Double optimal density gradients for harmonic generation from relativistically oscillating plasma surfaces

The influence of plasma density gradients on the harmonic generation process from relativistically oscillating mirror (ROM) is studied experimentally. It is observed that the harmonic intensities from orders of 21 st to 24 th first drop and then reach the maximum value with the increase of plasma scale length L. 2D particle-in-cell simulations are performed to investigate the intensities of high-order harmonics at different L values, which show that there are two optimal scale lengths Lopt for efficient ROM harmonic generation. The two optimal Lopt values are interpreted by a quasi-1D analytical model. By matching the potential energies provided by laser pulse and charge displacement in the plasma with an exponential distributed density profile, the model can quantitatively predict the optimal Lopt at the given laser incidence angle and intensity. Our work is beneficial for better understanding the role of L in ROM harmonic generation and the parameters affecting the optimal Lop

Spectral volume index creation and performance evaluation: A preliminary test for tree species identification

To fully mine information regarding differences among various tree species from remote sensing data and improve the accuracy of tree species recognition, this study utilized the spectral reflection value, wavelength, and time as parameters and employed three algorithms to create an expression for the spectral volume index (SVI). Then, data were obtained by applying RedEdge-MX to four phases, SVI features were extracted, and a mixed feature set of spectral band + texture + digital surface model + SVI was constructed. A random forest algorithm was employed to determine the importance of the SVI features and derive the optimal feature set for tree species classification. The additional objectives were to determine if the SVI features have an active role in tree species classification and which algorithm is more conducive for extracting useful SVI features. The SVI features extracted with volume constraints exhibit better performance in tree species recognition than those extracted without volume constraints. Moreover, the SVI features extracted using a variable-constrained volume were better than those extracted using a constant-constrained volume. The combination of SVI features could improve the accuracy of tree species recognition (the highest overall accuracy was 92.76%), but the improvement effect was limited (the value was 92.16% when SVI features were not combined). These findings show that the SVI obtained using this method could be used to mine the difference information of tree species in images to a certain extent and hence, could be used in tree species identification

Effectiveness of the spectral area index created by three algorithms for tree species recognition

Abstract Key message Tree species identification analysis of the two images (Luoyang and Hohhot of China) shows that the polygonal area indices extracted by the specific band-constrained polygon relative area (algorithm 3, obtained accuracy was ~ 13% higher than that of other algorithms in WorldView-3 and ~ 2% higher in WorldView-2) can effectively improve the classification accuracy of tree species compared to those with a constant polygon relative area constraint (algorithm 2) and without area constraint (algorithm 1) (equal accuracy was obtained by algorithms 1 and 2 in each data). Context Solving the problem of tree species identification by remote sensing technology is an international issue. Exploring the improvement of tree species recognition accuracy through multiple methods is currently widely attempted. A previous study has indicated that mining the differential information of various tree species in images using area differences of the polygons formed by tree species spectral curves and creating the polygon area index can improve tree species recognition accuracy. However, this study only created two such indices. Thus, a general model was developed to extract more potential polygon area indices and help tree species classification. However, the improvement of this model using a constant and a specific band to constrain the relative area of polygons still needs to be fully studied. Aims To obtain new algorithms for extracting polygon area indices that can mine the differential information of tree species and determine the index that is the most effective for tree species classification. Methods By unconstraining the area of polygons and constraining the relative area of polygons with constant and specific bands, three formulations of polygon area indices were created. Polygon area indices were extracted from WorldView-3 and WorldView-2 imagery based on three algorithms and combined with textures and spectral bands to form three feature sets. Random forest was used to classify images and rank the importance of features in the feature sets, and the effectiveness of the polygon area indices extracted by each algorithm in tree species recognition was analysed in accordance with their performance in the classifications. Results The proportion of polygon area index in the optimal feature sets ranged from 36.4 to 63.1%. The polygon area indices extracted with constant constrained polygon relative area and those without area constraint have minimal effect on tree species classification accuracy. Meanwhile, the polygon area indices extracted by the algorithm of specific band-constrained polygon relative area could remarkably improve tree species recognition accuracy (compared with spectral bands, WorldView-3 and WorldView-2 improved by 9.69% and 4.19%, respectively). Conclusion The experiments confirmed that polygon area indices are beneficial for tree species classification, and polygon area indices extracted by specific band-constrained polygon relative area play an important role in tree species identification

Monitoring vegetation coverage in Tongren from 2000 to 2016 based on Landsat7 ETM+ and Landsat8

Abstract Vegetation coverage is an important indicator in regional ecological environment monitoring and plays a key role in its quality assessment. We consider Landsat7 ETM+ in 2000 and Landsat8 in 2016 as data sources using a different time phase partial image substitution method to eliminate cloud effects and an NDVI dimidiate pixel model to invert the vegetation coverage of the two time phases. We further classify them into five grades, provide statistics and analyse the areas of different grades at different time periods, while monitoring the spatial evolution of vegetation coverage over the past 16 years in Tongren. Experimental results showed that: (1) the different time phase partial image substitution method could reduce the influence of clouds on vegetation extraction; (2) in Tongren, the vegetation coverage area was decreased from 17,300.1 km2 to 17,224.8 km2 (i.e. decreased by 75.3 km2); (3) the areas of grade I and V increased by 0.42% and 15.08%, respectively, whereas the areas of grade II, III and IV decreased by 3.15%, 6.98% and 5.37%, respectively, which indicates that most of the area containing lower amount of vegetation gradually altered into an area containing a higher coverage of vegetation, whereas a few areas became bare land; and (4) the vegetation areas decreased due to expansion of cities and construction of dams, while vegetation increased due to the cultivation of crops and trees. Research shows that the overall evolution of vegetation coverage in Tongren is considerably good. However, while undertaking future development in the mountainous Karst region, one should be aware of the land’s intensive use and environmental protection

Atomistic Study of Mechanical Behaviors of Carbon Honeycombs

With an ultralarge surface-to-volume ratio, a recently synthesized three-dimensional graphene structure, namely, carbon honeycomb, promises important engineering applications. Herein, we have investigated, via molecular dynamics simulations, its mechanical properties, which are inevitable for its integrity and desirable for any feasible implementations. The uniaxial tension and nanoindentation behaviors are numerically examined. Stress–strain curves manifest a transformation of covalent bonds of hinge atoms when they are stretched in the channel direction. The load–displacement curve in nanoindentation simulation implies the hardness and Young’s modulus to be 50.9 GPa and 461±9 GPa, respectively. Our results might be useful for material and device design for carbon honeycomb-based systems

A Review of Current Development of Graphene Mechanics

Graphene, a two-dimensional carbon in honeycomb crystal with single-atom thickness, possesses extraordinary properties and fascinating applications. Graphene mechanics is very important, as it relates to the integrity and various nanomechanical behaviors including flexing, moving, rotating, vibrating, and even twisting of graphene. The relationship between the strain and stress plays an essential role in graphene mechanics. Strain can dramatically influence the electronic and optical properties, and could be utilized to engineering those properties. Furthermore, graphene with specific kinds of defects exhibit mechanical enhancements and thus the electronic enhancements. In this short review, we focus on the current development of graphene mechanics, including tension and compression, fracture, shearing, bending, friction, and dynamics properties of graphene from both experiments and numerical simulations. We also touch graphene derivatives, including graphane, graphone, graphyne, fluorographene, and graphene oxide, which carve some fancy mechanical properties out from graphene. Our review summarizes the current achievements of graphene mechanics, and then shows the future prospects