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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:

Upscaling Forest Biomass from Field to Satellite Measurements: Sources of Errors and Ways to Reduce Them
Maxime Réjou‐Méchain, Nicolas Barbier, Pierre Couteron, et al.
Surveys in Geophysics (2019) Vol. 40, Iss. 4, pp. 881-911
Closed Access | Times Cited: 100

Showing 26-50 of 100 citing articles:

Spatial Scale Effect and Correction of Forest Aboveground Biomass Estimation Using Remote Sensing
Ying Yu, Yan Pan, Xiguang Yang, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2828-2828
Open Access | Times Cited: 23
Forest Emissions Reduction Assessment Using Optical Satellite Imagery and Space LiDAR Fusion for Carbon Stock Estimation
Yue Jiao, Dacheng Wang, Xiaojing Yao, et al.
Remote Sensing (2023) Vol. 15, Iss. 5, pp. 1410-1410
Open Access | Times Cited: 15
Tree height-diameter, aboveground and belowground biomass allometries for two West African mangrove species
Serge M.G. Zanvo, Sylvanus Mensah, Kolawolé Valère Salako, et al.
Biomass and Bioenergy (2023) Vol. 176, pp. 106917-106917
Closed Access | Times Cited: 14
Evaluation of Height Metrics and Above-Ground Biomass Density from GEDI and ICESat-2 Over Indian Tropical Dry Forests using Airborne LiDAR Data
Suraj Reddy Rodda, ‪Rama Rao Nidamanuri, Rakesh Fararoda, et al.
Journal of the Indian Society of Remote Sensing (2023) Vol. 52, Iss. 4, pp. 841-856
Closed Access | Times Cited: 13
Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors
Edward A. Velasco Pereira, Ma Ángeles Varo-Martínez, Francisco J. Ruíz-Gómez, et al.
Remote Sensing (2023) Vol. 15, Iss. 13, pp. 3430-3430
Open Access | Times Cited: 13
Harmonised statistics and maps of forest biomass and increment in Europe
Valerio Avitabile, Roberto Pilli, Mirco Migliavacca, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 5
Machine learning feature importance selection for predicting aboveground biomass in African savannah with landsat 8 and ALOS PALSAR data
Saad Eddin Ibrahim, Heiko Balzter, Kevin Tansey
Machine Learning with Applications (2024) Vol. 16, pp. 100561-100561
Open Access | Times Cited: 5
Mapping aboveground biomass in Indonesian lowland forests using GEDI and hierarchical models
Paul May, Michael Schlund, John Armston, et al.
Remote Sensing of Environment (2024) Vol. 313, pp. 114384-114384
Closed Access | Times Cited: 5
Advancing forest carbon stocks’ mapping using a hierarchical approach with machine learning and satellite imagery
Svetlana Illarionova, Polina Tregubova, Islomjon Shukhratov, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Modeling and mapping aboveground biomass of the restored mangroves using ALOS-2 PALSAR-2 in East Kalimantan, Indonesia
Karimon Nesha, Y.A. Hussin, L.M. van Leeuwen, et al.
International Journal of Applied Earth Observation and Geoinformation (2020) Vol. 91, pp. 102158-102158
Open Access | Times Cited: 33
Biomass estimation in mangrove forests: a comparison of allometric models incorporating species and structural information
Md. Saidur Rahman, Daniel N.M. Donoghue, Louise J. Bracken, et al.
Environmental Research Letters (2021) Vol. 16, Iss. 12, pp. 124002-124002
Open Access | Times Cited: 31
Biomass from trees for bioenergy and biofuels – A briefing paper
Gyanaranjan Sahoo, Amita Sharma, Asim Chandra Dash
Materials Today Proceedings (2022) Vol. 65, pp. 461-467
Closed Access | Times Cited: 21
Mapping tree mortality rate in a tropical moist forest using multi-temporal LiDAR
Claudia Elizabeth Mora Huertas, Daniel Sabatier, Géraldine Derroire, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 109, pp. 102780-102780
Open Access | Times Cited: 19
Prediction of Strawberry Dry Biomass from UAV Multispectral Imagery Using Multiple Machine Learning Methods
Caiwang Zheng, Amr Abd‐Elrahman, Vance M. Whitaker, et al.
Remote Sensing (2022) Vol. 14, Iss. 18, pp. 4511-4511
Open Access | Times Cited: 19
Design and performance of the Climate Change Initiative Biomass global retrieval algorithm
Maurizio Santoro, Oliver Cartus, S. Quegan, et al.
Science of Remote Sensing (2024) Vol. 10, pp. 100169-100169
Open Access | Times Cited: 4
The Application of Fast Fourier Transform Filtering to High Spatial Resolution Digital Terrain Models Derived from LiDAR Sensors for the Objective Mapping of Surface Features and Digital Terrain Model Evaluations
A. González, Ignacio Díaz‐Martínez, Pablo Cruz‐Hernández, et al.
Remote Sensing (2025) Vol. 17, Iss. 1, pp. 150-150
Open Access
Aboveground Biomass and Tree Mortality Revealed Through Multi-Scale LiDAR Analysis
Inácio Thomaz Bueno, Carlos Alberto Silva, Kristina J. Anderson‐Teixeira, et al.
Remote Sensing (2025) Vol. 17, Iss. 5, pp. 796-796
Open Access
Mapping Tropical Forested Wetlands Biomass with LiDAR: A Machine Learning Comparison
Jonathan V. Solórzano, Candelario Peralta-Carreta, J. Alberto Gallardo-Cruz
Remote Sensing (2025) Vol. 17, Iss. 6, pp. 1076-1076
Open Access
Evaluating Lorenz entropy for tropical forest discrimination using GEDI and supervised machine learning approach
Nooshin Mashhadi, Arturo Sánchez‐Azofeifa
Ecological Indicators (2025) Vol. 173, pp. 113374-113374
Closed Access
Cross-scale patterns of structure and maximum biomass in late-seral Douglas-fir-dominated rainforests
Russell D. Kramer, Stephen C. Sillett, Sean M.A. Jeronimo, et al.
Forest Ecology and Management (2025) Vol. 585, pp. 122594-122594
Open Access
A Joint ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP) for Biomass, NISAR, and GEDI
C. Albinet, Amanda Whitehurst, L. A. Jewell, et al.
Surveys in Geophysics (2019) Vol. 40, Iss. 4, pp. 1017-1027
Open Access | Times Cited: 30
The Effect of Synergistic Approaches of Features and Ensemble Learning Algorithms on Aboveground Biomass Estimation of Natural Secondary Forests Based on ALS and Landsat 8
Chunyu Du, Wenyi Fan, Ye Ma, et al.
Sensors (2021) Vol. 21, Iss. 17, pp. 5974-5974
Open Access | Times Cited: 25
The real potential of current passive satellite data to map aboveground biomass in tropical forests
Nidhi Jha, Nitin Kumar Tripathi, Nicolas Barbier, et al.
Remote Sensing in Ecology and Conservation (2021) Vol. 7, Iss. 3, pp. 504-520
Open Access | Times Cited: 24
Predicting eucalyptus plantation growth and yield using Landsat imagery in Minas Gerais, Brazil
Jeangelis Silva Santos, Adriano Ribeiro de Mendonça, F. G. Gonçalves, et al.
Ecological Informatics (2023) Vol. 75, pp. 102120-102120
Closed Access | Times Cited: 9
Evaluating the impact of field-measured tree height errors correction on aboveground biomass modeling using airborne laser scanning and GEDI datasets in Brazilian Amazonia
Nadeem Fareed, Izaya Numata
Trees Forests and People (2024), pp. 100751-100751
Open Access | Times Cited: 3

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