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:

Coverage of high biomass forests by the ESA BIOMASS mission under defense restrictions
João M. B. Carreiras, S. Quegan, Thuy Le Toan, et al.
Remote Sensing of Environment (2017) Vol. 196, pp. 154-162
Open Access | Times Cited: 105

Showing 1-25 of 105 citing articles:

Forest management in southern China generates short term extensive carbon sequestration
Xiaowei Tong, Martin Brandt, Yuemin Yue, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 418
The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space
S. Quegan, Thuy Le Toan, Jérôme Chave, et al.
Remote Sensing of Environment (2019) Vol. 227, pp. 44-60
Open Access | Times Cited: 265
SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives
Jean‐Pierre Wigneron, Xiaojun Li, Frédéric Frappart, et al.
Remote Sensing of Environment (2020) Vol. 254, pp. 112238-112238
Open Access | Times Cited: 241
Satellite-observed pantropical carbon dynamics
Lei Fan, Jean‐Pierre Wigneron, Philippe Ciais, et al.
Nature Plants (2019) Vol. 5, Iss. 9, pp. 944-951
Closed Access | Times Cited: 220
Tropical forests did not recover from the strong 2015–2016 El Niño event
Jean‐Pierre Wigneron, Lei Fan, Philippe Ciais, et al.
Science Advances (2020) Vol. 6, Iss. 6
Open Access | Times Cited: 187
Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles
Nico Lang, Nikolai Kalischek, John Armston, et al.
Remote Sensing of Environment (2021) Vol. 268, pp. 112760-112760
Open Access | Times Cited: 183
Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping
Carlos Alberto Silva, Laura Duncanson, Steven Hancock, et al.
Remote Sensing of Environment (2020) Vol. 253, pp. 112234-112234
Open Access | Times Cited: 171
Global-scale assessment and inter-comparison of recently developed/reprocessed microwave satellite vegetation optical depth products
Xiaojun Li, Jean‐Pierre Wigneron, Frédéric Frappart, et al.
Remote Sensing of Environment (2020) Vol. 253, pp. 112208-112208
Open Access | Times Cited: 147
Siberian carbon sink reduced by forest disturbances
Lei Fan, Jean‐Pierre Wigneron, Philippe Ciais, et al.
Nature Geoscience (2022) Vol. 16, Iss. 1, pp. 56-62
Open Access | Times Cited: 99
Estimating aboveground biomass and forest canopy cover with simulated ICESat-2 data
Lana L. Narine, Sorin C. Popescu, Amy Neuenschwander, et al.
Remote Sensing of Environment (2019) Vol. 224, pp. 1-11
Closed Access | Times Cited: 121
Combining satellite lidar, airborne lidar, and ground plots to estimate the amount and distribution of aboveground biomass in the boreal forest of North America
Hank A. Margolis, Ross Nelson, Paul Montesano, et al.
Canadian Journal of Forest Research (2015) Vol. 45, Iss. 7, pp. 838-855
Closed Access | Times Cited: 108
Active restoration accelerates the carbon recovery of human-modified tropical forests
Christopher D. Philipson, Mark Cutler, Philip G. Brodrick, et al.
Science (2020) Vol. 369, Iss. 6505, pp. 838-841
Open Access | Times Cited: 104
Synergy of ICESat-2 and Landsat for Mapping Forest Aboveground Biomass with Deep Learning
Lana L. Narine, Sorin C. Popescu, Lonesome Malambo
Remote Sensing (2019) Vol. 11, Iss. 12, pp. 1503-1503
Open Access | Times Cited: 85
The NASA AfriSAR campaign: Airborne SAR and lidar measurements of tropical forest structure and biomass in support of current and future space missions
Temilola Fatoyinbo, John Armston, Marc Simard, et al.
Remote Sensing of Environment (2021) Vol. 264, pp. 112533-112533
Open Access | Times Cited: 61
Large loss and rapid recovery of vegetation cover and aboveground biomass over forest areas in Australia during 2019–2020
Yuanwei Qin, Xiangming Xiao, Jean‐Pierre Wigneron, et al.
Remote Sensing of Environment (2022) Vol. 278, pp. 113087-113087
Open Access | Times Cited: 57
A stacking ensemble algorithm for improving the biases of forest aboveground biomass estimations from multiple remotely sensed datasets
Yuzhen Zhang, Jun Ma, Shunlin Liang, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 234-249
Open Access | Times Cited: 55
Spatially Continuous Mapping of Forest Canopy Height in Canada by Combining GEDI and ICESat-2 with PALSAR and Sentinel
Camile Sothe, Alemu Gonsamo, Ricardo Barros Lourenço, et al.
Remote Sensing (2022) Vol. 14, Iss. 20, pp. 5158-5158
Open Access | Times Cited: 49
PolGAN: A deep-learning-based unsupervised forest height estimation based on the synergy of PolInSAR and LiDAR data
Qi Zhang, Linlin Ge, Scott Hensley, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 186, pp. 123-139
Open Access | Times Cited: 39
Estimating Aboveground Carbon Dynamic of China Using Optical and Microwave Remote-Sensing Datasets from 2013 to 2019
Zhongbing Chang, Lei Fan, Jean‐Pierre Wigneron, et al.
Journal of Remote Sensing (2023) Vol. 3
Open Access | Times Cited: 27
An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots
Valerio Avitabile, Andrea Camia
Forest Ecology and Management (2017) Vol. 409, pp. 489-498
Open Access | Times Cited: 81
Evaluation of the Sensitivity of SMOS L-VOD to Forest Above-Ground Biomass at Global Scale
Arnaud Mialon, Nemesio Rodríguez-Fernández, Maurizio Santoro, et al.
Remote Sensing (2020) Vol. 12, Iss. 9, pp. 1450-1450
Open Access | Times Cited: 63
Fusion of Multiple Gridded Biomass Datasets for Generating a Global Forest Aboveground Biomass Map
Yuzhen Zhang, Shunlin Liang
Remote Sensing (2020) Vol. 12, Iss. 16, pp. 2559-2559
Open Access | Times Cited: 57
Small-Satellite Synthetic Aperture Radar for Continuous Global Biospheric Monitoring: A Review
Sung Wook Paek, Sivagaminathan Balasubramanian, Sangtae Kim, et al.
Remote Sensing (2020) Vol. 12, Iss. 16, pp. 2546-2546
Open Access | Times Cited: 55
An alternative AMSR2 vegetation optical depth for monitoring vegetation at large scales
Mengjia Wang, Lei Fan, Frédéric Frappart, et al.
Remote Sensing of Environment (2021) Vol. 263, pp. 112556-112556
Open Access | Times Cited: 46
ASCAT IB: A radar-based vegetation optical depth retrieved from the ASCAT scatterometer satellite
Xiangzhuo Liu, Jean‐Pierre Wigneron, Lei Fan, et al.
Remote Sensing of Environment (2021) Vol. 264, pp. 112587-112587
Open Access | Times Cited: 45
Page 1 - Next Page

Scroll to top