Indonesia is periodically affected by severe volcanic eruptions and earthquakes, which are geologically coupled to the convergence of the Australian tectonic plate beneath the Sunda Plate. Multi-temporal SAR interferometry (MTI) can be used to support studying and modelling of terrain movements. This work is aimed at performing an analysis of ground displacements over Indonesian sites through MTI techniques. Test sites have been selected according to the availability of archived SAR data, GNSS networks, and geological data. A stack of COSMO-SkyMed data, acquired in stripmap mode between 2011 and 2015, has been selected over the Banda Aceh region in Sumatra island. Geological maps of the test sites are available, and several GNSS stations from the Continuously Operating Reference Stations Indonesian network are found in the area of interest. Both the SPINUA and the StaMPS MTI algorithms have been used for processing the data, and deriving displacement maps. The ground deformations detected on the area are interpreted according to the available geological and geophysical information. The MTI results seem to confirm the inactivity of the Aceh fault segment, while the lack of coherent targets hinders reliable displacement measurements along the Seulineum segment. MTI data additionally allowed to identify local, non-tectonic ground instabilities: several areas are affected by subsidence due to unconsolidated coastal and alluvial sediments, deserving more investigations by local authorities. Finally, MTI results could be useful to integrate and update data from the existing GPS network.

Spaceborne X-band synthetic aperture radars (SARs) represent a well-established tool for Earth remote sensing at very high spatial resolution (order of meters). Until now, SAR has not been exploited for hydrological cycle modelling and numerical weather forecast, however, there are scientific evidences that at X band and beyond: i) atmospheric precipitation in liquid and ice phase affect SAR imagery and its intensity can be retrieved, ii) snow areal extent and mass (water-equivalent) can be detected and estimated. KydroSAT mission concept foresees a miniaturised fully-digital SAR at Ku and Ka band (KydroSAR), specifically devoted to detecting and estimating atmospheric precipitation and surface snow; its baseline includes dual-polarization capability, high orbit duty cycle (>75%), flexible ground resolution (5-150 m), and a large variable swath (50-150 km), doubled with formation of two minisatellites both carrying a KydroSAR. Moreover, the mission concept foresees the along-track convoy with the COSMO-SkyMed and SAOCOM SAR platforms, allowing the observation of the same scene at L, X, Ku and Ka bands. The challenging requirements of this architecture require the development of new technologies such as Digital Beam Forming and Direct Digital to RF Conversion. In order to exploit the synergic approach of the KydroSAT convoy for precipitation, in this work we will simulate and discuss the SAR response at X, Ku and Ka bands of the same scene, using the SAR forward model described in Mori et al. (2017). Subsequently, an example retrieval of Snow Equivalent Water (SWE) by Ku-SAR will be given.

The heavy rain occurred in Hiroshima city on 20 August 2014. Then, debris flows and shallow slides were induced by the heavy rain. Rapid damage assessment after natural disasters is crucial for initiating effective emergency response actions. Synthetic Aperture Radar (SAR) has a great potential due primarily to its all-weather day-and- night imaging capabilities. In this study, we examined an extraction of damaged area caused by debris flows using three COSMO-SkyMed images. The extraction methods are interferometric coherence, intensity correlation and normalized difference sigma nought index (NDSI) calculated from COSMO-SkyMed image pair. In this study, we investigated the applicability of the methods for extraction of damaged area caused by debris flows. The single look complex data of COSMO-SkyMed were co-registered each other for calculating interferometric coherence. The interferometric coherence images were ortho-rectified using 10 m gridded Digital Elevation Model (DEM) generated by the Geospatial Information Authority of Japan (GSI). The intensity correlation and NDSI were calculated from ortho-rectified images. For damaged area extraction, we investigated the mean and standard deviation of interferometric coherence, intensity correlation and NDSI using pre- and co-disaster image pairs. The mean values derived from the three methods in damaged area almost increased between pre- and co-disaster images. As a result, NDSI in damaged area indicated good separation between pre- and co-disaster images. In conclusion, NDSI showed good capability for extraction of damaged area caused by the debris flows at a rapid disaster response phase.

Ground Based Interferometric Radar (GBInRad) is a class of terrestrial remote sensing imaging system, based on microwave interferometric techniques. The principal application of GBInRad system is deformation monitoring, since respect to other techniques they can provide remote sensing, high sensitivity to small deformations, long range of measurements, imaging capability and fast scan time. The main limitation of standard GBInRad system is their capability of detecting movements only along the Line of Sight (LoS) of the sensor, although actual targets may show deformations in any direction of space; this represents an important limitation with respect to other techniques able to estimate the full 3D deformation vector. If the displacement direction is not known a priori, combining together LoS displacement measured from different spatial positions, it is possible to reconstruct the actual 3D displacement vector of monitored targets. In this paper are introduced and analysed the various aspect of the displacement vector measurement with multiple GBInRad system that work both in a monostatic and in a bistatic configuration. In the monostatic configuration every system transmits and receives the signal independently from the others; this approach requires multiple GBInRad system deployed to monitoring the same scenario and therefore its main limitations lie in the costs, power consumption and maintenance. A possible cost-effective evolution of the monostatic configuration is to exploit GBInRad system in a multiple bistatic configuration; a multiple bistatic Radar is a system in which a transmitter operates together with multiple receivers located in different positions in space. In this paper, the deformation vector measurement by means of bistatic GBInRad is proposed.

In this work, a second-order phase approximation is introduced to provide an improved analytical model of the signal received in forward scatter radar systems. A typical configuration with a rectangular metallic object illuminated while crossing the baseline, in far- or near-field conditions, is considered. An improved second-order model is compared with a simplified one already proposed by the authors and based on a paraxial approximation. A phase error analysis is carried out to investigate benefits and limitations of the second-order modeling. The results are validated by developing full-wave numerical simulations implementing the relevant scattering problem on a commercial tool.

Flood disaster is one of the heaviest disasters in the world. It is necessary to monitor and evaluate the flood disaster in order to mitigate the consequences. As floods do not recognize borders, transboundary flood risk management is imperative in shared river basins. Disaster management is highly dependent on early information and requires data from the whole river basin. Based on the hypothesis that the flood events over the same area with same magnitude have almost identical evolution, it is crucial to develop a repository database of historical flood events. This tool, in the case of extended transboundary river basins, could constitute an operational warning system for the downstream area. The utility of SAR images for flood mapping, was demonstrated by previous studies but the SAR systems in orbit were not characterized by high operational capacity. Copernicus system will fill this gap in operational service for risk management, especially during emergency phase. The operational capabilities have been significantly improved by newly available satellite constellation, such as the Sentinel-1A AB mission, which is able to provide systematic acquisitions with a very high temporal resolution in a wide swath coverage. The present study deals with the monitoring of a transboundary flood event in Evros basin. The objective of the study is to create the “migration story” of the flooded areas on the basis of the evolution in time for the event occurred from October 2014 till May 2015. Flood hazard maps will be created, using SAR-based semi-automatic algorithms and then through the synthesis of the related maps in a GIS-system, a spatiotemporal thematic map of the event will be produced. The thematic map combined with TanDEM-X DEM, 12m/pixel spatial resolution, will define the non- affected areas which is a very useful information for the emergency planning and emergency response phases. The Sentinels meet the main requirements to be an effective and suitable operational tool in transboundary flood risk management.

The use of ground return signals is investigated for checks on the calibration of power measurements of a polarimetric C-band radar. To this aim, a peculiar permanent single scatterer (PSS) consisting of a big metallic roof with a periodic mesh grid structure and having a hemisphere-like shape is considered. The latter is positioned in the near-field region of the weather radar and its use, as a reference calibrator, shows fairly good results in terms of reflectivity and differential reflectivity monitoring. In addition, the use of PSS indirectly allows to check for the radar antenna de-pointing which is another issue usually underestimated when dealing with weather radars. Because of the periodic structure of the considered PSS, simulations of its electromagnetic behavior were relatively easy to perform. To this goal, we used an electromagnetic Computer-Aided-Design (CAD) with an ad-hoc numerical implementation of a full-wave solution to model our PSS in terms of reflectivity and differential reflectivity factor. Comparison of model results and experimental measurements are then shown in this work. Our preliminary investigation can pave the way for future studies aiming at characterizing ground-clutter returns in a more accurate way for radar calibration purposes.

The results of application of microwave and optical satellite data for soil moisture (SM) assessment are presented. The research has been carried out from 2015 to 2016 at Biebrza Wetlands test site located in North-East Poland, designated by Ramsar Convention as Wetlands of International Importance. A regression models based on Sentinel-1 backscattering coefficients (σ°) have been developed to generate the soil moisture (SM) maps over Biebrza Wetlands. The optical data from Sentinel-2 have been used for the classification of wetlands vegetation habitats to improve SM predictions. The wetland vegetation differed, there were reeds, sedge-moss, sedges, grass-herbs, and grass. The majority of the changes occurred in moist habitats, while anthropogenic appeared more stable during study period. The observed changes were referred to moving/grazing changes and weather effects causing droughts/floods. SM differed from 30% during the drought season in 2015 to 95% in the wet season in 2016. It has been examined the impact of biomass and SM on microwave signal under changing soil moisture and vegetation growth conditions. Vegetation biomass has been characterized by measured in-situ LAI and by vegetation indices calculated from Sentinel-2, Terra MODIS data. The impact of SM and LAI on σ° calculated from Sentinel-1 data showed that LAI dominates the influence on σ° when SM is low. The analysis have been done to estimate the threshold of the SM values which dominate the backscatter. This study demonstrates the capability of Sentinel-1/2 data to estimate SM, offering an important advantage for wetlands monitoring.

The main scope of this study is to investigate the potential correlation between land cover and ground vulnerability over Alexandria city, Egypt. Two different datasets for generating ground deformation and land cover maps were used. Hence, two different approaches were followed, a PSI approach for surface displacement mapping and a supervised classification algorithm for land cover/use mapping.

The interferometric results show a gradual qualitative and quantitative differentiation of ground deformation from East to West of Alexandria government. We selected three regions of interest, in order to compare the obtained interferometric results with the different land cover types. The ground deformation may be resulted due to different geomorphic and geologic factors encompassing the proximity to the active deltaic plain of the Nile River, the expansion of the urban network within arid regions of recent deposits, the urban density increase, and finally the combination of the above mentioned parameters.

The 2016 Kumamoto earthquake sequence started with a Mj (Japan Meteorological Agency magnitude) 6.5 event on 14 April, and culminated in a Mj 7.3 event on 16 April. Rapid damage assessment after natural disasters is crucial to fast crisis response. Synthetic aperture radar (SAR) interferometric analysis has a great potential due primarily to its phase difference. In this study, we demonstrated the applicability of interferometric coherence from SAR images for detection of building damages and liquefactions caused by the earthquake. Three ALOS-2/PALSAR-2 data acquired on 30 November, 2015, 7 March, 2016 and 18 April, 2016 were used. The interferometric coherence was calculated within several moving window pixels from pre- and post-disaster PALSAR-2 images. For damage assessment, normalized difference (ND) of interferometric coherence was calculated using pre- and co-disaster SAR image pairs. For validation, we adopted a map of estimated number of collapsed buildings calculated by the National research Institute for Earth science and Disaster resilience, Japan (NIED). The estimation map shows seven ranking of collapsed buildings within 250 m × 250 m area. The averaged ND of interferometric coherence indicates the trend of increase with corresponding to the increase of the estimated number of collapsed buildings. In addition, ND of interferometric coherence image showed liquefaction as a high value in urban areas. The distribution pattern was in good agreement with a liquefaction map referred to literatures. These results indicate the possibility of rapid damage mapping after the earthquake for fast crisis response using SAR interferometric coherence.

This paper presents a spatiotemporal study of surface subsidence over urban area due to coal mining using Persistent scatterer interferometry. In the past few years Differential Interferometric Synthetic Aperture Radar has emerged as a very useful remote sensing technique for measuring land subsidence. It plays a vital role in insitu subsidence prediction of coal mining area. However there are some limitation viz. atmospheric decorrelation, temporal decorrelation and spatial decorrelation with conventional D-InSAR techniques, which can be overcome up to certain extent by using multiinterferogram framework approach. The Persistent Scatterer interferometry technique comprises of more number of SAR datasets, it only concentrates over the pixel which remain coherent over long time period. Persistent Scatterer interferometry makes deformation measurement on permanent scattering location for the targeted ground surface. Mainly, these permanent scatterer are manmade features like metallic bridges, dams, antennae roof of buildings etc. apart that some permanent scatterer may comprise of prominent stable natural targets. The results obtained from PS-InSAR gives more precised measurement of surface deformation. Total eight ALOS PALSAR scenes covering the time period from 2007 to 2010 have been utilized to produce ground deformation map using PSInSAR techniques for Jharia Coal field, Dhanbad. This is proven technique, which helps to identify the persistent land surface movement .The results were analyzed Sijua area in Jharia coalfield. The subsidence fringes were demarcated over the entire study area. The PSInSAR results were validated using precision leveling data provided by mining authorities. The results demonstrates that PSInSAR can be used as potential tool to highlight the subsidence prone area depending upon the spatial and temporal coherency of SAR data.

The sea surface salinity (SSS) can be measured from space by using L-band (1.4 GHz) microwave radiometers. The L-band has been chosen for its sensitivity of brightness temperature to the change of salinity. However, SSS remote sensing is still challenging due to the low sensitivity of brightness temperature to SSS variation: for the vertical polarization, the sensitivity is about 0.4 to 0.8 K/psu with different incident angles and sea surface temperature; for horizontal polarization, the sensitivity is about 0.2 to 0.6 K/psu. It means that we have to make radiometric measurements with accuracy better than 1K even for the best sensitivity of brightness temperature to SSS. Therefore, in order to retrieve SSS, the measured brightness temperature at the top of atmosphere (TOA) needs to be corrected for many sources of error. One main geophysical source of error comes from atmosphere. Currently, the atmospheric effect at L-band is usually corrected by absorption and emission model, which estimate the radiation absorbed and emitted by atmosphere. However, the radiation scattered by precipitation is neglected in absorption and emission models, which might be significant under heavy precipitation. In this paper, a vector radiative transfer model for coupled atmosphere and ocean systems with a rough surface is developed to simulate the brightness temperature at the TOA under different precipitations. The model is based on the adding-doubling method, which includes oceanic emission and reflection, atmospheric absorption and scattering. For the ocean system with a rough surface, an empirical emission model established by Gabarro and the isotropic Cox-Munk wave model considering shadowing effect are used to simulate the emission and reflection of sea surface. For the atmospheric attenuation, it is divided into two parts: For the rain layer, a Marshall-Palmer distribution is used and the scattering properties of the hydrometeors are calculated by Mie theory (the scattering hydrometeors are assumed to be spherical). For the other atmosphere layers, which are assumed to be clear sky, Liebe's millimeter wave propagation model (MPM93) is used to calculate the absorption coefficients of oxygen, water vapor, and cloud droplets. To simulate the change of brightness temperature caused by different rain rate (0-50 mm/h), we assume a 26-layer precipitation structure corresponding to NCEP FNL data. Our radiative transfer simulations showed that the brightness temperature at TOA can be influenced significantly by the heavy precipitation, the results indicate that the atmospheric attenuation of L-band at incidence angle of 42.5° should be a positive bias, and when rain rate rise up to 50 mm/h, the brightness temperature increases are close to 0.6 K and 0.8 K for horizontally and vertically polarized brightness temperature, respectively. Thus, in the case of heavy precipitation, the current absorption and emission model is not accurate enough to correct atmospheric effect, and a radiative transfer model which considers the effect of radiation scattering should be used.

The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

One of the key input parameters in obtaining end products from SAR data is the DEM used during their processing. This holds true especially when persistent scatterers InSAR method should be applied for example to study slow moving landslides or subsidence. Since nowadays most of the raw SAR data are of space borne origin for their correct processing to high precision products for relatively small areas with centimeter accuracy a DEM taking into account the particularities of the local topography is needed. Most of the DEMs used by the SAR processing software such as SRTM or ASTER are obtained by the same type of instrument and present some disagreements with height information acquired by leveling measurements or other geodetic means. This was the motivation for initiating this research – to prove the need of creating and using local DEM in SAR data processing at small scale and to check what the magnitude of the discrepancy between final InSAR products is in both cases where SRTM/ASTER and local DEM has been used. In addition investigated were two scenarios for SAR data processing – one with small baseline between image pairs and one having large baseline image pairs – in order to find out in which case local DEM has bigger impact. In course of this study two reference areas were considered – Bankya village near Sofia (SW region of Bulgaria) and Mirovo salt extraction site (NE region of Bulgaria). The reason those areas were selected lies in the high number of landslides registered and monitored by the competent authorities in the mentioned locations. The significance of the results obtained is witnessed by the fact that both sites we used have been included as reference sites for Bulgaria in the PanGeo EU funded project dealing with delivering information regarding ground instability geohazard as areas prone to subsidence of natural and manmade origin. In the said project largest part of the information has been extracted from Envisat SAR data, but now this information could be supplemented by adding such from Sentinel-1 derived by us. During this research two local DEMs have been extracted from the tiles including the areas of investigation, one using SRTM data and one from ASTER, and after this procedure both were compared to the DEM gathered by leveling measurements. Finally conclusions are drawn and a direction for future research steps is provided.