainty of remotely sensed observation
Yining Tang, Ruiheng Zhou, Ping He, et al.
Agricultural and Forest Meteorology (2023) Vol. 339, pp. 109574-109574
Closed Access | Times Cited: 14
Spectral-spatial multi-feature classification of remote sensing big data based on a random forest classifier for land cover mapping
X. M. Zhang, Guojin He, Zikun Zhang, et al.
Cluster Computing (2017) Vol. 20, Iss. 3, pp. 2311-2321
Closed Access | Times Cited: 42
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