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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:

Effects of temporally external auxiliary data on model-based inference
Zhengyang Hou, Qing Xu, Ronald E. McRoberts, et al.
Remote Sensing of Environment (2017) Vol. 198, pp. 150-159
Closed Access | Times Cited: 20

Showing 20 citing articles:

Estimating Forest Volume and Biomass and Their Changes Using Random Forests and Remotely Sensed Data
Jéssica Esteban, Ronald E. McRoberts, Alfredo Fernández-Landa, et al.
Remote Sensing (2019) Vol. 11, Iss. 16, pp. 1944-1944
Open Access | Times Cited: 88
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
Quantification of uncertainty in aboveground biomass estimates derived from small-footprint airborne LiDAR
Qing Xu, Albert Man, Mark Fredrickson, et al.
Remote Sensing of Environment (2018) Vol. 216, pp. 514-528
Open Access | Times Cited: 50
Assessing components of the model-based mean square error estimator for remote sensing assisted forest applications
Ronald E. McRoberts, Erik Næsset, Terje Gobakken, et al.
Canadian Journal of Forest Research (2018) Vol. 48, Iss. 6, pp. 642-649
Closed Access | Times Cited: 49
Estimation of tropical forest aboveground biomass in Nepal using multiple remotely sensed data and deep learning
Parvez Rana, Sorin C. Popescu, Anne Tolvanen, et al.
International Journal of Remote Sensing (2023) Vol. 44, Iss. 17, pp. 5147-5171
Open Access | Times Cited: 14
Three-phase hierarchical model-based and hybrid inference
Svetlana Saarela, Petri Varvia, Lauri Korhonen, et al.
MethodsX (2023) Vol. 11, pp. 102321-102321
Open Access | Times Cited: 10
Remote sensing-assisted data assimilation and simultaneous inference for forest inventory
Zhengyang Hou, Lauri Mehtätalo, Ronald E. McRoberts, et al.
Remote Sensing of Environment (2019) Vol. 234, pp. 111431-111431
Closed Access | Times Cited: 24
Estimating the Forest Carbon Storage of Chongming Eco-Island, China, Using Multisource Remotely Sensed Data
Chao Zhang, Tongtong Song, Runhe Shi, et al.
Remote Sensing (2023) Vol. 15, Iss. 6, pp. 1575-1575
Open Access | Times Cited: 8
On the model-assisted regression estimators using remotely sensed auxiliary data
Ronald E. McRoberts, Erik Næsset, Juha Heikkinen, et al.
Remote Sensing of Environment (2022) Vol. 281, pp. 113168-113168
Open Access | Times Cited: 12
Updating annual state- and county-level forest inventory estimates with data assimilation and FIA data
Zhengyang Hou, Grant M. Domke, Matthew B. Russell, et al.
Forest Ecology and Management (2020) Vol. 483, pp. 118777-118777
Open Access | Times Cited: 18
How much can natural resource inventory benefit from finer resolution auxiliary data?
Zhengyang Hou, Ronald E. McRoberts, Göran Ståhl, et al.
Remote Sensing of Environment (2018) Vol. 209, pp. 31-40
Closed Access | Times Cited: 15
Increasing Precision for French Forest Inventory Estimates using the k-NN Technique with Optical and Photogrammetric Data and Model-Assisted Estimators
Dinesh Babu Irulappa-Pillai-Vijayakumar, Jean-Pierre Renaud, François Morneau, et al.
Remote Sensing (2019) Vol. 11, Iss. 8, pp. 991-991
Open Access | Times Cited: 14
A new small area estimation algorithm to balance between statistical precision and scale
Cédric Vega, Jean-Pierre Renaud, Ankit Sagar, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 97, pp. 102303-102303
Open Access | Times Cited: 12
Multisource forest inventories: A model-based approach using k-NN to reconcile forest attributes statistics and map products
Ankit Sagar, Cédric Vega, Olivier Bouriaud, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 192, pp. 175-188
Open Access | Times Cited: 8
A Model-Based Volume Estimator that Accounts for Both Land Cover Misclassification and Model Prediction Uncertainty
Jéssica Esteban, Ronald E. McRoberts, Alfredo Fernández-Landa, et al.
Remote Sensing (2020) Vol. 12, Iss. 20, pp. 3360-3360
Open Access | Times Cited: 11
Leveraging remotely sensed non-wall-to-wall data for wall-to-wall upscaling in forest inventory
Fangting Chen, Zhengyang Hou, Svetlana Saarela, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 119, pp. 103314-103314
Open Access | Times Cited: 3
Generalizing systematic adaptive cluster sampling for forest ecosystem inventory
Qing Xu, Göran Ståhl, Ronald E. McRoberts, et al.
Forest Ecology and Management (2021) Vol. 489, pp. 119051-119051
Closed Access | Times Cited: 7
Estimating forest attributes in airborne laser scanning based inventory using calibrated predictions from external models
Ana de Lera Garrido, Terje Gobakken, Hans Ole Ørka, et al.
Silva Fennica (2022) Vol. 56, Iss. 2
Open Access | Times Cited: 2
Multi-sensor approach for evaluating forest resources in large areas
Jesica Esteban Cava
(2020)
Open Access
A new method for modelling precipitation variability in relation to climate change
Sadia Qamar, Zulfiqar Ali, Saad Sh. Sammen
Journal of Water and Climate Change (2022) Vol. 14, Iss. 1, pp. 289-304
Open Access
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