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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:

Estimating Aboveground Biomass Using Sentinel-2 MSI Data and Ensemble Algorithms for Grassland in the Shengjin Lake Wetland, China
Chunhua Li, Lizhi Zhou, Wenbin Xu
Remote Sensing (2021) Vol. 13, Iss. 8, pp. 1595-1595
Open Access | Times Cited: 87

Showing 1-25 of 87 citing articles:

Improving above ground biomass estimates of Southern Africa dryland forests by combining Sentinel-1 SAR and Sentinel-2 multispectral imagery
Ruusa Magano David, Nick Rosser, Daniel N.M. Donoghue
Remote Sensing of Environment (2022) Vol. 282, pp. 113232-113232
Closed Access | Times Cited: 75
Improving potato above ground biomass estimation combining hyperspectral data and harmonic decomposition techniques
Yang Liu, Haikuan Feng, Yiguang Fan, et al.
Computers and Electronics in Agriculture (2024) Vol. 218, pp. 108699-108699
Closed Access | Times Cited: 50
Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data
Yang Liu, Haikuan Feng, Jibo Yue, et al.
Computers and Electronics in Agriculture (2024) Vol. 219, pp. 108808-108808
Closed Access | Times Cited: 48
Improving National Forest Mapping in Romania Using Machine Learning and Sentinel-2 Multispectral Imagery
Mohamed Islam Keskes, Aya Hamed Mohamed, Stelian Alexandru Borz, et al.
Remote Sensing (2025) Vol. 17, Iss. 4, pp. 715-715
Open Access | Times Cited: 2
Estimating Above-Ground Biomass of Potato Using Random Forest and Optimized Hyperspectral Indices
Haibo Yang, Fei Li, Wei Wang, et al.
Remote Sensing (2021) Vol. 13, Iss. 12, pp. 2339-2339
Open Access | Times Cited: 59
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: 12
From Air to Space: A Comprehensive Approach to Optimizing Aboveground Biomass Estimation on UAV-Based Datasets
Muhammad Nouman Khan, Yumin Tan, Lingfeng He, et al.
Forests (2025) Vol. 16, Iss. 2, pp. 214-214
Open Access | Times Cited: 1
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: 33
Spatiotemporal fusion of multi-source remote sensing data for estimating aboveground biomass of grassland
Zhou Yajun, Tingxi Liu, Okke Batelaan, et al.
Ecological Indicators (2023) Vol. 146, pp. 109892-109892
Open Access | Times Cited: 19
Improving forest above-ground biomass estimation using genetic-based feature selection from Sentinel-1 and Sentinel-2 data (case study of the Noor forest area in Iran)
Armin Moghimi, Ava Tavakoli Darestani, Nikrouz Mostofi, et al.
Kuwait Journal of Science (2023) Vol. 51, Iss. 2, pp. 100159-100159
Open Access | Times Cited: 18
Comparing the Utility of Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) on Sentinel-2 MSI to Estimate Dry Season Aboveground Grass Biomass
Mohamed Ismail Vawda, Romano Lottering, Onisimo Mutanga, et al.
Sustainability (2024) Vol. 16, Iss. 3, pp. 1051-1051
Open Access | Times Cited: 8
Estimating Above-Ground Biomass of the Regional Forest Landscape of Northern Western Ghats Using Machine Learning Algorithms and Multi-sensor Remote Sensing Data
Faseela V. Sainuddin, Guljar Malek, Ankur Rajwadi, et al.
Journal of the Indian Society of Remote Sensing (2024) Vol. 52, Iss. 4, pp. 885-902
Closed Access | Times Cited: 8
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: 7
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
Improving Aboveground Biomass Estimation in Lowland Tropical Forests across Aspect and Age Stratification: A Case Study in Xishuangbanna
Yong Wu, Guanglong Ou, Teng-Fei Lu, et al.
Remote Sensing (2024) Vol. 16, Iss. 7, pp. 1276-1276
Open Access | Times Cited: 7
Mapping Phragmites australis Aboveground Biomass in the Momoge Wetland Ramsar Site Based on Sentinel-1/2 Images
Yuxin Zhao, Dehua Mao, Dongyou Zhang, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 694-694
Open Access | Times Cited: 23
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: 16
Seasonal water storage and release dynamics of bofedal wetlands in the Central Andes
A. Ross, Marc Martínez Mendoza, Fabián Drenkhan, et al.
Hydrological Processes (2023) Vol. 37, Iss. 8
Open Access | Times Cited: 16
Estimating high-density aboveground biomass within a complex tropical grassland using Worldview-3 imagery
Rowan Naicker, Onisimo Mutanga, Kabir Peerbhay, et al.
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 4
Open Access | Times Cited: 6
Estimation of Coastal Wetland Vegetation Aboveground Biomass by Integrating UAV and Satellite Remote Sensing Data
Xiaomeng Niu, Binjie Chen, Weiwei Sun, et al.
Remote Sensing (2024) Vol. 16, Iss. 15, pp. 2760-2760
Open Access | Times Cited: 6
Comparing Pixel- and Object-Based Approaches for Classifying Multispectral Drone Imagery of a Salt Marsh Restoration and Reference Site
Gregory S. Norris, Armand LaRocque, Brigitte Leblon, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 1049-1049
Open Access | Times Cited: 4
Lake total suspended matter retrieval by wind speed: A machine learning model trained by time-series satellite imagery
Ashkan Noori, Seyed Hossein Mohajeri, Mojtaba Mehraein, et al.
Ecological Informatics (2024) Vol. 81, pp. 102565-102565
Open Access | Times Cited: 4
UAV-based modelling of vegetation recovery under extreme habitat stresses in the water level fluctuation zone of the Three Gorges Reservoir, China
J. Prakasha Rao, Qiang Tang, Dingqi Duan, et al.
The Science of The Total Environment (2024) Vol. 934, pp. 173185-173185
Closed Access | Times Cited: 4
Evaluating the performance of airborne and spaceborne lidar for mapping biomass in the United States' largest dry woodland ecosystem
Michael J. Campbell, Jessie F. Eastburn, Philip E. Dennison, et al.
Remote Sensing of Environment (2024) Vol. 308, pp. 114196-114196
Closed Access | Times Cited: 4
Aboveground biomass inversion of forestland in a Jinsha River dry-hot valley by integrating high and medium spatial resolution optical images: A case study on Yuanmou County of Southwest China
Zihao Liu, Tian‐Bao Huang, Yong Wu, et al.
Ecological Informatics (2024) Vol. 83, pp. 102796-102796
Open Access | Times Cited: 4
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