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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:

Estimation of tree height and aboveground biomass of coniferous forests in North China using stereo ZY-3, multispectral Sentinel-2, and DEM data
Yueting Wang, Xiaoli Zhang, Zhengqi Guo
Ecological Indicators (2021) Vol. 126, pp. 107645-107645
Open Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Spectral saturation in the remote sensing of high-density vegetation traits: A systematic review of progress, challenges, and prospects
Onisimo Mutanga, Anita Masenyama, Mbulisi Sibanda
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 198, pp. 297-309
Closed Access | Times Cited: 84
Improved potato AGB estimates based on UAV RGB and hyperspectral images
Yang Liu, Haikuan Feng, Jibo Yue, et al.
Computers and Electronics in Agriculture (2023) Vol. 214, pp. 108260-108260
Closed Access | Times Cited: 60
Improved random forest algorithms for increasing the accuracy of forest aboveground biomass estimation using Sentinel-2 imagery
Xiaoli Zhang, Hanwen Shen, Tian‐Bao Huang, et al.
Ecological Indicators (2024) Vol. 159, pp. 111752-111752
Open Access | Times Cited: 26
Harmonizing remote sensing and ground data for forest aboveground biomass estimation
Ying Su, Zhifeng Wu, Xiaoman Zheng, et al.
Ecological Informatics (2025) Vol. 86, pp. 103002-103002
Open Access | Times Cited: 4
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
Evaluating machine learning approaches for aboveground biomass prediction in fragmented high-elevated forests using multi-sensor satellite data
Asim Qadeer, Muhammad Shakir, Li Wang, et al.
Remote Sensing Applications Society and Environment (2024) Vol. 36, pp. 101291-101291
Closed Access | Times Cited: 8
Estimating Aboveground Biomass of Two Different Forest Types in Myanmar from Sentinel-2 Data with Machine Learning and Geostatistical Algorithms
Phyo Wai, Huiyi Su, Mingshi Li
Remote Sensing (2022) Vol. 14, Iss. 9, pp. 2146-2146
Open Access | Times Cited: 34
How can UAV contribute in satellite-based Phragmites australis aboveground biomass estimating?
Lu Lirong, Juhua Luo, Yihao Xin, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 114, pp. 103024-103024
Open Access | Times Cited: 32
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
Improved Object-Based Estimation of Forest Aboveground Biomass by Integrating LiDAR Data from GEDI and ICESat-2 with Multi-Sensor Images in a Heterogeneous Mountainous Region
Lin Chen, Chunying Ren, Guangdao Bao, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2743-2743
Open Access | Times Cited: 30
Estimation of Forest Aboveground Biomass of Two Major Conifers in Ibaraki Prefecture, Japan, from PALSAR-2 and Sentinel-2 Data
Hantao Li, Tomomichi Kato, Masato Hayashi, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 468-468
Open Access | Times Cited: 28
Advancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges
Shunlin Liang, Tao He, Jianxi Huang, et al.
Science of Remote Sensing (2024) Vol. 10, pp. 100152-100152
Open Access | Times Cited: 6
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: 5
Retrieval performance of mangrove tree heights using multiple machine learning regression models and UAV-LiDAR point clouds
Bolin Fu, Linhang Jiang, Hang Yao, et al.
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 5
Improving Forest Canopy Height Mapping in Wuyishan National Park Through Calibration of ZiYuan-3 Stereo Imagery Using Limited Unmanned Aerial Vehicle LiDAR Data
Jian Kai, Dengsheng Lu, Yagang Lu, et al.
Forests (2025) Vol. 16, Iss. 1, pp. 125-125
Open Access
Mapping Forest Aboveground Biomass Using Multi-Source Remote Sensing Data Based on the XGBoost Algorithm
Dejun Wang, Yanqiu Xing, Anmin Fu, et al.
Forests (2025) Vol. 16, Iss. 2, pp. 347-347
Open Access
Estimating vegetation aboveground biomass in Yellow River Delta coastal wetlands using Sentinel-1, Sentinel-2 and Landsat-8 imagery
Yiming Xu, Yong Qin, Bin Li, et al.
Ecological Informatics (2025), pp. 103096-103096
Open Access
Harnessing AI for Precise AGB Estimation in Remote Areas
Fajar W. Wijaya, Mikael Prakoso, Muhammad Bondan V. Ramadhan, et al.
Advances in computational intelligence and robotics book series (2025), pp. 99-132
Closed Access
Retrieval of forest canopy height in a mountainous region with ICESat-2 ATLAS
Shiyun Pang, Guiying Li, Xiandie Jiang, et al.
Forest Ecosystems (2022) Vol. 9, pp. 100046-100046
Open Access | Times Cited: 21
Enhancing carbon stock estimation in forests: Integrating multi-data predictors with random forest method
Gabriel E. Suárez-Fernández, J. Martínez-Sánchez, Pedro Arias
Ecological Informatics (2025), pp. 102997-102997
Open Access
Accuracy and consistency of the machine learning models for predicting carbon stock in different carbon pools using satellite-based predictor variables
Dipankar Bera, Nilanjana Das Chatterjee, Vivek Dhiman, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Closed Access
Accuracy assessment of topography and forest canopy height in complex terrain conditions of Southern China using ICESat-2 and GEDI data
L. Fu, Qingtai Shu, Zhengdao Yang, et al.
Frontiers in Plant Science (2025) Vol. 16
Open Access
A comparative analysis of modeling approaches and canopy height-based data sources for mapping forest growing stock volume in a northern subtropical ecosystem of China
Wenke Lin, Yagang Lu, Guiying Li, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 568-589
Open Access | Times Cited: 16
Estimation of Forest Parameters in Boreal Artificial Coniferous Forests Using Landsat 8 and Sentinel-2A
Rula Sa, Wenyi Fan
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3605-3605
Open Access | Times Cited: 9
Dryland Social-Ecological Systems in Changing Environments
Bojie Fu, Mark Stafford‐Smith
(2024)
Open Access | Times Cited: 3
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