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Conference object . 2025
License: CC BY
Data sources: ZENODO
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Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Drone-Enabled Data Collection for Sustainable Viticulture: A Practical Framework for Precision Viticulture

Authors: Samoili, Sofia; Gaspar, João; Ferreira, Renato; Vieira Duque Carreira Monteiro, Maria da Graça; Sebastião, Pedro; Kalakou, Sofia;

Drone-Enabled Data Collection for Sustainable Viticulture: A Practical Framework for Precision Viticulture

Abstract

A structured framework is developed for the use of unmanned aerial vehicles (UAVs), particularly drones, in precision viticulture, within the SmartVitiNet project. The approach includes a detailed process for drone operation in vineyards, incorporating technical, environmental, and operational parameters, from equipment setup and pre-flight route planning for efficient data collection, to post-flight data management. Route automation (area and waypoint-based), and advanced sensor and imaging configurations, allow the collection of precision data for vineyard monitoring, and the rapid coverage of large areas. The drone-based framework enhances sustainability through data-driven insights, which optimise pesticide, fertiliser, and water use. Moreover, the guide presents a replicable methodology that facilitates a wider adoption of drones by vineyard managers, bridging the gap between AI-assisted practices and agricultural reality. The uses and benefits of drones in viticulture are also thoroughly discussed. By integrating geospatial data collection with climate-sensitive flight planning, the methodology contributes to the broader digital transition towards sustainability land and resource management. The study provides a representative potential of the future of drone systems services as mobile data platforms for climate-wise agriculture, aligning with incorporating innovation for improving sustainability in transport, mobility, and environmental performance in agriculture.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average