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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:

Synergistic use of Landsat 8 OLI image and airborne LiDAR data for above-ground biomass estimation in tropical lowland rainforests
Mui‐How Phua, Shazrul Azwan Johari, Ong Cieh Wong, et al.
Forest Ecology and Management (2017) Vol. 406, pp. 163-171
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Individual Tree Crown Segmentation and Crown Width Extraction From a Heightmap Derived From Aerial Laser Scanning Data Using a Deep Learning Framework
Chenxin Sun, Chengwei Huang, Huaiqing Zhang, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 64
Mapping Forest Aboveground Biomass Using Multisource Remotely Sensed Data
Dekker Ehlers, Chao Wang, John W. Coulston, et al.
Remote Sensing (2022) Vol. 14, Iss. 5, pp. 1115-1115
Open Access | Times Cited: 34
Combining hyperspectral imagery and LiDAR pseudo-waveform for predicting crop LAI, canopy height and above-ground biomass
Shezhou Luo, Cheng Wang, Xiaohuan Xi, et al.
Ecological Indicators (2019) Vol. 102, pp. 801-812
Closed Access | Times Cited: 51
Predicting Growing Stock Volume of Scots Pine Stands Using Sentinel-2 Satellite Imagery and Airborne Image-Derived Point Clouds
Paweł Hawryło, Piotr Wężyk
Forests (2018) Vol. 9, Iss. 5, pp. 274-274
Open Access | Times Cited: 39
Modelling Forest Ecosystems: a crossroad between scales, techniques and applications
Juan A. Blanco, Aitor Améztegui, Francisco Rodríguez
Ecological Modelling (2020) Vol. 425, pp. 109030-109030
Open Access | Times Cited: 35
Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
Shun Li, Tianming Wang, Zhengyang Hou, et al.
Ecological Indicators (2020) Vol. 121, pp. 107011-107011
Open Access | Times Cited: 33
Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data
Ali Masjedi, Melba M. Crawford, Neal R. Carpenter, et al.
Remote Sensing (2020) Vol. 12, Iss. 21, pp. 3587-3587
Open Access | Times Cited: 29
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
A multimodal and meta-learning approach for improved estimation of 3D vegetation structure from satellite imagery
Ram C. Sharma
Applied Geomatics (2025)
Closed Access
A review of remote sensing applications in tropical forestry with a particular emphasis in the plantation sector
Bambang H. Trisasongko, David Paull
Geocarto International (2018) Vol. 35, Iss. 3, pp. 317-339
Closed Access | Times Cited: 30
High-Precision Stand Age Data Facilitate the Estimation of Rubber Plantation Biomass: A Case Study of Hainan Island, China
Bangqian Chen, Ting Yun, Jun Ma, et al.
Remote Sensing (2020) Vol. 12, Iss. 23, pp. 3853-3853
Open Access | Times Cited: 24
Do airborne laser scanning biomass prediction models benefit from Landsat time series, hyperspectral data or forest classification in tropical mosaic landscapes?
Janne Heiskanen, Hari Adhikari, Rami Piiroinen, et al.
International Journal of Applied Earth Observation and Geoinformation (2019) Vol. 81, pp. 176-185
Open Access | Times Cited: 22
Mapping forest structural heterogeneity of tropical montane forest remnants from airborne laser scanning and Landsat time series
Hari Adhikari, Rubén Valbuena, Petri Pellikka, et al.
Ecological Indicators (2019) Vol. 108, pp. 105739-105739
Open Access | Times Cited: 22
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
Saf Kızılçam (Pinus brutia Ten.) Meşcerelerinde Aktif ve Pasif Uydu Görüntüleri Kullanılarak Topraküstü Biyokütlenin Tahmin Edilmesi (Anamur Orman İşletme Şefliği Örneği)
İzzet GÜVERÇİN, Alkan Günlü
Bartın Orman Fakültesi Dergisi (2023) Vol. 25, Iss. 1, pp. 177-191
Open Access | Times Cited: 6
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
Diagnosing pristine pine forest development through pansharpened-surface-reflectance Landsat image derived aboveground biomass productivity
Nova D. Doyog, Chinsu Lin, Young Jin Lee, et al.
Forest Ecology and Management (2021) Vol. 487, pp. 119011-119011
Closed Access | Times Cited: 12
Canopy height recovery after selective logging in a lowland tropical rain forest
Toshinori Okuda, Toshihiro Yamada, Tetsurō Hosaka, et al.
Forest Ecology and Management (2019) Vol. 442, pp. 117-123
Closed Access | Times Cited: 10
An allometric area-based approach—a cost-effective method for stand volume estimation based on ALS and NFI data
Jarosław Socha, Paweł Hawryło, M. Pierzchalski, et al.
Forestry An International Journal of Forest Research (2019) Vol. 93, Iss. 3, pp. 344-358
Open Access | Times Cited: 10
Multi-scale approach to estimating aboveground biomass in the Brazilian Amazon using Landsat and LiDAR data
Erone Ghizoni Santos, Yosio Edemir Shimabukuro, Yhasmin Mendes de Moura, et al.
International Journal of Remote Sensing (2019) Vol. 40, Iss. 22, pp. 8635-8645
Open Access | Times Cited: 7
REGRESSÕES ROBUSTA E LINEAR PARA ESTIMATIVA DE BIOMASSA VIA IMAGEM SENTINEL EM UMA FLORESTA TROPICAL
Aline Bernarda Debastiani, Marks Melo Moura, Franciel Eduardo Rex, et al.
BIOFIX Scientific Journal (2019) Vol. 4, Iss. 2, pp. 81-81
Open Access | Times Cited: 5
Predictive Model of Mangroves Carbon Stocks in Kedah, Malaysia using Remote Sensing
Tengku Mohd Zarawie Tengku Hashim, Mohd Nazip Suratman, H.R. Singh, et al.
IOP Conference Series Earth and Environmental Science (2020) Vol. 540, Iss. 1, pp. 012033-012033
Open Access | Times Cited: 4
Aboveground Biomass Changes in Tropical Montane Forest of Northern Borneo Estimated Using Spaceborne and Airborne Digital Elevation Data
Ho Yan Loh, Daniel James, Keiko Ioki, et al.
Remote Sensing (2020) Vol. 12, Iss. 22, pp. 3677-3677
Open Access | Times Cited: 4
Energy Production from Forest Biomass: An Overview
Ana Cristina Gonçalves, Isabel Malico, Adélia Sousa
IntechOpen eBooks (2021)
Open Access | Times Cited: 4
Lost in the woods: Forest vegetation, and not topography, most affects the connectivity of mesh radio networks for public safety
Eloise G. Zimbelman, Robert Keefe
PLoS ONE (2022) Vol. 17, Iss. 12, pp. e0278645-e0278645
Open Access | Times Cited: 3
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