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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:

A deep learning approach for deriving winter wheat phenology from optical and SAR time series at field level
Felix Lobert, Johannes Löw, Marcel Schwieder, et al.
Remote Sensing of Environment (2023) Vol. 298, pp. 113800-113800
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Unveiling year-round cropland cover by soil-specific spectral unmixing of Landsat and Sentinel-2 time series
Felix Lobert, Marcel Schwieder, Jonas Alsleben, et al.
Remote Sensing of Environment (2025) Vol. 318, pp. 114594-114594
Open Access | Times Cited: 2
A time-continuous land surface temperature (LST) data fusion approach based on deep learning with microwave remote sensing and high-density ground truth observations
Jiahao Han, Shibo Fang, Qianchuan Mi, et al.
The Science of The Total Environment (2024) Vol. 914, pp. 169992-169992
Closed Access | Times Cited: 10
Fast Dynamic Time Warping and Hierarchical Clustering with Multispectral and Synthetic Aperture Radar Temporal Analysis for Unsupervised Winter Food Crop Mapping
Hsuan-Yi Li, James A. Lawarence, Philippa J. Mason, et al.
Agriculture (2025) Vol. 15, Iss. 1, pp. 82-82
Open Access | Times Cited: 1
Modern computational approaches for rice yield prediction: A systematic review of statistical and machine learning-based methods
Djavan De Clercq, Adam Mahdi
Computers and Electronics in Agriculture (2025) Vol. 231, pp. 109852-109852
Closed Access | Times Cited: 1
Winter wheat harvest detection via Sentinel-2 MSI images
Jibo Yue, Yihan Yao, Jianing Shen, et al.
International Journal of Remote Sensing (2025), pp. 1-19
Closed Access | Times Cited: 1
A transformer-based model for detecting land surface phenology from the irregular harmonized Landsat and Sentinel-2 time series across the United States
Khuong H. Tran, Xiaoyang Zhang, Hankui K. Zhang, et al.
Remote Sensing of Environment (2025) Vol. 320, pp. 114656-114656
Closed Access | Times Cited: 1
Winter wheat maturity date prediction using MODIS/ECMWF data: Accuracy evaluation and spatiotemporal variation analysis
Ruixuan Liu, Fangzhao Zhang, Yuhe Gao, et al.
European Journal of Agronomy (2025) Vol. 167, pp. 127581-127581
Closed Access | Times Cited: 1
Machine Learning-Based Harvest Date Detection and Prediction Using SAR Data for the Vojvodina Region (Serbia)
Gordan Mimić, Amit Kumar Mishra, Miljana Marković, et al.
Sensors (2025) Vol. 25, Iss. 7, pp. 2239-2239
Open Access | Times Cited: 1
Winter Wheat Mapping Method Based on Pseudo-Labels and U-Net Model for Training Sample Shortage
Jianhua Zhang, Shucheng You, Aixia Liu, et al.
Remote Sensing (2024) Vol. 16, Iss. 14, pp. 2553-2553
Open Access | Times Cited: 6
Review of synthetic aperture radar with deep learning in agricultural applications
Mahya G.Z. Hashemi, Ehsan Jalilvand, Hamed Alemohammad, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 218, pp. 20-49
Closed Access | Times Cited: 6
Insights from field phenotyping improve satellite remote sensing based in-season estimation of winter wheat growth and phenology
Lukas Valentin Graf, Quirina Noëmi Merz, Achim Walter, et al.
Remote Sensing of Environment (2023) Vol. 299, pp. 113860-113860
Open Access | Times Cited: 12
Deep learning in multi-sensor agriculture and crop management
Darwin Alexis Arrechea-Castillo, Yady Tatiana Solano‐Correa
Elsevier eBooks (2025), pp. 335-379
Closed Access
Prediction of sugar beet yield and quality parameters using stacked-LSTM model with pre-harvest UAV time series data and meteorological factors
Qing Wang, Ke Shao, Zhibo Cai, et al.
Artificial Intelligence in Agriculture (2025)
Open Access
Potential of Sentinel-1 time-series data for monitoring the phenology of European temperate forests
Michael Schlund
ISPRS Journal of Photogrammetry and Remote Sensing (2025) Vol. 223, pp. 131-145
Open Access
A Novel Fusion of Sentinel-1 and Sentinel-2 with Climate Data for Crop Phenology Estimation using Machine Learning
Shahab Aldin Shojaeezadeh, Abdelrazek Elnashar, Tobias K. D. Weber
Science of Remote Sensing (2025), pp. 100227-100227
Open Access
PSeqNet: A crop phenology monitoring model accounting for phenological associations
Qiyu Tian, Hao Jiang, Renhai Zhong, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2025) Vol. 225, pp. 257-274
Closed Access
Cloud–Aerosol Classification Based on the U-Net Model and Automatic Denoising CALIOP Data
Xingzhao Zhou, Bin Chen, Qia Ye, et al.
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 904-904
Open Access | Times Cited: 2
Detection of Maize Crop Phenology Using Planet Fusion
Çağlar Şenaras, Maddie Grady, Akhil Singh Rana, et al.
Remote Sensing (2024) Vol. 16, Iss. 15, pp. 2730-2730
Open Access | Times Cited: 2
Towards Optimising the Derivation of Phenological Phases of Different Crop Types over Germany Using Satellite Image Time Series
Abdelaziz Htitiou, Markus Möller, Tanja Riedel, et al.
Remote Sensing (2024) Vol. 16, Iss. 17, pp. 3183-3183
Open Access | Times Cited: 2
Approaching holistic crop type mapping in Europe through winter vegetation classification and the Hierarchical Crop and Agriculture Taxonomy
David Gackstetter, Marco Körner, Kang Yu
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 134, pp. 104159-104159
Open Access | Times Cited: 2
Evaluating the Ability of the Sentinel-1 Cross-Polarization Ratio to Detect Spring Maize Phenology Using Adaptive Dynamic Threshold
Yuyang Ma, Gongxin Jiang, Jianxi Huang, et al.
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 826-826
Open Access | Times Cited: 1
How Phenology Shapes Crop-Specific Sentinel-1 PolSAR Features and InSAR Coherence across Multiple Years and Orbits
Johannes Löw, Steven C. Hill, Insa Otte, et al.
Remote Sensing (2024) Vol. 16, Iss. 15, pp. 2791-2791
Open Access | Times Cited: 1
A novel approach: Coupling prior knowledge and deep learning methods for large-scale plastic greenhouse extraction using Sentinel-1/2 data
Chang Zhou, Jingfeng Huang, Yuanjun Xiao, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 132, pp. 104073-104073
Open Access | Times Cited: 1
Deep learning classification of winter wheat from Sentinel optical-radar image time series in smallholder farming areas
Xiaofang Sun, Meng Wang, Junbang Wang, et al.
Advances in Space Research (2024)
Closed Access
Modeling time series of vegetation indices in tallgrass prairie using machine and deep learning algorithms
Pradeep Wagle, Gopichandh Danala, Catherine Donner, et al.
Ecological Informatics (2024), pp. 102917-102917
Open Access
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