Modulational instability of ion-acoustic waves in a plasma with two-temperature kappa-distributed electrons

Existence and characteristics of ion-acoustic (IA) wave modulation are studied in a plasma with two-temperature electron satisfying kappa distribution. Based on the multiple time scales perturbation, a nonlinear Schrödinger equation (NLS) is derived. Similar to the case of double Maxwellian electrons, both polarities of envelope soliton can exist over restricted ranges of the fractional hot electron density ratio and two-temperature superthermal electrons. The transition from stable dark solitons to unstable bright ones shifts to the smaller wavelength regions in the presence of cool and hot superthermal electrons. It is shown that the small values of the hot electron populations leads to shrinking the modulation instability region. It is also found the instability growth rate reduces due to the presence of hot electrons. The result of present investigation contributes to the physics of wave modulation in Saturn’s magnetosphere where two-temperature electrons with kappa distribution exist.     

Speckle filtering of Synthetic Aperture Radar images using filters with object-size-adapted windows

Speckle degrades the radiometric quality of a Synthetic Aperture Radar (SAR) image. Previous methods for speckle reduction have used a fixed-size window for filtering the entire image. This, however, may not be effective for the entire image, as land covers of different sizes require different filtering windows. In this paper, a novel method is proposed by which each pixel in the image is filtered with a window appropriate for the size of object within it. The real in-phase and the imaginary quadrature components of the SAR images determine the best window size and the pixels in the intensity image are filtered using their own optimal windows. The proposed method is presented for both single- and multi-polarized SAR images, and the results of several common filters that were modified are presented. This approach is applied to two RADARSAT-2 images: one over San Francisco, California, USA and the other over St. John’s, Newfoundland and Labrador, Canada, producing results that were similar to, or outperformed, comparable filters while retaining details and suppressing speckle effectively. While the method was successful for single-look intensity data, it offers great potential for multi-look and amplitude data as well.     

Simulation of land subsidence using finite element method: Rafsanjan plain case study

Land subsidence caused by the excessive use of groundwater resources has caused serious damage to Rafsanjan area. In this study, using finite element method, a 2D plain strain simulation of land subsidence has been conducted. A linear elastic constitutive law has been used for the simulation of the soil material skeleton. Actual water level during the analysis period has been modeled via specifying nodal water pressure at piezometer wells situation. The solution procedure consists of two parts. First, an initial static analysis is carried out in order to find initial steady-state solution for the pore pressure and stress distribution. Then, the above solution is used as initial condition for dynamic computation of consolidation equations during pumpage period. Tectonic effect has been considered as a rigid body motion. Numerical results showed that if the rate of pumpage remains constant in the future, settlement due to water withdrawal near Rafsanjan city will reach up to 110 cm by the year 2022.     

Wetland classification in Newfoundland and Labrador using multi-source SAR and optical data integration

A vast portion of Newfoundland and Labrador (NL) is covered by wetland areas. Notably, it is the only province in Atlantic Canada that does not have a wetland inventory system. Wetlands are important areas of research because they play a pivotal role in ecological conservation and impact human activities in the province. Therefore, classifying wetland types and monitoring their changes are crucial tasks recommended for the province. In this study, wetlands in five pilot sites, distributed across NL, were classified using the integration of aerial imagery, Synthetic Aperture Radar, and optical satellite data. First, each study area was segmented using the object-based method, and then various spectral and polarimetric features were evaluated to select the best features for identifying wetland classes using the Random Forest algorithm. The accuracies of the classifications were assessed by the parameters obtained from confusion matrices, and the overall accuracies varied between 81% and 91%. Moreover, the average producer and user accuracies for wetland classes, considering all pilot sites, were 71% and 72%, respectively. Since the proposed methodology demonstrated high accuracies for wetland classification in different study areas with various ecological characteristics, the application of future classifications in other areas of interest is promising.