Using Multi-Spectral UAV Imagery to Extract Tree Crop Structural Properties and Assess Pruning Effects

Kasper Johansen,Matthew Mccabe,Tri Raharjo

doi:10.3390/rs10060854

Kasper Johansen, Matthew Mccabe + Show 1 more

Open Access

https://doi.org/10.3390/rs10060854

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Abstract

Unmanned aerial vehicles (UAV) provide an unprecedented capacity to monitor the development and dynamics of tree growth and structure through time. It is generally thought that the pruning of tree crops encourages new growth, has a positive effect on fruiting, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. To establish the response of pruning in an orchard of lychee trees, an assessment of changes in tree structure, i.e., tree crown perimeter, width, height, area and Plant Projective Cover (PPC), was undertaken using multi-spectral UAV imagery collected before and after a pruning event. While tree crown perimeter, width and area could be derived directly from the delineated tree crowns, height was estimated from a produced canopy height model and PPC was most accurately predicted based on the NIR band. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in tree crown perimeter of 1.94 m, tree crown width of 0.57 m, tree crown height of 0.62 m, tree crown area of 3.5 m2, and PPC of 14.8%. In order to provide guidance on data collection protocols for orchard management, the impact of flying height variations was also examined, offering some insight into the influence of scale and the scalability of this UAV-based approach for larger orchards. The different flying heights (i.e., 30, 50 and 70 m) produced similar measurements of tree crown width and PPC, while tree crown perimeter, area and height measurements decreased with increasing flying height. Overall, these results illustrate that routine collection of multi-spectral UAV imagery can provide a means of assessing pruning effects on changes in tree structure in commercial orchards, and highlight the importance of collecting imagery with consistent flight configurations, as varying flying heights may cause changes to tree structural measurements.

Highlights

In order to increase the production of any agricultural system, activities such as crop monitoring for assessing growth, stresses, pests, fertiliser, water, nutrient condition and irrigation are all required [1,2]
The results proved the importance of the tree crown delineation process, as this process enabled the extraction of tree structural parameters used to assess changes before and after pruning at the individual tree crown level
We present an innovative and novel approach that exploits multi-spectral Unmanned aerial vehicles (UAV) imagery to measure tree structural differences pre- and post-pruning, and apply this to a small commercial lychee orchard

Summary

Introduction

In order to increase the production of any agricultural system, activities such as crop monitoring for assessing growth, stresses, pests, fertiliser, water, nutrient condition and irrigation are all required [1,2]. Jimenez-Brenes et al [4] reported that only 80% (512) of the trees within the orchard were correctly photo-reconstructed on the three image dates, which highlights the need to include spectral information as well in the object-based tree crown delineation process rather than heavily relying on the generated DSM. Existing methods for mapping structure and pruning effects based on olive trees may not be feasible for other tree crops To expand upon this lack, this research paper explores a novel and innovative approach to assess changes in tree structure, i.e., tree crown perimeter, width, height, area and Plant Projective Cover (PPC), using multi-spectral UAV derived imagery collected before and after pruning. Given the lack of any systematic evaluation of how UAV-based data acquisition configurations, including varying flying heights, affect image derived information extraction of tree structure, a secondary objective was to assess any variations in the results as a function of various flying heights (30 m/4.1 cm Ground Sampling Distance (GSD), 50 m/6.5 cm GSD and 70 m/8.8 cm GSD)

Study Area

Tree Crown Parameter Extraction

Results and Discussion

Tree Crown Delineation

Conclusions