Comparing UAV-Based Technologies and RGB-D Reconstruction Methods for Plant Height and Biomass Monitoring on Grass...

Area of Science:

• Agricultural Science
• Remote Sensing
• Digital Modeling

Background:

• Pastures are botanically complex, making characterization challenging.
• Non-destructive digital modeling of pasture biomass and quality aids decision-making.
• Evaluating aerial and on-ground methods for pasture assessment is crucial.

Purpose of the Study:

• To assess aerial (UAV) and on-ground (RGB-D camera) methods for characterizing grass ley fields.
• To estimate plant height, biomass, and volume using digital grass models.
• To compare the accuracy and economic feasibility of different sensing systems.

Main Methods:

• Two grass ley fields (timothy-dominant and ryegrass-dominant) were sampled.
• Digital grass models were created using UAV-based and RGB-D camera systems.
• Ground-truth data were obtained through manual, destructive sampling of 1m² plots.

Main Results:

• Both systems estimated plant height, biomass, and volume with varying accuracy.
• RGB-D estimation showed high correlation with ground truth for plant height (R² > 0.80) and dry biomass (R² = 0.88) in timothy fields.
• UAV-based systems demonstrated weaker estimation capabilities (R² < 0.6) but offered cost and coverage advantages.

Conclusions:

• On-ground RGB-D cameras provide detailed models but with more variable results.
• UAV systems are more affordable and suitable for large-scale grassland monitoring.
• Aerial platforms are a practical option for agricultural operations requiring broad characterization rather than fine detail.