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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:

Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data
Svetlana Saarela, Sören Holm, Sean P. Healey, et al.
Remote Sensing (2018) Vol. 10, Iss. 11, pp. 1832-1832
Open Access | Times Cited: 76

Showing 1-25 of 76 citing articles:

The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography
R. Dubayah, J. B. Blair, S. J. Goetz, et al.
Science of Remote Sensing (2020) Vol. 1, pp. 100002-100002
Open Access | Times Cited: 876
Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission
Laura Duncanson, James R. Kellner, John Armston, et al.
Remote Sensing of Environment (2022) Vol. 270, pp. 112845-112845
Open Access | Times Cited: 259
Modelling lidar-derived estimates of forest attributes over space and time: A review of approaches and future trends
Nicholas C. Coops, Piotr Tompalski, Tristan R.H. Goodbody, et al.
Remote Sensing of Environment (2021) Vol. 260, pp. 112477-112477
Open Access | Times Cited: 241
Performance evaluation of GEDI and ICESat-2 laser altimeter data for terrain and canopy height retrievals
Aobo Liu, Xiao Cheng, Zhuoqi Chen
Remote Sensing of Environment (2021) Vol. 264, pp. 112571-112571
Open Access | Times Cited: 240
Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping
Carlos Alberto Silva, Laura Duncanson, Steven Hancock, et al.
Remote Sensing of Environment (2020) Vol. 253, pp. 112234-112234
Open Access | Times Cited: 171
GEDI launches a new era of biomass inference from space
R. Dubayah, John Armston, Sean P. Healey, et al.
Environmental Research Letters (2022) Vol. 17, Iss. 9, pp. 095001-095001
Open Access | Times Cited: 137
Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI
Chu Wang, Wangfei Zhang, Yongjie Ji, et al.
Forests (2024) Vol. 15, Iss. 1, pp. 215-215
Open Access | Times Cited: 20
Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data
Wenlu Qi, Svetlana Saarela, John Armston, et al.
Remote Sensing of Environment (2019) Vol. 232, pp. 111283-111283
Closed Access | Times Cited: 119
Using ICESat-2 to Estimate and Map Forest Aboveground Biomass: A First Example
Lana L. Narine, Sorin C. Popescu, Lonesome Malambo
Remote Sensing (2020) Vol. 12, Iss. 11, pp. 1824-1824
Open Access | Times Cited: 90
Highly Local Model Calibration with a New GEDI LiDAR Asset on Google Earth Engine Reduces Landsat Forest Height Signal Saturation
Sean P. Healey, Zhiqiang Yang, Noel Gorelick, et al.
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2840-2840
Open Access | Times Cited: 75
Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
Andrew J. Lister, Hans Henrik Andersen, Tracey S. Frescino, et al.
Forests (2020) Vol. 11, Iss. 12, pp. 1364-1364
Open Access | Times Cited: 75
Integrating GEDI and Landsat: Spaceborne Lidar and Four Decades of Optical Imagery for the Analysis of Forest Disturbances and Biomass Changes in Italy
Saverio Francini, Giovanni D’Amico, Elia Vangi, et al.
Sensors (2022) Vol. 22, Iss. 5, pp. 2015-2015
Open Access | Times Cited: 61
State-wide forest canopy height and aboveground biomass map for New York with 10 m resolution, integrating GEDI, Sentinel-1, and Sentinel-2 data
Haifa Tamiminia, Bahram Salehi, Masoud Mahdianpari, et al.
Ecological Informatics (2023) Vol. 79, pp. 102404-102404
Open Access | Times Cited: 31
Continuous mapping of aboveground biomass using Landsat time series
Paulo Arévalo, Alessandro Baccini, Curtis E. Woodcock, et al.
Remote Sensing of Environment (2023) Vol. 288, pp. 113483-113483
Open Access | Times Cited: 28
Estimation of above ground biomass in tropical heterogeneous forests in India using GEDI
Indu Indirabai, Mats Nilsson
Ecological Informatics (2024) Vol. 82, pp. 102712-102712
Open Access | Times Cited: 12
Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors
Svetlana Saarela, André Wästlund, Emma Holmström, et al.
Forest Ecosystems (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 55
Scaled biomass estimation in woodland ecosystems: Testing the individual and combined capacities of satellite multispectral and lidar data
Michael J. Campbell, Philip E. Dennison, Kelly L. Kerr, et al.
Remote Sensing of Environment (2021) Vol. 262, pp. 112511-112511
Open Access | Times Cited: 54
Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data
Rodrigo Vieira Leite, Carlos Alberto Silva, Eben N. Broadbent, et al.
Remote Sensing of Environment (2021) Vol. 268, pp. 112764-112764
Open Access | Times Cited: 48
How many bootstrap replications are necessary for estimating remote sensing-assisted, model-based standard errors?
Ronald E. McRoberts, Erik Næsset, Zhengyang Hou, et al.
Remote Sensing of Environment (2023) Vol. 288, pp. 113455-113455
Closed Access | Times Cited: 17
Evaluating the potential of full‐waveform lidar for mapping pan‐tropical tree species richness
Suzanne Marselis, Katharine Abernethy, Alfonso Alonso, et al.
Global Ecology and Biogeography (2020) Vol. 29, Iss. 10, pp. 1799-1816
Open Access | Times Cited: 46
Assessing the Performance of ICESat-2/ATLAS Multi-Channel Photon Data for Estimating Ground Topography in Forested Terrain
Yanqiu Xing, Jiapeng Huang, Armin Gruen, et al.
Remote Sensing (2020) Vol. 12, Iss. 13, pp. 2084-2084
Open Access | Times Cited: 41
Requirements for a global lidar system: spaceborne lidar with wall-to-wall coverage
Steven Hancock, Ciara McGrath, Christopher Lowe, et al.
Royal Society Open Science (2021) Vol. 8, Iss. 12
Open Access | Times Cited: 41
Supervised Segmentation of Ultra-High-Density Drone Lidar for Large-Area Mapping of Individual Trees
Martin Krůček, Kamil Král, K. C. Cushman, et al.
Remote Sensing (2020) Vol. 12, Iss. 19, pp. 3260-3260
Open Access | Times Cited: 40
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
Quantifying and correcting geolocation error in spaceborne LiDAR forest canopy observations using high spatial accuracy data: A Bayesian model approach
Elliot S. Shannon, Andrew O. Finley, Daniel J. Hayes, et al.
Environmetrics (2024) Vol. 35, Iss. 4
Open Access | Times Cited: 5
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