Murilo Maeda

28 papers receiving 1.4k citations

Murilo Maeda's Hit Papers

The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems 2020 · 332 citations
3320+2+4Years since publication100200300

Peers

Murilo Maeda
Comparison fields: 5 of 95
  • Environmental Engineering 546
  • Ecology 821
  • Plant Science 874
  • Analytical Chemistry 117
  • Ecological Modeling 45
Replace Andrew Robson with:
Andrew Robson Australia
Anjin Chang United States
Yeyin Shi United States
Benoît de Solan France
Juan Landivar United States
Alexis Comar France
Shanyu Huang China
Jacopo Primicerio Italy
Yan Gong China
Shouyang Liu China
Murilo Maeda relative to Andrew Robson Australia Andrew Robson's profile →
Citations per field
00.5×1.6×
Andrew Robson · 1×
Citations per year

Countries citing papers authored by Murilo Maeda

Since Specialization
Citations

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

Fields of papers citing papers by Murilo Maeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Murilo Maeda, 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 Murilo Maeda Line = papers co-authored together Murilo Maeda 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
The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems
Hit paper breakdown →
2020332
2 2017158
3 2020104
4 201791
5 201986
6 201971
7 202067
8 202067
9 201865
10 201862
11 201760
12 201949
13 201845
14 201644
15 201939
16 202332
17 202129
18 201714
19 202011
20
Studies on the Penicillium- and Fusarium-rots of Chinese Yam and their control.
19559

About Murilo Maeda

Murilo Maeda is a scholar working on Ecology, Environmental Engineering, Plant Science, Global and Planetary Change and Agronomy and Crop Science, having authored 32 papers that have together received 1.5k indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (22 papers), Remote Sensing and LiDAR Applications (18 papers), Smart Agriculture and AI (9 papers), Research in Cotton Cultivation (4 papers), Land Use and Ecosystem Services (4 papers), Crop Yield and Soil Fertility (2 papers), Plant Water Relations and Carbon Dynamics (2 papers) and Species Distribution and Climate Change (2 papers). The work is most often cited by research in Environmental Engineering (546 citations), Ecology (821 citations), Plant Science (874 citations), Analytical Chemistry (117 citations) and Ecological Modeling (45 citations). Murilo Maeda has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Jinha Jung, Anjin Chang, Juan Landivar, Akash Ashapure, Mahendra Bhandari, Junho Yeom, Tianxing Chu, Sungchan Oh, Michael J. Starek and Michael J. Brewer. Their work appears in journals such as Computers and Electronics in Agriculture, Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing, ˜The œjournal of cotton science/Journal of cotton science and Water.

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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