Influence of Wind Speed on RGB-D Images in Tree Plantations

Area of Science:

• Agricultural Engineering
• Plant Science
• Remote Sensing

Background:

• Depth cameras are valuable for plant phenotyping but susceptible to field conditions.
• Previous research established lighting effects, but wind's impact on depth cameras remains unquantified.

Purpose of the Study:

• To quantify the impact of wind speed on depth camera accuracy for tree characterization.
• To establish operational wind speed limits for reliable tree measurements using depth cameras.

Main Methods:

• A Kinect v2 sensor and custom software were used to model poplar and plum trees under varying wind speeds (0-10 m/s).
• Leaf Area (LA), tree volume, and height were measured and analyzed for accuracy at different wind conditions.

Main Results:

• Wind speed affects tree measurement accuracy, with species-specific responses observed.
• Plum trees showed more consistent Leaf Area (LA) and volume estimations at higher wind speeds.
• Poplar height measurements were more stable than plum trees, but poplars were significantly impacted by wind speeds above 5 m/s.

Conclusions:

• Wind conditions are a critical factor to consider when using depth cameras for field-based tree characterization.
• A conservative wind speed limit of 5 m/s (18 km/h) is recommended for reliable depth camera estimations in tree studies.