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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:

Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations
Aleksandra Wolanin, Gustau Camps‐Valls, Luis Gómez‐Chova, et al.
Remote Sensing of Environment (2019) Vol. 225, pp. 441-457
Open Access | Times Cited: 181

Showing 1-25 of 181 citing articles:

Deep learning in environmental remote sensing: Achievements and challenges
Qiangqiang Yuan, Huanfeng Shen, Tongwen Li, et al.
Remote Sensing of Environment (2020) Vol. 241, pp. 111716-111716
Closed Access | Times Cited: 1218
Machine Learning in Agriculture: A Comprehensive Updated Review
Lefteris Benos, Aristotelis C. Tagarakis, Georgios Dolias, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3758-3758
Open Access | Times Cited: 526
Internet of Things in arable farming: Implementation, applications, challenges and potential
Andrés Villa‐Henriksen, Gareth Edwards, Liisa Pesonen, et al.
Biosystems Engineering (2020) Vol. 191, pp. 60-84
Open Access | Times Cited: 318
Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review
Michel Eustáquio Dantas Chaves, Michelle Cristina Araújo Picoli, Ieda Del’Arco Sanches
Remote Sensing (2020) Vol. 12, Iss. 18, pp. 3062-3062
Open Access | Times Cited: 259
Integrating Multi-Source Data for Rice Yield Prediction across China using Machine Learning and Deep Learning Approaches
Juan Cao, Zhao Zhang, Fulu Tao, et al.
Agricultural and Forest Meteorology (2020) Vol. 297, pp. 108275-108275
Closed Access | Times Cited: 249
Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods
Elisa Kamir, François Waldner, Zvi Hochman
ISPRS Journal of Photogrammetry and Remote Sensing (2019) Vol. 160, pp. 124-135
Closed Access | Times Cited: 238
Predicting Wheat Yield at the Field Scale by Combining High-Resolution Sentinel-2 Satellite Imagery and Crop Modelling
Yan Zhao, Andries Potgieter, Miao Zhang, et al.
Remote Sensing (2020) Vol. 12, Iss. 6, pp. 1024-1024
Open Access | Times Cited: 143
A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020
Shaoyang He, Yongqiang Zhang, Ning Ma, et al.
Earth system science data (2022) Vol. 14, Iss. 12, pp. 5463-5488
Open Access | Times Cited: 75
Drones in vegetable crops: A systematic literature review
Marco Canicattì, Mariangela Vallone
Smart Agricultural Technology (2024) Vol. 7, pp. 100396-100396
Open Access | Times Cited: 26
Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods
Wenquan Zhu, Zhiying Xie, Cenliang Zhao, et al.
GIScience & Remote Sensing (2024) Vol. 61, Iss. 1
Open Access | Times Cited: 18
Predicting Canopy Nitrogen Content in Citrus-Trees Using Random Forest Algorithm Associated to Spectral Vegetation Indices from UAV-Imagery
Lucas Prado Osco, Ana Paula Marques Ramos, Danilo Roberto Pereira, et al.
Remote Sensing (2019) Vol. 11, Iss. 24, pp. 2925-2925
Open Access | Times Cited: 127
Leaf Nitrogen Concentration and Plant Height Prediction for Maize Using UAV-Based Multispectral Imagery and Machine Learning Techniques
Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, et al.
Remote Sensing (2020) Vol. 12, Iss. 19, pp. 3237-3237
Open Access | Times Cited: 108
Estimating crop biomass using leaf area index derived from Landsat 8 and Sentinel-2 data
Taifeng Dong, Jiangui Liu, Budong Qian, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 168, pp. 236-250
Closed Access | Times Cited: 99
Mapping Winter Crops Using a Phenology Algorithm, Time-Series Sentinel-2 and Landsat-7/8 Images, and Google Earth Engine
Li Pan, Haoming Xia, Xiaoyang Zhao, et al.
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2510-2510
Open Access | Times Cited: 93
Remote Sensing and Machine Learning in Crop Phenotyping and Management, with an Emphasis on Applications in Strawberry Farming
Caiwang Zheng, Amr Abd‐Elrahman, Vance M. Whitaker
Remote Sensing (2021) Vol. 13, Iss. 3, pp. 531-531
Open Access | Times Cited: 81
ECOSTRESS estimates gross primary production with fine spatial resolution for different times of day from the International Space Station
Xing Li, Jingfeng Xiao, Joshua B. Fisher, et al.
Remote Sensing of Environment (2021) Vol. 258, pp. 112360-112360
Open Access | Times Cited: 64
A method to avoid spatial overfitting in estimation of grassland above-ground biomass on the Tibetan Plateau
Hui Yu, Yufeng Wu, Liting Niu, et al.
Ecological Indicators (2021) Vol. 125, pp. 107450-107450
Open Access | Times Cited: 59
Improving the Accuracy of Multiple Algorithms for Crop Classification by Integrating Sentinel-1 Observations with Sentinel-2 Data
Amal Chakhar, David Hernández‐López, Rocío Ballesteros, et al.
Remote Sensing (2021) Vol. 13, Iss. 2, pp. 243-243
Open Access | Times Cited: 58
Optimal county-level crop yield prediction using MODIS-based variables and weather data: A comparative study on machine learning models
Sungha Ju, Hyoungjoon Lim, Jong‐Uk Won, et al.
Agricultural and Forest Meteorology (2021) Vol. 307, pp. 108530-108530
Closed Access | Times Cited: 57
Farming and Earth Observation: Sentinel-2 data to estimate within-field wheat grain yield
Joel Segarra, J. L. Araus, Shawn C. Kefauver
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 107, pp. 102697-102697
Open Access | Times Cited: 49
Using Machine Learning Models to Predict Hydroponically Grown Lettuce Yield
Ali Mokhtar, Wessam El-Ssawy, Hongming He, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 47
Evaluation of Random Forests (RF) for Regional and Local-Scale Wheat Yield Prediction in Southeast Australia
Alexis Pang, Melissa W L Chang, Yang Chen
Sensors (2022) Vol. 22, Iss. 3, pp. 717-717
Open Access | Times Cited: 45
Integrating Sentinel-1 and 2 with LiDAR data to estimate aboveground biomass of subtropical forests in northeast Guangdong, China
Linjing Zhang, Xiaoxue Zhang, Zhenfeng Shao, et al.
International Journal of Digital Earth (2023) Vol. 16, Iss. 1, pp. 158-182
Open Access | Times Cited: 32
Towards Improving Sustainable Water Management in Geothermal Fields: SVM and RF Land Use Monitoring
Widya Utama, Rista Fitri Indriani, Maman Hermana, et al.
Journal of Human Earth and Future (2024) Vol. 5, Iss. 2, pp. 216-242
Open Access | Times Cited: 17
Satellite Imagery in Precision Agriculture
Joel Segarra
Springer eBooks (2024), pp. 325-340
Closed Access | Times Cited: 13
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