Toward High-Precision Plant Height Monitoring by Structure from Motion (SfM): Influence of Sunshine Condition to SfM Using Image Sets Acquired by UAV Equipped with High-Precision Positioning Systems

Abstract

Unmanned aerial vehicles (UAVs) used in combination with structure from motion (SfM) data analysis are expected to be an effective method for estimating crop height without human intervention. Subtraction between a digital surface model (DSM) and a digital terrain model (DTM) was utilized to calculate crop height. DTM is normally estimated before planting or after harvest. Real-Time Kinematic-Global Navigation Satellite System (RTK-GNSS) can provide accurate georeferencing for better crop height estimations without the need for Ground Control Points. This study evaluated location errors by UAV-SfM between check points and estimated ones, comparing SfM settings and sunshine conditions. Adjusting the SfM settings with RTK-GNSS data improved both horizontal accuracy and vertical precision. Cloudy conditions improved vertical accuracy when adjusting the SfM settings with RTK-GNSS data. In conclusion, our best results were achieved on cloudy days.