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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:

Lidar sampling — Using an airborne profiler to estimate forest biomass in Hedmark County, Norway
R. Nelson, Terje Gobakken, Erik Næsset, et al.
Remote Sensing of Environment (2012) Vol. 123, pp. 563-578
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems
Dengsheng Lu, Qi Chen, Guangxing Wang, et al.
International Journal of Digital Earth (2014) Vol. 9, Iss. 1, pp. 63-105
Open Access | Times Cited: 689
Lidar sampling for large-area forest characterization: A review
Michael A. Wulder, Joanne C. White, Ross Nelson, et al.
Remote Sensing of Environment (2012) Vol. 121, pp. 196-209
Open Access | Times Cited: 672
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
Model-based inference for biomass estimation in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.
Göran Ståhl, Sören Holm, Timothy G. Grégoire, et al.
Canadian Journal of Forest Research (2011) Vol. 41, Iss. 1, pp. 96-107
Open Access | Times Cited: 171
Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.
Timothy G. Grégoire, Göran Ståhl, Erik Næsset, et al.
Canadian Journal of Forest Research (2011) Vol. 41, Iss. 1, pp. 83-95
Closed Access | Times Cited: 160
Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation
Göran Ståhl, Svetlana Saarela, Sebastian Schnell, et al.
Forest Ecosystems (2016) Vol. 3, Iss. 1
Open Access | Times Cited: 153
Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar
Anu Swatantran, Hao Tang, Terence Barrett, et al.
Scientific Reports (2016) Vol. 6, Iss. 1
Open Access | Times Cited: 136
Model-assisted estimation of change in forest biomass over an 11year period in a sample survey supported by airborne LiDAR: A case study with post-stratification to provide “activity data”
Erik Næsset, Ole Martin Bollandsås, Terje Gobakken, et al.
Remote Sensing of Environment (2012) Vol. 128, pp. 299-314
Open Access | Times Cited: 129
A Review of Methods for Mapping and Prediction of Inventory Attributes for Operational Forest Management
Kimberley D. Brosofske, Robert E. Froese, Michael J. Falkowski, et al.
Forest Science (2014) Vol. 60, Iss. 4, pp. 733-756
Open Access | Times Cited: 129
The role of remote sensing in process-scaling studies of managed forest ecosystems
Jeffrey G. Masek, Daniel J. Hayes, M. Joseph Hughes, et al.
Forest Ecology and Management (2015) Vol. 355, pp. 109-123
Open Access | Times Cited: 127
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
Estimating biomass in Hedmark County, Norway using national forest inventory field plots and airborne laser scanning
Terje Gobakken, Erik Næsset, Ross Nelson, et al.
Remote Sensing of Environment (2012) Vol. 123, pp. 443-456
Closed Access | Times Cited: 119
Comparison of precision of biomass estimates in regional field sample surveys and airborne LiDAR-assisted surveys in Hedmark County, Norway
Erik Næsset, Terje Gobakken, Ole Martin Bollandsås, et al.
Remote Sensing of Environment (2012) Vol. 130, pp. 108-120
Open Access | Times Cited: 118
Lidar plots — a new large-area data collection option: context, concepts, and case study
Michael A. Wulder, Joanne C. White, Christopher W. Bater, et al.
Canadian Journal of Remote Sensing (2012) Vol. 38, Iss. 5, pp. 600-618
Closed Access | Times Cited: 118
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
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
Forest aboveground biomass mapping and estimation across multiple spatial scales using model-based inference
Qi Chen, Ronald E. McRoberts, Changwei Wang, et al.
Remote Sensing of Environment (2016) Vol. 184, pp. 350-360
Closed Access | Times Cited: 91
Comparison of Small- and Large-Footprint Lidar Characterization of Tropical Forest Aboveground Structure and Biomass: A Case Study From Central Gabon
Carlos Alberto Silva, Sassan Saatchi, Mariano Garcı́a, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2018) Vol. 11, Iss. 10, pp. 3512-3526
Open Access | Times Cited: 84
Taking stock of circumboreal forest carbon with ground measurements, airborne and spaceborne LiDAR
C. S. R. Neigh, Ross Nelson, K.J. Ranson, et al.
Remote Sensing of Environment (2013) Vol. 137, pp. 274-287
Open Access | Times Cited: 100
Assessing the accuracy of regional LiDAR-based biomass estimation using a simulation approach
Liviu Theodor Ene, Erik Næsset, Terje Gobakken, et al.
Remote Sensing of Environment (2012) Vol. 123, pp. 579-592
Closed Access | Times Cited: 93
Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations
Chad Babcock, Andrew O. Finley, Hans‐Erik Andersen, et al.
Remote Sensing of Environment (2018) Vol. 212, pp. 212-230
Open Access | Times Cited: 56
Estimates of Forest Canopy Height Using a Combination of ICESat-2/ATLAS Data and Stereo-Photogrammetry
Xiaojuan Lin, Min Xu, Chunxiang Cao, et al.
Remote Sensing (2020) Vol. 12, Iss. 21, pp. 3649-3649
Open Access | Times Cited: 47
Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation
Svetlana Saarela, Sören Holm, Sean P. Healey, et al.
Remote Sensing of Environment (2022) Vol. 278, pp. 113074-113074
Open Access | Times Cited: 26
Improving Aboveground Forest Biomass Maps: From High-Resolution to National Scale
Pilar Durante, Santiago Martín‐Alcón, Assu Gil‐Tena, et al.
Remote Sensing (2019) Vol. 11, Iss. 7, pp. 795-795
Open Access | Times Cited: 32
Large-area hybrid estimation of aboveground biomass in interior Alaska using airborne laser scanning data
Liviu Theodor Ene, Terje Gobakken, Hans‐Erik Andersen, et al.
Remote Sensing of Environment (2017) Vol. 204, pp. 741-755
Open Access | Times Cited: 33
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