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:

A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps
Arnan Araza, Sytze de Bruin, Martin Herold, et al.
Remote Sensing of Environment (2022) Vol. 272, pp. 112917-112917
Open Access | Times Cited: 79

Showing 1-25 of 79 citing articles:

Integrated global assessment of the natural forest carbon potential
Lidong Mo, Constantin M. Zohner, Peter B. Reich, et al.
Nature (2023) Vol. 624, Iss. 7990, pp. 92-101
Open Access | Times Cited: 173
The effectiveness of global protected areas for climate change mitigation
Laura Duncanson, Mengyu Liang, Veronika Leitold, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 73
Estimating vertically growing crop above-ground biomass based on UAV remote sensing
Jibo Yue, Hao Yang, Guijun Yang, et al.
Computers and Electronics in Agriculture (2023) Vol. 205, pp. 107627-107627
Closed Access | Times Cited: 59
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: 19
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
Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean forests
Juan Guerra-Hernández, Lana L. Narine, Adrián Pascual, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 1509-1533
Open Access | Times Cited: 43
Changes in land use and management led to a decline in Eastern Europe’s terrestrial carbon sink
Karina Winkler, Hui Yang, Raphael Ganzenmüller, et al.
Communications Earth & Environment (2023) Vol. 4, Iss. 1
Open Access | Times Cited: 30
Past decade above-ground biomass change comparisons from four multi-temporal global maps
Arnan Araza, Martin Herold, Sytze de Bruin, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 118, pp. 103274-103274
Open Access | Times Cited: 26
Development of forest aboveground biomass estimation, its problems and future solutions: A review
Taiyong Ma, Chao Zhang, Liping Ji, et al.
Ecological Indicators (2024) Vol. 159, pp. 111653-111653
Open Access | Times Cited: 13
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: 12
SCARF: A new algorithm for continuous prediction of biomass dynamics using machine learning and Landsat time series
Yingchun Fu, Runhao Li, Zhe Zhu, et al.
Remote Sensing of Environment (2024) Vol. 314, pp. 114348-114348
Open Access | Times Cited: 9
Calibration of GEDI footprint aboveground biomass models in Mediterranean forests with NFI plots: A comparison of approaches
Adrián Pascual, Paul May, Aarón Cárdenas-Martínez, et al.
Journal of Environmental Management (2025) Vol. 375, pp. 124313-124313
Open Access | Times Cited: 1
A new synergistic approach for Sentinel-1 and PALSAR-2 in a machine learning framework to predict aboveground biomass of a dense mangrove forest
A. Jaya Prakash, Mukunda Dev Behera, Sujit Madhab Ghosh, et al.
Ecological Informatics (2022) Vol. 72, pp. 101900-101900
Closed Access | Times Cited: 33
Estimation of Aboveground Biomass in Agroforestry Systems over Three Climatic Regions in West Africa Using Sentinel-1, Sentinel-2, ALOS, and GEDI Data
Dan Kanmegne Tamga, Hooman Latifi, Tobias Ullmann, et al.
Sensors (2022) Vol. 23, Iss. 1, pp. 349-349
Open Access | Times Cited: 29
On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake
Neha Hunka, Maurizio Santoro, John Armston, et al.
Environmental Research Letters (2023) Vol. 18, Iss. 12, pp. 124042-124042
Open Access | Times Cited: 17
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
Global estimation of above-ground biomass from spaceborne C-band scatterometer observations aided by LiDAR metrics of vegetation structure
Maurizio Santoro, Oliver Cartus, U. Wegmüller, et al.
Remote Sensing of Environment (2022) Vol. 279, pp. 113114-113114
Closed Access | Times Cited: 27
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
Satellite-based global maps are rarely used in forest reference levels submitted to the UNFCCC
Joana Melo, Timothy R. Baker, Dirk Nemitz, et al.
Environmental Research Letters (2023) Vol. 18, Iss. 3, pp. 034021-034021
Open Access | Times Cited: 14
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
Using bi-temporal ALS and NFI-based time-series data to account for large-scale aboveground carbon dynamics: the showcase of mediterranean forests
Juan Guerra-Hernández, Adrián Pascual, Frederico Tupinambá‐Simões, et al.
European Journal of Remote Sensing (2024) Vol. 57, Iss. 1
Open Access | Times Cited: 5
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
A parametric approach for global estimation of forest above-ground biomass with SMOS and SMAP L-band radiometer data
Oliver Cartus, Maurizio Santoro, Carlos Jiménez, et al.
Remote Sensing of Environment (2025) Vol. 318, pp. 114601-114601
Closed Access
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
Machine learning technique for carbon sequestration estimation of mango orchards area using Sentinel-2 Data
Gitsada Panumonwatee, Sittichai Choosumrong, Savent Pampasit, et al.
Carbon Research (2025) Vol. 4, Iss. 1
Open Access
Page 1 - Next Page

Scroll to top