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Updated: Feb 28, 2026

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A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs.

Gabriela Calvario1, Basilio Sierra2, Teresa E Alarcón3

  • 1Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco UPV/EHU, 20018 Donostia-San Sebastián, Spain. gcalvario001@ikasle.ehu.eus.

Sensors (Basel, Switzerland)
|June 17, 2017
PubMed
Summary

Low-cost Unmanned Aerial Vehicle (UAV) remote sensing enables efficient agave crop monitoring. Integrating photogrammetry and computer vision aids in distinguishing agave plants from weeds, enhancing crop management.

Keywords:
UAVagave monitoringcomputer visiondata mininggeomatics

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Area of Science:

  • Agricultural Science
  • Geomatics
  • Computer Science

Background:

  • Remote sensing using Unmanned Aerial Vehicles (UAVs) offers a cost-effective method for rapid data acquisition in agriculture.
  • Traditional monitoring methods can be time-consuming and labor-intensive for large-scale crop analysis.

Purpose of the Study:

  • To evaluate the effectiveness of low-cost UAV remote sensing for agave crop analysis.
  • To demonstrate the potential of integrated data processing techniques for improved agave crop management.

Main Methods:

  • Utilized a low-cost UAV equipped with remote sensing capabilities for data collection.
  • Applied traditional photogrammetric processing workflows to the acquired data.
  • Employed data extraction techniques, combining photogrammetry, computer vision, data mining, geomatics, and computer science.

Main Results:

  • Successfully extracted relevant layers from UAV data to differentiate agave plants from environmental elements like weeds.
  • Achieved significant insights into agave crop status through the fusion of multiple data processing techniques.
  • Demonstrated the feasibility of low-cost UAVs for detailed agricultural monitoring.

Conclusions:

  • UAV-based remote sensing presents a viable and economical solution for agave crop monitoring.
  • The integration of advanced data processing methods enhances the utility of UAV data for precise agricultural management.
  • Reliable data processing is crucial for realizing the full potential of UAV monitoring in agriculture.