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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:

Comparing spatial regression to random forests for large environmental data sets
Eric W. Fox, Jay M. Ver Hoef, Anthony R. Olsen
PLoS ONE (2020) Vol. 15, Iss. 3, pp. e0229509-e0229509
Open Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Global relationships in tree functional traits
Daniel S. Maynard, Lalasia Bialic‐Murphy, Constantin M. Zohner, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 80
Machine learning and geostatistical approaches for estimating aboveground biomass in Chinese subtropical forests
Huiyi Su, Wenjuan Shen, Jingrui Wang, et al.
Forest Ecosystems (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 82
Comparing the prediction performance, uncertainty quantification and extrapolation potential of regression kriging and random forest while accounting for soil measurement errors
Bertin Takoutsing, G.B.M. Heuvelink
Geoderma (2022) Vol. 428, pp. 116192-116192
Open Access | Times Cited: 50
Predicting Optical Water Quality Indicators from Remote Sensing Using Machine Learning Algorithms in Tropical Highlands of Ethiopia
Elias S. Leggesse, Fasikaw A. Zimale, Dagnenet Sultan, et al.
Hydrology (2023) Vol. 10, Iss. 5, pp. 110-110
Open Access | Times Cited: 35
Spatiotemporal modelling of $$\hbox {PM}_{2.5}$$ concentrations in Lombardy (Italy): a comparative study
Philipp Otto, Alessandro Fusta Moro, Jacopo Rodeschini, et al.
Environmental and Ecological Statistics (2024) Vol. 31, Iss. 2, pp. 245-272
Open Access | Times Cited: 13
Random Forests for Spatially Dependent Data
Arkajyoti Saha, Sumanta Basu, Abhirup Datta
Journal of the American Statistical Association (2021) Vol. 118, Iss. 541, pp. 665-683
Open Access | Times Cited: 55
Global patterns and key drivers of stream nitrogen concentration: A machine learning approach
Razi Sheikholeslami, Jim W. Hall
The Science of The Total Environment (2023) Vol. 868, pp. 161623-161623
Open Access | Times Cited: 19
Using social media data and machine learning to map recreational ecosystem services
Charity Nyelele, Catherine Keske, Min Gon Chung, et al.
Ecological Indicators (2023) Vol. 154, pp. 110606-110606
Open Access | Times Cited: 17
Unveiling greenwashing in Colombian manufacturing: A machine learning approach
Carolina Henao-Rodríguez, Jenny-Paola Lis-Gutiérrez, Harold Delfín Angulo Bustinza
Research in Globalization (2024) Vol. 8, pp. 100196-100196
Open Access | Times Cited: 7
Mapping and modeling the impact of climate change on recreational ecosystem services using machine learning and big data
Kyle Manley, Benis N. Egoh
Environmental Research Letters (2022) Vol. 17, Iss. 5, pp. 054025-054025
Open Access | Times Cited: 24
Continuous‐surface geographic assignment of migratory animals using strontium isotopes: A case study with monarch butterflies
Megan S. Reich, D. T. Tyler Flockhart, D. Ryan Norris, et al.
Methods in Ecology and Evolution (2021) Vol. 12, Iss. 12, pp. 2445-2457
Open Access | Times Cited: 32
Spatial machine-learning model diagnostics: a model-agnostic distance-based approach
Alexander Brenning
International Journal of Geographical Information Science (2022) Vol. 37, Iss. 3, pp. 584-606
Open Access | Times Cited: 20
Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest
Shashika Himandi Gardeye Lamahewage, Chandi Witharana, Rachel Riemann, et al.
Research Square (Research Square) (2025)
Closed Access
Spatial autocorrelation in machine learning for modelling soil organic carbon
Alexander Kmoch, Chris Harrison, Jeong-Hwan Choi, et al.
Ecological Informatics (2025), pp. 103057-103057
Open Access
A novel high-resolution gridded precipitation dataset for Peruvian and Ecuadorian watersheds – development and hydrological evaluation
Carlos Antonio Fernández-Palomino, Fred F. Hattermann, Valentina Krysanova, et al.
Journal of Hydrometeorology (2021)
Open Access | Times Cited: 23
Mapping the groundwater memory across Ireland: A step towards a groundwater drought susceptibility assessment
Philip Schuler, Joan Campanyà, Henning Moe, et al.
Journal of Hydrology (2022) Vol. 612, pp. 128277-128277
Open Access | Times Cited: 17
TRANCO: Thermo radiometric normalization of crop observations
Juanma Cintas, B. Franch, Kristof Van-Tricht, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 118, pp. 103283-103283
Open Access | Times Cited: 10
Reducing the Uncertainty of Radiata Pine Site Index Maps Using an Spatial Ensemble of Machine Learning Models
Gonzalo Gavilán-Acuña, Guillermo F. Olmedo, Pablo Mena-Quijada, et al.
Forests (2021) Vol. 12, Iss. 1, pp. 77-77
Open Access | Times Cited: 21
Soil quality estimation using environmental covariates and predictive models: an example from tropical soils of Nigeria
Isong Abraham Isong, Kingsley John, Paul B. Okon, et al.
Ecological Processes (2022) Vol. 11, Iss. 1
Open Access | Times Cited: 14
Assessing the Efficiency of a Random Forest Regression Model for Estimating Water Quality Indicators
Maryam Zavareh, Viviana Maggioni, Xinxuan Zhang
Meteorology Hydrology and Water Management (2024)
Open Access | Times Cited: 2
Unravelling the impact of soil data quality on species distribution models of temperate forest woody plants
Francesco Rota, Daniel Scherrer, Ariel Bergamini, et al.
The Science of The Total Environment (2024) Vol. 944, pp. 173719-173719
Open Access | Times Cited: 2
Predicting species abundance using machine learning approach: a comparative assessment of random forest spatial variants and performance metrics
Ciza Arsène Mushagalusa, Adandé Belarmain Fandohan, Romain Glèlè Kakaï
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 4, pp. 5145-5171
Closed Access | Times Cited: 2
Construction and evaluation of a liver cancer risk prediction model based on machine learning
Yingying Wang, Wan-Xia Yang, Qiajun Du, et al.
World Journal of Gastrointestinal Oncology (2024) Vol. 16, Iss. 9, pp. 3839-3850
Open Access | Times Cited: 2
Utilizing Machine Learning and Geospatial Techniques to Evaluate Post-Fire Vegetation Recovery in Mediterranean Forest Ecosystem: Tenira, Algeria
Ali Ahmed Souane, Abbas Khurram, Hui Huang, et al.
Forests (2024) Vol. 16, Iss. 1, pp. 53-53
Open Access | Times Cited: 2
A new statistical downscaling approach for short‐term forecasting of summer air temperatures through a fusion of deep learning and spatial interpolation
Dongjin Cho, Jungho Im, Sihun Jung
Quarterly Journal of the Royal Meteorological Society (2023) Vol. 150, Iss. 760, pp. 1222-1242
Closed Access | Times Cited: 6
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