Academic literature on the topic 'Canopy volume detection'

The canopy volume of fruit trees is an important input for the precise and varying application of pesticides in orchards. The fixed mesh division method is mostly used to calculate canopy volumes with variable target-oriented spraying. To reduce the influence of the working speed on the detection accuracy under a fixed mesh width division, the cuboid accumulation of divided areas (CADAs), which is a light detection and ranging (LiDAR) online detection method for a fruit tree canopy volume based on dynamic mesh division, is proposed in this paper. In the method, the area is divided according to the number of unilateral nozzles of the sprayer in the canopy height direction of the fruit tree, and the mesh width is dynamically adjusted according to the change in the working speed in the moving direction of the sprayer. To verify the accuracy and applicability of the method, the simulation canopy and peach tree canopy detection experiments were carried out. The test results show that the CADA method can be used to calculate the contour and volume of the canopy. However, detection errors easily occur at the edge of the canopy, resulting in a detection error of 8.33% for the simulated canopy volume. The CADA method has a good detection accuracy under different moving speeds and fruit tree canopy sizes. At a speed of 1 m/s, the detection accuracy of the canopy volume reaches 99.18%. Compared with the existing canopy volume calculation methods based on the alpha-shape algorithm and canopy meshing-profile characterization (CMPC), the detection accuracy of the CADA method is 2.73% and 7.22% better, respectively. This method can not only reduce the influence of the moving speed on the detection accuracy of the canopy volume, but also improve the detection accuracy. Thus, this method can provide theoretical support for the research and development of target-oriented variable spraying control systems for orchards.

HighlightsReview the research status of variable-rate spraying technology and point out the direction for the future researchDiscussed the advantages and disadvantages of different techniques to detect canopy volume and canopy biomassThe air speed and volume adjustment need to be controlled based on the canopy detection systemAbstract. Variable-rate pesticide application in orchards aims to solve the problems of low pesticide utilization rates and serious environmental pollution in traditional pesticide applications. In this article, we have reviewed the research status of the technology to point out the direction for future research. Orchard tree canopy volume detection, biomass detection, and variable-rate spraying control methods were systematically summarized and analyzed. The advantages and disadvantages of different sensing techniques for detecting canopy volume and canopy biomass have been discussed. Canopy volume is mainly detected by ultrasonic sensors and light detection and ranging (LiDAR) sensors. Canopy biomass detection can be realized by manual, ultrasonic sensors, LiDAR sensors, and other sensors. Variable-rate spraying control is in two parts: liquid flow rate regulation and air supply rate regulation. In order to determine the volume of the liquid variable-spray, the variable air supply of air-assisted sprayer has been proven to be important. Liquid flow regulation can be achieved by pipeline pressure control and nozzle flow rate control together with a series of algorithms. The direction of air supply is easy to determine, but the air speed and volume adjustment need to be controlled based on the canopy detection system. Finally, future research on variable-rate spraying technology should focus on: 1) the application of advanced sensing technology for accurate and real-time measurement of canopy volume and biomass, 2) accurate control algorithms for liquid flow rate regulation and methods for airflow regulation, and 3) design of variable-rate sprayers with both liquid and air regulations, and the establishment of different types of variable-rate models for different sprayer types. Keywords: Air supply rate regulation, Canopy biomass detection, Canopy volume detection, Liquid flow rate regulation, Orchard, Variable-rate spraying.

Highlights A real time stereo vision controlled variable rate sprayer for specialty crops was developed. The stereo vision system of the sprayer detected outdoor trees with similar canopy profiles under travel speeds ranging from 3.2 to 8 km h-1. Canopy volume measurements of the sprayer were impacted by lateral distances between the sprayer and the tree center and travel speeds. The sprayer required less than 200 ms from tree canopy detection to spray decisions. The sprayer achieved spray volume reductions from 72.6% to 80.5% compared to constant rate spray application. Abstract. A real time variable rate sprayer controlled by a stereo vision system was developed to increase the accuracy of spray applications and reduce the use of crop protection products. The sprayer was designed to detect tree canopies and calculate its volume using depth images from the stereo vision system, and discharge corresponding spray volumes every 200 ms through the embedded software in the graphical user interface. The sprayer was evaluated in an apple orchard at different travel speeds (3.2 to 8.0 km h-1) for its performance in detecting canopy and measuring its volume. In addition, spray volume, deposition, and coverage of the variable rate application of the sprayer were evaluated against a constant rate application. Test results showed that the sprayer detected visually similar tree canopies during the evaluations, although its canopy volume measurements deviated from manually measured canopy volume from 0.11 to 0.83 m3 due to lateral position changes of the sprayer. The sprayer adjusted duty cycles of pulse width modulated valves to accurately spray the intended volume for detected canopies (0.073 to 0.083 L m-3) and only used spray volumes of 19.5% to 26.7% compared to a constant rate spray application (338 L ha-1). The constant rate spray application generally had more spray deposition and coverage in tree canopies than the variable rate sprayer, as expected since its spray volume was approximately 3.7 times higher. However, the mean spray depositions from the constant rate spray application were significantly varied (p=0.05) by tree sizes, while the variable rate spray application achieved statistically equivalent mean spray depositions regardless of tree sizes. The stereo vision controlled sprayer offers a cost-effective real-time variable rate spray option for growers with the potential to perform other tasks by using image processing algorithms while applying crop protection products. Keywords: Automation, Canopy volume, Crop protection, Depth image, Orchard, Precision agriculture, Real-time application.

Canopy characterization detection is essential for target-oriented spray, which minimizes pesticide residues in fruits, pesticide wastage, and pollution. In this study, a novel canopy meshing-profile characterization (CMPC) method based on light detection and ranging (LiDAR)point-cloud data was designed for high-precision canopy volume calculations. First, the accuracy and viability of this method were tested using a simulated canopy. The results show that the CMPC method can accurately characterize the 3D profiles of the simulated canopy. These simulated canopy profiles were similar to those obtained from manual measurements, and the measured canopy volume achieved an accuracy of 93.3%. Second, the feasibility of the method was verified by a field experiment where the canopy 3D stereogram and cross-sectional profiles were obtained via CMPC. The results show that the 3D stereogram exhibited a high degree of similarity with the tree canopy, although there were some differences at the edges, where the canopy was sparse. The CMPC-derived cross-sectional profiles matched the manually measured results well. The CMPC method achieved an accuracy of 96.3% when the tree canopy was detected by LiDAR at a moving speed of 1.2 m/s. The accuracy of the LiDAR system was virtually unchanged when the moving speeds was reduced to 1 m/s. No detection lag was observed when comparing the start and end positions of the cross-section. Different CMPC grid sizes were also evaluated. Small grid sizes (0.01 m × 0.01 m and 0.025 m × 0.025 m) were suitable for characterizing the finer details of a canopy, whereas grid sizes of 0.1 m × 0.1 m or larger can be used for characterizing its overall profile and volume. The results of this study can be used as a technical reference for the development of a LiDAR-based target-oriented spray system.

The accurate detection of canopy characteristics is the basis of precise variable spraying. Canopy characteristics such as canopy density, thickness and volume are needed to vary the pesticide application rate and adjust the spray flow rate and air supply volume. Canopy thickness is an important canopy dimension for the calculation of tree canopy volume in pesticide variable spraying. With regard to the phenomenon of ultrasonic waves with multiple reflections and the further analysis of echo signals, we found that there is a proportional relationship between the canopy thickness and echo interval time. In this paper, we propose a method to calculate canopy thickness using echo signals that come from ultrasonic sensors. To investigate the application of this method, we conducted a set of lab-based experiments with a simulated canopy. The results show that we can accurately estimate canopy thickness when the detection distance, canopy density, and canopy thickness range between 0.5and 1.5 m, 1.2 and 1.4, and 0.3and 0.6 m, respectively. The relative error between the estimated value and actual value of the simulated canopy thickness is no higher than 8.8%. To compare our lab results with trees in the field, we measured canopy thickness from three naturally occurring Osmanthus trees (Osmanthus fragrans Lour). The results showed that the mean relative errors of three Osmanthus trees are 19.2%, 19.4% and 18.8%, respectively. These results can be used to improve measurements for agricultural production that includes both orchards and facilities by providing a reference point for the precise application of variable spraying.

Monitoring of plant vegetative growth can provide the basis for precise crop management. In this study, a 2D light detection and ranging (LiDAR) laser scanner, mounted on a linear conveyor, was used to acquire multi-temporal three-dimensional (3D) data from strawberry plants (‘Honeoye’ and ‘Malling Centenary’) 14–77 days after planting (DAP). Canopy geometrical variables, i.e., points per plant, height, ground projected area, and canopy volume profile, were extracted from 3D point cloud. The manually measured leaf area exhibited a linear relationship with LiDAR-derived parameters (R2 = 0.98, 0.90, 0.93, and 0.96 with number of points per plant, volume, height, and projected canopy area, respectively). However, the measuring uncertainty was high in the dense canopies. Particularly, the canopy volume estimation was adapted to the plant habitus to remove gaps and empty spaces in the canopy point cloud. The parametric values for maximum point to point distance (Dmax) = 0.15 cm and slice height (S) = 0.10 cm resulted in R² = 0.80 and RMSPE = 26.93% for strawberry plant volume estimation considering actual volume measured by water displacement. The vertical volume profiling provided growth data for cultivars ‘Honeoye’ and ‘Malling Centenary’ being 51.36 cm³ at 77 DAP and 42.18 cm3 at 70 DAP, respectively. The results contribute an approach for estimating plant geometrical features and particularly strawberry canopy volume profile based on LiDAR point cloud for tracking plant growth.

Light detection and ranging (LiDAR) technology provides horizontal and vertical information at high spatial resolutions and vertical accuracies. Forest attributes such as canopy height can be directly retrieved from LiDAR data. Direct retrieval of canopy height provides opportunities to model above-ground biomass and canopy volume. Access to the vertical nature of forest ecosystems also offers new opportunities for enhanced forest monitoring, management and planning.

LiDAR (Light detection and ranging) technology is an alternative to current manual methods of canopy geometry estimations in orange trees. The objective of this work was to compare different types of canopy volume estimations of orange trees, some inspired on manual methods and others based on a LiDAR sensor. A point cloud was generated for 25 individual trees using a laser scanning system. The convex-hull and the alpha-shape surface reconstruction algorithms were tested. LiDAR derived models are able to represent orange trees more accurately than traditional methods. However, results differ significantly from the current manual method. In addition, different 3D modeling algorithms resulted in different canopy volume estimations. Therefore, a new standard method should be developed and established.

Precise knowledge of fuel conditions is important for predicting fire hazards and simulating fire growth and intensity across the landscape. We present a methodology to retrieve and map forest canopy fuel and other forest structural parameters using small-footprint full-waveform airborne light detection and ranging (LiDAR) data. Full-waveform LiDAR sensors register the complete returned backscattered signal through time and can describe physical properties of the intercepted objects. This study was undertaken in a mixed forest dominated by Douglas-fir, occasionally mixed with other conifers, in north-west Oregon (United States). We extracted two sets of LiDAR metrics using pulse detection and waveform modelling and then constructed several predictive models using forward stepwise multiple linear regression. The resulting models explained ~80% of the variability for many of the canopy fuel and forest structure parameters: aboveground biomass (R2=0.84), quadratic mean diameter (R2=0.82), canopy height (R2=0.79), canopy base height (R2=0.78) and canopy fuel load (R2=0.79). The lowest performing models included basal area (R2=0.76), stand volume (R2=0.73), canopy bulk density (R2=0.67) and stand density index (R2=0.66). Our results indicate that full-waveform LiDAR systems show promise in systematically characterising the structure and canopy fuel loads of forests, which may enable accurate fire behaviour forecasting that in turn supports the development of prevention and planning policies.

Forest plantations are globally important for the economy and are significant for carbon sequestration. Properly managing plantations requires accurate information about stand timber stocks. In this study, we used the area (ABA) and individual tree (ITD) based approaches for estimating stem volume in fast-growing Eucalyptus spp forest plantations. Herein, we propose a new method to improve individual tree detection (ITD) in dense canopy homogeneous forests and assess the effects of stand age, slope and scan angle on ITD accuracy. Field and Light Detection and Ranging (LiDAR) data were collected in Eucalyptus urophylla x Eucalyptus grandis even-aged forest stands located in the mountainous region of the Rio Doce Valley, southeastern Brazil. We tested five methods to estimate volume from LiDAR-derived metrics using ABA: Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), and linear and Gompertz models. LiDAR-derived canopy metrics were selected using the Recursive Feature Elimination algorithm and Spearman’s correlation, for nonparametric and parametric methods, respectively. For the ITD, we tested three ITD methods: two local maxima filters and the watershed method. All methods were tested adding our proposed procedure of Tree Buffer Exclusion (TBE), resulting in 35 possibilities for treetop detection. Stem volume for this approach was estimated using the Schumacher and Hall model. Estimated volumes in both ABA and ITD approaches were compared to the field observed values using the F-test. Overall, the ABA with ANN was found to be better for stand volume estimation ( r y y ^ = 0.95 and RMSE = 14.4%). Although the ITD results showed similar precision ( r y y ^ = 0.94 and RMSE = 16.4%) to the ABA, the results underestimated stem volume in younger stands and in gently sloping terrain (<25%). Stem volume maps also differed between the approaches; ITD represented the stand variability better. In addition, we discuss the importance of LiDAR metrics as input variables for stem volume estimation methods and the possible issues related to the ABA and ITD performance.

Au cours de la croissance des plantes, leur suivi apporte beaucoup d'avantages aux producteurs. Cette surveillance comprend la mesure des propriétés physiques, le comptage des feuilles des plantes, la détection des plantes et leur séparation des mauvaises herbes. Toutes ces techniques peuvent être réalisées de différentes manières, cependant, les techniques favorables sont non destructives car la plante est une créature très sensible que toute manipulation peut perturber sa croissance ou entraîner la perte de feuilles ou de branches. Les techniques d'imagerie sont les meilleures solutions pour le suivi de la croissance des plantes et les mesures géométriques. À cet égard, dans ce projet, l'utilisation de l'imagerie stéréo et des données multispectrales a été étudiée. L'imagerie stéréo active et passive a été utilisée pour l'estimation des propriétés physiques et le comptage des feuilles et des données multispectrales ont été utilisées pour la séparation des cultures et des mauvaises herbes. La plante de poivron a été utilisée pour des mesures d'imagerie pendant une période de 30 jours et pour la séparation culture/mauvaise herbe, les réponses spectrales du poivron et de cinq mauvaises herbes ont été mesurées. Neuf propriétés physiques des feuilles de poivre (c. Le système stéréo était composé de deux caméras LogiTech et d'un vidéoprojecteur. Tout d'abord, le système stéréo a été calibré à l'aide d'images d'échantillons d'un damier standard dans différentes positions et angles. Le système a été contrôlé à l'aide de l'ordinateur pour allumer une ligne lumineuse, enregistrer des vidéos des deux caméras pendant que la lumière est balayée sur la plante, puis arrêter la lumière. Les cadres ont été extraits et traités. L'algorithme de traitement a d'abord filtré les images pour supprimer le bruit, puis a seuillé les pixels indésirables de l'environnement. Ensuite, en utilisant la méthode de détection de pic du centre de masse, la partie principale et centrale de la ligne lumineuse a été extraite. Ensuite, les images ont été rectifiées en utilisant les informations d'étalonnage. Ensuite, les pixels correspondants ont été détectés et utilisés pour le développement du modèle 3D. Le nuage de points obtenu a été transformé en une surface maillée et utilisé pour la mesure des propriétés physiques. Pour les réponses spectrales des plantes, celles-ci ont été fraîchement déplacées au laboratoire, les feuilles ont été détachées des plantes et placées sur un fond sombre flou. Des lumières de type A ont été utilisées pour l'éclairage et les mesures spectrales ont été effectuées à l'aide d'un spectroradiomètre de 380 nm à 1000 nm. Pour réduire la dimensionnalité des données, l'ACP et la transformée en ondelettes ont été utilisées. Les résultats de cette étude ont montré que l'utilisation de l'imagerie stéréo peut proposer un outil bon marché et non destructif pour l'agriculture. Un avantage important de l'imagerie stéréo active est qu'elle est indépendante de la lumière et peut être utilisée pendant la nuit. Cependant, l'utilisation de la stéréo active pour le stade primaire de croissance fournit des résultats acceptables, mais après ce stade, le système sera incapable de détecter et de reconstruire toutes les feuilles et les parties de la plante. En utilisant l'ASI, les valeurs R2 de 0,978 et 0,967 ont été obtenues pour l'estimation de la surface foliaire et du périmètre, respectivement. Les résultats de la séparation des cultures et des mauvaises herbes à l'aide de données spectrales étaient très prometteurs et le classificateur, qui était basé sur un apprentissage en profondeur, pouvait complètement séparer le poivre des cinq autres mauvaises herbes
During the growth of plants, monitoring them brings much benefits to the producers. This monitoring includes the measurement of physical properties, counting plants leaves, detection of plants and separation of them from weeds. All these can be done different techniques, however, the techniques are favorable that are non-destructive because plant is a very sensitive creature that any manipulation can put disorder in its growth or lead to losing leaves or branches. Imaging techniques are of the best solutions for plants growth monitoring and geometric measurements. In this regard, in this project the use of stereo imaging and multispectral data was studied. Active and passive stereo imaging were employed for the estimation of physical properties and counting leaves and multispectral data was utilized for the separation of crop and weed. Bell pepper plant was used for imaging measurements for a period of 30 days and for crop/weed separation, the spectral responses of bell pepper and five weeds were measured. Nine physical properties of pepper leaves (i.e. main leaf diameters, leaf area, leaf perimeter etc.) were measured using a scanner and was used as a database and also for comparing the estimated values to the actual values. The stereo system consisted of two LogiTech cameras and a video projector. First the stereo system was calibrated using sample images of a standard checkerboard in different position and angles. The system was controlled using the computer for turning a light line on, recording videos of both cameras while light is being swept on the plant and then stopping the light. The frames were extracted and processed. The processing algorithm first filtered the images for removing noise and then thresholded the unwanted pixels of environment. Then, using the peak detection method of Center of Mass the main and central part of the light line was extracted. After, the images were rectified by using the calibration information. Then the correspondent pixels were detected and used for the 3D model development. The obtained point cloud was transformed to a meshed surface and used for physical properties measurement. Passive stereo imaging was used for leaf detection and counting. For passive stereo matching six different matching algorithms and three cost functions were used and compared. For spectral responses of plants, they were freshly moved to the laboratory, leaves were detached from the plants and placed on a blur dark background. Type A lights were used for illumination and the spectral measurements were carried out using a spectroradiometer from 380 nm to 1000 nm. To reduce the dimensionality of the data, PCA and wavelet transform were used. Results of this study showed that the use of stereo imaging can propose a cheap and non-destructive tool for agriculture. An important advantage of active stereo imaging is that it is light-independent and can be used during the night. However, the use of active stereo for the primary stage of growth provides acceptable results but after that stage, the system will be unable to detect and reconstruct all leaves and plant's parts. Using ASI the R2 values of 0.978 and 0.967 were obtained for the estimation leaf area and perimeter, respectively. The results of separation of crop and weeds using spectral data were very promising and the classifier—which was based on deep learning—could completely separate pepper from other five weeds

Abstract It seems appropriate to launch a volume of shipboard and shoreline mystery stories with a tale of murder, mayhem, and mutiny on deck. This also happens to be the account of the first case undertaken by the world’s great consulting detective, Sherlock Holmes. Although Holmes was introduced in Sir Arthur Conan Doyle’s “A Study in Scarlet” in 1887, “The ‘Gloria Scott,’” published six years later, holds a special place in the canon of Holmes stories. Here Holmes recounts the case that revealed to him that his extraordinary skills at observation might serve him-and others in need-as more than the “hobby” of a restless intellect.

The cracking of CANOPY Seal Weld (CSW) of the Control Rod Drive Mechanism (CRDM) ever occurred and led to Boric acid solution leakage in nuclear power plant worldwide. The failure analysis on above failure CSW shows that stress corrosion crack (SCC) is main failure mode of CSW, and the crack usually originate from the weld root and grows along weld or HAZ under PWR service environment. The CSW structure parameter presented here are as following, the wall thickness is 2–3 mm, radius of curvature of cross-section is 6–12 mm, and the gyration radius is 50–100mm. In the latest year, CSW is required to implement surface examination (i.e. Visual Test or Penetration Test) during the plant outage. The flaw is that the CSW won’t be repaired till its failure is detected; therefore effective preventive maintenance can’t be performed. The specific inspection technology is developed for NDT volume testing method, aiming to detect the root crack occurred in weld and its adjacent base metal. This paper introduces the CSW structure, in-service inspection requirements, and technical solutions. The NDT technology corresponding UT, ET and CCTV was finally applied as applicable technical solution with automatic scanning devices to detect CSW crack. Ultrasonic inspection technology uses high-frequency water immersion focusing probes with frequency higher than 10MHz which is investigated to detect the defect in the weld root area. Meanwhile, Eddy current inspection technology is applied to detect the surface crack or subsurface crack with orthogonal difference array probes, which helps to distinguish false signals detected by UT in outer surface. Ultrasonic inspection technical solutions based on high-frequency water immersion focusing methods and the key technical parameters are discussed emphatically in this paper. By testing on blocks with characteristic artificial reflectors, characteristic rule of ultrasonic signals in different areas and sizing methods for crack is investigated respectively. It show that UT has higher detecting sensitivity for crack of where the height reaches 0.5mm and the length reaches 4mm, and sizing is accuracy and reliable for crack when the height over than 1 mm and the length over than 4mm. CSW is not incorporated in-service scope referring to ASME code or Chinese in-service code, and the acceptance criterion of weld flaw is also not found. So, the integrity shall be evaluated as far as CSW with flaw is concerned. Thus, the stress analysis and temperature field are carried out on the CSW mentioned above, and the structural integrity assessment is simultaneously performed based on ASME code. Finally, the acceptance criteria are recommended for both volumetric and planar flaw.

Control of fluids at the microscale represents an important point of interest in the widely studied field of Microfluidics. In fact, most of the biological and medical research undergone would benefit from Microfluidic solutions. One of the engineering challenges brought about by this technologic evolution involves the dispensing of fluids at these scales. The study presented in this paper concerns the development of a novel dispenser of biofluids, which would find its first application in the measurement of multi-gene expression levels as part of cancer diagnosis. The studied geometry is termed “two-way liquid bridge” and consists of injecting a continuous fluid to be segmented via an inlet PFE tubing in a microgravity environment until an isothermal mass of liquid is held by surface tension between the inlet and outlet tubings, parallel and opposite. Due to constant pressurisation of the microgravity environment, this mass eventually ruptures delivering a segmented volume of biofluids on which an analysis such as PCR can be performed. Experimental investigations were conducted in a backlighted transparent PMMA device in which fluids were injected using Harvard Apparatus syringe pumps. A CMOS colour camera recorded the images which were automatically analysed using a Canny edge detection algorithm. A dimensional analysis was conducted highlighting the main dimensionless groups for a complete understanding of the occurring phenomena. Experimental observations showed good repeatability and consistency in the dispensing process. It was also shown that fluids flowrates, tubings sizes and length of separation between inlet and outlet tubings have a direct impact on the size and frequency of the produced droplets. The present paper addresses the complete characterisation of the geometry as well as the establishment of correlations in order to provide a useful engineering design tool.