Extraction of Information about Individual Trees from High-Spatial-Resolution UAV-Acquired Images of an Orchard

Abstract

The extraction of information about individual trees is essential to supporting the growing of fruit in orchard management. Data acquired from spectral sensors mounted on unmanned aerial vehicles (UAVs) have very high spatial and temporal resolution. However, an efficient and reliable method for extracting information about individual trees with irregular tree-crown shapes and a complicated background is lacking. In this study, we developed and tested the performance of an approach, based on UAV imagery, to extracting information about individual trees in an orchard with a complicated background that includes apple trees (Plot 1) and pear trees (Plot 2). The workflow involves the construction of a digital orthophoto map (DOM), digital surface models (DSMs), and digital terrain models (DTMs) using the Structure from Motion (SfM) and Multi-View Stereo (MVS) approaches, as well as the calculation of the Excess Green minus Excess Red Index (ExGR) and the selection of various thresholds. Furthermore, a local-maxima filter method and marker-controlled watershed segmentation were used for the detection and delineation, respectively, of individual trees. The accuracy of the proposed method was evaluated by comparing its results with manual estimates of the numbers of trees and the areas and diameters of tree-crowns, all three of which parameters were obtained from the DOM. The results of the proposed method are in good agreement with these manual estimates: The F-scores for the estimated numbers of individual trees were 99.0% and 99.3% in Plot 1 and Plot 2, respectively, while the Producer’s Accuracy (PA) and User’s Accuracy (UA) for the delineation of individual tree-crowns were above 95% for both of the plots. For the area of individual tree-crowns, root-mean-square error (RMSE) values of 0.72 m2 and 0.48 m2 were obtained for Plot 1 and Plot 2, respectively, while for the diameter of individual tree-crowns, RMSE values of 0.39 m and 0.26 m were obtained for Plot 1 (339 trees correctly identified) and Plot 2 (203 trees correctly identified), respectively. Both the areas and diameters of individual tree-crowns were overestimated to varying degrees.

Assessing the Influence of UAV Altitude on Extracted Biophysical Parameters of Young Oil Palm

“…In the oil palm industry, UAV-based imaging provides low cost flexible data acquisition with less weather constraints and higher spatial/temporal resolution, as compared to high-resolution satellite data [15]. There are various applications of UAV, such as monitoring canopy structure and condition, mapping biomass, and precision agriculture [16,17]. There are ground-based sensors available for precision agriculture applications, but UAV-based monitoring is advantageous in generating smaller ground sample distances, instantaneous calibration to reflectance, and point cloud construction [18].…”

“…There are ground-based sensors available for precision agriculture applications, but UAV-based monitoring is advantageous in generating smaller ground sample distances, instantaneous calibration to reflectance, and point cloud construction [18]. The structure from motion (SfM) technique is useful to characterize individual trees [17]. Díaz-Varela et al and Zarco-Tejada et al used the SfM technique to estimate olive tree height and crown diameter in Spain [19,20].…”

Catalyzing Holistic Agriculture Innovation Through Industrial Biotechnology

“…161,163,164 Unmanned aerial drones are capable of offering centimeter resolution. 166,[174][175][176][177] Temporal resolution is also important for monitoring and tracking crop development, and for different satellite systems temporal resolution can range from 18 days to 12 hours. 161,164 The cost and ease of deploying an unmanned aerial drone, with advanced sensors, allows for high spatial resolution and unprecedented temporal frequency.…”

“…161,164 The cost and ease of deploying an unmanned aerial drone, with advanced sensors, allows for high spatial resolution and unprecedented temporal frequency. 166,177,178 As mentioned earlier, the miniaturization of sensors has led to the development of hand-held devices with multiple sensing capability for measuring life processes in cropping systems. 162,179,180 This miniaturization has also given us chip-based laboratories that are operating at the nano-and micrometer scale.…”

Multispectral Mapping on 3D Models and Multi-Temporal Monitoring for Individual Characterization of Olive Trees

“…Nevertheless, the modeling of 3D plant structures is still challenging because olive trees contain many overlapping branches in the crown and a high leaf density, which make the generation of plant geometry quite complicated. Some studies proposed different methods for the assessment of geometric features such as the height, area or volume of fruit trees [19][20][21] and for the detection of potential phytosanitary problems at the canopy level [22,23]. Undoubtedly, the complete plant geometry provides a real perception of many morphological traits, which cannot be directly identified in the image.…”