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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 of Plantation with Different Tree Species Using Airborne LiDAR and Hyperspectral Data
Linghan Gao, Guoqi Chai, Xiaoli Zhang
Remote Sensing (2022) Vol. 14, Iss. 11, pp. 2568-2568
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Correcting forest aboveground biomass biases by incorporating independent canopy height retrieval with conventional machine learning models using GEDI and ICESat-2 data
Biao Zhang, Zhichao Wang, Tiantian Ma, et al.
Ecological Informatics (2025), pp. 103045-103045
Open Access | Times Cited: 2
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
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: 12
Estimation of Urban Forest Characteristic Parameters Using UAV-Lidar Coupled with Canopy Volume
Bo Zhang, Xuejian Li, Huaqiang Du, et al.
Remote Sensing (2022) Vol. 14, Iss. 24, pp. 6375-6375
Open Access | Times Cited: 20
Development of Estimation Models for Individual Tree Aboveground Biomass Based on TLS-Derived Parameters
Fan Wang, Yuman Sun, Weiwei Jia, et al.
Forests (2023) Vol. 14, Iss. 2, pp. 351-351
Open Access | Times Cited: 13
Leveraging Deep Learning Models for Targeted Aboveground Biomass Estimation in Specific Regions of Interest
Selvin Samuel Arumai Shiney, Ramachandran Geetha, Ramasamy Seetharaman, et al.
Sustainability (2024) Vol. 16, Iss. 11, pp. 4864-4864
Open Access | Times Cited: 4
Application of Machine Learning for Aboveground Biomass Modeling in Tropical and Temperate Forests from Airborne Hyperspectral Imagery
Patrick Osei Darko, Samy Metari, J. Pablo Arroyo‐Mora, et al.
Forests (2025) Vol. 16, Iss. 3, pp. 477-477
Open Access
Evaluation of crop water status using UAV-based images data with a model updating strategy
Ning Yang, Zhitao Zhang, Xiaofei Yang, et al.
Agricultural Water Management (2025) Vol. 312, pp. 109445-109445
Open Access
Improving the estimation of rice above-ground biomass based on spatio-temporal UAV imagery and phenological stages
Yan Dai, Shuang’en Yu, Tao Ma, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 3
Aboveground Biomass Mapping in SemiArid Forests by Integrating Airborne LiDAR with Sentinel-1 and Sentinel-2 Time-Series Data
Linjing Zhang, Xinran Yin, Yaru Wang, et al.
Remote Sensing (2024) Vol. 16, Iss. 17, pp. 3241-3241
Open Access | Times Cited: 3
A Comparison of UAV-Derived Dense Point Clouds Using LiDAR and NIR Photogrammetry in an Australian Eucalypt Forest
Megan Winsen, Grant Hamilton
Remote Sensing (2023) Vol. 15, Iss. 6, pp. 1694-1694
Open Access | Times Cited: 8
Utilizing LiDAR to quantify aboveground tree biomass within an urban university
Maggi Schick, Robert Griffin, Emil Cherrington, et al.
Urban forestry & urban greening (2023) Vol. 89, pp. 128098-128098
Open Access | Times Cited: 8
Using UAV LiDAR Intensity Frequency and Hyperspectral Features to Improve the Accuracy of Urban Tree Species Classification
Yulin Gong, Di’en Zhu, Xuejian Li, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023) Vol. 17, pp. 2849-2865
Open Access | Times Cited: 7
Constructing a eucalyptus identification model based on NDVI time-series remote sensing images
Nianxu Xu, Dong Cai, Xiaoqiao Zhao
CATENA (2024) Vol. 238, pp. 107846-107846
Closed Access | Times Cited: 2
Assessment of Aboveground Biomass in a Tropical Dry Deciduous Forest Using PRISMA Data
Rajani Kant Verma, Laxmi Kant Sharma, Kariya Ishita Bhaveshkumar, et al.
Journal of the Indian Society of Remote Sensing (2024) Vol. 52, Iss. 4, pp. 747-756
Closed Access | Times Cited: 2
Forest Aboveground Biomass Estimation Based on Unmanned Aerial Vehicle–Light Detection and Ranging and Machine Learning
Yan Yan, Jingjing Lei, Yuqing Huang
Sensors (2024) Vol. 24, Iss. 21, pp. 7071-7071
Open Access | Times Cited: 2
Forest aboveground biomass estimation based on spaceborne LiDAR combining machine learning model and geostatistical method
Li Xu, Jinge Yu, Qingtai Shu, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 2
Individual Tree Aboveground Biomass Estimation Based on UAV Stereo Images in a Eucalyptus Plantation
Yao Liu, Peng Lei, Qixu You, et al.
Forests (2023) Vol. 14, Iss. 9, pp. 1748-1748
Open Access | Times Cited: 4
Satellite Image Fusion Airborne LiDAR Point-Clouds-Driven Machine Learning Modeling to Predict the Carbon Stock of Typical Subtropical Plantation in China
Guangpeng Fan, Binghong Zhang, Jialing Zhou, et al.
Forests (2024) Vol. 15, Iss. 5, pp. 751-751
Open Access | Times Cited: 1
Mapping soil properties in tropical rainforest area using UAV-based hyperspectral images and LiDAR points
Yiqing Chen, Tiezhu Shi, Qipei Li, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Mapping Soil Properties in Tropical Rainforest Regions Using Integrated UAV-Based Hyperspectral Images and LiDAR Points
Yiqing Chen, Tiezhu Shi, Qipei Li, et al.
Forests (2024) Vol. 15, Iss. 12, pp. 2222-2222
Open Access | Times Cited: 1
A Novel Method for Estimating Biomass and Carbon Sequestration in Tropical Rainforest Areas Based on Remote Sensing Imagery: A Case Study in the Kon Ha Nung Plateau, Vietnam
Nguyen Dang Hoi, Duy Dinh Ba, Dung Trung Ngo, et al.
Sustainability (2022) Vol. 14, Iss. 24, pp. 16857-16857
Open Access | Times Cited: 6
Improving the Accuracy of Estimating Forest Carbon Density Using the Tree Species Classification Method
Ziheng Pang, Gui Zhang, Sanqing Tan, et al.
Forests (2022) Vol. 13, Iss. 12, pp. 2004-2004
Open Access | Times Cited: 5
Enhancing Aboveground Biomass Prediction through Integration of the SCDR Paradigm into the U-Like Hierarchical Residual Fusion Model
Ruofan Zhang, Jialiang Peng, Hailin Chen, et al.
Sensors (2024) Vol. 24, Iss. 8, pp. 2464-2464
Open Access
An Efficient IoT-based Crop Damage Prediction Framework in Smart Agricultural Systems
Nermeen Gamal Rezk, Abdel-Fattah Attia, Mohamed A. El-Rashidy, et al.
Research Square (Research Square) (2024)
Open Access
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