In the last few years, ALOS/PALSAR (L-band) (HH, HV, VH and VV) images have been widely used due toits ability to penetrate the surface in certain conditions for example of low moisture or dry friable sandysoil. Images from ALOS-1 sensor have been applied to delineate subsurface structures. Optical imagessuch as Landsat-7 ETM+ data are used to discriminate between scatterings from earth surface andsubsurface materials. Thus, Farafra desert is an optimal environment for L-band microwave penetration.Therefore, this research involves mapping and interpretation of lineaments, surface and subsurfacestructures. The interested four spots at Farafara sand sheets display many structures that not have beentraced in the Egyptian official geological maps. Speckle noise is found in radar images due to many reasons, for example, when an object stronglyreflected between itself and the spacecraft causing noise. Refined LEE Filter (RLF) is applied for specklenoise reduction; speckle noise near strong edges is not strongly filtered, leaving the center of the pixelunfiltered, so, this procedure is an essential step in processing of polarimetric data to improve theaccuracy of the data and enhance resolution. ALOS/PALSAR data are processed into circular polarizationfor providing the best viewing of morphological and subsurface lineaments. The ellipse shape governed bytwo axes; semi-major axis ‘a’ and semi-minor axis ‘b’. Orientation angle(ψ) is measured frompositive horizontal axis X counter clockwise direction, orientation angle range from 0° to 180°. Ellipticity(χ) is a shape parameter defined by the degree of oval shape, defined by χ=arctanb/a and can takevalues between -45° to +45°. As, the circular polarization yielded best outputs of subsurface structure indifferent trends, full polarimetric ALOS/PALSAR images (PLR) are transformed into circular polarization, bychanging both angles into orientation angle ψ=0° and elliptical angle χ=45°. Full polarimetric images arerepresented in Pauli RGB. Landsat-7 ETM+ data are freely uploaded with the same date and location ofALOS/PALSAR images. Bands 1, 2, 3, 4, 5 and 7 are merged together, then bands (R:2, G:4, B:7) arechanged to obtain best spatial resolution. Landsat-7 images have some gap areas, which is essentially befilled with Landsat-7 data acquired at the same time of the year by histogram matching technique to fillthe missed pixels of the interested target scenes according to Landsat 7. The obtained rose diagramshows two trends of dominant and secondary; the most dominant direction is North West (NW 330°),while the secondary trend is North (North 10°). This result is confirmed by the field survey. The dominantdirection of lineaments extracted from ALOS/PALSAR images is well fitted with the secondary direction ofthe geological structure in the study area. This work represents a stage of achievement in detecting buried lineaments covered by sand sheets byusing ALOS/PALSAR and Landsat-7 ETM+. Surface and subsurface

Infrasound waves can be defined as the sound waves with frequency range from 0.003 to 20 Hz. Kochi University of Technology (KUT) Infrasound Sensor Network contains 30 infrasound sensors which are distributed all over Japan, a large number of sensors are located in Shikoku Island, all infrasound stations installed with accelerometers to measure the peak ground acceleration (PGA) which can be a good detector for infrasound sources occur on or under the ground like earthquakes. Many earthquakes detected by our network after establishing of the network since 2016. In this study we will focus on all the possibilities for infrasound detection from earthquakes using KUT sensor network and International Monitoring system (IMS) stations for the earthquakes which were detected in southern of Japan during 2019. The selected events for this study are recorded in different international databases; Reviewed Event Bulletin (REB) database of International Data Center (IDC) , Japan Meteorological Agency (JMA) and United States Geological Survey (USGS). There are different scenarios for infrasound coupling from earthquakes one of these scenarios is the conversion of seismic waves to acoustic from the generated T-phases of oceanic earthquakes. On 09 of May 2019, at 23:48:00 UTC an earthquake with magnitude 6.0 mb happened in west of Kyushu Island and infrasound sensors recorded a clear P-waves, However station K53 and I30JP recorded infrasound waves at distances ranges between 850 to 870 km, In addition to T-phases well-recorded from the earthquake in H11N station near Wake island at 3750 km from the event. Progressive multi-channel cross correlation method applied on both infrasound and hydroacoustic data to identify the arrival phases and the back-azimuth of the waves from station to the source. Moreover, infrasound propagation simulation applied to the event to confirm the infrasound arrivals. Ground to Space Model (AVO-G2S) used with HWM-14 and NRL-MSISE to construct the atmospheric profile for higher altitudes up to 180 km over the event area, furthermore the 3d ray tracing process and the calculation of the transmission loss equation by normal modes and parabolic equation methods applied. In conclusion this study shows the earthquake detectability from infrasound waves using local infrasound sensors for the largest earthquakes occurred in southern of Japan during 2019. Many parameters control the generation of infrasound from earthquakes; magnitude, depth, mechanism and the topographic features. In addition to the T-phases generation through the SOFAR layer can be an evidence of seismic conversion to sound for the oceanic earthquakes as occurred on the earthquake of 09 May 2019, after applying the propagation simulation with (AVO-G2S) model on this earthquake the tropospheric arrivals confirmed and the calculated celerities well-correlated with the real detected data .

We investigate ionospheric disturbances using the total electron content (TEC) data retrieved by the three satellites after the foreshock of the 2011 Tohoku Earthquake on 9 March 2011. Co-seismic ionospheric disturbances (CIDs) appeared to extend from an onset point concentrically in all of the satellite data. We have found, however, that the geographic coordinates of the onset points did not coincide if the observed CIDs were assumed to occur at one altitude. Admitting that the altitudes of the onset points are different, we searched for coinciding geographic coordinates of the onset points using the two data sets by changing the altitudes and identified the altitude of the two onset points at 155.4 and 234.9 km, and the onset time at these altitudes. As a result, the vertical velocity of acoustic wave is estimated to be 1.04 km/s from the travel time between the altitudes of 155.4 and 234.9 km. This is 1.4 times higher than the sound velocity calculated using the empirical model NRLMSISE-00. The present study provides a method of determining the source location of the acoustic wave from the ionospheric TEC analysis without using the seismic data.