Robert Minařík

676 total citations
22 papers, 464 citations indexed

About

Robert Minařík is a scholar working on Ecology, Environmental Engineering and Soil Science. According to data from OpenAlex, Robert Minařík has authored 22 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Ecology, 13 papers in Environmental Engineering and 6 papers in Soil Science. Recurrent topics in Robert Minařík's work include Remote Sensing and LiDAR Applications (8 papers), Soil Geostatistics and Mapping (6 papers) and Remote Sensing in Agriculture (5 papers). Robert Minařík is often cited by papers focused on Remote Sensing and LiDAR Applications (8 papers), Soil Geostatistics and Mapping (6 papers) and Remote Sensing in Agriculture (5 papers). Robert Minařík collaborates with scholars based in Czechia, Netherlands and Slovakia. Robert Minařík's co-authors include Jakub Langhammer, Daniel Žížala, Tereza Zádorová, Anna Juřicová, Jan Hanuš, Jan Skála, Bohumír Jánský, Vít Penížek, Leandro Parente and Tomislav Hengl and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Environmental Management.

In The Last Decade

Robert Minařík

20 papers receiving 446 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Robert Minařík Czechia 10 312 243 100 99 65 22 464
Jasmine Muir Australia 11 297 1.0× 276 1.1× 85 0.8× 123 1.2× 17 0.3× 15 497
Camile Söthe Brazil 10 394 1.3× 431 1.8× 69 0.7× 186 1.9× 37 0.6× 23 658
Shaban Shataee Iran 14 364 1.2× 360 1.5× 44 0.4× 193 1.9× 28 0.4× 47 608
R. Denham Australia 11 228 0.7× 272 1.1× 83 0.8× 154 1.6× 12 0.2× 18 475
Lili Lin China 11 281 0.9× 243 1.0× 41 0.4× 149 1.5× 13 0.2× 40 467
Annett Frick Germany 11 366 1.2× 412 1.7× 39 0.4× 252 2.5× 15 0.2× 23 691
F. G. Gonçalves Brazil 13 315 1.0× 182 0.7× 73 0.7× 143 1.4× 14 0.2× 38 523
Lorenzo Bottai Italy 14 269 0.9× 291 1.2× 91 0.9× 243 2.5× 15 0.2× 33 602
Pierre Karrasch Germany 7 132 0.4× 95 0.4× 90 0.9× 64 0.6× 28 0.4× 20 352
Polyanna da Conceição Bispo Brazil 13 190 0.6× 198 0.8× 48 0.5× 153 1.5× 20 0.3× 54 493

Countries citing papers authored by Robert Minařík

Since Specialization
Citations

This map shows the geographic impact of Robert Minařík'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 Robert Minařík with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Minařík more than expected).

Fields of papers citing papers by Robert Minařík

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert Minařík. 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 Robert Minařík. The network helps show where Robert Minařík may publish in the future.

Co-authorship network of co-authors of Robert Minařík

This figure shows the co-authorship network connecting the top 25 collaborators of Robert Minařík. A scholar is included among the top collaborators of Robert Minařík 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 Robert Minařík. Robert Minařík 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.
Skála, Jan, Daniel Žížala, & Robert Minařík. (2025). Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland. Journal of Environmental Management. 380. 125035–125035.
2.
Schneider, Florian, et al.. (2025). Time series of Landsat-based bimonthly and annual spectral indices for continental Europe for 2000–2022. Earth system science data. 17(2). 741–772. 2 indexed citations
3.
Safanelli, José Lucas, Tomislav Hengl, Leandro Parente, et al.. (2025). Open Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement. PLoS ONE. 20(1). e0296545–e0296545. 7 indexed citations
4.
5.
Juřicová, Anna, Florian Wilken, Tomáš Chuman, et al.. (2024). Tillage erosion as an underestimated driver of carbon dynamics. Soil and Tillage Research. 245. 106287–106287. 4 indexed citations
6.
7.
Žížala, Daniel, Jan Skála, Anna Juřicová, et al.. (2024). Soil sampling design matters - Enhancing the efficiency of digital soil mapping at the field scale. Geoderma Regional. 39. e00874–e00874. 3 indexed citations
8.
Maxwell, Tania L., Tomislav Hengl, Leandro Parente, et al.. (2023). Global mangrove soil organic carbon stocks dataset at 30 m resolution for the year 2020 based on spatiotemporal predictive machine learning. Data in Brief. 50. 109621–109621. 8 indexed citations
9.
Žížala, Daniel, Robert Minařík, Jan Skála, et al.. (2022). High-resolution agriculture soil property maps from digital soil mapping methods, Czech Republic. CATENA. 212. 106024–106024. 56 indexed citations
10.
Langhammer, Jakub, et al.. (2021). Mapping the Groundwater Level and Soil Moisture of a Montane Peat Bog Using UAV Monitoring and Machine Learning. Remote Sensing. 13(5). 907–907. 28 indexed citations
11.
Žížala, Daniel, Robert Minařík, Anna Juřicová, et al.. (2021). High-Resolution Soil Property Maps from Digital Soil Mapping Methods, Czech Republic. SSRN Electronic Journal. 3 indexed citations
12.
Minařík, Robert, et al.. (2021). Detection of Bark Beetle Disturbance at Tree Level Using UAS Multispectral Imagery and Deep Learning. Remote Sensing. 13(23). 4768–4768. 35 indexed citations
13.
Minařík, Robert, Daniel Žížala, & Anna Juřicová. (2020). Creation of detailed soil properties maps of the Czech Republic based on national legacy data and digital soil mapping. 1 indexed citations
14.
Minařík, Robert, et al.. (2020). Automatic Tree Crown Extraction from UAS Multispectral Imagery for the Detection of Bark Beetle Disturbance in Mixed Forests. Remote Sensing. 12(24). 4081–4081. 31 indexed citations
15.
Minařík, Robert, Jakub Langhammer, & Jan Hanuš. (2019). Radiometric and Atmospheric Corrections of Multispectral μMCA Camera for UAV Spectroscopy. Remote Sensing. 11(20). 2428–2428. 28 indexed citations
16.
Žížala, Daniel, Robert Minařík, & Tereza Zádorová. (2019). Soil Organic Carbon Mapping Using Multispectral Remote Sensing Data: Prediction Ability of Data with Different Spatial and Spectral Resolutions. Remote Sensing. 11(24). 2947–2947. 99 indexed citations
17.
Minařík, Robert & Jakub Langhammer. (2019). RAPID RADIOMETRIC CALIBRATION OF MULTIPLE CAMERA ARRAY USING IN-SITU DATA FOR UAV MULTISPECTRAL PHOTOGRAMMETRY. SHILAP Revista de lepidopterología. XLII-2/W17. 209–215. 3 indexed citations
18.
Žížala, Daniel, et al.. (2018). Mapping soil degradation using remote sensing data and ancillary data: South-East Moravia, Czech Republic. European Journal of Remote Sensing. 52(sup1). 108–122. 40 indexed citations
19.
Minařík, Robert & Jakub Langhammer. (2016). USE OF A MULTISPECTRAL UAV PHOTOGRAMMETRY FOR DETECTION AND TRACKING OF FOREST DISTURBANCE DYNAMICS. SHILAP Revista de lepidopterología. XLI-B8. 711–718. 43 indexed citations
20.
Minařík, Robert & Jakub Langhammer. (2016). USE OF A MULTISPECTRAL UAV PHOTOGRAMMETRY FOR DETECTION AND TRACKING OF FOREST DISTURBANCE DYNAMICS. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences. XLI-B8. 711–718. 34 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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