Thesis subject

Automatic apple trees height estimation from digital elevation models (DEM) obtained from aerial surveys

Unmanned aerial vehicles (UAV) shipped with on-board sensors have become an effective remote sensing (RS) tool in agriculture and environmental studies. However, the full potential of those platforms has not been yet achieved. Working with UAV it’s an added valuable point for any professional who wishes to succeed in this competitive market. Herein, you will have the opportunity to work in a novel and ambitious project using small UAV for precision agriculture.

Keeping track of the apple trees height is an important task for fruit growers to control the tree growth. This task is often achieved manually by experienced professionals making it hard to achieve in a reasonable time and with a good accuracy.

This thesis proposes the development of a machine vision algorithm that computes the orchards flower density variability that can be afterwards used for yield estimation. This thesis will be carry out within the follow steps:

  1. Review previous works about yield estimation in apple orchards;
  2. Algorithm design;
  3. Experiments in the already available dataset.


  • Díaz-Varela, R., de la Rosa, R., León, L., and Zarco-Tejada,P.: High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3-D Photo Reconstruction: Application in Breeding Trials, Remote Sensing, 7, 4213–4232, 2015.
  • Abraham Mejia-Aguilar, Enrico Tomelleri, Andrea Vilardi, and Marc Zebisch, Geophysical Research Abstracts, Vol. 17, EGU2015-7082, 2015.
  • Anıl Can Birdal, Uğur Avdan & Tarık Türk (2017) Estimating tree heights with images from an unmanned aerial vehicle, Geomatics, Natural Hazards and Risk, 8:2, 1144-1156.


  • UAV enthusiast
  • Willing for learning novel software and hardware tools
  • Excited to work in robotics

Theme(s): Sensing & measuring