Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines.
- DOI
- 10.3390/s25020431
- Published
- 2025 Jan 13
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s25020431,
title = {Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines.},
author = {Dillner RP and Wimmer MA and Porten M and Udelhoven T and Retzlaff R},
year = {2025},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s25020431},
url = {https://doi.org/10.3390/s25020431}
}RIS
TY - JOUR TI - Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines. AU - Dillner RP AU - Wimmer MA AU - Porten M AU - Udelhoven T AU - Retzlaff R PY - 2025 JO - Sensors (Basel, Switzerland) DO - 10.3390/s25020431 UR - https://doi.org/10.3390/s25020431 ER -
APA
RP, D., MA, W., M, P., T, U., & R, R. (2025). Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s25020431
Source records
- pubmed · retrieved 2026-09-27T10:25:37.750Z