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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:

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

Showing 1-25 of 71 citing articles:

Predicting factors affecting the intention to use a 3PL during the COVID-19 pandemic: A machine learning ensemble approach
Josephine D. German, Ardvin Kester S. Ong, Anak Agung Ngurah Perwira Redi, et al.
Heliyon (2022) Vol. 8, Iss. 11, pp. e11382-e11382
Open Access | Times Cited: 40
Optimal Channels and Features Selection Based ADHD Detection From EEG Signal Using Statistical and Machine Learning Techniques
Md. Maniruzzaman, Md. Al Mehedi Hasan, Nobuyoshi Asai, et al.
IEEE Access (2023) Vol. 11, pp. 33570-33583
Open Access | Times Cited: 34
Estimation of above ground biomass in tropical heterogeneous forests in India using GEDI
Indu Indirabai, Mats Nilsson
Ecological Informatics (2024) Vol. 82, pp. 102712-102712
Open Access | Times Cited: 11
Forest Aboveground Biomass Estimation and Inventory: Evaluating Remote Sensing-Based Approaches
Muhammad Nouman Khan, Yumin Tan, Ahmad Ali Gul, et al.
Forests (2024) Vol. 15, Iss. 6, pp. 1055-1055
Open Access | Times Cited: 9
Towards carbon neutrality: Enhancing CO2 sequestration by plants to reduce carbon footprint
Dawid Skrzypczak, Katarzyna Gorazda, Katarzyna Mikula, et al.
The Science of The Total Environment (2025) Vol. 966, pp. 178763-178763
Closed Access | Times Cited: 1
On the Scale Effect of Relationship Identification between Land Surface Temperature and 3D Landscape Pattern: The Application of Random Forest
Qiong Wu, Zhaoyi Li, Changbao Yang, et al.
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 279-279
Open Access | Times Cited: 28
Automated detection of construction work at heights and deployment of safety hooks using IMU with a barometer
Hunsang Choo, Bogyeong Lee, Hyunsoo Kim, et al.
Automation in Construction (2022) Vol. 147, pp. 104714-104714
Closed Access | Times Cited: 28
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
Mapping aboveground biomass of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress using Sentinel-2 imagery
Lingyan Chen, Anqi He, Zhanghua Xu, et al.
Ecological Indicators (2024) Vol. 158, pp. 111564-111564
Open Access | Times Cited: 6
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
Predictive Modeling of Above-Ground Biomass in Brachiaria Pastures from Satellite and UAV Imagery Using Machine Learning Approaches
César Iván Álvarez Mendoza, Diego Guzman, Jorge Casas, et al.
Remote Sensing (2022) Vol. 14, Iss. 22, pp. 5870-5870
Open Access | Times Cited: 22
A Novel Vegetation Index Approach Using Sentinel-2 Data and Random Forest Algorithm for Estimating Forest Stock Volume in the Helan Mountains, Ningxia, China
Taiyong Ma, Yang Hu, Jie Wang, et al.
Remote Sensing (2023) Vol. 15, Iss. 7, pp. 1853-1853
Open Access | Times Cited: 14
Integrating Remote Sensing Data and CNN-LSTM-Attention Techniques for Improved Forest Stock Volume Estimation: A Comprehensive Analysis of Baishanzu Forest Park, China
Bo Wang, Yao Chen, Zhijun Yan, et al.
Remote Sensing (2024) Vol. 16, Iss. 2, pp. 324-324
Open Access | Times Cited: 5
A New Spatiotemporal Filtering Method to Reconstruct Landsat Time-Series for Improving Estimation Accuracy of Forest Aboveground Carbon Stock
Kai Huang, Chenkai Teng, Jialong Zhang, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2025) Vol. 18, pp. 6503-6519
Open Access
Methods for analysing renewable energy potentials in energy system modelling: A review
Alina Kerschbaum, Lennart Trentmann, Andreas Hänel, et al.
Renewable and Sustainable Energy Reviews (2025) Vol. 215, pp. 115559-115559
Open Access
Total and component forest aboveground biomass inversion via LiDAR-derived features and machine learning algorithms
Jiamin Ma, Wangfei Zhang, Yongjie Ji, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 12
The contributions of stand characteristics on carbon sequestration potential are triple that of climate variables for Larix spp. plantations in northeast China
Lingbo Dong, Xueying Lin, Pete Bettinger, et al.
The Science of The Total Environment (2023) Vol. 911, pp. 168726-168726
Closed Access | Times Cited: 11
An artificial intelligence model estimation for functionalized graphene quantum dot-based diode characteristics
Ali Öter, Betül Ersöz, Zeynep Berktaş, et al.
Physica Scripta (2024) Vol. 99, Iss. 5, pp. 056001-056001
Closed Access | Times Cited: 4
Machine Learning Modelling for Predicting the Efficacy of Ionic Liquid-Aided Biomass Pretreatment
Biswanath Mahanty, Munmun Gharami, Dibyajyoti Haldar
BioEnergy Research (2024) Vol. 17, Iss. 3, pp. 1569-1583
Open Access | Times Cited: 4
Assessment of Carbon Stock and Sequestration Dynamics in Response to Land Use and Land Cover Changes in a Tropical Landscape
Dipankar Bera, Nilanjana Das Chatterjee, Santanu Dinda, et al.
Land (2024) Vol. 13, Iss. 10, pp. 1689-1689
Open Access | Times Cited: 4
Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest
Shashika Himandi Gardeye Lamahewage, Chandi Witharana, Rachel Riemann, et al.
Research Square (Research Square) (2025)
Closed Access
Assessing and optimizing the potential for climate change mitigation and carbon sequestration in urban residential green spaces: energizing sustainable cities
Hancheng Liu, Jialong Zhang, Zijun Wang
Frontiers in Environmental Science (2025) Vol. 13
Open Access
Assessing Above-Ground Biomass Dynamics and Carbon Sequestration Potential Using Machine Learning and Spaceborne LiDAR in Hilly Conifer Forests of Mansehra District, Pakistan
Muhammad Imran, Guanhua Zhou, Guifei Jing, et al.
Forests (2025) Vol. 16, Iss. 2, pp. 330-330
Open Access
Remote sensing estimation of aboveground biomass of different forest types in Xinjiang based on machine learning
Zhou Jia, Mei Zan, Lili Zhai, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A Comprehensive Comparison of Machine Learning and Feature Selection Methods for Maize Biomass Estimation Using Sentinel-1 SAR, Sentinel-2 Vegetation Indices, and Biophysical Variables
Chi Xu, Yanling Ding, Xingming Zheng, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 4083-4083
Open Access | Times Cited: 18
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