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

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.