Research Article: High-resolution imagery acquired from an unmanned platform to estimate biophysical and geometrical parameters of olive trees under different irrigation regimes

Date Published: January 22, 2019

Publisher: Public Library of Science

Author(s): Giovanni Caruso, Pablo J. Zarco-Tejada, Victoria González-Dugo, Marco Moriondo, Letizia Tozzini, Giacomo Palai, Giovanni Rallo, Alberto Hornero, Jacopo Primicerio, Riccardo Gucci, John Toland Van Stan.

http://doi.org/10.1371/journal.pone.0210804

Abstract

The experiments were conducted in a fully-productive olive orchard (cv. Frantoio) at the experimental farm of University of Pisa at Venturina (Italy) in 2015 to assess the ability of an unmanned aerial vehicle (UAV) equipped with RGB-NIR cameras to estimate leaf area index (LAI), tree height, canopy diameter and canopy volume of olive trees that were either irrigated or rainfed. Irrigated trees received water 4–5 days a week (1348 m3 ha-1), whereas the rainfed ones received a single irrigation of 19 m3 ha-1 to relieve the extreme stress. The flight altitude was 70 m above ground level (AGL), except for one flight (50 m AGL). The Normalized Difference Vegetation Index (NDVI) was calculated by means of the map algebra technique. Canopy volume, canopy height and diameter were obtained from the digital surface model (DSM) obtained through automatic aerial triangulation, bundle block adjustment and camera calibration methods. The NDVI estimated on the day of the year (DOY) 130 was linearly correlated with both LAI and leaf chlorophyll measured on the same date (R2 = 0.78 and 0.80, respectively). The correlation between the on ground measured canopy volumes and the ones by the UAV-RGB camera techniques yielded an R2 of 0.71–0.86. The monthly canopy volume increment estimated from UAV surveys between (DOY) 130 and 244 was highly correlated with the daily water stress integral of rainfed trees (R2 = 0.99). The effect of water stress on the seasonal pattern of canopy growth was detected by these techniques in correspondence of the maximum level of stress experienced by the rainfed trees. The highest level of accuracy (RMSE = 0.16 m) in canopy height estimation was obtained when the flight altitude was 50 m AGL, yielding an R2 value of 0.87 and an almost 1:1 ratio of measured versus estimated canopy height.

Partial Text

Although olive (Olea europaea L.) is a drought tolerant species, irrigation is widely used in modern, high density olive orchards due to its beneficial effects on growth, yield components and oil quality [1, 2, 3, 4]. Shoot growth, leaf area and canopy volume are very sensitive to water stress as they affect tree water requirements [5, 6, 7, 8]. Pérez-López et al. [9] compared the effects of different irrigation regimes on shoot growth and canopy volume of young olive trees (3-year-old at the beginning of the trial) and found significant differences only in the third year of the experiment. They attributed the lack of significant differences in canopy volume in the first two years to the low accuracy of the measurement method and to the high variability within each treatment; as canopy volume progressively increased differences became evident. Another study conducted in a high-density olive orchard showed marked effects of water deficit on canopy volume and leaf area index (LAI), with the highest values measured in fully-irrigated trees and the lowest ones in trees subjected to regulated deficit irrigation [10]. They concluded that the increase in canopy volume could be used as an indicator to quantify the effect of water stress on vegetative growth. In that work differences in vegetative parameters between irrigation treatments were detected also thanks to the precise and accurate methods used for estimating both LAI and tree canopy volume [11, 12]. The reduction in vegetative growth induced by water deficit can be used effectively to control canopy size in mature trees, especially in high and very high density orchards [6]. Moreover, both LAI and tree canopy volume are directly related to solar radiation interception, water consumption and potential productivity of olive trees [13, 14] and provide valuable information for both pest and pruning management [15, 16].

The SWP of the irrigated trees was maintained above –2.2 MPa with an average of –1.8 MPa during the entire irrigation period in 2015, whereas the SWP of RF trees decreased progressively with increasing seasonal water stress and reached a minimum value of -4.5 MPa on DOY 267 (Fig 4A). The SWP of RF trees increased during the irrigation period (DOY 225) following a rainfall event, and then again on DOY 280 after the only irrigation applied to the RF trees (DOY 273) and three consecutive rainy days (DOY 275–277, a total of 45 mm). The degree of water deficit experienced by IR and RF trees, expressed as the water stress integral, was 73 and 190 MPa ˑd, respectively, at the end of the irrigation period (Fig 4B).

The methodology proposed in this study is similar, in its first steps, to that used in previous experiments for the generation of the bare terrain surface (DTM) and the subsequent estimation of the canopy geometrical characteristics [37, 38]. Regardless of the height of flight, the number of GCPs used for the DSM generation and the height of the canopy from the ground (individual for each tree or mean orchard value) used for the calculation, the canopy volume was satisfactorily estimated. The correlations between the UAV-estimated and the on-ground-measured canopy volume of the individual trees showed coefficient of determination and RMSE values always comprised between 0.71 and 0.86 and 1.6 m3 and 2.1 m3, respectively. A previous study conducted on mature olive trees in Spain reported lower coefficient of determination between estimated and measured canopy volumes by using images taken at an altitude of 50 m (R2 = 0.65) and 100 m (R2 = 0.63) [27]. In our study, R2 increased substantially (from 0.76 to 0.85) by reducing the flight altitude from 70 to 50 m. The slight underestimation observed in the UAV-estimated canopy volume can be reasonably interpreted as a higher accuracy with respect to the on-ground-measured values. In fact, while the SfM technique can detect (and exclude) the empty volume in the central part of the olive tree canopy, typical of the vase training system, the ellipsoid method used for the on ground canopy measurement cannot. Previous studies on the canopy geometry of olive and eucalypt trees confirm this hypothesis [16, 38]. In both studies, by comparing the canopy volumes estimated through the ellipsoid method with those estimated by laser scanner technique (LIDAR), which actually represents the most precise technology available for this purpose, an overestimation of the ellipsoid method was observed [16, 39]. A possible limitation of the methodology presented here is that it requires the value of the mean height of the canopy from the ground as input data for canopy volume estimation. This information is easier to determine in modern, intensive olive orchards than in traditional, irregular olive orchards in which olive trees are irregular in age and/or training system.

In this study we showed that UAV, RGB-NIR cameras and SfM techniques can be used to effectively estimate biophysical and geometrical parameters such as LAI, tree height, canopy diameter and canopy volume of olive trees. The method we propose for the tree canopy volume estimation, based on the processing of DTM and DSM raster files, has been previously used for the canopy height identification. The UAV imagery was successfully used to assess the effects of different soil water availability on canopy growth. These results show promising perspective in the use of this technique in field experiments on irrigation management. Further investigations are required to verify whether the good results of accuracies assessment obtained in a flat olive orchard can also be confirmed on slopes.

 

Source:

http://doi.org/10.1371/journal.pone.0210804

 

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