Development of a robust canopy height model derived from ALS point clouds for predicting individual crown attributes at the species level

ABSTRACT

Tree crown attributes are important parameters during the assessment and monitoring of forest ecosystems. Canopy height models (CHMs) derived from airborne laser scanning (ALS) data have proved to be a reliable source for extracting different biophysical characteristics of single trees and at stand level. However, ALS-derived tree measurements (e.g., mean crown diameter) can be negatively affected by pits that appear in the CHMs. Thus, we propose a novel method for generating pit-free CHMs from ALS point clouds for estimating crown attributes (i.e., area and mean diameter) at the species level. The method automatically calculates a threshold for a pixel based on the range of height values within neighbouring pixels; if the pixel falls below the threshold then it is recognized as a pitted pixel. The pit is then filled with the median of the values of the neighbouring pixels. Manually delineated individual tree crowns (ITC) of four deciduous and two coniferous species on Colour Infrared (CIR) stereo images were used as a reference in the analysis. In addition, a variety of different algorithms for constructing CHMs were compared to investigate the performance of different CHMs in similar forest conditions. Comparisons between the estimated and observed crown area (R² = 0.95, RMSE% = 19.12% for all individuals) and mean diameter (R² = 0.92, RMSE% = 12.16% for all individuals) revealed that ITC attributes were correctly estimated by segmentation of the pit-free CHM proposed in this study. The goodness of matching and geometry revealed that the delineated crowns correctly matched up to the reference data and had identical geometry in approximately 70% of cases. The results showed that the proposed method produced a CHM that estimates crown attributes more accurately than the other investigated CHMs. Furthermore, the findings suggest that the proposed algorithm used to fill pits with the median of height observed in surrounding pixels significantly improve the accuracy of the results the species level due to a higher correlation between the estimated and observed crown attributes. Based on these results, we concluded that the proposed pit filling method is capable of providing an automatic and objective solution for constructing pit-free CHMs for assessing individual crown attributes of mixed forest stands.     

Motion planning in velocity affine mechanical systems

We address the motion planning problem in specific mechanical systems whose linear and angular velocities depend affinely on control. The configuration space of these systems encompasses the rotation group, and the motion planning involves the system orientation. Derivation of the motion planning algorithm for velocity affine systems has been inspired by the continuation method. Performance of this algorithm is illustrated with examples of the kinematics of a serial nonholonomic manipulator, the plate-ball kinematics and the attitude control of a rigid body.     

Iterative learning control and the singularity robust Jacobian inverse for mobile manipulators

The method of iterative learning control, to a large extent, has been inspired by robotics research, focused on the control of stationary manipulators. In this article we deal with the inverse kinematics problem for mobile manipulators, and show that a very basic singularity robust Jacobian inverse can be derived in a natural way within the framework of iterative learning control. To achieve this objective we have exploited the endogenous configuration space approach. The introduced Jacobian inverse defines the singularity robust Jacobian inverse kinematics algorithm for mobile manipulators. A Kantorovich-type estimate of the region of guaranteed convergence of the algorithm is derived. For two example kinematics, this estimate has been computed efficiently.     

Extended Jacobian inverse kinematics algorithm for nonholonomic mobile robots

By a generalization of the well-known extended Jacobian method for stationary manipulators, we derive the extended Jacobian inverse kinematics algorithm for nonholonomic mobile robots. Key points of the derivation consist in defining the kinematics of a mobile robot as the end-point map of a driftless control system, decomposing the space of control functions of this system into a finite and an infinite dimensional subspaces, and introducing an augmenting kinematics map subordinated to this decomposition. The original kinematics and the augmenting kinematics constitute the extended kinematics. The inverse Jacobian of the extended kinematics defines the extended Jacobian inverse kinematics algorithm. By design, the algorithm is repeatable. As an example, we derive a specific extended Jacobian inverse kinematics algorithm and illustrate its performance with the computer simulations.     

Microstructure Evolution as an Effect of Strain Reversal During the Hot Deformation of Microalloyed Steels

Susceptibility of the steel for further cold processing strongly depends on the whole prior history of deformation in the hot working regime.In the industrial hot working processes,e.g.at the roughing stage of hot rolling,or forging,material undergoes complex deformation modes that leads to gradients of both microstructure and properties across the deformed cross-section.Torsion and multiaxial compression tests with different amounts of strain reversals were conducted at elevated temperatures to study the effect of applied strain path on the phenomena occurring during microstructure evolution of Nb-microalloyed steels.Gathered results will provide data for the modification of existing constitutive equations that mostly do not account for the strain path changes.Better through-process modelling will then enable to achieve better properties and quality of the products for further cold processing.     

Epileptic seizure detection.

In this study, radial basis function (RBF) neural networks are used to identify seizure or preseizure states. As input to the RBF networks the study used raw EEG data, coefficients from a Fourier transform, and wavelet decomposition of the raw data. An RBF network consists of an input layer, a single hidden layer, and an output node. The use of half-second windows of raw data as input demonstrates the ability of the RBF network to learn differences in the patterns of ictal and interictal EEG data without feature extraction. Wavelet decomposition of the narrow window of raw data improves performance while transformation of a wider window, up to about five seconds, improves it even further. The ability of wavelet decomposition to transform five seconds of raw data into a vector of manageable length without substantial loss of relevant information makes it an effective tool for preprocessing EEG data     

Microstructure-Sensitive Computational Estimates of Driving Forces for Surface Versus Subsurface Fatigue Crack Formation in Duplex Ti-6Al-4V and Al 7075-T6

Statistical realizations of three-dimensional digital microstructures with different crystallographic orientation distributions, grain shapes, and grain size distributions are subjected to uniaxial cyclic straining to compare the cases of bulk and free surface on driving forces for fatigue crack formation. Crystal plasticity finite element simulations are conducted using both fully periodic (more representative of the bulk) and traction-free (i.e., free surface) boundary conditions for duplex Ti-6Al-4V and rolled Al 7075-T6. Following elastic–plastic shakedown, mesoscale volume-averaged fatigue indicator parameters (FIPs) are computed within fatigue damage process zones of grains and are fit to known extreme value distributions (EVDs). Owing to differences in crystallographic slip symmetry, FIPs for fcc Al 7075-T6 statistically occur much closer to the traction-free surface than for hcp Ti-6Al-4V. Additionally, surface versus bulk EVDs of FIPs vary differently for the two material systems, indicating a coupled role of microstructure and surface proximity that had not been previously elucidated.

     

X-ray Microtomography Analysis of the Aluminum Alloy Composite Reinforced by SiC After Friction Stir Processing

Despite many years of using friction stir processing (FSP), there are many unexplained aspects concerning the processes which appear during FSP: determining the direction of flow and mixing of the materials and the degree of mixing and microstructure fragmentation in specific areas. This paper presents the impact of FSP on the micro- and macrostructure of the composite with hypo-eutectic Si matrix reinforced by SiC particles. The analysis of the structure of the processed area in FSP in the relation to the microstructure of the base material has been made using x-ray microtomography. The results of these studies have been juxtaposed with studies using microscopic methods (light microscopy and SEM). The microtomography images revealed an additional separation on the advancing side and the weld nugget, where on the basis of a 3D reconstruction a layer microstructure on the direction of linear movement of the tool has been demonstrated. The analyses have revealed a limited flow of the material above the weld nugget. The main advantages of the research method applied were the possibility to show the invisible or barely visible elements of the microstructure using standard test methods and the ability to analyze the microstructure changes uninterruptedly in different directions in the volume of the material.     

Framework for application management with dynamic aspects J-EARS case study

The cost of computer system maintenance rises together with the increasing complexity of such systems. The use of an autonomic system architecture saves money by delegating some forms of maintenance to the systems themselves. The aim of this paper is to describe the results of creating a tool which introduces elements of adaptivity to Java applications using dynamic aspects. The impact of introducing aspects on the performance of various Application Servers is also discussed. Finally, benefits and problems arising from the use of the tool are presented, basing on sample use cases.