Student information

Msc thesis subject: Modelling plant-height, growth and canopy dynamics using UAV Remote-Sensing

Plant responses to biotic and abiotic legacies left in soil by preceding plants is known as plant–soil feedback (PSF). Most PSF studies are short-term and small-scale due to practical constraints for field-scale quantification of PSF effects, yet field experiments are warranted to assess actual PSF effects under less controlled conditions in the field. We used unmanned aerial vehicle (UAV)-based optical sensors to test whether PSF effects on plant traits can be quantified remotely and in a non-destructive way. By combining repeated UAV observations over the growing season, canopy structure over the growing season can be modelled.

Canopy structure can be derived from UAV based observations using the so-called Structure from Motion approach. This methods calculates the Digital Surface Model from which 3D canopy information can be derived of the crop canopy. From temporal observations, growth curves and canopy dynamics can be derived. The UAV-based canopy measurement using RGB images is a suitable alternative for quantifying canopy structure through fitting a fitting a Weibull distribution to the 3-dimensional point cloud of a plant structure or given region of interest. This method has been applied for tree objects but also the relevance for agricultural plants and plots has been indicated.

Objectives

  • Develop a processing chain to derive crop height using SfM applied on a time-series of UAV images
  • Evaluate the Weibull distribution approach for modelling growth and canopy dynamics

Literature

Theme(s): Sensing & measuring