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Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

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Published on: September 12, 2017

Light Drone-Based Application to Assess Soil Tillage Quality Parameters.

Roberto Fanigliulo¹, Francesca Antonucci¹, Simone Figorilli¹

¹Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria (CREA) - Centro di ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo (Rome), Italy.

Sensors (Basel, Switzerland)

|February 5, 2020

Summary

Light drone 3D imaging effectively assesses soil tillage quality, matching traditional methods like laser profilometry and manual sieving. This drone technology offers improved efficiency, repeatability, and reduced human error for precision agriculture.

Keywords:

UAV cloddiness digital agriculture laser profile meter precision agriculture soil surface roughness

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Area of Science:

Agricultural Engineering
Soil Science
Remote Sensing

Background:

Traditional soil tillage assessment relies on manual sieving or laser profilometry.
These methods face limitations in time efficiency, repeatability, and potential for human error.
Precision Agriculture techniques are evolving for better soil quality evaluation.

Purpose of the Study:

To compare traditional soil roughness and cloddiness assessment methods with light drone RGB 3D imaging.
To evaluate the effectiveness of drone technology across different tillage methods (ploughed, harrowed, grassed).

Main Methods:

Utilized light drone RGB 3D imaging for soil surface analysis.
Compared drone data with traditional methods: laser profile meter and manual sieving.
Assessed soil cloddiness and surface roughness parameters.

Main Results:

Light drone 3D imaging successfully replicated results from traditional assessment methods.
Drone application demonstrated significant advantages in time, repeatability, and coverage area.
Reduced human error in data collection was observed with drone usage.

Conclusions:

Light drone RGB 3D imaging is a viable and advantageous alternative for evaluating soil tillage quality.
Drone technology enhances field monitoring for digital farming and reduces errors associated with traditional tools.
Future research should focus on streamlining drone data processing and exploring advanced indices like Entropy and Angular Second Moment (ASM) for broader surface analysis.