Extract Row-Strcture Parameters of the Maize From UAV Imageries

Abstract

The planting pattern (e.g. row orientation, width and spacing) has an important effect on the photosynthesis and yields of maize. UAV remote sensing offers a potential way to extract these pattern parameters conveniently and fast. A method based on the imagery acquired with an unmanned aerial vehicle (UAV) is proposed to extract row-structure parameters of the maize. A revised parallel-beam radon transform (RPRT) is performed and row orientation angle, row width and space distance are determined in Radon transform domain. The validation results using the in-situ measurements data show that the extraction results have high accuracy. These parameters obtained by UAV imageries can be as the input ones to maize growth and yield estimation model and later used in decision support tools.