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:

Regional Forest Volume Estimation by Expanding LiDAR Samples Using Multi-Sensor Satellite Data
Bo Xie, Chunxiang Cao, Min Xu, et al.
Remote Sensing (2020) Vol. 12, Iss. 3, pp. 360-360
Open Access | Times Cited: 13

Showing 13 citing articles:

Estimating Forest Growing Stock Volume Using Feature Selection and Advanced Remote Sensing Algorithm
Yabing Zhao, Famiao Guo, Yin Wang, et al.
Remote Sensing Applications Society and Environment (2025), pp. 101458-101458
Closed Access | Times Cited: 1

Estimating the Growing Stem Volume of Coniferous Plantations Based on Random Forest Using an Optimized Variable Selection Method
Fugen Jiang, Mykola Kutia, Arbi J. Sarkissian, et al.
Sensors (2020) Vol. 20, Iss. 24, pp. 7248-7248
Open Access | Times Cited: 41

Improved estimation of forest stand volume by the integration of GEDI LiDAR data and multi-sensor imagery in the Changbai Mountains Mixed forests Ecoregion (CMMFE), northeast China
Lin Chen, Chunying Ren, Bai Zhang, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 100, pp. 102326-102326
Open Access | Times Cited: 39

Eucalyptus diameter and volume prediction with deep neural networks: A Long Short-Term Memory model approach
Welington G. Rodrigues, Gabriel da Silva Vieira, Christian Dias Cabacinha, et al.
Expert Systems with Applications (2025), pp. 126704-126704
Closed Access

Comparison of Modeling Algorithms for Forest Canopy Structures Based on UAV-LiDAR: A Case Study in Tropical China
Xi Peng, Anjiu Zhao, Yongfu Chen, et al.
Forests (2020) Vol. 11, Iss. 12, pp. 1324-1324
Open Access | Times Cited: 20

Estimation of Boreal Forest Growing Stock Volume in Russia from Sentinel-2 MSI and Land Cover Classification
Gareth Rees, Jack Tomaney, Olga Tutubalina, et al.
Remote Sensing (2021) Vol. 13, Iss. 21, pp. 4483-4483
Open Access | Times Cited: 13

Analysis of Regional Distribution of Tree Species Using Multi-Seasonal Sentinel-1&2 Imagery within Google Earth Engine
Bo Xie, Chunxiang Cao, Min Xu, et al.
Forests (2021) Vol. 12, Iss. 5, pp. 565-565
Open Access | Times Cited: 12

Mapping Aboveground Woody Biomass on Abandoned Agricultural Land Based on Airborne Laser Scanning Data
Ivan Sačkov, Ivan Barka, Tomáš Bucha
Remote Sensing (2020) Vol. 12, Iss. 24, pp. 4189-4189
Open Access | Times Cited: 12

Understanding the Spatially Explicit Distribution of Regional Tree Species Using Multi-Seasonal Sentinel-1&2 Imagery within Google Earth Engine
Bo Xie, Chunxiang Cao, Min Xu, et al.
Research Square (Research Square) (2021)
Closed Access | Times Cited: 11

Applications of artificial intelligence and LiDAR in forest inventories: A Systematic Literature Review
Welington G. Rodrigues, Gabriel da Silva Vieira, Christian Dias Cabacinha, et al.
Computers & Electrical Engineering (2024) Vol. 120, pp. 109793-109793
Closed Access | Times Cited: 1

Improved Forest Canopy Closure Estimation Using Multispectral Satellite Imagery within Google Earth Engine
Bo Xie, Chunxiang Cao, Min Xu, et al.
Remote Sensing (2022) Vol. 14, Iss. 9, pp. 2051-2051
Open Access | Times Cited: 4

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