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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:

Importance of spatial predictor variable selection in machine learning applications – Moving from data reproduction to spatial prediction
Hanna Meyer, Christoph Reudenbach, Stephan Wöllauer, et al.
Ecological Modelling (2019) Vol. 411, pp. 108815-108815
Open Access | Times Cited: 330

Showing 1-25 of 330 citing articles:

Spatial validation reveals poor predictive performance of large-scale ecological mapping models
Pierre Ploton, Frédéric Mortier, Maxime Réjou‐Méchain, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 468
Global prevalence of non-perennial rivers and streams
Mathis Messager, Bernhard Lehner, Charlotte Cockburn, et al.
Nature (2021) Vol. 594, Iss. 7863, pp. 391-397
Closed Access | Times Cited: 442
Machine learning for digital soil mapping: Applications, challenges and suggested solutions
Alexandre M.J.‐C. Wadoux, Budiman Minasny, Alex B. McBratney
Earth-Science Reviews (2020) Vol. 210, pp. 103359-103359
Open Access | Times Cited: 407
Predicting into unknown space? Estimating the area of applicability of spatial prediction models
Hanna Meyer, Edzer Pebesma
Methods in Ecology and Evolution (2021) Vol. 12, Iss. 9, pp. 1620-1633
Open Access | Times Cited: 356
Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks
Janne Mäyrä, Sarita Keski‐Saari, Sonja Kivinen, et al.
Remote Sensing of Environment (2021) Vol. 256, pp. 112322-112322
Open Access | Times Cited: 190
Spatial cross-validation is not the right way to evaluate map accuracy
Alexandre M.J.‐C. Wadoux, G.B.M. Heuvelink, Sytze de Bruin, et al.
Ecological Modelling (2021) Vol. 457, pp. 109692-109692
Closed Access | Times Cited: 177
Urban flood modeling using deep-learning approaches in Seoul, South Korea
Xinxiang Lei, Wei Chen, Mahdi Panahi, et al.
Journal of Hydrology (2021) Vol. 601, pp. 126684-126684
Open Access | Times Cited: 160
Prospects and limitations of genomic offset in conservation management
Christian Rellstab, Benjamin Dauphin, Moisés Expósito‐Alonso
Evolutionary Applications (2021) Vol. 14, Iss. 5, pp. 1202-1212
Open Access | Times Cited: 129
Spatial flood susceptibility mapping using an explainable artificial intelligence (XAI) model
Biswajeet Pradhan, Saro Lee, Abhirup Dikshit, et al.
Geoscience Frontiers (2023) Vol. 14, Iss. 6, pp. 101625-101625
Open Access | Times Cited: 109
A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps
Arnan Araza, Sytze de Bruin, Martin Herold, et al.
Remote Sensing of Environment (2022) Vol. 272, pp. 112917-112917
Open Access | Times Cited: 82
Dealing with clustered samples for assessing map accuracy by cross-validation
Sytze de Bruin, D.J. Brus, G.B.M. Heuvelink, et al.
Ecological Informatics (2022) Vol. 69, pp. 101665-101665
Open Access | Times Cited: 72
Assessing and improving the transferability of current global spatial prediction models
Marvin Ludwig, Álvaro Moreno‐Martínez, Norbert Hölzel, et al.
Global Ecology and Biogeography (2023) Vol. 32, Iss. 3, pp. 356-368
Open Access | Times Cited: 54
Benthic habitat mapping: A review of three decades of mapping biological patterns on the seafloor
Benjamin Misiuk, Craig J. Brown
Estuarine Coastal and Shelf Science (2023) Vol. 296, pp. 108599-108599
Open Access | Times Cited: 46
Improving Forest Above-Ground Biomass Estimation by Integrating Individual Machine Learning Models
Mi Luo, Shoaib Ahmad Anees, Qiuyan Huang, et al.
Forests (2024) Vol. 15, Iss. 6, pp. 975-975
Open Access | Times Cited: 30
Heavy metals concentration in soils across the conterminous USA: Spatial prediction, model uncertainty, and influencing factors
Kabindra Adhikari, Marcelo Mancini, Zamir Libohova, et al.
The Science of The Total Environment (2024) Vol. 919, pp. 170972-170972
Open Access | Times Cited: 20
Crop Type Classification Using Fusion of Sentinel-1 and Sentinel-2 Data: Assessing the Impact of Feature Selection, Optical Data Availability, and Parcel Sizes on the Accuracies
Aiym Orynbaikyzy, Ursula Geßner, Benjamin Mack, et al.
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2779-2779
Open Access | Times Cited: 99
Continental-Scale Land Cover Mapping at 10 m Resolution Over Europe (ELC10)
Zander S. Venter, Markus A. K. Sydenham
Remote Sensing (2021) Vol. 13, Iss. 12, pp. 2301-2301
Open Access | Times Cited: 89
Spatial dependence between training and test sets: another pitfall of classification accuracy assessment in remote sensing
Nicolas Karasiak, Jean-François Dejoux, Claude Monteil, et al.
Machine Learning (2021) Vol. 111, Iss. 7, pp. 2715-2740
Open Access | Times Cited: 76
Machine Learning of Spatial Data
Behnam Nikparvar, Jean‐Claude Thill
ISPRS International Journal of Geo-Information (2021) Vol. 10, Iss. 9, pp. 600-600
Open Access | Times Cited: 71
Digital soil mapping and assessment for Australia and beyond: A propitious future
Ross Searle, Alex B. McBratney, Mike Grundy, et al.
Geoderma Regional (2021) Vol. 24, pp. e00359-e00359
Open Access | Times Cited: 66
Mapping peat thickness and carbon stocks of the central Congo Basin using field data
Bart Crezee, Greta C. Dargie, Corneille E. N. Ewango, et al.
Nature Geoscience (2022) Vol. 15, Iss. 8, pp. 639-644
Open Access | Times Cited: 61
Nearest neighbour distance matching Leave‐One‐Out Cross‐Validation for map validation
Carles Milà, Jorge Mateu, Edzer Pebesma, et al.
Methods in Ecology and Evolution (2022) Vol. 13, Iss. 6, pp. 1304-1316
Open Access | Times Cited: 52
Using explainable machine learning to understand how urban form shapes sustainable mobility
Felix Wagner, Nikola Milojevic-Dupont, Lukas Franken, et al.
Transportation Research Part D Transport and Environment (2022) Vol. 111, pp. 103442-103442
Closed Access | Times Cited: 49
A Forest of Forests: A Spatially Weighted and Computationally Efficient Formulation of Geographical Random Forests
Stefanos Georganos, Stamatis Kalogirou
ISPRS International Journal of Geo-Information (2022) Vol. 11, Iss. 9, pp. 471-471
Open Access | Times Cited: 46
Change Detection Techniques with Synthetic Aperture Radar Images: Experiments with Random Forests and Sentinel-1 Observations
Pietro Mastro, Guido Masiello, Carmine Serio, et al.
Remote Sensing (2022) Vol. 14, Iss. 14, pp. 3323-3323
Open Access | Times Cited: 45
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