Direct derivation of maize plant and crop height from low-cost time-of-flight camera measurements

In agriculture, information about the spatial distribution of crop height is valuable for applications such as biomass and yield estimation, or increasing field work efficiency in terms of fertilizing, applying pesticides, irrigation, etc. Established methods for capturing crop height often comprise restrictions in terms of cost and time efficiency, flexibility, and temporal and spatial resolution of measurements. Furthermore, crop height is mostly derived from a measurement of the bare terrain prior to plant growth and measurements of the crop surface when plants are growing, resulting in the need of multiple field campaigns. In our study, we examine a method to derive crop heights directly from data of a plot of full grown maize plants captured in a single field campaign. We assess continuous raster crop height models (CHMs) and individual plant heights derived from data collected with the low-cost 3D camera Microsoft？ Kinect？ for Xbox One？ based on a comprehensive comparison to terrestrial laser scanning (TLS) reference data