Erick Mata‐Montero

755 citations
32 papers · 577 · h-index 11

Impact in

Papers in

Erick Mata‐Montero

30 papers receiving 563 citations

Peers

Erick Mata‐Montero
Comparison fields: 5 of 80
  • Ecological Modeling 137
  • Plant Science 285
  • Analytical Chemistry 61
  • Ecology 121
  • Ecology, Evolution, Behavior and Systematics 77
Replace Jonathan Y. Clark with:
Jonathan Y. Clark United Kingdom
Mauro dos Santos de Arruda Brazil
Ziyuan Hao China
Youjie Zhao China
Julien Champ France
James Cope United Kingdom
Willem-Pier Vellinga France
Nathalie Wuyts Belgium
Sue Han Lee Malaysia
Dewei Wu China
Erick Mata‐Montero relative to Jonathan Y. Clark United Kingdom Jonathan Y. Clark's profile →
Citations per field
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Citations per year

Countries citing papers authored by Erick Mata‐Montero

Since Specialization
Citations

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

Fields of papers citing papers by Erick Mata‐Montero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erick Mata‐Montero. 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 Erick Mata‐Montero. The network helps show where Erick Mata‐Montero may publish in the future.

Co-authors

The 18 scholars most cited alongside Erick Mata‐Montero, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Erick Mata‐Montero Line = papers co-authored together Erick Mata‐Montero links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017180
2 202096
3 201952
4 202039
5 201636
6 202031
7 201819
8 202217
9 201815
10 201812
11 201811
12 201610
13 20159
14 19918
15 20178
16 20196
17 20185
18 20204
19 20183
20
Domain Adaptation in the Context of Herbarium Collections: A submission to PlantCLEF 2020.
20202

About Erick Mata‐Montero

Erick Mata‐Montero is a scholar working on Plant Science, Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Organic Chemistry and Environmental Engineering, having authored 32 papers that have together received 577 indexed citations. Recurring topics across this work include Smart Agriculture and AI (13 papers), Species Distribution and Climate Change (9 papers), Plant and animal studies (7 papers), Wood and Agarwood Research (6 papers), Remote Sensing and LiDAR Applications (6 papers), Data Visualization and Analytics (4 papers), Spectroscopy and Chemometric Analyses (4 papers) and Remote Sensing in Agriculture (3 papers). The work is most often cited by research in Ecological Modeling (137 citations), Plant Science (285 citations), Analytical Chemistry (61 citations), Ecology (121 citations) and Ecology, Evolution, Behavior and Systematics (77 citations). Erick Mata‐Montero has collaborated with scholars based in Costa Rica, France and United States. Frequent co-authors include Hervé Goëau, Pierre Bonnet, Alexis Joly, Julien Champ, Juan Carlos Valverde, Dagoberto Arias‐Aguilar, Susan J. Mazer, Titouan Lorieul, Elizabeth R. Ellwood and Patrick W. Sweeney. Their work appears in journals such as Applications in Plant Sciences, Frontiers in Plant Science, PeerJ Computer Science, BMC Evolutionary Biology and Networks.

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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