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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 Review of Estimation Methods for Aboveground Biomass in Grasslands Using UAV
Clara Oliva Gonçalves Bazzo, Bahareh Kamali, Christoph Hütt, et al.
Remote Sensing (2023) Vol. 15, Iss. 3, pp. 639-639
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Estimating aboveground biomass of grassland in central Asia mountainous areas using unmanned aerial vehicle vegetation indices and image textures – A case study of typical grassland in Tajikistan
Tianli Pan, Huping Ye, Xinyu Zhang, et al.
Environmental and Sustainability Indicators (2024) Vol. 22, pp. 100345-100345
Open Access | Times Cited: 9
Garlic yield monitoring using vegetation indices and texture features derived from UAV multispectral imagery
Andrea Marcone, Giorgio Impollonia, Michele Croci, et al.
Smart Agricultural Technology (2024) Vol. 8, pp. 100513-100513
Open Access | Times Cited: 9
Using Unmanned Aerial Vehicles and Multispectral Sensors to Model Forage Yield for Grasses of Semiarid Landscapes
Alexander J. Hernández, Kevin B. Jensen, Steve Larson, et al.
Grasses (2024) Vol. 3, Iss. 2, pp. 84-109
Open Access | Times Cited: 5
Grid grazing: A case study on the potential of combining virtual fencing and remote sensing for innovative grazing management on a grid base
Dina Hamidi, Christoph Hütt, Martin Komainda, et al.
Livestock Science (2023) Vol. 278, pp. 105373-105373
Open Access | Times Cited: 12
Integration of UAV-sensed features using machine learning methods to assess species richness in wet grassland ecosystems
Clara Oliva Gonçalves Bazzo, Bahareh Kamali, Murilo dos Santos Vianna, et al.
Ecological Informatics (2024), pp. 102813-102813
Open Access | Times Cited: 4
Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
Celina M. Laplacette, Germán D. Berone, Santiago A. Utsumi, et al.
Agriculture (2025) Vol. 15, Iss. 5, pp. 492-492
Open Access
In-Field Forage Biomass and Quality Prediction Using Image and VIS-NIR Proximal Sensing with Machine Learning and Covariance-Based Strategies for Livestock Management in Silvopastoral Systems
Claudia M. Serpa-Imbett, Erika L. Gómez-Palencia, Diego Andrés Medina Herrera, et al.
AgriEngineering (2025) Vol. 7, Iss. 4, pp. 111-111
Open Access
Integrating livestock and cropping systems: Interseeding cereal rye into corn for grazing
K.J. Soder, Paul R. Adler, Curtis J. Dell, et al.
Journal of Environmental Quality (2025)
Open Access
Using UAV-based multispectral and RGB imagery to monitor above-ground biomass of oat-based diversified cropping
Pengpeng Zhang, Bing Lu, Junbo Ge, et al.
European Journal of Agronomy (2024) Vol. 162, pp. 127422-127422
Closed Access | Times Cited: 3
Prediction of pasture yield using machine learning-based optical sensing: a systematic review
Christoph Stumpe, Joerg Leukel, Tobias Zimpel
Precision Agriculture (2023) Vol. 25, Iss. 1, pp. 430-459
Open Access | Times Cited: 9
Comparative Analysis of Feature Importance Algorithms for Grassland Aboveground Biomass and Nutrient Prediction Using Hyperspectral Data
Yue Zhao, Dawei Xu, Shuzhen Li, et al.
Agriculture (2024) Vol. 14, Iss. 3, pp. 389-389
Open Access | Times Cited: 3
UAV LiDAR-based grassland biomass estimation for precision livestock management
Christoph Hütt, J. Isselstein, Martin Komainda, et al.
Journal of Applied Remote Sensing (2024) Vol. 18, Iss. 01
Open Access | Times Cited: 2
Assessment of Carbon Sink and Carbon Flux in Forest Ecosystems: Instrumentation and the Influence of Seasonal Changes
Dangui Lu, Yuan Chen, Zhongke Feng, et al.
Remote Sensing (2024) Vol. 16, Iss. 13, pp. 2293-2293
Open Access | Times Cited: 2
Estimation of standing crop biomass in rangelands of the Middle Atlas mountains using remote sensing data
Soumaya Boukrouh, Y Bouazzaoui, A. El Aïch, et al.
African Journal of Range and Forage Science (2024) Vol. 41, Iss. 4, pp. 244-259
Closed Access | Times Cited: 2
APPLICATIONS OF SATELLITE PLATFORMS AND MACHINE LEARNING FOR MAPPING AND MONITORING GRASSLANDS AND PASTURES: A SYSTEMATIC AND COMPREHENSIVE REVIEW
Daniele Pinna, Andrea Pezzuolo, Alessia Cogato, et al.
Smart Agricultural Technology (2024), pp. 100571-100571
Open Access | Times Cited: 2
Integrating Copernicus LMS with ground measurements data for leaf area index and biomass assessment for grasslands in Poland and Norway
Katarzyna Dąbrowska‐Zielińska, Konrad Wróblewski, P. Goliński, et al.
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 2
Estimation of Biophysical Parameters of Forage Cactus Under Different Agricultural Systems Through Vegetation Indices and Machine Learning Using RGB Images Acquired with Unmanned Aerial Vehicles
Gabriel Ítalo Novaes da Silva, Alexandre Maniçoba da Rosa Ferraz Jardim, Wagner Martins dos Santos, et al.
Agriculture (2024) Vol. 14, Iss. 12, pp. 2166-2166
Open Access | Times Cited: 2
Comparison of Ground-Based, Unmanned Aerial Vehicles and Satellite Remote Sensing Technologies for Monitoring Pasture Biomass on Dairy Farms
J.I. Gargiulo, N.A. Lyons, Fernando Masía, et al.
Remote Sensing (2023) Vol. 15, Iss. 11, pp. 2752-2752
Open Access | Times Cited: 6
Pasture Biomass Estimation Using Ultra-High-Resolution RGB UAVs Images and Deep Learning
Milad Vahidi, Sanaz Shafian, Summer Thomas, et al.
Remote Sensing (2023) Vol. 15, Iss. 24, pp. 5714-5714
Open Access | Times Cited: 6
Sensitivity of LiDAR Parameters to Aboveground Biomass in Winter Spelt
Carsten Montzka, Marco Donat, Rahul Raj, et al.
Drones (2023) Vol. 7, Iss. 2, pp. 121-121
Open Access | Times Cited: 5
Estimation and mapping of pasture biomass in Mongolia using machine learning methods
Enkhmanlai Amarsaikhan, Nyamjargal Erdenebaatar, D. Amarsaikhan, et al.
Geocarto International (2023) Vol. 38, Iss. 1
Open Access | Times Cited: 5
Analysis of the influence of species composition, projective cover, and phytomass of arid landscape pasture vegetation on spectral reflectance properties based on ground measurements
С.С. Шинкаренко, S.A. Bartalev
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa (2023) Vol. 20, Iss. 3, pp. 176-192
Open Access | Times Cited: 5
Towards Prediction and Mapping of Grassland Aboveground Biomass Using Handheld LiDAR
Jeroen S. de Nobel, Kenneth F. Rijsdijk, Perry Cornelissen, et al.
Remote Sensing (2023) Vol. 15, Iss. 7, pp. 1754-1754
Open Access | Times Cited: 4
Assessment of Grassland Biomass Prediction Using AquaCrop Model: Integrating Sentinel-2 Data and Ground Measurements in Wielkopolska and Podlasie Regions, Poland
Ewa Panek, Ceren Nisanur Ozbilge, Katarzyna Dąbrowska‐Zielińska, et al.
Agriculture (2024) Vol. 14, Iss. 6, pp. 837-837
Open Access | Times Cited: 1
Extending Multi-Output Methods for Long-Term Aboveground Biomass Time Series Forecasting Using Convolutional Neural Networks
Efrain Noa‐Yarasca, Javier M. Osorio Leyton, Jay P. Angerer
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 3, pp. 1633-1652
Open Access | Times Cited: 1
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