F.J.A. van Ruitenbeek

4.4k citations
62 papers · 3.6k indexed · 2 hit papers · h-index 25

F.J.A. van Ruitenbeek

59 papers receiving 3.5k citations

Hit Papers

Multi- and hyperspectral geologic remote sensing: A review201120262016202120112011250500750

Peers

F.J.A. van Ruitenbeek
Comparison fields: 5 of 105
  • Artificial Intelligence 2.4k
  • Media Technology 2.1k
  • Environmental Engineering 917
  • Mechanical Engineering 588
  • Ecology 377
Replace H.M.A. van der Werff with:
H.M.A. van der Werff Netherlands
C.A. Hecker Netherlands
M. van der Meijde Netherlands
T. Woldai South Africa
Fred A. Kruse United States
Thomas Cudahy Australia
J.B. de Smeth Netherlands
M. Noomen Netherlands
Carlos Roberto de Souza Filho Brazil
Keith E. Livo United States
F.J.A. van Ruitenbeek relative to H.M.A. van der Werff Netherlands H.M.A. van der Werff's profile →
Citations per field
00.5×1.5×
H.M.A. van der Werff · 1×
Citations per year

Countries citing papers authored by F.J.A. van Ruitenbeek

Since Specialization
Citations

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

Fields of papers citing papers by F.J.A. van Ruitenbeek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F.J.A. van Ruitenbeek. 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 F.J.A. van Ruitenbeek. The network helps show where F.J.A. van Ruitenbeek may publish in the future.

Co-authorship network of co-authors of F.J.A. van Ruitenbeek

This figure shows the co-authorship network connecting the top 25 collaborators of F.J.A. van Ruitenbeek. A scholar is included among the top collaborators of F.J.A. van Ruitenbeek 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 F.J.A. van Ruitenbeek. F.J.A. van Ruitenbeek 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
#WorkIndexed citations
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5 20
6 8
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11 29
12 50
13 0
14 24
15 54
16 43
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Hyperspectral image mapping by automatic color coding of absorption features : abstract
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18 126
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Geologic mapping on mars by segmentation of omega data
3
20 3

About F.J.A. van Ruitenbeek

F.J.A. van Ruitenbeek is a scholar working on Media Technology, Artificial Intelligence and Environmental Engineering, having authored 62 papers that have together received 3.6k indexed citations. Recurring topics across this work include Geochemistry and Geologic Mapping (57 papers), Remote-Sensing Image Classification (35 papers) and Mineral Processing and Grinding (12 papers). The work is most often cited by research in Media Technology (2.1k citations), Artificial Intelligence (2.4k citations) and Environmental Engineering (917 citations). F.J.A. van Ruitenbeek has collaborated with scholars based in Netherlands, South Africa and Australia. Frequent co-authors include F.D. van der Meer, H.M.A. van der Werff, C.A. Hecker, M. van der Meijde, Emmanuel John M. Carranza, T. Woldai, J.B. de Smeth, M. Noomen, W.H. Bakker and W.T. Bakker. Their work appears in journals such as Remote Sensing of Environment, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

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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