Using Unmanned Aerial Systems for Deriving Forest Stand Characteristics in Mixed Hardwoods of West Virginia

Forest inventory information is a principle driver for forest management decisions. Information gathered through these inventories provides a summary of the condition of forested stands. The method by which remote sensing aids land managers is changing rapidly. Imagery produced from unmanned aerial systems (UAS) offer high temporal and spatial resolutions to small-scale forest management. UAS imagery is less expensive and easier to coordinate to meet project needs compared to traditional manned aerial imagery. This study focused on producing an efficient and approachable work flow for producing forest stand board volume estimates from UAS imagery in mixed hardwood stands of West Virginia. A supplementary aim of this project was to evaluate which season was best to collect imagery for forest inventory. True color imagery was collected with a DJI Phantom 3 Professional UAS and was processed in Agisoft Photoscan Professional. Automated tree crown segmentation was performed with Trimble eCognition Developer’s multi-resolution segmentation function with manual optimization of parameters through an iterative process. Individual tree volume metrics were derived from field data relationships and volume estimates were processed in EZ CRUZ forest inventory software. The software, at best, correctly segmented 43% of the individual tree crowns. No correlation between season of imagery acquisition and quality of segmentation was shown. Volume and other stand characteristics were not accurately estimated and were faulted by poor segmentation. However, the imagery was able to capture gaps consistently and provide a visualization of forest health. Difficulties, successes and time required for these procedures were thoroughly noted

Compact and explicit physical model for lateral metal-oxide-semiconductor field-effect transistor with nanoelectromechanical system based resonant gate

We propose a simple analytical model of a metal-oxide-semiconductor field-effect transistor with a lateral resonant gate based on the coupled electromechanical equations, which are self-consistently solved in time. All charge densities according to the mechanical oscillations are evaluated. The only input parameters are the physical characteristics of the device. No extra mathematical parameters are used to fit the experimental results. Theoretical results are in good agreement with the experimental data in static and dynamic operation. Our model is comprehensive and may be suitable for any electromechanical device based on the field-effect transduction

Large-Scale Integration of Nanoelectromechanical Systems for Gas Sensing Applications

We have developed arrays of nanomechanical systems (NEMS) by large-scale integration, comprising thousands of individual nanoresonators with densities of up to 6 million NEMS per square centimeter. The individual NEMS devices are electrically coupled using a combined series-parallel configuration that is extremely robust with respect to lithographical defects and mechanical or electrostatic-discharge damage. Given the large number of connected nanoresonators, the arrays are able to handle extremely high input powers (>1 W per array, corresponding to <1 mW per nanoresonator) without excessive heating or deterioration of resonance response. We demonstrate the utility of integrated NEMS arrays as high-performance chemical vapor sensors, detecting a part-per-billion concentration of a chemical warfare simulant within only a 2 s exposure period

Piezoelectric nanoelectromechanical resonators based on aluminum nitride thin films

We demonstrate piezoelectrically actuated, electrically tunable nanomechanical resonators based on multilayers containing a 100-nm-thin aluminum nitride (AlN) layer. Efficient piezoelectric actuation of very high frequency fundamental flexural modes up to ~80 MHz is demonstrated at room temperature. Thermomechanical fluctuations of AlN cantilevers measured by optical interferometry enable calibration of the transduction responsivity and displacement sensitivities of the resonators. Measurements and analyses show that the 100 nm AlN layer employed has an excellent piezoelectric coefficient, d_(31)=2.4 pm/V. Doubly clamped AlN beams exhibit significant frequency tuning behavior with applied dc voltage

The structure of epitaxial V2O3 films and their surfaces : a medium energy ion scattering study

Medium energy ion scattering, using 100 keV H+ incident ions, has been used to investigate the growth of epitaxial films, up to thicknesses of ~200 Å, of V2O3 on both Pd(111) and Au(111). Scattered-ion energy spectra provide a measure of the average film thickness and the variations in this thickness, and show that, with suitable annealing, the crystalline quality is good. Plots of the scattering yield as a function of scattering angle, so-called blocking curves, have been measured for two different incidence directions and have been used to determine the surface structure. Specifically, scattering simulations for a range of different model structures show poor agreement with experiment for half-metal (….V’O3V) and vanadyl (….V’O3V=O) terminations, with and without surface interlayer relaxations. However, good agreement with experiment is found for the modified oxygen-termination structure, first proposed by Kresse et al., in which a subsurface V half-metal layer is moved up into the outermost V buckled metal layer to produce a VO2 overlayer on the underlying V2O3, with an associated layer structure of ….O3VV’’V’O3

TREEDETECTION: AUTOMATIC TREE DETECTION USING UAV-BASED DATA

In this study it is presented a toolbox built in ArcGIS using ArcPy designed to automatically detect trees in high resolution data obtained from Unmanned Aerial Vehicles (UAV). The toolbox, TreeDetection, contains a tool called TreeDetect, which requires three parameters: a raster input, a conversion factor and an output folder. Three other optional parameters can be changed to improve the detection according to characteristics of the forest and raster source. We tested the TreeDetect tool in three study sites: a young Eucalyptus plantation; adult Eucalyptus and Pinus stands; and a Mixed Hardwood natural forest. We also tested distinct raster inputs, according to the data availability in each site. The tool was considered efficient to detect the trees in the three study areas. The detection accuracy was lower in the natural stand, as expected considering the complex structure of this forest type. All the raster input rested provided satisfactory results, but in the homogeneous stand the Digital Surface Model (DSM) was not as effective as the spectral bands. Furthermore, research can be performed with emphasis in different sensors and band combinations, as well in the parameters’ selection