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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:

A National, Detailed Map of Forest Aboveground Carbon Stocks in Mexico
Oliver Cartus, Josef Kellndorfer, Wayne Walker, et al.
Remote Sensing (2014) Vol. 6, Iss. 6, pp. 5559-5588
Open Access | Times Cited: 118

Showing 1-25 of 118 citing articles:

An integrated pan‐tropical biomass map using multiple reference datasets
Valerio Avitabile, Martin Herold, G.B.M. Heuvelink, et al.
Global Change Biology (2015) Vol. 22, Iss. 4, pp. 1406-1420
Open Access | Times Cited: 639
A Review of Wetland Remote Sensing
Meng Guo, Jing Li, Chunlei Sheng, et al.
Sensors (2017) Vol. 17, Iss. 4, pp. 777-777
Open Access | Times Cited: 430
Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD+
Anthea L. Mitchell, Åke Rosenqvist, B. Mora
Carbon Balance and Management (2017) Vol. 12, Iss. 1
Open Access | Times Cited: 253
An above-ground biomass map of African savannahs and woodlands at 25 m resolution derived from ALOS PALSAR
Alexandre Bouvet, Stéphane Mermoz, Thuy Le Toan, et al.
Remote Sensing of Environment (2017) Vol. 206, pp. 156-173
Open Access | Times Cited: 236
Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects
Lei Tian, Xiaocan Wu, Tao Yu, et al.
Forests (2023) Vol. 14, Iss. 6, pp. 1086-1086
Open Access | Times Cited: 78
Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR
Maurizio Santoro, André Beaudoin, Christian Beer, et al.
Remote Sensing of Environment (2015) Vol. 168, pp. 316-334
Closed Access | Times Cited: 175
Carbon stocks and soil sequestration rates of tropical riverine wetlands
María Fernanda Adame, Nadia S. Santini, C. Tovilla, et al.
Biogeosciences (2015) Vol. 12, Iss. 12, pp. 3805-3818
Open Access | Times Cited: 144
Quantifying Forest Biomass Carbon Stocks From Space
Pedro Rodríguez‐Veiga, James Wheeler, Valentin Louis, et al.
Current Forestry Reports (2017) Vol. 3, Iss. 1, pp. 1-18
Open Access | Times Cited: 144
Identifying effects of land use cover changes and climate change on terrestrial ecosystems and carbon stocks in Mexico
Alma Mendoza‐Ponce, Rogelio O. Corona‐Núñez, Florian Kraxner, et al.
Global Environmental Change (2018) Vol. 53, pp. 12-23
Open Access | Times Cited: 142
Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico
Mikhail Urbazaev, Christian Thiel, Felix Cremer, et al.
Carbon Balance and Management (2018) Vol. 13, Iss. 1
Open Access | Times Cited: 137
Integration of multi-resource remotely sensed data and allometric models for forest aboveground biomass estimation in China
Huabing Huang, Caixia Liu, Xiaoyi Wang, et al.
Remote Sensing of Environment (2018) Vol. 221, pp. 225-234
Closed Access | Times Cited: 111
An Evaluation of Eight Machine Learning Regression Algorithms for Forest Aboveground Biomass Estimation from Multiple Satellite Data Products
Yuzhen Zhang, Jun Ma, Shunlin Liang, et al.
Remote Sensing (2020) Vol. 12, Iss. 24, pp. 4015-4015
Open Access | Times Cited: 109
Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations
Ross Nelson, Hank A. Margolis, Paul Montesano, et al.
Remote Sensing of Environment (2016) Vol. 188, pp. 127-140
Open Access | Times Cited: 108
Magnitude, spatial distribution and uncertainty of forest biomass stocks in Mexico
Pedro Rodríguez‐Veiga, Sassan Saatchi, Kevin Tansey, et al.
Remote Sensing of Environment (2016) Vol. 183, pp. 265-281
Open Access | Times Cited: 106
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
Forest biomass retrieval approaches from earth observation in different biomes
Pedro Rodríguez‐Veiga, S. Quegan, João M. B. Carreiras, et al.
International Journal of Applied Earth Observation and Geoinformation (2019) Vol. 77, pp. 53-68
Open Access | Times Cited: 96
Anthropogenic impact on habitat connectivity: A multidimensional human footprint index evaluated in a highly biodiverse landscape of Mexico
Camilo Andrés Correa Ayram, Manuel E. Mendoza, Andrés Etter, et al.
Ecological Indicators (2016) Vol. 72, pp. 895-909
Closed Access | Times Cited: 93
Estimating aboveground biomass in subtropical forests of China by integrating multisource remote sensing and ground data
Rong Zhang, Xuhui Zhou, Zutao Ouyang, et al.
Remote Sensing of Environment (2019) Vol. 232, pp. 111341-111341
Closed Access | Times Cited: 79
Modeling of Aboveground Biomass with Landsat 8 OLI and Machine Learning in Temperate Forests
Pablito Marcelo López-Serrano, José Luis Cárdenas Domínguez, José Javier Corral‐Rivas, et al.
Forests (2019) Vol. 11, Iss. 1, pp. 11-11
Open Access | Times Cited: 79
Improving aboveground biomass density mapping of arid and semi-arid vegetation by combining GEDI LiDAR, Sentinel-1/2 imagery and field data
Luis Ángel Hernández-Martínez, Juan Manuel Dupuy, Alfonso Medel‐Narváez, et al.
Science of Remote Sensing (2025) Vol. 11, pp. 100204-100204
Open Access | Times Cited: 1
Understanding ‘saturation’ of radar signals over forests
Neha Joshi, Edward T. A. Mitchard, Matthew Brolly, et al.
Scientific Reports (2017) Vol. 7, Iss. 1
Open Access | Times Cited: 86
National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China
Hong Chi, Guoqing Sun, Jinliang Huang, et al.
Remote Sensing (2015) Vol. 7, Iss. 5, pp. 5534-5564
Open Access | Times Cited: 74
Reanalyzing environmental lidar data for archaeology: Mesoamerican applications and implications
Charles J. Golden, Timothy Murtha, Bruce D. Cook, et al.
Journal of Archaeological Science Reports (2016) Vol. 9, pp. 293-308
Open Access | Times Cited: 68
Predicting forest fire kernel density at multiple scales with geographically weighted regression in Mexico
Norma Angélica Monjarás-Vega, Carlos Iván Briones-Herrera, Daniel José Vega-Nieva, et al.
The Science of The Total Environment (2020) Vol. 718, pp. 137313-137313
Closed Access | Times Cited: 64
A Review of Regional and Global Gridded Forest Biomass Datasets
Yuzhen Zhang, Shunlin Liang, Lu Yang
Remote Sensing (2019) Vol. 11, Iss. 23, pp. 2744-2744
Open Access | Times Cited: 61
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