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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:

Forest inventory with high-density UAV-Lidar: Machine learning approaches for predicting individual tree attributes
Ana Paula Dalla Côrte, Deivison Venicio Souza, Franciel Eduardo Rex, et al.
Computers and Electronics in Agriculture (2020) Vol. 179, pp. 105815-105815
Open Access | Times Cited: 99

Showing 1-25 of 99 citing articles:

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission
Laura Duncanson, James R. Kellner, John Armston, et al.
Remote Sensing of Environment (2022) Vol. 270, pp. 112845-112845
Open Access | Times Cited: 250
A Review of Ensemble Learning Algorithms Used in Remote Sensing Applications
Yuzhen Zhang, Jingjing Liu, Wenjuan Shen
Applied Sciences (2022) Vol. 12, Iss. 17, pp. 8654-8654
Open Access | Times Cited: 182
LiDAR Applications to Estimate Forest Biomass at Individual Tree Scale: Opportunities, Challenges and Future Perspectives
Dandan Xu, Haobin Wang, Weixin Xu, et al.
Forests (2021) Vol. 12, Iss. 5, pp. 550-550
Open Access | Times Cited: 112
UAV-Supported Forest Regeneration: Current Trends, Challenges and Implications
Midhun Mohan, Gabriella Richardson, Gopika Gopan, et al.
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2596-2596
Open Access | Times Cited: 105
Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR
Stefan Oehmcke, Lei Li, Katerina Trepekli, et al.
Remote Sensing of Environment (2024) Vol. 302, pp. 113968-113968
Open Access | Times Cited: 27
Above-ground biomass estimation from LiDAR data using random forest algorithms
Leyre Torre‐Tojal, Aitor Bastarrika, A. Boyano, et al.
Journal of Computational Science (2021) Vol. 58, pp. 101517-101517
Open Access | Times Cited: 71
Maize and soybean heights estimation from unmanned aerial vehicle (UAV) LiDAR data
Shezhou Luo, Weiwei Liu, Yaqian Zhang, et al.
Computers and Electronics in Agriculture (2021) Vol. 182, pp. 106005-106005
Closed Access | Times Cited: 67
Deep Learning in Plant Phenological Research: A Systematic Literature Review
Negin Katal, Michael Rzanny, Patrick Mäder, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 48
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: 45
Latest Trends on Tree Classification and Segmentation Using UAV Data—A Review of Agroforestry Applications
Babak Chehreh, Alexandra Moutinho, Carlos Viegas
Remote Sensing (2023) Vol. 15, Iss. 9, pp. 2263-2263
Open Access | Times Cited: 28
Q-Learning based system for Path Planning with Unmanned Aerial Vehicles swarms in obstacle environments
Alejandro Puente-Castro, Daniel Rivero, Eurico Pedrosa, et al.
Expert Systems with Applications (2023) Vol. 235, pp. 121240-121240
Open Access | Times Cited: 23
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data
Máira Beatriz Teixeira da Costa, Carlos Alberto Silva, Eben N. Broadbent, et al.
Forest Ecology and Management (2021) Vol. 491, pp. 119155-119155
Open Access | Times Cited: 51
UAV swarm path planning with reinforcement learning for field prospecting
Alejandro Puente-Castro, Daniel Rivero, Alejandro Pazos, et al.
Applied Intelligence (2022) Vol. 52, Iss. 12, pp. 14101-14118
Open Access | Times Cited: 35
Review of Automatic Processing of Topography and Surface Feature Identification LiDAR Data Using Machine Learning Techniques
Zahra Gharineiat, Fayez Tarsha Kurdi, Glenn Campbell
Remote Sensing (2022) Vol. 14, Iss. 19, pp. 4685-4685
Open Access | Times Cited: 35
GNSS-IMU-assisted colored ICP for UAV-LiDAR point cloud registration of peach trees
Wenan Yuan, Daeun Choi, Dimitrios Bolkas
Computers and Electronics in Agriculture (2022) Vol. 197, pp. 106966-106966
Open Access | Times Cited: 31
Machine learning assisted remote forestry health assessment: a comprehensive state of the art review
Juan Sebastián Estrada, Andrés Fuentes, Pedro Reszka, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 17
Mangrove Biodiversity Assessment Using UAV Lidar and Hyperspectral Data in China’s Pinglu Canal Estuary
Yichao Tian, Huang Hu, Guoqing Zhou, et al.
Remote Sensing (2023) Vol. 15, Iss. 10, pp. 2622-2622
Open Access | Times Cited: 16
An Individual Tree Detection and Segmentation Method from TLS and MLS Point Clouds Based on Improved Seed Points
Qiuji Chen, Hao Luo, Cheng Yan, et al.
Forests (2024) Vol. 15, Iss. 7, pp. 1083-1083
Open Access | Times Cited: 6
Unmanned aerial vehicle and artificial intelligence revolutionizing efficient and precision sustainable forest management
Tiedong Liu, Yuxin Sun, Cai Wang, et al.
Journal of Cleaner Production (2021) Vol. 311, pp. 127546-127546
Closed Access | Times Cited: 34
Afforestation, reforestation and new challenges from COVID-19: Thirty-three recommendations to support civil society organizations (CSOs)
Midhun Mohan, Hayden A. Rue, Shaurya Bajaj, et al.
Journal of Environmental Management (2021) Vol. 287, pp. 112277-112277
Open Access | Times Cited: 33
Integrating Satellite and UAV Technologies for Maize Plant Height Estimation Using Advanced Machine Learning
Marcelo Araújo Junqueira Ferraz, Thiago Orlando Costa Barboza, Pablo de Sousa Arantes, et al.
AgriEngineering (2024) Vol. 6, Iss. 1, pp. 20-33
Open Access | Times Cited: 5
Forestry conservation through machine learning innovations
Fernando Coelho Eugênio, Sally Deborah Pereira da Silva, Roberta Aparecida Fantinel, et al.
Elsevier eBooks (2025), pp. 95-104
Closed Access
Individual Tree Diameter Estimation in Small-Scale Forest Inventory Using UAV Laser Scanning
Yuanshuo Hao, Faris Rafi Almay Widagdo, Xin Liu, et al.
Remote Sensing (2020) Vol. 13, Iss. 1, pp. 24-24
Open Access | Times Cited: 36
Predicting Individual Tree Diameter of Larch (Larix olgensis) from UAV-LiDAR Data Using Six Different Algorithms
Yusen Sun, Xingji Jin, Timo Pukkala, et al.
Remote Sensing (2022) Vol. 14, Iss. 5, pp. 1125-1125
Open Access | Times Cited: 21
A New Strategy for Individual Tree Detection and Segmentation from Leaf-on and Leaf-off UAV-LiDAR Point Clouds Based on Automatic Detection of Seed Points
Yihan Pu, Dandan Xu, Haobin Wang, et al.
Remote Sensing (2023) Vol. 15, Iss. 6, pp. 1619-1619
Open Access | Times Cited: 12
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