Kim Ely

45 papers receiving 959 citations

Kim Ely's Hit Papers

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression 2021 · 159 citations
1590+1+3Years since publication50100150

Peers

Kim Ely
Comparison fields: 5 of 56
  • Ecology 428
  • Global and Planetary Change 339
  • Analytical Chemistry 145
  • Nature and Landscape Conservation 54
  • Atmospheric Science 53
Replace Kenneth Davidson with:
Kenneth Davidson United States
Dylan N. Dillaway United States
Julien Lamour United States
Flávia Machado Durgante Brazil
Jia Jin Japan
Shan Kothari Canada
Atsuhiro Iio Japan
Christopher M. Montes United States
M. Méthy France
Rafael Sánchez‐Cuesta Spain
Kim Ely relative to Kenneth Davidson United States Kenneth Davidson's profile →
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Countries citing papers authored by Kim Ely

Since Specialization
Citations

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

Fields of papers citing papers by Kim Ely

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression
Hit paper breakdown →
2021159
2 2019123
3 201985
4 201784
5 201984
6 201967
7 202142
8 201841
9 202131
10 202129
11 202227
12 202323
13 202219
14 202218
15 201916
16 202116
17 202115
18 202215
19 202111
20 202110

About Kim Ely

Kim Ely is a scholar working on Global and Planetary Change, Atmospheric Science, Ecology, Environmental Engineering and Information Systems, having authored 50 papers that have together received 966 indexed citations. Recurring topics across this work include Plant Water Relations and Carbon Dynamics (26 papers), Remote Sensing in Agriculture (14 papers), Climate change and permafrost (13 papers), Photosynthetic Processes and Mechanisms (7 papers), Research Data Management Practices (5 papers), Remote Sensing and LiDAR Applications (4 papers), Spectroscopy and Chemometric Analyses (2 papers) and Leaf Properties and Growth Measurement (1 paper). The work is most often cited by research in Ecology (428 citations), Global and Planetary Change (339 citations), Analytical Chemistry (145 citations), Nature and Landscape Conservation (54 citations) and Atmospheric Science (53 citations). Kim Ely has collaborated with scholars based in United States, Hong Kong and Panama. Frequent co-authors include Shawn Paul Serbin, Alistair Rogers, Angela C. Burnett, Kenneth Davidson, Jin Wu, Brett T. Wolfe, Julien Lamour, Qianyu Li, Jeremiah A. Anderson and Stan D. Wullschleger. Their work appears in journals such as New Phytologist, Journal of Experimental Botany, Global Change Biology, Plant Cell & Environment and ISPRS Journal of Photogrammetry 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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