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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.

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Showing 25 citing articles:

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: 190
Faba bean above-ground biomass and bean yield estimation based on consumer-grade unmanned aerial vehicle RGB images and ensemble learning
Yishan Ji, Rong Liu, Yonggui Xiao, et al.
Precision Agriculture (2023) Vol. 24, Iss. 4, pp. 1439-1460
Closed Access | Times Cited: 34
A brief overview and perspective of using airborne Lidar data for forest biomass estimation
Dengsheng Lu, Xiandie Jiang
International Journal of Image and Data Fusion (2024) Vol. 15, Iss. 1, pp. 1-24
Closed Access | Times Cited: 14
Aboveground biomass estimation in forests with random forest and Monte Carlo-based uncertainty analysis
Zizhao Li, Shoudong Bi, Shuang Hao, et al.
Ecological Indicators (2022) Vol. 142, pp. 109246-109246
Open Access | Times Cited: 31
Towards accurate individual tree parameters estimation in dense forest: optimized coarse-to-fine algorithms for registering UAV and terrestrial LiDAR data
Yuting Zhao, Jungho Im, Zhen Zhen, et al.
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 18
Estimation of Individual Tree Biomass in Natural Secondary Forests Based on ALS Data and WorldView-3 Imagery
Yinghui Zhao, Ye Ma, Lindi J. Quackenbush, et al.
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 271-271
Open Access | Times Cited: 27
Machine learning-based grassland aboveground biomass estimation and its response to climate variation in Southwest China
Wenjun Liu, Cong Xu, Zhiming Zhang, et al.
Frontiers in Ecology and Evolution (2023) Vol. 11
Open Access | Times Cited: 14
Biomass Estimation and Saturation Value Determination Based on Multi-Source Remote Sensing Data
Rula Sa, Yonghui Nie, С. И. Чумаченко, et al.
Remote Sensing (2024) Vol. 16, Iss. 12, pp. 2250-2250
Open Access | Times Cited: 6
Upscaling aboveground biomass of larch (Larix olgensis Henry) plantations from field to satellite measurements: a comparison of individual tree-based and area-based approaches
Zhen Zhen, Lan Yu Yang, Ye Ma, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 722-743
Open Access | Times Cited: 20
Multi-Platform LiDAR for Non-Destructive Individual Aboveground Biomass Estimation for Changbai Larch (Larix olgensis Henry) Using a Hierarchical Bayesian Approach
Man Wang, Jungho Im, Yinghui Zhao, et al.
Remote Sensing (2022) Vol. 14, Iss. 17, pp. 4361-4361
Open Access | Times Cited: 17
Assessing the effect of ensemble learning algorithms and validation approach on estimating forest aboveground biomass: a case study of natural secondary forest in Northeast China
Hung-Il Jin, Yinghui Zhao, Unil Pak, et al.
Geo-spatial Information Science (2024), pp. 1-20
Open Access | Times Cited: 4
A framework for upscaling aboveground biomass from an individual tree to landscape level and qualifying the multiscale spatial uncertainties for secondary forests
Ye Ma, Jungho Im, Zhen Zhen, et al.
Geo-spatial Information Science (2025), pp. 1-20
Open Access
Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data
Zige Lan, Xiandie Jiang, Guiying Li, et al.
GIScience & Remote Sensing (2025) Vol. 62, Iss. 1
Open Access
Novel Features of Canopy Height Distribution for Aboveground Biomass Estimation Using Machine Learning: A Case Study in Natural Secondary Forests
Ye Ma, Lianjun Zhang, Jungho Im, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4364-4364
Open Access | Times Cited: 7
Research on Estimation Model of Carbon Stock Based on Airborne LiDAR and Feature Screening
Xuan Liu, Ruirui Wang, W. Shi, et al.
Sustainability (2024) Vol. 16, Iss. 10, pp. 4133-4133
Open Access | Times Cited: 2
An innovative lightweight 1D-CNN model for efficient monitoring of large-scale forest composition: a case study of Heilongjiang Province, China
Ye Ma, Zhen Zhen, Fengri Li, et al.
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 5
The power of voting
Ronny Hänsch
Elsevier eBooks (2024), pp. 201-235
Closed Access | Times Cited: 1
Estimation of the Aboveground Carbon Storage of Dendrocalamus giganteus Based on Spaceborne Lidar Co-Kriging
Huanfen Yang, Zhen Qin, Qingtai Shu, et al.
Forests (2024) Vol. 15, Iss. 8, pp. 1440-1440
Open Access | Times Cited: 1
A Framework for Upscaling Aboveground Biomass from an Individual Tree to Landscape Level and Qualifying the Multiscale Spatial Uncertainties for Natural Secondary Forests
Ye Ma, Jungho Im, Zhen Zhen, et al.
(2024)
Closed Access
More Accurately Estimating Aboveground Biomass in Tropical Forests With Complex Forest Structures and Regions of High‐Aboveground Biomass
Ying Su, Matteo Mura, Xiaoman Zheng, et al.
Journal of Geophysical Research Biogeosciences (2024) Vol. 129, Iss. 6
Closed Access
Improving the Accuracy of Aboveground Biomass Estimation of Natural Secondary Forests Using Individual Tree Features
Feiyu Long, Yinghui Zhao, Zhen Zhen
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (2024) Vol. 26, pp. 4226-4229
Closed Access
Aboveground biomass estimation and mapping using Sentinel-2 data in a dry afromontane forest
Buruh Abebe Tetemke, Emiru Birhane, Meley Mekonen Rannestad, et al.
International Journal of Remote Sensing (2024) Vol. 45, Iss. 24, pp. 9461-9479
Closed Access
Enhancing the Precision of Forest Growing Stock Volume in the Estonian National Forest Inventory with Different Predictive Techniques and Remote Sensing Data
Temitope Olaoluwa Omoniyi, Allan Sims
Remote Sensing (2024) Vol. 16, Iss. 20, pp. 3794-3794
Open Access
Mangrove Tree Species Classification Based on Leaf, Stem, and Seed Characteristics Using Convolutional Neural Networks with K-Folds Cross Validation Optimalization
Fadillah Farhan, Christy Atika Sari, Eko Hari Rachmawanto, et al.
Advance Sustainable Science Engineering and Technology (2023) Vol. 5, Iss. 3, pp. 02303011-02303011
Open Access
Incorporating Individual Tree Features into an Area-Based Approach for Estimating Forest Stock Volume
Feiyu Long, Ye Ma, Yinghui Zhao, et al.
(2023)
Closed Access
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