Power spectrum techniques were applied to two time series of wind speed values recorded at the Arctowski Station in order to investigate the influence of turbulent and laminar air flow on the quasi-periodicity of the micro-scale wind structure.

Satellite remote sensing provides a synoptic view of the land and a spatial context for measuring drought impacts, which have proved to be a valuable source of spatially continuous data with improved information for monitoring vegetation dynamics. Many studies have focused on detecting drought effects over large areas, given the wide availability of low-resolution images. In this study, however, the objective was to focus on a smaller area (1085 km2) using Landsat ETM+ images (multispectral resolution of 30 m and 15 m panchromatic), and to process very accurate Land Use Land Cover (LULC) classification to determine with great precision the effects of drought in specific classes. The study area was the Tortugas-Tepezata sub watershed (Moctezuma River), located in the state of Hidalgo in central Mexico. The LULC classification was processed using a new method based on available ancillary information plus analysis of three single date satellite images. The newly developed LULC methodology developed produced overall accuracies ranging from 87.88% to 92.42%. Spectral indices for vegetation and soil/vegetation moisture were used to detect anomalies in vegetation development caused by drought; furthermore, the area of water bodies was measured and compared to detect changes in water availability for irrigated crops. The proposed methodology has the potential to be used as a tool to identify, in detail, the effects of drought in rainfed agricultural lands in developing regions, and it can also be used as a mechanism to prevent and provide relief in the event of droughts.

Position time series from permanent Global Navigation Satellite System (GNSS) stations are commonly used for estimating secular velocities of discrete points on the Earth’s surface. An understanding of background noise in the GNSS position time series is essential to obtain realistic estimates of velocity uncertainties. The current study focuses on the investigation of background noise in position time series obtained from thirteen permanent GNSS stations located in Nepal Himalaya using the spectral analysis method. The power spectrum of the GNSS position time series has been estimated using the Lomb–Scargle method. The iterative nonlinear Levenberg–Marquardt (LM) algorithm has been applied to estimate the spectral index of the power spectrum. The power spectrum can be described by white noise in the high frequency zone and power law noise in the lower frequency zone. The mean and the standard deviation of the estimated spectral indices are −1.46±0.14,−1.39±0.16 and −1.53±0.07 for north, east and vertical components, respectively. On average, the power law noise extends up to a period of ca. 21 days. For a shorter period, i.e. less than ca. 21 days, the spectra are white. The spectral index corresponding to random walk noise (ca. –2) is obtained for a site located above the base of a seismogenic zone which can be due to the combined effect of tectonic and nontectonic factors rather than a spurious monumental motion. Overall, the usefulness of investigating the background noise in the GNSS position time series is discussed.

The behaviour of energy levels and optical spectra of a charged particle (electron or hole) confined within a potential well of ellipsoidal shape is investigated as a function of the shape-anisotropy parameter. If two energy levels of the same symmetry intersect in a perturbation-theory approximation, they move apart on direct diagonalization of the appropriate Hamiltonian. The intersection of the energy levels leads to a discontinuity of the corresponding dipole-moment matrix element. The discontinuity of matrix elements is not reflected in the behaviour of transition probabilities which are continuous functions of the shape-anisotropy parameter. The profiles of a spectral line emitted or absorbed by an ensemble of ellipsoidally shaped nanoparticles with a Gaussian distribution of size are calculated and discussed.

Solar radiation reflectance was analysed to characterize Arctic ornithogenic tundra developing in the vicinity of large breeding colony of Brunnich‘s guillemots Uria lomvia and kittiwakes Rissa tridactyla at the foot of Gnĺlberget cliff (Hornsund, SW Spitsbergen). Radiometric method was found to be a useful tool for studying structure and functioning of plant formations. We measured reflectance of four wavelengths: 554 nm (YG), 655 nm (RED), 870 nm (NIR) and 1650 nm (SWIR) at 10 plots situated along the transect running from the colony to the sea. Moreover, data of plant community character, species quantitative composition as well as total biomass were collected to relate these parameters with the spectral values. The results showed that radiometric data characterized vegetation well enough to recognize the same plant communities on the basis of spectral reflectance as distinguished with traditional phytosociological methods.

In order to solve the problem of large error of delay estimation in low SNR environment, a new delay estimation method based on cross power spectral frequency domain weighting and spectrum subtraction is proposed. Through theoretical analysis and MATLAB simulation, among the four common weighting functions, it is proved that the cross-power spectral phase weighting method has a good sharpening effect on the peak value of the cross-correlation function, and it is verified that the improved spectral subtraction method generally has a good noise reduction effect under different SNR environments. Finally, the joint simulation results of the whole algorithm show that the combination of spectrum subtraction and crosspower spectrum phase method can effectively sharpen the peak value of cross-correlation function and improve the accuracy of time delay estimation in the low SNR environment. The results of this paper can provide useful help for sound source localization in complex environments.

In this study, the temperature influence on the spectral responsivity of a Light Emitting Diode (LED) used as a photoreceptor, combined to light source spectrum is correlated to electrical characteristics in order to propose an alternative method to estimate LED junction temperature, regardless of the absolute illumination intensity and based on the direct correlation between the integral of the product of two optical spectra and the photo-generated currents. A laboratory test bench for experimental optical measurements has been set in order to enable any characterizing of photoelectric devices in terms of spectral behaviour, in a wavelength range placed between 400–1000 nm, and of current-voltage characteristics as function of temperature by using two different illumination sources. The temperature is analysed in a range from 5°C up to 85°C, so as to evaluate thermal variation effects on the sensor performance. The photo-generated current of two LEDs with different peak wavelengths has been studied. Research has observed and mathematically analysed what follows: since the photo-generated current strictly depends on the combination between the spectral response of the photoreceptor and the lighting source response, it becomes possible to estimate indirectly the junction temperature of the LEDs by considering the ratio between the photogenerated currents obtained by using two different illumination sources. Such results may for one thing increase knowledge in the fields where LEDs are used as photo-detectors for many applications and for another, they could be extended to generic photodetectors, thus providing useful information in photovoltaic field, for instance.