Evaluating the Performance of Airborne and Ground Sensors for Applications in Precision Agriculture: Enhancing the...

Area of Science:

• Agricultural Science
• Remote Sensing
• Geospatial Analysis

Background:

• Accurate vegetation analysis requires comparing airborne and ground-based spectral measurements.
• Existing workflows for multitemporal image processing can be time-consuming.

Purpose of the Study:

• To evaluate and compare the performance of two multispectral airborne sensors against in situ spectral measurements.
• To present an enhanced workflow for processing multitemporal image data using diverse software solutions.
• To address the need for reliable sensor comparison in vegetation monitoring.

Main Methods:

• Utilized an eBee fixed-wing drone equipped with multiSPEC 4c and Sequoia sensors.
• Conducted field spectral measurements using a Trimble-GreenSeeker handheld spectrometer.
• Performed two flight campaigns in the Czech Republic for data acquisition and validation.

Main Results:

• Initial flight campaign data showed limited correlation between airborne and ground measurements.
• Second flight campaign data demonstrated a very high percentage of correlation.
• The enhanced photogrammetric workflow significantly reduces data processing time.

Conclusions:

• High correlation achieved in the second campaign validates the use of specific airborne sensors for vegetation monitoring.
• The developed enhanced workflow streamlines multitemporal data processing for both experts and non-professionals.
• This research provides a validated methodology for comparing airborne and ground-based spectral data in agriculture.