Volterra algorithm for modelling sea surface current circulation from satellite altimetry data

This paper was utilized a new approach for modelling sea surface current from JASON-1 satellite altimetry data. This was based on utilizing of the Volterra series expansion in order to transform the time series satellite altimetry data into a real ocean surface current. Thus,the basic equation of hydrodynamic has been solved by second order Volterra model. Then, the Volterra kernel inversion used to obtain the sea surface current velocity. The finite element model of Lax-Wendorff schemes used which was based on triangular space-time elements to map the spatial current variation in the South China Sea over different monsoon periods. In situ sea surface current measurements were collected along the east coast of peninsular Malaysia by using electromagnetic current meters. The study shows that the maximum current magnitude of 1.2 m/s was occurred during the northeast monsoon period as compared to other monsoon periods. The main noticeable feature was an existence of anticlockwise eddy in the Gulf of Thailand. The results also shows a good correlation between in situ current measurements and the Volterra-Lax-Wendrof scheme with high R2 of 0.91. It can be said that Volterra-Lax-Wendrof scheme can be used as numerical scheme for modelling sea surface current from altimetry data

Monitoring of underground coal fires using thermal infrared data

The potential utility of thermal infrared and short wavelength infrared data for detecting and mapping sub-surface high temperature sources is analysed. In this study, NOAA-9 AVHRR data and Landsat-5 TM data were used to detect and map sub-surface coal fires. Brightness temperature depicted by AVHRR band 3 illustrated high thermal anomalies in the suspected area. Due to the relatively low spatial resolution of the AVHRR data, only TM data is used in detailed analysis. The short wavelength infrared sensors (bands 5 and 7) have been used to locate the positions of the most intense burning. The thermal band (band 6) has been useful in distinguishing gross thermal anomalies from the background of solar warming, The resultant surface temperature anomalies are compared to surface temperatures derived from thermal infrared aerial survey and ground measurements. Correlation of these data indicate that the relatively coarse resolution of the thermal TM data enabled the detection, delineation and quantifying of sub-surface coal fire zones. However, the capability of the short wavelength infrared bands to locate the position of the fire fronts is only preliminary. The research shows that the information gathered from the TM data could only be used as a basis for planning the detailed ground geothermal operation. The investigation also reveals the potential capability of the AVHRR band 3 to detect sub-surface high temperature sources such as coal fires

Theory of oscillations in the STM conductance resulting from subsurface defects (Review Article)

In this review we present recent theoretical results concerning investigations of single subsurface defects by means of a scanning tunneling microscope (STM). These investigations are based on the effect of quantum interference between the electron partial waves that are directly transmitted through the contact and the partial waves scattered by the defect. In particular, we have shown the possibility imaging the defect position below a metal surface by means of STM. Different types of subsurface defects have been discussed: point-like magnetic and non-magnetic defects, magnetic clusters in a nonmagnetic host metal, and non-magnetic defects in a s-wave superconductor. The effect of Fermi surface anisotropy has been analyzed. Also, results of investigations of the effect of a strong magnetic field to the STM conductance of a tunnel point contact in the presence of a single defect has been presented.Comment: 31 pages, 10 figuers Submitted to Low. Temp. Phy

Assessment of three long-term gridded climate products for hydro-climatic simulations in tropical river basins

10.3390/w9030229Water (Switzerland)9322

3D bathymetry reconstruction from airborne topsar polarized data

This paper introduces a new methods for three-dimensional(3D) ocean bathymetry reconstruction using Airborne TOPSAR Synthetic Aperture data. The new method is based on integration between Fuzzy B-spline and Volterra algorithm. Volterra algorithm is used to simulate the ocean surface current from TOPSAR data. Then, ocean surface current information used as input for continuity equation to estimate the water depths at different locations in TOPSAR data. This study shows that 3D ocean bathymetry can be reconstructed from TOPSAR data. The maximum water depth of 20 m can be captured from TOPSAR data

Modeling sea surface current circulation from satellite altimetry data by using first order volterra model

This paper introduces a new technique for acquiring accurate sea surface current from AVISO satellite altimetry data. The new technique was involved Volterra series expansion in order to transform the time series satellite altimetry data into a real ocean surface current. The basic equation of hydrodynamic has been solved by first order Volterra model. Then, the Volterra kernel inversion used to obtain the sea surface current velocity. The finite element model of Lax-Wendorff schemes was used to model the spatial current variations in the South China Sea during March 2003, April 2004 and March 2005. In situ sea surface current measurements were collected along the east coast of peninsular Malaysia by using Valeport electro-magnetic. The result shows that the integration between Volterra model and Lax-Wendroff scheme provides a means as a complementary tool to model sea surface current variations from AVISO satellite altimetry data with r2 value of 0.910 and root mean square error (RMSE) of ±0.4 m/s

Hopfield neural network for sea surface current tracking from Tiungsat-1 data

This paper introduces a new approach for neural network application to coastal studies. The method is based on the utilization of the Hopfield neural network to model sea surface current movements from single TiungSAT-1 image. In matching process using Hopfield neural network, identified features have to be mathematically compared to each other in order to build an energy function that will be minimized. In this context, the neuron network has been taken in two dimensions; raw and column in order to match between the similar features of surface pattern. It was required that the two features were extracted from the same location. The Euler method is used to minimized the energy function of neuron equation. The study shows that the surface current features such as structure morphology of water plume can be automatically detected. In TiungSAT-1 data, green and near-infrared bands were competent at sea surface current features detection with high accuracy speed of ±0.14 m/s. It can be said that, Hopfield neural network has highly promised feature enhancement and detection in optical satellite sensor such as TiungSAT-1 image. In conclusion, Hopfield neural network can be used advance computational tool for modeling the pattern movement of sea surface in satellite data

Quasi linear algorithm for modelling shoreline change from AIRSAR/POLSAR polarized data

This paper presents a new approach for modeling shoreline change due to wave energy effects from remotely sensed data. The airborne AIRSAR and POLSAR data were employed to extract wave spectra information and integrate them with historical remotely sensed data such as aerial photography data to model the rate of change of the shoreline. A partial differential equation (PDF) of wave conversation model was applied to investigate the wave refraction patterns. The volume of sediment transport at several locations was estimated based on the wave refraction patterns. The shoreline change model developed was designed to cover a 14 km stretch of shoreline of Kuala Terengganu in peninsular Malaysia. The model utilized data from aerial photographs, AIRSAR, POLSAR and ERS-2 and in situ wave data. The results showed that the shoreline change rate modeled from the quasi-linear wave spectra model has a significant relationship with one modeled from historical vector layers of aerial photography, AIRSAR and POLSAR data. With the quasi-linear model an error of ± 0.18 m/year in shoreline change rate determination was obtained with Cvv band. According to the above prospective, small polarized microwave sensor mounts on satellite platform might be provided similar out put results for shoreline change predictions. In fact, microwave spectra can be used with such tropical climate circumstances of cloud covers due to its longer wavelength and its polarization properties. As different polarization behaviour enable to study several coastal problems such as wave- current interaction, and wave-shoreline interaction