Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Showing 1-25 of 42 citing articles:

Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI
Chu Wang, Wangfei Zhang, Yongjie Ji, et al.
Forests (2024) Vol. 15, Iss. 1, pp. 215-215
Open Access | Times Cited: 20
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: 5
UAV Multispectral Image-Based Urban River Water Quality Monitoring Using Stacked Ensemble Machine Learning Algorithms—A Case Study of the Zhanghe River, China
Yi Xiao, Yahui Guo, Guodong Yin, et al.
Remote Sensing (2022) Vol. 14, Iss. 14, pp. 3272-3272
Open Access | Times Cited: 51
Integrating Sentinel-1 and 2 with LiDAR data to estimate aboveground biomass of subtropical forests in northeast Guangdong, China
Linjing Zhang, Xiaoxue Zhang, Zhenfeng Shao, et al.
International Journal of Digital Earth (2023) Vol. 16, Iss. 1, pp. 158-182
Open Access | Times Cited: 32
Evaluation of machine learning methods and multi-source remote sensing data combinations to construct forest above-ground biomass models
Xingguang Yan, Jing Li, Andrew R. Smith, et al.
International Journal of Digital Earth (2023) Vol. 16, Iss. 2, pp. 4471-4491
Open Access | Times Cited: 26
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: 10
Progress and Limitations in Forest Carbon Stock Estimation Using Remote Sensing Technologies: A Comprehensive Review
Weifeng Xu, Yu-Hao Cheng, Mengyuan Luo, et al.
Forests (2025) Vol. 16, Iss. 3, pp. 449-449
Open Access | Times Cited: 1
Estimating the Aboveground Biomass of Various Forest Types with High Heterogeneity at the Provincial Scale Based on Multi-Source Data
Tian‐Bao Huang, Guanglong Ou, Yong Wu, et al.
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3550-3550
Open Access | Times Cited: 22
Vegetation fuel characterization using machine learning approach over southern Portugal
Filippe L.M. Santos, Flavio T. Couto, Susana Dias, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 32, pp. 101017-101017
Open Access | Times Cited: 17
Estimating Leaf Chlorophyll Content of Winter Wheat from UAV Multispectral Images Using Machine Learning Algorithms under Different Species, Growth Stages, and Nitrogen Stress Conditions
Liyuan Zhang, Aichen Wang, Huiyue Zhang, et al.
Agriculture (2024) Vol. 14, Iss. 7, pp. 1064-1064
Open Access | Times Cited: 8
Estimating Sugarcane Aboveground Biomass and Carbon Stock Using the Combined Time Series of Sentinel Data with Machine Learning Algorithms
Savittri Ratanopad Suwanlee, Dusadee Pinasu, Jaturong Som-ard, et al.
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 750-750
Open Access | Times Cited: 7
Evaluating the Canopy Chlorophyll Density of Maize at the Whole Growth Stage Based on Multi-Scale UAV Image Feature Fusion and Machine Learning Methods
Lili Zhou, Chenwei Nie, Tao Su, et al.
Agriculture (2023) Vol. 13, Iss. 4, pp. 895-895
Open Access | Times Cited: 15
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
Investigating Dual-Source Satellite Image Data and ALS Data for Estimating Aboveground Biomass
Wen Fan, Jiaojiao Tian, Thomas Knoke, et al.
Remote Sensing (2024) Vol. 16, Iss. 10, pp. 1804-1804
Open Access | Times Cited: 4
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
UAV-based stomatal conductance estimation under water stress using the PROSAIL model coupled with meteorological factors
Ning Yang, Zhitao Zhang, X. F. Yang, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 137, pp. 104425-104425
Open Access
Estimation of Aboveground Biomass of Picea schrenkiana Forests Considering Vertical Zonality and Stand Age
Guohui Zhang, Donghua Chen, Hu Li, et al.
Forests (2025) Vol. 16, Iss. 3, pp. 445-445
Open Access
Forest Height and Volume Mapping in Northern Spain with Multi-Source Earth Observation Data: Method and Data Comparison
Iyán Teijido-Murias, Oleg Antropov, Carlos A. López‐Sánchez, et al.
Forests (2025) Vol. 16, Iss. 4, pp. 563-563
Open Access
Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud
Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, et al.
Forest Science and Technology (2025), pp. 1-20
Open Access
Estimating Forest Variables for Major Commercial Timber Plantations in Northern Spain Using Sentinel-2 and Ancillary Data
Alís Novo‐Fernández, Carlos A. López‐Sánchez, Asunción Cámara-Obregón, et al.
Forests (2024) Vol. 15, Iss. 1, pp. 99-99
Open Access | Times Cited: 3
Analysis of the Application of Machine Learning Algorithms Based on Sentinel-1/2 and Landsat 8 OLI Data in Estimating Above-Ground Biomass of Subtropical Forests
Yuping Wang, Steven Hancock, Wenquan Dong, et al.
Forests (2025) Vol. 16, Iss. 4, pp. 559-559
Open Access
Effects of Driving Factors on Forest Aboveground Biomass (AGB) in China’s Loess Plateau by Using Spatial Regression Models
Shichuan Yu, Quanping Ye, Qingxia Zhao, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2842-2842
Open Access | Times Cited: 14
UAV-Based Characterization of Tree-Attributes and Multispectral Indices in an Uneven-Aged Mixed Conifer-Broadleaf Forest
Eduardo Daniel Vivar-Vivar, Marin Pompa-García, José Alexis Martínez-Rivas, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2775-2775
Open Access | Times Cited: 13
Estimating Aboveground Biomass of a Regional Forest Landscape by Integrating Textural and Spectral Variables of Sentinel-2 Along with Ancillary Data
Debabrata Behera, V. Ashok Kumar, J. Prakasa Rao, et al.
Journal of the Indian Society of Remote Sensing (2023) Vol. 52, Iss. 4, pp. 917-929
Closed Access | Times Cited: 8
Examining the Potential of Sentinel Imagery and Ensemble Algorithms for Estimating Aboveground Biomass in a Tropical Dry Forest
Mike H. Salazar Villegas, Mohammad Qasim, Elmar Csaplovics, et al.
Remote Sensing (2023) Vol. 15, Iss. 21, pp. 5086-5086
Open Access | Times Cited: 7
Page 1 - Next Page

Scroll to top