Murilo Maeda

1.8k total citations · 1 hit paper
31 papers, 1.3k citations indexed

About

Murilo Maeda is a scholar working on Ecology, Environmental Engineering and Plant Science. According to data from OpenAlex, Murilo Maeda has authored 31 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Ecology, 18 papers in Environmental Engineering and 16 papers in Plant Science. Recurrent topics in Murilo Maeda's work include Remote Sensing in Agriculture (22 papers), Remote Sensing and LiDAR Applications (18 papers) and Smart Agriculture and AI (9 papers). Murilo Maeda is often cited by papers focused on Remote Sensing in Agriculture (22 papers), Remote Sensing and LiDAR Applications (18 papers) and Smart Agriculture and AI (9 papers). Murilo Maeda collaborates with scholars based in United States, South Korea and China. Murilo Maeda's co-authors include Anjin Chang, Jinha Jung, Juan Landivar, Akash Ashapure, Junho Yeom, Mahendra Bhandari, Tianxing Chu, Sungchan Oh, Michael J. Starek and Chenghai Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Current Opinion in Biotechnology and Remote Sensing.

In The Last Decade

Murilo Maeda

28 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems

2020 279 citations Jinha Jung, Murilo Maeda et al. Current Opinion in Biotechnology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Murilo Maeda United States	17	826	794	522	167	113	31	1.3k
Juan Landivar United States	22	993 1.2×	765 1.0×	498 1.0×	190 1.1×	106 0.9×	59	1.4k
Yeyin Shi United States	23	1.1k 1.4×	823 1.0×	436 0.8×	188 1.1×	235 2.1×	80	1.8k
Benoît de Solan France	16	930 1.1×	728 0.9×	341 0.7×	141 0.8×	200 1.8×	30	1.2k
Jiangang Liu China	15	758 0.9×	771 1.0×	463 0.9×	167 1.0×	139 1.2×	56	1.4k
Anjin Chang United States	23	974 1.2×	967 1.2×	657 1.3×	203 1.2×	133 1.2×	67	1.7k
Alexis Comar France	18	1.1k 1.4×	1.2k 1.5×	668 1.3×	289 1.7×	216 1.9×	25	1.7k
David M. Deery Australia	14	1.0k 1.3×	605 0.8×	330 0.6×	196 1.2×	96 0.8×	22	1.4k
Nadia Shakoor United States	16	829 1.0×	592 0.7×	347 0.7×	148 0.9×	150 1.3×	36	1.4k
Shouyang Liu China	21	1.1k 1.4×	987 1.2×	537 1.0×	324 1.9×	239 2.1×	45	1.7k
Xiaoqing Zhao China	8	578 0.7×	658 0.8×	378 0.7×	139 0.8×	180 1.6×	15	992

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-authorship network of co-authors of Murilo Maeda

This figure shows the co-authorship network connecting the top 25 collaborators of Murilo Maeda. A scholar is included among the top collaborators of Murilo Maeda 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 Murilo Maeda. Murilo Maeda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Tedesco, Danilo, Bruno Rafael de Almeida Moreira, Marcelo Rodrigues Barbosa Júnior, Murilo Maeda, & Rouverson Pereira da Silva. (2023). Sustainable management of sweet potatoes: A review on practices, strategies, and opportunities in nutrition-sensitive agriculture, energy security, and quality of life. Agricultural Systems. 210. 103693–103693. 26 indexed citations

Young, Andrew W., et al.. (2023). Estimating Cotton Canopy Temperature Artifacts in UAV-Based Thermal Measurements. The journal of cotton science/Journal of cotton science. 27(4). 140–148.

Dever, Jane K., et al.. (2023). Cotton Seed Size – What is the “Fuzz” all About?. The journal of cotton science/Journal of cotton science. 23(2). 81–89. 5 indexed citations

McInnes, Kevin J., et al.. (2022). Radiative balance and temperature of differently pigmented cotton canopies. International Journal of Biometeorology. 66(3). 591–600. 2 indexed citations

Hague, Steve, Jinha Jung, Akash Ashapure, et al.. (2021). Cotton row spacing and unmanned aerial vehicle sensors. Agronomy Journal. 114(1). 331–339.

Chang, Anjin, Jinha Jung, Junho Yeom, et al.. (2021). Unmanned Aircraft System‐ (UAS‐) Based High‐Throughput Phenotyping (HTP) for Tomato Yield Estimation. Journal of Sensors. 2021(1). 29 indexed citations

Jung, Jinha, et al.. (2020). The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems. Current Opinion in Biotechnology. 70. 15–22. 279 indexed citations breakdown →

Ashapure, Akash, Jinha Jung, Anjin Chang, et al.. (2020). Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data. ISPRS Journal of Photogrammetry and Remote Sensing. 169. 180–194. 96 indexed citations

Oh, Sungchan, Anjin Chang, Akash Ashapure, et al.. (2020). Plant Counting of Cotton from UAS Imagery Using Deep Learning-Based Object Detection Framework. Remote Sensing. 12(18). 2981–2981. 61 indexed citations

10.

Bhandari, Mahendra, Amir M. H. Ibrahim, Qingwu Xue, et al.. (2020). Assessing winter wheat foliage disease severity using aerial imagery acquired from small Unmanned Aerial Vehicle (UAV). Computers and Electronics in Agriculture. 176. 105665–105665. 61 indexed citations

11.

Ashapure, Akash, Jinha Jung, Junho Yeom, et al.. (2019). A novel framework to detect conventional tillage and no-tillage cropping system effect on cotton growth and development using multi-temporal UAS data. ISPRS Journal of Photogrammetry and Remote Sensing. 152. 49–64. 38 indexed citations

12.

Enciso, Juan, Carlos A. Avila, Jinha Jung, et al.. (2019). Validation of agronomic UAV and field measurements for tomato varieties. Computers and Electronics in Agriculture. 158. 278–283. 45 indexed citations

13.

Ashapure, Akash, Jinha Jung, Anjin Chang, et al.. (2019). A Comparative Study of RGB and Multispectral Sensor-Based Cotton Canopy Cover Modelling Using Multi-Temporal UAS Data. Remote Sensing. 11(23). 2757–2757. 70 indexed citations

14.

Yang, Yubin, Lloyd T. Wilson, John L. Jifon, et al.. (2018). Energycane growth dynamics and potential early harvest penalties along the Texas Gulf Coast. Biomass and Bioenergy. 113. 1–14. 4 indexed citations

15.

Yeom, Junho, Jinha Jung, Anjin Chang, Murilo Maeda, & Juan Landivar. (2018). Automated Open Cotton Boll Detection for Yield Estimation Using Unmanned Aircraft Vehicle (UAV) Data. Remote Sensing. 10(12). 1895–1895. 62 indexed citations

16.

Chang, Anjin, Jinha Jung, Murilo Maeda, & Juan Landivar. (2017). Crop height monitoring with digital imagery from Unmanned Aerial System (UAS). Computers and Electronics in Agriculture. 141. 232–237. 147 indexed citations

17.

Starek, Michael J., et al.. (2017). Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment. Journal of Applied Remote Sensing. 11(2). 26035–26035. 84 indexed citations

18.

Chen, Ruizhi, Tianxing Chu, Juan Landivar, Chenghai Yang, & Murilo Maeda. (2017). Monitoring cotton (Gossypium hirsutum L.) germination using ultrahigh-resolution UAS images. Precision Agriculture. 19(1). 161–177. 58 indexed citations

19.

Maeda, Murilo. (2012). Advanced Analysis of the Responses of Cotton Genotypes Growing Under Water Stress. OakTrust (Texas A&M University Libraries).

20.

Maeda, Murilo, et al.. (1955). Studies on the Penicillium- and Fusarium-rots of Chinese Yam and their control.. 2(1). 8 indexed citations

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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