Markus P. Eichhorn

1.9k citations
49 papers · 1.5k · 1 hit paper · h-index 18

Impact in

Papers in

Markus P. Eichhorn

46 papers receiving 1.4k citations

Markus P. Eichhorn's Hit Papers

Status, advancements and prospects of deep learning methods applied in forest studies 2024 · 59 citations
590+1Years since publication1020304050

Peers

Markus P. Eichhorn
Comparison fields: 5 of 119
  • Forestry 229
  • Nature and Landscape Conservation 508
  • Environmental Engineering 388
  • Geology 106
  • Ecological Modeling 79
Replace Jeremy Lindsell with:
Jeremy Lindsell United Kingdom
Peter Annighöfer Germany
Matteo Garbarino Italy
Fernando Montes Spain
Francesco Chianucci Italy
Izak P. J. Smit South Africa
Cédric Vermeulen Belgium
Andrew B. Davies United States
Karen A. Harper Canada
Greg C. Liknes United States
Markus P. Eichhorn relative to Jeremy Lindsell United Kingdom Jeremy Lindsell's profile →
Citations per field
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Citations per year

Countries citing papers authored by Markus P. Eichhorn

Since Specialization
Citations

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

Fields of papers citing papers by Markus P. Eichhorn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus P. Eichhorn. 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 Markus P. Eichhorn. The network helps show where Markus P. Eichhorn may publish in the future.

Co-authors

The 25 scholars most cited alongside Markus P. Eichhorn, 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 Markus P. Eichhorn Line = papers co-authored together Markus P. Eichhorn links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006327
2 2015129
3 2021127
4 200794
5 201966
6 201061
7
Status, advancements and prospects of deep learning methods applied in forest studies
Hit paper breakdown →
202459
8 201954
9 202239
10 201738
11 201635
12 200834
13 202029
14 201328
15 200727
16 202025
17 201322
18 202120
19 201817
20 201417

About Markus P. Eichhorn

Markus P. Eichhorn is a scholar working on Nature and Landscape Conservation, Ecology, Evolution, Behavior and Systematics, Ecology, Environmental Engineering and Global and Planetary Change, having authored 49 papers that have together received 1.5k indexed citations. Recurring topics across this work include Ecology and Vegetation Dynamics Studies (15 papers), Plant and animal studies (14 papers), Remote Sensing and LiDAR Applications (10 papers), Wildlife Ecology and Conservation (7 papers), Plant Parasitism and Resistance (6 papers), Forest ecology and management (6 papers), Forest Ecology and Biodiversity Studies (5 papers) and Forest Management and Policy (5 papers). The work is most often cited by research in Forestry (229 citations), Nature and Landscape Conservation (508 citations), Environmental Engineering (388 citations), Geology (106 citations) and Ecological Modeling (79 citations). Markus P. Eichhorn has collaborated with scholars based in United Kingdom, Ireland and China. Frequent co-authors include Martin J. Smith, Francis Gilbert, Olivia Norfolk, Ting Yun, Mark Griffiths, Kate C. Baker, Félix Herzog, Fabien Liagre, Christian Dupraz and M. Mayus. Their work appears in journals such as Biotropica, Agricultural and Forest Meteorology, Diversity and Distributions, Remote Sensing and Insect Conservation and Diversity.

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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