Data and code from: Unoccupied aerial systems adoption in agricultural research
Creators
Description
This repository contains data and code supporting the findings of the study on the adoption of Unoccupied Aerial Systems (UAS) in agricultural research as reported by Lachowiec et al (2024) in The Plant Phenome Journal.
We collected data through an online survey as well as through in person interviews.
Description of Repository Contents
Data
Data are in the /data directory:
Ag_Drones_Codebook_14Jun2023.pdf: Codebook providing detailed descriptions of survey questions and coding schemes. This contains detailed descriptions of the content of the two CSV files listed below.Results_Ag_Drones_2021_Survey.csv: This is raw survey data collected from agricultural researchers regarding their use of UAS technology.countries_code.csv: Country codes used in the survey data for respondent location.interviews/: A directory containing interview transcripts and summary provided as both Microsoft Word and plain text (Markdown) formats, specifically:- Notes from nine one on one interviews named
<interviewee last name>)UAS_Interview.[md|docx] - A summary document,
Feldman_AG2PI_InterviewSummary_2022-08-10.docx.
- Notes from nine one on one interviews named
Code
Code used to process data and generate the manuscript's analysis and figures.
data_code.R: R Script for preprocessing and cleaning the survey data.dataAnalysis.R: R script for statistical analysis and visualization of survey results.
Citing this work
This repository contains data and code to support the manuscript:
Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Unoccupied aerial systems adoption in agricultural research. Zenodo. The Plant Phenome Journal Volume(Issue), pages 00. doi:DOI
If you use the data or code from this repository, please also cite:
Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Data and code from: Unoccupied aerial systems adoption in agricultural research. Zenodo. doi:10.5281/zenodo.10573428
And consider contributing cleaned data and code to this repository.
Acknowlegements and Support
Acknowledgments
We thank all survey respondents for their participation. We acknowledge the Montana State University HELPS lab for aiding in the development and implementation of the survey.
Funding
This research was supported by the intramural research program of the U.S. Department of Agriculture, National Institute of Food and Agriculture, Agricultural Genome to Phenome Initiative (2020-70412-32615 and 2021-70412-35233). The findings and conclusions in this preliminary presentation have not been formally disseminated by the U. S. Department of Agriculture and should not be construed to represent any agency determination or policy.
Files
Ag_Drones_Codebook_14Jun2023.pdf
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Additional details
Software
- Repository URL
- https://github.com/Lachowiec-Lab/agDronesSurvey
- Programming language
- R
- Development Status
- Inactive