José Padarian

7.8k total citations · 4 hit papers
50 papers, 3.0k citations indexed

About

José Padarian is a scholar working on Environmental Engineering, Soil Science and Artificial Intelligence. According to data from OpenAlex, José Padarian has authored 50 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Environmental Engineering, 18 papers in Soil Science and 12 papers in Artificial Intelligence. Recurrent topics in José Padarian's work include Soil Geostatistics and Mapping (29 papers), Soil Carbon and Nitrogen Dynamics (15 papers) and Soil and Unsaturated Flow (10 papers). José Padarian is often cited by papers focused on Soil Geostatistics and Mapping (29 papers), Soil Carbon and Nitrogen Dynamics (15 papers) and Soil and Unsaturated Flow (10 papers). José Padarian collaborates with scholars based in Australia, United Kingdom and United States. José Padarian's co-authors include Budiman Minasny, Alex B. McBratney, Wartini Ng, Ignacio Fuentes, Maryam Montazerolghaem, Richard Ferguson, W. Vervoort, Uta Stockmann, Alexandre M.J.‐C. Wadoux and Damien J. Field and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and PLoS ONE.

In The Last Decade

José Padarian

45 papers receiving 2.9k citations

Hit Papers

Pedotransfer Functions in Earth System Science: Challenge... 2017 2026 2020 2023 2017 2019 2018 2020 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Pedotransfer Functions in Earth System Science: Challenges and Perspectives
    2017 377 citations Budiman Minasny, José Padarian et al. profile →
  2. Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra
    2019 331 citations Wartini Ng, Budiman Minasny et al. Geoderma profile →
  3. Using deep learning to predict soil properties from regional spectral data
    2018 328 citations José Padarian, Budiman Minasny et al. profile →
  4. Machine learning and soil sciences: a review aided by machine learning tools
    2020 306 citations José Padarian, Budiman Minasny et al. SOIL profile →

Peers

José Padarian
Cristine L.S. Morgan United States
Karsten Schmidt Germany
Mogens Humlekrog Greve Denmark
Gabriele Buttafuocò Italy
Annamaria Castrignanò Italy
Philippe Lagacherie France
Thomas F. A. Bishop Australia
D.J.J. Walvoort Netherlands
Pierre Roudier New Zealand
Jianli Ding China
Cristine L.S. Morgan United States
José Padarian
Citations per year, relative to José Padarian José Padarian (= 1×) peers Cristine L.S. Morgan

Countries citing papers authored by José Padarian

Since Specialization
Citations

This map shows the geographic impact of José Padarian's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by José Padarian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José Padarian more than expected).

Fields of papers citing papers by José Padarian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Padarian. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by José Padarian. The network helps show where José Padarian may publish in the future.

Co-authorship network of co-authors of José Padarian

This figure shows the co-authorship network connecting the top 25 collaborators of José Padarian. A scholar is included among the top collaborators of José Padarian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with José Padarian. José Padarian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Francos, Nicolas, Amin Sharififar, José Padarian, et al.. (2025). The global pedogenon map: Combining and spatialising the factors of soil formation. Geoderma. 460. 117462–117462. 2 indexed citations
3.
Minasny, Budiman, José Padarian, Federico Maggi, et al.. (2025). Digital mapping of peat thickness and carbon stock of global peatlands. CATENA. 258. 109243–109243. 1 indexed citations
4.
McBratney, Alex B., et al.. (2025). The Evolution of (Digital) Pedology – drawing from the past, adapting to the future. Geoderma. 463. 117588–117588.
5.
Padarian, José, et al.. (2025). Using Monte Carlo conformal prediction to evaluate the uncertainty of deep-learning soil spectral models. SOIL. 11(2). 553–563. 3 indexed citations
6.
Ng, Wartini, et al.. (2025). Creating soil districts for Australia based on pedogenon mapping. Geoderma. 454. 117164–117164. 6 indexed citations
7.
Ng, Wartini, José Padarian, Tom O’Donoghue, et al.. (2024). Estimating surrogates, utility graphs and indicator sets for soil capacity and security assessments using legacy data. Soil Research. 62(2). 6 indexed citations
8.
Minasny, Budiman, Alex B. McBratney, Dominique Arrouays, et al.. (2023). Soil Carbon Sequestration: Much More Than a Climate Solution. Environmental Science & Technology. 57(48). 19094–19098. 27 indexed citations
9.
Padarian, José, Budiman Minasny, Alex B. McBratney, & Pete Smith. (2021). Additional soil organic carbon storage potential in global croplands. 5 indexed citations
10.
Padarian, José, Budiman Minasny, & Alex B. McBratney. (2020). Machine learning and soil sciences: a review aided by machine learning tools. SOIL. 6(1). 35–52. 306 indexed citations breakdown →
11.
Padarian, José & Alex B. McBratney. (2020). A new model for intra- and inter-institutional soil data sharing. SOIL. 6(1). 89–94. 9 indexed citations
12.
Padarian, José, Alex B. McBratney, & Budiman Minasny. (2020). Game theory interpretation of digital soil mapping convolutional neural networks. SOIL. 6(2). 389–397. 91 indexed citations
13.
Padarian, José & Marco Pfeiffer. (2019). CHLSOC: The Chilean Soil Organic Carbon database. OSF Preprints (OSF Preprints). 1 indexed citations
14.
Wadoux, Alexandre M.J.‐C., José Padarian, & Budiman Minasny. (2019). Multi-source data integration for soil mapping using deep learning. SOIL. 5(1). 107–119. 94 indexed citations
15.
Padarian, José & Ignacio Fuentes. (2019). Word embeddings for application in geosciences: development, evaluation, and examples of soil-related concepts. SOIL. 5(2). 177–187. 16 indexed citations
16.
Padarian, José, Budiman Minasny, & Alex B. McBratney. (2019). Using deep learning for digital soil mapping. SOIL. 5(1). 79–89. 183 indexed citations
17.
Padarian, José, Budiman Minasny, & Alex B. McBratney. (2019). Machine learning and soil sciences: A review aided by machine learning tools. 12 indexed citations
18.
Huang, Jingyi, Budiman Minasny, Alex B. McBratney, José Padarian, & John Triantafilis. (2017). The location- and scale- specific correlation between temperature and soil carbon sequestration across the globe. The Science of The Total Environment. 615. 540–548. 32 indexed citations
19.
Chen, Yizhao, Jianlong Li, Weimin Ju, et al.. (2017). Quantitative assessments of water-use efficiency in Temperate Eurasian Steppe along an aridity gradient. PLoS ONE. 12(7). e0179875–e0179875. 29 indexed citations
20.
Padarian, José, Budiman Minasny, Alex B. McBratney, & Neal Dalgliesh. (2014). Ensemble Model to Predict the Available Water Capacity of Australian Soils. 618–618. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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