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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:

Modelling aboveground forest biomass using airborne laser scanner data in the miombo woodlands of Tanzania
Ernest William Mauya, Liviu Theodor Ene, Ole Martin Bollandsås, et al.
Carbon Balance and Management (2015) Vol. 10, Iss. 1
Open Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery
André Beaudoin, Pierre Y. Bernier, Luc Guindon, et al.
Canadian Journal of Forest Research (2014) Vol. 44, Iss. 5, pp. 521-532
Open Access | Times Cited: 284
Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations
Kun Liu, Xin Shen, Lin Cao, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2018) Vol. 146, pp. 465-482
Closed Access | Times Cited: 170
Biomass Estimation Using 3D Data from Unmanned Aerial Vehicle Imagery in a Tropical Woodland
Daud Kachamba, Hans Ole Ørka, Terje Gobakken, et al.
Remote Sensing (2016) Vol. 8, Iss. 11, pp. 968-968
Open Access | Times Cited: 111
Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision
Erik Næsset, Hans Ole Ørka, Svein Solberg, et al.
Remote Sensing of Environment (2016) Vol. 175, pp. 282-300
Closed Access | Times Cited: 109
Mapping and estimating the total living biomass and carbon in low-biomass woodlands using Landsat 8 CDR data
Belachew Gizachew, Svein Solberg, Erik Næsset, et al.
Carbon Balance and Management (2016) Vol. 11, Iss. 1
Open Access | Times Cited: 79
A sampling design for a large area forest inventory: case Tanzania
Erkki Tomppo, R. E. Malimbwi, Matti Katila, et al.
Canadian Journal of Forest Research (2014) Vol. 44, Iss. 8, pp. 931-948
Closed Access | Times Cited: 73
Large-scale estimation of change in aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data
Liviu Theodor Ene, Erik Næsset, Terje Gobakken, et al.
Remote Sensing of Environment (2016) Vol. 188, pp. 106-117
Closed Access | Times Cited: 64
Large scale mapping of forest attributes using heterogeneous sets of airborne laser scanning and National Forest Inventory data
Marius Hauglin, Johannes Rahlf, Johannes Schumacher, et al.
Forest Ecosystems (2021) Vol. 8, pp. 65-65
Open Access | Times Cited: 50
Application of unmanned aerial vehicles in earth resources monitoring: focus on evaluating potentials for forest monitoring in Ethiopia
Habitamu Taddese Berie, I. Burud
European Journal of Remote Sensing (2018) Vol. 51, Iss. 1, pp. 326-335
Open Access | Times Cited: 51
Comparison of Statistical Modelling Approaches for Estimating Tropical Forest Aboveground Biomass Stock and Reporting Their Changes in Low-Intensity Logging Areas Using Multi-Temporal LiDAR Data
Franciel Eduardo Rex, Carlos Alberto Silva, Ana Paula Dalla Côrte, et al.
Remote Sensing (2020) Vol. 12, Iss. 9, pp. 1498-1498
Open Access | Times Cited: 34
Utility of UAS-LIDAR for estimating forest structural attributes of the Miombo woodlands in Zambia
Hastings Shamaoma, Paxie W. Chirwa, Jules Christian Zekeng, et al.
PLoS ONE (2025) Vol. 20, Iss. 3, pp. e0315664-e0315664
Open Access
Predicting Selected Forest Stand Characteristics with Multispectral ALS Data
Michele Dalponte, Liviu Theodor Ene, Terje Gobakken, et al.
Remote Sensing (2018) Vol. 10, Iss. 4, pp. 586-586
Open Access | Times Cited: 34
Modelling and Predicting the Growing Stock Volume in Small-Scale Plantation Forests of Tanzania Using Multi-Sensor Image Synergy
Ernest William Mauya, Joni Koskinen, Katri Tegel, et al.
Forests (2019) Vol. 10, Iss. 3, pp. 279-279
Open Access | Times Cited: 31
Aboveground Biomass Distribution in a Multi-Use Savannah Landscape in Southeastern Kenya: Impact of Land Use and Fences
Edward Amara, Hari Adhikari, Janne Heiskanen, et al.
Land (2020) Vol. 9, Iss. 10, pp. 381-381
Open Access | Times Cited: 31
Use of local and global maps of forest canopy height and aboveground biomass to enhance local estimates of biomass in miombo woodlands in Tanzania
Erik Næsset, Ronald E. McRoberts, Anssi Pekkarinen, et al.
International Journal of Applied Earth Observation and Geoinformation (2020) Vol. 93, pp. 102138-102138
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
Model-based estimation of above-ground biomass in the miombo ecoregion of Zambia
James Halperin, Valerie LeMay, Emmanuel N. Chidumayo, et al.
Forest Ecosystems (2016) Vol. 3, Iss. 1
Open Access | Times Cited: 31
Pre-stratified modelling plus residuals kriging reduces the uncertainty of aboveground biomass estimation and spatial distribution in heterogeneous savannas and forest environments
Eduarda Martiniano de Oliveira Silveira, Fernando Del Bon Espírito-Santo, Michael A. Wulder, et al.
Forest Ecology and Management (2019) Vol. 445, pp. 96-109
Closed Access | Times Cited: 26
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: 21
Use of local and global maps of forest canopy height and aboveground biomass to enhance local estimates of biomass in miombo woodlands in Tanzania
Erik Næsset, Ronald E. McRoberts, Anssi Pekkarinen, et al.
International Journal of Applied Earth Observation and Geoinformation (2020) Vol. 89, pp. 102109-102109
Open Access | Times Cited: 18
Multi-sensor forest vegetation height mapping methods for Tanzania
Øivind Due Trier, Arnt-Børre Salberg, Jörg Haarpaintner, et al.
European Journal of Remote Sensing (2018) Vol. 51, Iss. 1, pp. 587-606
Open Access | Times Cited: 15
Above ground tree biomass modeling using machine learning algorithms in western Terai Sal Forest of Nepal
Bikram Singh, Amit Kumar Verma, Kasip Tiwari, et al.
Heliyon (2023) Vol. 9, Iss. 11, pp. e21485-e21485
Open Access | Times Cited: 4
Understanding the contribution of structural diversity to stand biomass for carbon management of mixed forests using machine learning algorithms
Xiao He, Xiangdong Lei, Di Liu, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Modelling above Ground Biomass in Tanzanian Miombo Woodlands Using TanDEM-X WorldDEM and Field Data
Stefano Puliti, Svein Solberg, Erik Næsset, et al.
Remote Sensing (2017) Vol. 9, Iss. 10, pp. 984-984
Open Access | Times Cited: 12
Comparing Empirical and Semi-Empirical Approaches to Forest Biomass Modelling in Different Biomes Using Airborne Laser Scanner Data
Endre Hansen, Liviu Theodor Ene, Ernest William Mauya, et al.
Forests (2017) Vol. 8, Iss. 5, pp. 170-170
Open Access | Times Cited: 11
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