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The paper discusses the major modes of mapping the underlying surface using algorithms synthetic aperture radar antenna system onboard. The causes of the appearance of systematic errors in the mathematical modeling of the synthetic aperture antenna device. A method for reducing these methodological errors, is to increase the number of active reflectors radar signals. It is shown that in this case must take into account correlations between the echoes of individual reflectors. The mathematical model takes into account the spatial and temporal correlation characteristics of the observed signals. The mathematical model is implemented as a simulation algorithm of unsteady, non-Gaussian processes with the specified correlation-spectral characteristics of a given density and distribution of samples of these processes, simulating fluctuations in the amplitude of the observed echo in each bin. The possibility of a significant acceleration of the process simulation using the simplified forms correlations in the form of exponential curves.

Understanding the dynamics and processes of the ice sheets is crucial for predicting the behavior of climate change. A potential approach to achieve this is by using high resolution (HR) digital elevation models (DEMs) of the ice surface derived from remote sensing radar or laser altimeters. Unfortunately, at present HR DEMs of large portions of the ice sheets are not available. To address this issue, in this paper we propose a multisensor data fusion technique for the generation of a HR DEM of the ice sheets, which fuses two types of data, i.e., radargrams acquired by radar sounder (RS) instruments and ice surface elevation data measured by altimeter (ALT) instruments. The aim of the technique is to generate a DEM of the ice surface at the best possible horizontal resolution by exploiting the complementary characteristics of the RS and ALT data. This is done by defining a novel processing scheme that involves image processing techniques based on data rescaling, geostatistical interpolation and multiresolution analysis (MRA). The method has been applied to a subset of RS and ALT data acquired over a portion of the Byrd Glacier in Antarctica. Experimental results confirm the effectiveness of the proposed method.

Recently, remote sensing is considering one of the most important tools in studies of water scattering and water characterization. Traditional methods for monitoring pollutants depended on optical satellite rather than Radar data. Thus, many of Water Quality Parameters (WQP) from optical imagery are still limited. In this paper, a new approach based on the TerraSAR-X images has been presented which it is used to map the region of interest and to estimate physical and chemical WQPs. This approach based on a Small Perturbation Model (SPM) for the electromagnetic scattering is applied by using the Elfouhaily spectrum. A series of inversions have been included in this model started by finding the reflectivity from backscattering coefficients which are calculated from SAR images. Another inversion has been applied to find dielectric constant from the calculation models of the reflectivity (in HH and VV polarizations). Then, a Stogryn Debye formulation has been used to estimate temperature and salinity of water surface from SAR images. After many derivations we got a new model able to estimate temperature and salinity directly from backscattering coefficients obtained from radar images. Inorganic chemical parameters which are represented by Total Dissolved Salts (TDS) and the Electrical Conductivity (EC) are estimated directly from salinity. A tow dataset of instu data have been used to validate this work. The validation included a comparison between parameters measured in situ and those estimated from Terra SAR-X image.

WWe propose to apply the compressive sensing technique to the design of satellite radar altimeter for increasing the sampling time window (STW) while keeping the same data rate so as to enhance the tracking robustness of an altimeter. A satellite radar altimeter can measure the range between the satellite platform where it is aboard and the averaged sea surface with centimeter level accuracy. The rising slope of the received waveform by altimeter contains important information about the sea surface, e.g. the larger the slope of the waveform, means the smoother the sea surface. Besides, the half-power point of the slope refers to the range information. For satellite altimeter, due to the rising slope just occupies fewer range bins compared with the whole range bins illuminated by the long pulse signal, i.e. the signal is sparse in this sense, thus compressive sensing technique is applicable. Altimeter echoes are simulated and the waveforms are constructed by using the traditional method as well as by compressive sensing (CS) method, they are very well agreed with each other. The advantage of using CS is that we can increase the sampling time window without increasing the data, thus the tracking capability can be enhanced without sacrificing the resolution.

The results of long-term satellite survey of the aquatic area of the Caspian Sea are presented. The patterns of surface oil pollution of the Caspian Sea are described and analysed. It is demonstrated that surface oil pollution is often caused by natural causes, namely by natural hydrocarbon seepages and mud volcanoes activity on the sea bottom. A combined analysis of oil film signatures in satellite radar and optical imagery data is performed. Mapping of the main types of surface pollution of the Caspian Sea is performed and areas of the heaviest pollution are outlined and analysed. Dependence of radar signatures of sea surface oil patches on the wind/wave conditions is investigated. The large amount of the data available allowed us to make some generalizations and obtain statistically significant results on a spatial and temporal variability of various sea surface film manifestations in SAR images. The impact of dynamic and circulation processes and natural factors (current meandering, vortical activity, temperature and wind patterns) on spatial and temporal distributions and intensity of oil films is studied. The connection between manifestations of natural seepages and mud volcanoes and earthquake activity in South Caspian and adjacent areas is established.

Slicks on the sea surface are characterized by attenuation of short wind waves and appeаr in radar imagery at moderate incidence angles as areas of reduced intensity. In the proximity of oil platforms, ship routes, fish farms, etc. marine slicks are often identified as oil spills or biogenic films. However, probability of false alarm when detecting film slicks is very high because of the occurrence of structures in radar images looking similar but not related to surface films (“lookalikes”). One of the most frequent "look-alikes" is wind depression areas (WDAs) where the wind excitation of short surface waves is reduced compared to the ambient background. Results of field observations of films slicks and WDA are described and differences in character of wind wave attenuation in different parts of the wind wave spectrum are revealed. Model calculations of wave damping degree (contrast) in film slick and in WDA are carried out and are shown to be in general agreement with experiment. Capabilities of dual-polarization and multi-band microwave radar for discrimination between film slicks and “look-alikes” are analyzed based on experiment and model results.

An assessment of the agreement between the ERS scatterometers (ERS-1 and ERS-2) and the Metop scatterometers (ASCAT-A and ASCAT-B) is essential for the consistency of the C-band scatterometry dataset. ERS-1, ERS-2, ASCAT-A and ASCAT-B are C-band fan-beam radar scatterometers covering a range of common incidence angles. During these C-band scatterometry missions, different calibration campaigns have been carried out mainly relying on active ground transponders and natural distributed targets such as the rainforest. Additionally, these missions differ in time with some overlapping periods. Therefore, an assessment of the agreement between ERS and ASCAT measurements is an important and challenging task. This assessment is usually performed over the rainforest but only considering the common incidence angles. In order to perform the comparison over the whole incidence angle range of both radars, a Geophysical Model Function (GMF) is needed. An empirical correction of the CMOD5.n GMF has been suggested recently by KNMI resulting in a new GMF called CMOD6. This correction was derived from the comparison of the ASCAT backscatter measurements and the CMOD5.n model. Taking ASCAT’s measurements as reference, the differences between the CMOD5.n and ASCAT measurements were attributed to GMF errors. Additionally, an overview of the existing C-band models is given. The comparison of these models shows relatively large differences. The aim of this paper is the assessment of the CMOD6 GMF using ERS-1 and ERS-2 ocean backscatter measurements and the validation of the applicability of the corrected GMF to the whole C-band scatterometry dataset. Finally, a method is suggested to calibrate the residual bias of all the C-band scatterometers w.r.t CMOD6. It is shown that after calibration a consistent scatterometer data model is obtained.

Marine slicks are one of the most common features on the sea surface and a significant part of the slicks is a result of accidental or deliberate oil spills. The shape of oil slicks is their important characteristic that can be used to identify the nature of slick signatures in radar or optical images of the sea surface and possibly to describe them quantitatively. Nowadays, however, there is a lack of systematic experiments with slicks, and the very physical mechanisms of slick spreading are still not well understood. This paper presents results of controlled experiments with spills of surfactants, and a possible physical mechanism of slick asymmetry is discussed. Experiments with artificial film slicks were carried out in different environmental conditions: from an Oceanographic Platform on the Black Sea, and from a vessel on the Gorky Water Reservoir. Slick shape and its evolution were studied using photographic methods, and satellite radar imagery. In the satellite experiments surfactants were poured on the surface at certain time intervals before the satellite overpass. It is obtained that film spreading is not axial symmetric, and the spills are stretched along the wind, a long-to-short slick axis ratio weakly depends on spreading time and grows with wind speed. A physical mechanism of slick deformation due to mean surface currents induced by wind waves is proposed. Namely, drift currents induced by oblique propagating surface waves increase in film slicks due to enhanced wave damping and these currents result in reduced spreading rate in the cross wind direction. Theoretical analysis of slick spreading accounting for the effect of surface waves is presented, and theoretical estimates are shown to be consistent with experiment.

There is a need for small Sense and Avoid (SAA) systems for small and micro Unmanned Aerial Systems (UAS) to avoid collisions with obstacles and other aircraft. The proposed SAA systems will give drones the ability to “see” close up and give them the agility to maneuver through tight areas. Doppler radar is proposed for use in this sense and avoid system because in contrast to optical or infrared (IR) systems Doppler can work in more harsh conditions such as at dusk, and in rain and snow. And in contrast to ultrasound based systems, Doppler can better sense small sized obstacles such as wires and it can provide a sensing range from a few inches to several miles. An SAA systems comprised of Doppler radar modules and an array of directional antennas that are distributed around the perimeter of the drone can cover the entire sky. These modules are designed so that they can provide the direction to the obstacle and simultaneously generate an alarm signal if the obstacle enters within the SAA system’s adjustable “Protection Border”. The alarm signal alerts the drone’s autopilot to automatically initiate an avoidance maneuver. A series of Doppler radar modules with different ranges, angles of view and transmitting power have been designed for drones of different sizes and applications. The proposed Doppler radar micro SAA system has simple circuitry, works from a 5 volt source and has low power consumption. It is light weight, inexpensive and it can be used for a variety of small unmanned aircraft.

This paper describes a system concept for persistent (up to 365 days, 24/7), unmanned, local-area surveillance of air and maritime surface and sub-surface objects in the Canadian Arctic. The system concept is based on unmanned, remotely controlled and monitored Arctic Surveillance Systems that could be deployed at one or more maritime chokepoints, at locations in the Canadian Arctic Archipelago. The Artic Surveillance Systems would be operated over a satellite communication channel from a Southern Control Centre located in the south of Canada. Surveillance information for each detected platform and environmental reports for the local operating area would be compiled semi-automatically, from the integration of data transmitted from multiple above-water and underwater sensors and self-reporting systems, and be disseminated, in near real-time, to defence, security, and public safety clients. Potential sensors and self-reporting systems include radar, radar intercept receiver, underwater acoustic arrays, electro-optical/infrared camera system, Automatic Identification System (AIS), Automatic Dependent Surveillance - Broadcast (ADS-B), and a meteorological sensor system. The system concept is comprised of a surveillance concept – which includes environmental and geographic factors, platform types under potential surveillance, end-user information requirements, contributions of individual sensor types to surveillance, and the role of local-area surveillance within the broader context of Arctic Domain Awareness – and a system operating concept. The system operating concept describes the system capabilities and operating modes required to achieve the surveillance concept. Specific consideration is given to the interplay between the automation level, the quality and timeliness of the resulting information productions, the allocation of processing functions between the Control Centre and the Arctic Surveillance System, and transmitted data volumes. The system concept is being used in support of the specification of functional requirements for a concept demonstration system for Arctic surveillance, currently under development by Defence R&D Canada.

Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) is a Japanese-European collaborative earth observation satellite mission aimed to deepen understanding of the interaction process between clouds and aerosols and their effects on the Earth’s radiation. The outcome of this mission is expected to improve the accuracy of global climate change prediction. As one of instruments for EarthCARE, the Cloud Profiling Radar (CPR) is the world’s first space-borne Doppler cloud radar jointly developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT). In Japan, the critical design review of the CPR has been completed in 2013, and CPR proto-flight model was manufactured and integrated until summer in 2015. Finally, the proto-flight test have been just started. This paper describes the design results and current status of CPR proto-flight test.

The Dual-frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) core satellite was developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT). The GPM is a follow-on mission of the Tropical Rainfall Measuring Mission (TRMM). The objectives of the GPM mission are to observe global precipitation more frequently and accurately than TRMM. The frequent precipitation measurement about every three hours will be achieved by some constellation satellites with microwave radiometers (MWRs) or microwave sounders (MWSs), which will be developed by various countries. The accurate measurement of precipitation in mid-high latitudes will be achieved by the DPR. The GPM core satellite is a joint product of National Aeronautics and Space Administration (NASA), JAXA and NICT. NASA developed the satellite bus and the GPM Microwave Imager (GMI), and JAXA and NICT developed the DPR. JAXA and NICT developed the DPR through procurement. The configuration of precipitation measurement using active radar and a passive radiometer is similar to TRMM. The major difference is that DPR is used in GPM instead of the precipitation radar (PR) in TRMM. The inclination of the core satellite is 65 degrees, and the nominal flight altitude is 407 km. The non-sun-synchronous circular orbit is necessary for measuring the diurnal change of rainfall similarly to TRMM. The DPR consists of two radars, which are Ku-band (13.6 GHz) precipitation radar (KuPR) and Ka-band (35.5 GHz) precipitation radar (KaPR). Both KuPR and KaPR have almost the same design as TRMM PR. The DPR system design and performance were verified through the ground test. GPM core observatory was launched at 18:37:00 (UT) on February 27, 2014 successfully. DPR orbital check out was completed in May 2014. The results of orbital checkout show that DPR meets its specification on orbit. After completion of initial checkout, DPR started Normal Operations and Initial Calibration and Validation period was started. JAXA conducted internal calibrations, external calibrations and phase code changes to mitigate KuPR sidelobe clutter effect. JAXA evaluated these operations results and concluded that DPR data could go public. DPR products were released to the public on Sep. 2, 2014 and Normal Observation Operation period was started. JAXA is continuing DPR trend monitoring, calibration operations to confirm that DPR keeps its function and performance on orbit.

The Advanced Land Observing Satellite-2 (ALOS-2) was launched from Tanegashima Space Center by H-IIA rocket successfully on 24th May 2014. ALOS-2 carries the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) as the state-of-the-art L-band SAR system which succeeds to PALSAR onboard ALOS. PALSAR-2 uses almost whole bandwidth allocated for L-band active sensor of Earth Exploration Satellites Service specified by the Radio Regulation in order to realize the high resolution observation, and also, it transmits more than 6 kW power for lower Noise Equivalent Sigma Zero using 180 TRMs driven by Gallium Nitride (GaN) amplifier which is the first use in space. Furthermore, because ALOS-2 carries the SAR system only, PALSAR-2 antenna can be mounted under the satellite body. It enables to observe right-/left-looking observation by satellite maneuvering. And the high accuracy orbit control to maintain the satellite within 500 m radius tube against the reference orbit enables high coherence for the InSAR processing. Using these new technologies, ALOS-2 has been operating to fulfill the mission requirements such as disaster monitoring and so on. This document introduces the initial result of ALOS-2 from the first year operation.

In this paper we propose to simulate SAR radar images that can be acquired by aircraft or satellite. This corresponds to a real problematic, in fact, an airborne radar data acquisition campaign, was conducted in the south east of France. We want to estimate the geometric deformations that a digital terrain model can be subjected. By extrapolation, this construction should also allow to understand the image distortion if a plane is replaced by a satellite. This manipulation allow to judge the relevance of a space mission to quantify geological and geomorphological data. The radar wave is an electromagnetic wave, they have the advantage of overcoming atmospheric conditions since more wavelength is large is better crossing the cloud layer. Therefore imaging radar provides continuous monitoring.

A test environment is established to obtain experimental data for verifying the positioning model which was derived previously based on the pinhole imaging model and the theory of binocular stereo vision measurement. The model requires that the optical axes of the two cameras meet at one point which is defined as the origin of the world coordinate system, thus simplifying and optimizing the positioning model. The experimental data are processed and tables and charts are given for comparing the positions of objects measured with DGPS with a measurement accuracy of 10 centimeters as the reference and those measured with the positioning model. Sources of visual measurement model are analyzed, and the effects of the errors of camera and system parameters on the accuracy of positioning model were probed, based on the error transfer and synthesis rules. A conclusion is made that measurement accuracy of surface surveillances based on binocular stereo vision measurement is better than surface movement radars, ADS-B (Automatic Dependent Surveillance-Broadcast) and MLAT (Multilateration).

Correlation characteristics are important for sea clutter restraint in radar image processing, which is universal in certain features for both radar and optical image. The spatial-temporal dispersion relation contained in sea clutter, which usually fits into the sum of wind friction linear item and gravity wave item, is proved effective for sea clutter restraint recently. A sea clutter restraint method for mobile searching mode observation point, which is prevalent in maritime air-borne platform, is developed from a former restraint method for shore-based stationary radar. A new extraction method for intrinsic dispersion linear item parameter of sea clutter aiming at range profile of searching mode radar system is proposed, which forms the core of the restraint method. The statistical model is founded on spatial-temporal dispersion relation and radar illumination geometry. Simulation results shows Doppler shift of measured wind linear item have a bias from the sum of sea wind and radar platform velocity. A systematic study suggests the bias could be attributed to interaction between wind friction and gravity wave item, and a rather good fitting result is obtained. CFAR detection processing for a set of experimental clutter data shows that this intrinsic dispersion extraction method formula is found to be effective in detection probability enhancement. The restraint method based on the proposed dispersion extraction method could be utilized in mobile maritime surveillance equipments.

Currently, high resolution imaging of the space satellite is a popular topic in the field of radar technology. In contrast with regular targets, the satellite target often moves along with its trajectory and simultaneously its solar panel substrate changes the direction toward the sun to obtain energy. Aiming at the imaging problem, a signal separating and imaging approach based on the empirical mode decomposition (EMD) theory is proposed, and the approach can realize separating the signal of two parts in the satellite target, the main body and the solar panel substrate and imaging for the target. The simulation experimentation can demonstrate the validity of the proposed method.

Ship wake and oil slick signatures imaged by both multispectral ETM (enhanced thematic mapper) onboard Landsat-7 (L7) and multi-polarization SAR (synthetic aperture radar) onboard Radarsat-2 (R2) were analyzed in this paper. Spectral analysis used all the available band data together, not as an image but as a set of spectral features. Multipolarization imagery offers scattering information of the ground surface. Ship wake signatures were readily detected by local Hough transmission. Oil slicks are expected to benefit from spectral reflectance deviation from the background water color or phase differences between polarization channels. The appearance of ship wake in an area surrounded by oil slicks was also considered, although we have not yet conclusion at this moment. Comparing to our former efforts with polarized radar data only, the combined view by multispectral and multi-polarization sensors indicated detailed radiation and scattering characteristics of ship wake and oil slick signatures.

The Information Telecommunication System "Solaris" was created to solve the actual problems of navigation. The system allows analyzing an operational local and synoptic hydrometeorological situation on a vessel route to issue recommendations to navigators about the optimization of the movement from the point of view for the safety of navigation and economic efficiency. ITS "Solaris" represents a combination of two hardware-software complexes one of which is fitted on the vessel, and the other one ashore. The ship complex is based on the use of regular ship radar station to which AD converter and the computer with the software is connected. The coastal complex is a server that collects, processes, analyzes stores and transmits satellite and ship information. To operate the system on a particular ship the proposed model calculates the speed of the vessel, depending on the direction and speed of meteorological parameters such as wind, waves and currents, of ice conditions. The system can be used in the initial planning of the route on the basis of operational and climatic data according to the seasonal variability of the weather conditions. The created system improves the safety of navigation and increase economic efficiency.

As the similar cross track scanning mode of the measurements of Tropical Rainfall Measuring Mission’s (TRMM) Precipitation Radar (PR) and visible and infrared scanner (VIRS) results in near instantaneous synchronization in observing the same target, it is feasible to jointly use these two measurements to explore exactly the spectral characteristics of precipitating clouds (PCs). Meanwhile, it will effectively improve and extend the abilities to identify PCs using visible/infrared (VIR) measurements, because VIR sensors can be loaded aboard geostationary satellites with the opportunity of high sampling frequency. In this paper, PR and VIRS onboard TRMM are respectively used to capture PCs and identify their spectral signals during the Meiyu over the Yangtze-Huaihe River Valley from 1998 to 2007. Visible/infrared signals for PCs, which are the reflectance at 0.63μm and 1.6μm (referred to as RF1 and RF2, respectively), and the equivalent brightness temperature of a blackbody at 3.7μm, 10.8 μm and 12.0μm (referred to as TB3, TB4 and TB5, respectively), were derived by TRMM VIRS. Firstly, characteristics of rain rate, rain top and vertical profiles for stratiform and convective precipitations are investigated during the Meiyu periods. Moreover, VIRS individual-channel signals, and multi-channel indices for PCs of the Meiyu are evaluated quantitatively. Finally, revealed by long-term mean values, the differences of spectral signals between stratiform and convective PCs and their relationships with surface rain rates are explored.

The European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) are cooperating to develop the EarthCARE satellite mission with the fundamental objective of improving the understanding of the processes involving clouds, aerosols and radiation in the Earth’s atmosphere. The payload consists of two active and two passive instruments: an ATmospheric LIDar (ATLID), a Cloud Profiling Radar (CPR), a Multi-Spectral Imager (MSI) and a Broad-Band Radiometer (BBR). The four instruments' data are processed individually and in a synergetic manner to produce a large range of products, which include vertical profiles of aerosols, liquid water and ice, observations of cloud distribution and vertical motion within clouds, and will allow the retrieval of profiles of atmospheric radiative heating and cooling. The presentation will cover the configuration of the satellite with its four instruments, the mission implementation approach, an overview of the ground segment and the overall mission development status. The four instruments performance, based upon currently available analyses and test results will also be briefly addressed with a focus on the ESA instruments.

Ocean surface wind vectors (OVW) from scatterometers have been proved to be of great benefit to marine weather analysis and numerical model prediction. Conventional single-frequency scatterometers are capable to measure substantially accurate wind fields in clear atmospheric conditions, whereas winds obtained in marine extreme weather conditions are not so satisfying due to the high wind speed saturation effect and the rain perturbation. Therefore, a dualfrequency wind field measuring radar (WIFIR) to be onboard FengYun-3E is being predesigned to obtain relatively accurate wind fields in all weather conditions, which will compensate for the single-frequency shortcomings. The purpose of this study was to investigate the potential ability of WIFIR to measure OVW in tropical cyclones. A high-fidelity forward model was developed to simulate the sea surface normalize radar cross sections (NRCS) measured by WIFIR. The wind and rain rate fields used to drive the model are generated by UWNMS cloud model for Hurricane Ivan in 2004. High-wind GMFs and a theoretical rain model, which includes attenuation and volume scattering effect, have been utilized to describe the forward model. Based on the simulation results, the impact of rain on radar measurements and a dual-frequency retrieval algorithm were studied. The dual-frequency method was shown to have the ability to obtain information of rain rates up to 30mm/hr, and acquire more accurate wind vectors than single-frequency measurements. This method will be more effective to improve wind retrieval accuracy in tropical cyclones with the synchronous observation of microwave humidity sounder (MWHS) aboard FY-3 satellite.

Airborne Light Detection and Ranging (LiDAR) is an active remote sensing technology which can acquire the topographic information efficiently. It can record the accurate 3D coordinates of the targets and also the signal intensity (the amplitude of backscattered echoes) which represents reflectance characteristics of targets. The intensity data has been used in land use classification, vegetation fractional cover and leaf area index (LAI) estimation. Apart from the reflectance characteristics of the targets, the intensity data can also be influenced by many other factors, such as flying height, incident angle, atmospheric attenuation, laser pulse power and laser beam width. It is therefore necessary to calibrate intensity values before further applications. In this study, we analyze the factors affecting LiDAR intensity based on radar range equation firstly, and then applying the intensity calibration method, which includes the sensor-to-target distance and incident angle, to the laser intensity data over the study area. Finally the raw LiDAR intensity and normalized intensity data are used for land use classification along with LiDAR elevation data respectively. The results show that the classification accuracy from the normalized intensity data is higher than that from raw LiDAR intensity data and also indicate that the calibration of LiDAR intensity data is necessary in the application of land use classification.

The proposed spaceborne NASA-ISRO SAR (NISAR) mission would use the repeat-pass interferometric Synthetic Aperture Radar (InSAR) technique to measure the changing shape of Earth’s surface at the centimeter scale in support of investigations in solid Earth and cryospheric sciences. Repeat-pass InSAR relies on multiple SAR observations acquired from nearly identical positions of the spacecraft as seen from the ground. Consequently, there are tight constraints on the repeatability of the orbit, and given the narrow field of view of the radar antenna beam, on the repeatability of the beam pointing. The quality and accuracy of the InSAR data depend on highly precise control of both orbital position and observatory pointing throughout the science observation life of the mission. This paper describes preliminary NISAR requirements and rationale for orbit repeatability and attitude control in order to meet science requirements. A preliminary error budget allocation and an implementation approach to meet these allocations are also discussed.

Satellite-based products increasingly take an important role in filling data gaps in data sparse regions around the world. In recent years, precipitation products that utilize multi-satellite and multi-sensor datasets have been gaining more popularity than products from a single sensor or satellite. Adjusted with gauge and ground radar data, satellitebased products have been significantly improved. However the history of satellite-based precipitation products is relatively short compared to the length of 30 years in the definition for climatology from the World Meteorological Organization (WMO). For example, the NASA/JAXA Tropical Rainfall Measuring Mission (TRMM) has been in operation for over 16 years since 1997. The length of TRMM is far shorter than those from ground observations, raising a question whether TRMM climatology products are good enough for research and applications. In this study, three climatologies derived from ground observations (Global Precipitation Climatology Centre (GPCC) and Willmott and Matsuura (WM)) and a blended product (the TRMM Multi-Satellite Precipitation Analysis (TMPA) monthly product or 3B43) are compared on a global scale to assess the performance and weaknesses of the TMPAderived climatology. Results show that the 3B43 climatology matches well with the two gauge-based climatologies in all seasons in terms of spatial distribution, zonal means as well as seasonal variations. However, high variations in rain rates are found in light rain regions such as the Sahara Desert. Large negative biases (3B43

Soil moisture is a key component in the hydrologic cycle and climate system. It is an important input parameter for many hydrologic and meteorological models. NASA’S upcoming Soil Moisture Active Passive (SMAP) mission, to be launched in October 2014, will address this need by utilizing passive and active microwave measurements at L-band, which will penetrate moderately dense canopies. In preparation for the SMAP mission, the Soil Moisture Validation Experiment 2012 (SMAPVEX12) was conducted from 6 June to 17 July 2012 in the Carment-Elm Creek area in Manitoba, Canada. Over a period of six weeks diverse land cover types ranging from agriculture over pasture and grassland to forested sites were re-visited several times a week. The Passive/Active L-band Sensor (PALS) provides radiometer products, vertically and horizontally polarized brightness temperatures, and radar products. Over the past two decades, successful estimation of soil moisture has been accomplished using passive and active L-band data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. This work focuses on analyzing the Passive/Active L-band Sensor observations of sites covered during SMAPVEX12, investigating the observed data, parameterizing vegetation covered surface model, modeling inversion algorithm and analyzing observed soil moisture changes over the time period of six weeks. The data and analysis results from this study are aimed at increasing the accuracy and range of validity of SMAP soil moisture retrievals via enhancing the accuracy for soil moisture retrieval.

Radarsat-2 Synthetic Aperature Radar (SAR) remote sensing data were used to record soil surface moisture and evaluate the utility of a cross polarization (VV/VH) combination. Studies were conducted at Dingxi, in the semi-arid region of the Loess Plateau, China. We combined these data with MODIS optical data, used a Water-Cloud model to correct for the influence of vegetation, and then estimated the soil moisture under crop cover. For bare surfaces, the value of the cross polarization combination model was highly correlated to the measurement of soil moisture at 10~20 cm depth (R=0.75, P

Vegetation phenology reveals the response of vegetation to global climate change. The time series of remote sensing data have been applied to generate land surface pheology and vegetation seasonality information. In this study, land surface phenology was detected from time series of radar backscatter data from 2003 to 2007 and compared with phenological metrics derived from SPOT VEGETATION NDVI and MODIS land cover dynamic product across Australia. An asymmetric Gaussian method was used to extract phenological metrics, the start of season (SOS) and the end of season (EOS) from the time series. Comparing the spatial pattern of average SOS and EOS from the three datasets, similar spatial pattern are mapped across western and southeastern Australia. However, different phenological patterns are captured in the tropical ecosystems of northern and eastern Australia. These results showed the potential of microwave data in monitoring vegetation dynamics as complementary phenological information.

SMAPVEX12 is a pre-launch field campaign for evaluating and testing the soil moisture retrievals retrieved from the SMAP project. During this experiment, airborne microwave observations from PALS radiometer and radar: brightness temperature and radar backscatter, as well as ground measurements were acquired. In this study, the remote sensing soil moisture was retrieved from SMAPVEX12 PALS radiometer L-band (6GHz) brightness temperature at high altitude flight. The PALS soil moisture was then aggregated and compared with PALS radar backscatter coefficient to generate high spatial resolution microwave soil moisture in change. The R2 values of PALS soil moisture retrieval validation range from 0.407-0.881, indicating good accuracy of soil moisture retrieval. The R2 values of comparison between aggregated PALS Δ􀟠 and PALS Δ􀟪 range from 0.492-0.805, while the downscaled Δ􀟠 validation range from 0.128- 0.383.

In this study, space remote sensing data and crop specific information from the ESA-led AgriSAR 2009 campaign are used for studying the profiles of C-band SAR backscatter signals and multispectral-based leaf area index (LAI) over the growth period of canola, pea and wheat. In addition, the correlations between radar backscatter parameters and the crop yields were analyzed, based on extracted statistics of temporal profiles. The results show that the HV backscatter and LAI are correlated differently before and after LAI peak. In addition, the coefficient of determination between peakrelated statistics from polarimetric indicator profiles and yield for pea fields can reach up to 0.68, and for canola and wheat up to 0.47 and 0.5, respectively. HV backscatter and coherence between HH and VV are most.

This paper provides an overview of ground based operational remote sensing activities that enable a broad range of missions at the Eastern Range (ER), which includes the National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC) and U.S. Air Force Cape Canaveral Air Force Station (CCAFS). Many types of sensors are in use by KSC and across the ER. We examine remote sensors for winds, lightning and electric fields, precipitation and storm hazards. These sensors provide data that are used in real-time to evaluate launch commit criteria during space launches, major ground processing operations in preparation for space launches, issuing weather warnings/watches/advisories to protect over 25,000 people and facilities worth over $20 billion, and routine weather forecasts. The data from these sensors are archived to focus NASA launch vehicle design studies, to develop forecast techniques, and for incident investigation. The wind sensors include the 50-MHz and 915-MHz Doppler Radar Wind Profilers (DRWP) and the Doppler capability of the weather surveillance radars. The atmospheric electricity sensors include lightning aloft detectors, cloud-to-ground lightning detectors, and surface electric field mills. The precipitation and storm hazards sensors include weather surveillance radars. Next, we discuss a new type of remote sensor that may lead to better tracking of near-Earth asteroids versus current capabilities. The Ka Band Objects Observation and Monitoring (KaBOOM) is a phased array of three 12 meter (m) antennas being built as a technology demonstration for a future radar system that could be used to track deep-space objects such as asteroids. Transmissions in the Ka band allow for wider bandwidth than at lower frequencies, but the signals are also far more susceptible to de-correlation from turbulence in the troposphere, as well as attenuation due to water vapor, which is plentiful in the Central Florida atmosphere. If successful, KaBOOM will have served as the pathfinder for a larger and more capable instrument that will enable tracking 15 m asteroids up to 72 million kilometers (km) away, about half the distance to the Sun and five times further than we can track today. Finally, we explore the use of Site Test Interferometers (STI) as atmospheric sensors. The STI antennas continually observe signals emitted by geostationary satellites and produce measurements of the phase difference between the received signals. STIs are usually located near existing or candidate antenna array sites to statistically characterize atmospheric phase delay fluctuation effects for the site. An STI measures the fluctuations in the difference of atmospheric delay from an extraterrestrial source to two or more points on the Earth. There is a three-element STI located at the KaBOOM site at KSC.

In this paper, we propose an unsupervised change detection method using the labeled co-occurrence matrix on multitemporal SAR images. In SAR images, each land cover (LC) class has a distinct reflectivity to radar signals and presents a specific backscattering value. Generally, the amplitude of the SAR images can be roughly clustered into three classes according to the backscattering behaviors of the LC classes. The changes occurred between the images can be considered as a backscattering variation that is changed from one backscattering class into another. As a result, we analyzed the possible cases of the positive and negative backscattering variations, and merged the initial three backscattering classes into two classes with the pixel in the medium backscattering class being attached to the strong backscattering class and the low backscattering class respectively in a membership degree. Two pairs of fuzzy-label images are derived accordingly, where each pair of fuzzy-label images are computed from the multi-temporal SAR data. The labeled cooccurrence matrix is computed locally on each pair of fuzzy-label images by combining the membership values in a conjunctive operator, and the autocorrelation feature is extracted. The classifications are implemented by Otsu Nthresholding algorithm on the derived two autocorrelation features. The final binary change detection map is achieved by combining the obtained two classification results. Experiments were carried on portions of multi-temporal Radarsat-1 SAR data. The effectiveness of the proposed approach was confirmed.

An interferometric performance analysis for repeat-pass geosynchronous circular SAR (GEOCSAR) is presented. The analysis mainly includes the errors caused by the following sources: radar thermal noise, spatial baseline decorrelation, images’ misregistration and the atmospheric effects. For circular SAR (CSAR) imaging on the geosynchronous orbit, the altitude is very high, the atmospheric effect is severe and the high sidelobe is existed in the focused GEOCSAR signal, the characteristics of the various error sources of GEOCSAR interferometry will behave differently from the conventional interferometric SAR.

We present an investigation of surface deformation using Differential SAR Interferometry (DInSAR) time-series carried out in an active open pit iron mine, the N5W, located in the Carajas Mineral Province (Brazilian Amazon region), using 33 TerraSAR-X (TSX-1) scenes. This mine has presented a historical of instability and surface monitoring measurements over sectors of the mine (pit walls) have been done based on ground based radar. Two complementary approaches were used: the standard DInSAR configuration, as an early warning of the slope instability conditions, and the DInSAR timeseries analysis. In order to decrease the topographic phase error a high resolution DEM was generated based on a stereo GeoEye-1 pair. Despite the fact that a DinSAR contains atmospheric and topographic phase artifacts and noise, it was possible to detect deformation in some interferometric pairs, covering pit benches, road ramps and waste piles. The timeseries analysis was performed using the 31 interferometric pairs, which were selected based on the highest mean coherence of a stack of 107 interferograms, presenting less phase unwrapping errors. The time-series deformation was retrieved by the Least-Squares (LS) solution using an extension of the Singular Value Decomposition (SVD), with a set of additional weighted constrain on the acceleration deformation. The atmospheric phase artifacts were filtered in the space–time domain and the DEM height errors were estimated based on the normal baseline diversity. The DInSAR time-series investigation showed good results for monitoring surface displacement in the N5W mine located in a tropical rainforest environment, providing very useful information about the ground movement for alarm, planning and risk assessment.

The microphysical processes in fog are examined based on an analysis of four fog events captured by the in-situ and remote sensing synergy at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the western part of the Netherlands. A 35 GHz cloud radar at CESAR has been used in “fog mode” for the first time in the campaign. In this paper, the microphysical parameterization of fog is first introduced as the basis for analyzing the microphysical processes in the lifecycle of fog. The general microphysical characteristics of the four fog events are studied and key microphysical parameters (droplet number concentration, liquid water content, mean radius, and spectral standard deviation) related to fog are found lower than those in other sites due to the low aerosol concentration at Cabauw. The dominant processes in fog are investigated from the relationships among the key microphysical parameters. The positive correlations of each two parameters in lifecycle stages of a stratus-fog case suggest the dominant scheme in fog is droplet activation with subsequent hygroscopic growth and/or droplet evaporation, which is also supported by the combined observations of visibility and radar reflectivity. The shape of fog drop size distribution regularly broadens and then narrows in the whole lifecycle. However, other mechanisms could exist, although not dominating. Collision-coalescence is a significant factor for the continued growth of big fog droplets when they have reached certain sizes in the mature stage. In the datasets, the collision-coalescence process could be distinguished from the unusual negative correlations among the key microphysical parameters in the lifecycle of another stratus-fog case, and the temporal evolutions of droplet number concentration, mean radius, spectra width, visibility and radar reflectivity show the evidence of it.

Satellite altimeters on-board Envisat and SARAL (Altika) are routinely used to create virtual monitoring stations from the satellite path crossing with any river of significant width. These virtual stations have the advantage of having a low operational cost and providing near real-time absolute measurement of water level. However, many shortcomings still remain open questions and the precision of measurements can vary widely depending on a number of factors such as the river width and environmental conditions surrounding the water course. In this article we have concentrated our efforts on the relation between land cover classes, the shape of waveforms produced by the backscatter response and the separability among different land cover classes and water. Seven land cover classes often encountered nearby large river banks were analyzed: agriculture, native forest, planted forest, savanna, pasture, urban and open water. Waveforms of these classes were sampled to build a waveform library. They were compared among themselves using cross-correlation, cumulative difference and Kolmogorov-Smirnov distance. Average waveforms for each class were calculated and compared. The results show that only the open water" and forest" classes could be characterized as having a typical behavior, probably caused by the limitations of the measurements used. Furthermore, these two classes have very similar responses and could easily be confused. The other classes generally showed chaotic behavior which can mostly be attributed to variations in their cover characteristics. We expect that a better understanding of the influence of land cover on waveform shapes will increase accuracy of water level measurements.

The use of satellite methods for inland waters is often difficult because of their spatial resolution comparable to or greater thatn the size of water resevoirs. Remote sensing with high spatial resolution is often associated with ea large repeat period of data, or with a significant dependence of the quality of data on weather conditions. In this regard, the sue of Jason-2 sattelite equipped with dual-frequency (13.6 GHz and 5 GHz) radar altimeters and passive three-frequency (18,21 and 37 GHz) microwave radiometers is of interest, because the footprint diameter of their altimeters in Ku-band is about 10km and the repeat period of observations is ten days, that make it suitable for observations of large and medium-sized inland waters. In this work we use the data of Jason-2 satellite to determine the water level variations ice-cover regime of 6 lakes in Russia, water areas of which are intersected by the tracks of this satellite. Variations in water level is calculated on the base of retracking method taking into account the fact that the waveforms of altimetry pulses of satellites Jason-2 are distorted due to the influence of land. Satellite data are compared with available in situ observations and the correlation coefficient with in situ is calculated. The ice regime of lakes is determined using the a new method based on the analysis of the difference between the brightness temperatures of land and water in summer and winter periods. For validation of this method the visual images of the lakes from Aqua and Landsat satellites and in situ data are used.

The precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite has high vertical resolution, and ground radar (GR) has relatively good capability to detect weak precipitation and relatively good horizontal resolution. The joint utilization of PR and GR will be an important factor in maximizing the benefit to be reaped from both instruments. In this paper, we will blend the PR data and GR reflectivity in Nanjing, China based on image fusion algorithm. Integrating PR and GR mainly includes following steps: spatial-temporal matchup of PR and GR data, image fusion algorithms selection and quality evaluation of the fused image.

Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture. Satellite sensors operating in the low part of microwave spectrum are very suitable for this purpose, and their signals can be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and vegetation to the measured signal are properly accounted for. Among the algorithms used for the retrieval of SMC from both active (i.e. Synthetic Aperture Radar, SAR or real aperture radars) and passive (radiometers) microwave sensors, the artificial neural networks (ANN) represent the best compromise between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several radar and radiometric satellite sensors, in order to generate SMC products at different spatial resolutions, varying from hundreds of meters to tens of kilometers. These algorithms, which use the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced Integral Equation (AIEM), Oh models, and Radiative transfer Theory (RTT), have been adapted to the C-band acquisitions from SAR (Envisat/ASAR) and real aperture radar (ASCAT) and to the X-band SAR acquisitions of Cosmo-SkyMed and TerraSAR-X. Moreover, a specific ANN algorithm has also been implemented for the L-band active and passive acquisitions of the incoming SMAP mission. The latter satellite will carry onboard simultaneously one radar and one radiometer operating at the same frequency, but with different spatial resolutions (3 and 40 km, respectively). Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites located worldwide have been used along with simulations derived from forward electromagnetic models for setting up, training and validating these algorithms. An overall quality assessment of the obtained results in terms of accuracy and computational cost was carried out, and the main advantages and limitations for an operational use of these algorithms have been evaluated.

Ka-band RADAR frequency range has not yet been used for Synthetic Aperture Radar (SAR) from space so far, although this technology may lead to important applications for the next generation of SAR space sensors. Therefore, feasibility studies regarding a Ka-band SAR instrument have been started [1][2], for the next generation of SAR space sensors. In spite of this, the lack of trusted references on backscatter at Ka-band revealed to be the main limitation for the investigation of the potentialities of this technology. In the framework of the ESA project “Ka-band SAR backscatter analysis in support of future applications”, this paper is aimed at the study of wave interaction at Ka-band for a wide range of targets in order to define a set of well calibrated and reliable Ka-band backscatter coefficients for different kinds of targets. We propose several examples of backscatter data resulting from a critical survey of available datasets at Ka-band, focusing on the most interesting cases and addressing both correspondences and differences. The reliability of the results will be assessed via a preliminary comparison with ElectroMagnetic (EM) theoretical models. Furthermore, in support of future technological applications, we have designed a prototypal software acting as a “library” of earth surface radar response. In our intention, the output of the study shall contribute to answer to the need of a trustworthy Ka-Band backscatter reference. It will be of great value for future technological applications, such as support to instrument analysis, design and requirements’ definition (e.g.: Signal to Noise Ratio, Noise Equivalent Sigma Zero).

The NASA Earth Venture Cyclone Global Navigation Satellite System (CYGNSS) is a spaceborne mission scheduled to launch in October 2016 that is focused on tropical cyclone (TC) inner core process studies. CYGNSS attempts to resolve one of the principle deficiencies with current TC intensity forecasts, which lies in inadequate observations and modeling of the inner core. CYGNSS is specifically designed to address these two limitations by combining the all-weather performance of GNSS bistatic ocean surface scatterometry with the sampling properties of a constellation of satellites. CYGNSS measurements of bistatic radar cross section of the ocean can be directly related to the near surface wind speed, in a manner roughly analogous to that of conventional ocean wind scatterometers. The technique has been demonstrated previously from space by the UK-DMC mission in 2005-6.

In this work we propose a technique for 15-minutes cumulative rainfall mapping, applied over Tuscany, using Italian weather radar networks together with the regional rain gauge network. In order to assess the accuracy of the radar-based rainfall estimates, we have compared them with spatial coincident rain gauge measurements. Precipitation at ground is our target observable: rain gauge measurements of such parameter have a so small error that we consider it negligible (especially if compared from what retrievable from radars). In order to make comparable the observations given from these two types of sensors, we have collected cumulative rainfall over areas a few tens of kilometres wide. The method used to spatialise rain gauges data has been the Ordinary Block Kriging. In this case the comparison results have shown a good correlation between the cumulative rainfall obtained from the rain gauges and those obtained by the radar measurements. Such results are encouraging in the perspective of using the radar observations for near real time cumulative rainfall nowcasting purposes. In addition the joint use of satellite instruments as SEVIRI sensors on board of MSG-3 satellite can add relevant information on the nature, spatial distribution and temporal evolution of cloudiness over the area under study. For this issue we will analyse several MSG-3 channel images, which are related to cloud physical characteristics or ground features in case of clear sky.

At present time radar methods of the seas and oceans diagnostics are actively developing. Using of the radar stations based on satellites and planes allows to receive information on a sea surface and a atmosphere near-surface layer with coverage of big water surface areas independently of day time. The developed methods of satellite radio images processing can be applied to marine radar stations. In Institute of Applied Physics RAS works on sea surface diagnostics systems development on the basis of standard marine radar are actively conducted. Despite smaller coverage of the territory in comparison with satellite data, marine radar have possibility to record spatially temporary radar images and to receive information on a surrounding situation quickly. This work deals with results of the researches which were conducted within the international expedition in the Atlantic Ocean in the autumn of 2012 on a route Rotterdam (Netherlands) – Ushuaya (Argentina) – Antarctica — Ushuaya. During this expedition a complex measurements of a sea surface, a atmosphere near-surface layer parameters and subsurface currents in the wide range of hydroweather conditions, including the storm were carried out. The system developed in IAP RAS on the basis of a marine radar ICOM MR-1200RII and the ADC (Analog Digital Converter) block for data recording on the personal computer was used. Display of a non-uniform near-surface current on sea surface radar images in storm conditions is shown. By means of the high-speed anemometer and meteorological station the measurements of the atmosphere parameters were carried out. Comparison of the anemometer data with calculated from radar images is carried out. Dependence of radar cross section from wind speed in the wide range of wind speeds, including storm conditions is investigated. Possibility of marine radar using for surface waves intensity and ice situation estimates also as icebergs detection is shown.

Radar manifestations of ship wakes in zones of phytoplankton bloom are discussed. It is shown that these signatures can be regarded as indicators of biogenic activity. The main data are satellite radar images. Satellite visible (VIS) and infrared (IR) satellite data are also analyzed. The large amount of the available data allowed us to make some generalizations and obtain statistically reliable results concerning spatial and temporal variability of certain type of ship wake manifestations in synthetic aperture radar (SAR) images of the sea surface. Traditional classification of surface ship wakes manifestations in satellite SAR images specifies distinct features such as a dark trailing centreline region (turbulent wake), narrow V-wakes aligned at some angle to the ship’s path (the Kelvin wake), and, sometimes, internal wave wakes generated under conditions of shallow stratification. Their characteristic lengths are reported to be up to tens of kilometers and they can last from tens of minutes up to one hour. Instances of radar signatures of the ship wakes dissimilar to the previously described were detected in radar images obtained in the course of a satellite monitoring campaign of the central and south-eastern Baltic. These ship wakes can be seen in satellite radar images as long bright strips of enhanced backscatter with characteristic length of up to several hundred kilometres lasting more than 5 hours. A hypothesis is put forward of the coherence of this type of ship wakes detected in sea surface radar imagery and areas of intensive biogenic activity under conditions of low near-surface winds. Statistics on their seasonal, spatial and year-to-year distribution are drawn. These results are compared with temporal and spatial variations in chlorophyll a concentration and intensity of phytoplankton bloom in the area of interest. Chlorophyll a concentration maps derived from satellite data are used, as well as those based on in situ measurements. The relation between occurrences of this type of ship wake manifestations and areas of algae blooms is established.

Ship wakes can be clearly seen in satellite radar and optical images of the sea surface, and understanding of physical mechanisms responsible for the wake signatures is very important to develop methods of ship detection/identification. The wake surface signatures at small and intermediate stages are characterized by a smooth centerline area where surface waves are depressed due to the vessel turbulence and by a pair of rough bands at the sides of the centerline wake. At large wake ages two slick bands (a “railroad track” wake) appear instead of the rough bands, while the smooth centerline band is practically absent. In this paper results of field studies of the mean flow structure near the wake are presented. It is shown that two mean circulating currents (“rolls”) rotating in the opposite directions are formed at two sides of the median vertical plane of the wake. Near the water surface the rolls result in diverging horizontal flows, decreasing near the wake edges. Wind waves propagating against the diverging currents are amplified due to a wave straining mechanism thus increasing the surface roughness. Film sampling was carried out when crossing the wakes and analysis of films collected within the “railroad” slick bands and outside the bands has revealed enhanced surface wave damping, obviously due to accumulation of surfactants in the slick bands; the surfactant compression is explained by the action of the diverging currents. The diverging currents as part of the rolls and the surfactant transport to the water surface are supposed to be associated with air bubbles generated by ship propellers.

For detecting accidental and illegal pollution by mineral oil, the German exclusive economic zone and surrounding waters have been monitored by aircraft operationally for more than 25 years. Aircraft surveillance uses predominantly Side-Looking-Airborne-Radar for visualization of the effect of oil to smoothen capillary waves. A set of near range sensors complements the remote sensing data available for the human operator to classify the detected features as "mineral oil", "natural phenomenon", "other substance" or "unknown" pollution. Today, as an add-on to aerial surveillance, the German Central Command of Maritime Emergencies uses the operational satellite service "CleanSeaNet" provided by the European Maritime Safety Agency: Radar satellite data is analyzed in near real time and alerts of potential pollution are sent out. Shortly after receiving the results, aircraft surveillance flights are started by the 3rd Naval Air Wing and the locations of the satellite alerts are checked. Thus, a combined system of satellite and aerial surveillance is in place. The German Federal Institute of Hydrology, BfG, has access to the data of the pollution events detected during these flights and the corresponding meta-data of flights and satellite images. In this work, a period of two years of this data is analyzed. The probability to detect pollutions is evaluated for (A) flight missions associated with satellite scenes, and (B) additional flights performed independently from satellite scenes. Thus, the influence of satellite alerts on the efficiency of aircraft monitoring is investigated. Coverage and coordination of the monitoring by aircraft and satellite are assessed and implications for the operational monitoring are discussed.

Surface signatures of oceanic internal waves (IWs) are often observed in synthetic aperture radar (SAR) images since IWs change surface roughness through the interaction of small-scale ocean waves with varying currents induced by IWs. If we know the relationship between the vertical and horizontal parameters governing IWs, the mixed layer depth (MLD) can be estimated from SAR data since IWs propagate along a pycnocline where the water density changes rapidly. This study presents a method for estimating MLD from SAR data using IW images observed by RADARSAT-1 over the east waters of the Korean Peninsula. To interpret IWs using SAR data, the backscatter radar cross section is computed by applying the small perturbation model to the sea surface perturbed by varying surface currents. Wave height spectrum is computed by varying the upper layer depth of mixed layer from 5 m to 100 m with 1 m depth interval. The surface current field is assumed to move with the IWs, and is described by the KdV equation. The computed RCS is then compared with the RADARSAT-1 data, resulting in satisfactory agreement of the estimated depth of IWs with other data.

Satellite radar (SAR) and visible band data from Envisat ASAR, ERS-2 SAR, Lansat-5,7,8 sensors were used to investigate internal waves (IWs) in the Black Sea. The three main areas of the Black Sea where surface manifestations of internal waves (SMIWs) were mostly observed are: the Danube Delta, Crimea Peninsula and the northeastern region near Novorossiysk. The main goal of our investigation was to define the mechanisms of IW generation in the non-tidal sea. In the first area, IWs are observed rather often due to surface intrusions of fresh waters of the Danube River. In contrast to usual soliton-like IW trains caused by river plumes, soliton trains near the Danuba Delta propagate in different directions and often subject to nonlinear interactions. The interrelation between location and orientation of IW trains and fresh water fronts is discussed. In the area off Crimea, in our opinion, IWs are generated mainly by upwelling relaxation and interaction between internal inertial waves and bottom topography features. SMIW in the northeastern part of the Black Sea are scarce, though IWs are regularly revealed by in-situ measurements. Field measurements were conducted in the northeastern part of the Black Sea from a small boat and from scientific sea platform near Crimea employing CTD probes, thermistor chain and Acoustic Doppler Current Profilers (ADCP). ADCP measurements allowed us to detect a number of IW trains. Their amplitudes were estimated to reach 5-8 m. Joint analysis of satellite SAR and subsatellite data gave an assessment of their typical wavelength at 90-100 m.

Satellite altimetry has proven to be a useful tool to study oceanic processes in the deep ocean; however, its use is still limited in shallow waters near the coast where two main issues still need a more detailed analysis. On one side, the local characteristics of each coastal region imply that certain corrections applied to the altimetry measurements need to be reanalysed. On the other side, the radar signal retracking algorithms need to be improved because the waveforms do not follow the Brown's model, which is designed for deep waters. The ESA mission Envisat was launched in March 2002 with a dual-frequency radar altimetry (RA-2). The satellite was operative until the end of the mission in May 2012. The ESA mission Cryosat-2 was launched in April 2010 being still in operation. The radar instrument on-board Cryosat-2 improves the capabilities of previous pulse-limited altimeters, such as Envisat RA-2. The Spanish-funded ALCOVA project aims at analyzing and improving the altimetry measurements obtained from these two altimetry missions. Regarding the RA-2 data a new prototype retracker -ALES- has been developed under the frame of the ESA-DUE eSurge project. Two pilot regions are proposed, namely, the Gulf of Cadiz and the Strait of Gibraltar in the Southwestern Iberian Peninsula. Cryosat-2 data (in SAR mode), the newly corrected RA-2 data (based on ALES) and the standard RA- 2 product (based on Brown's model) are being validated with available in-situ data (sea level height) to ensure their correct performance in the selected coastal areas.

A scatterometer is a radar designed to measure the backscattering coefficient of distributed targets. In order to compute the backscatter from the received power, the scatterometer measures also the thermal noise power. This noise signal is composed of two components, the receiver thermal noise and the viewed ground radiance. The first component is instrument dependent and hence independent of the target and viewing geometry. The second component is target and viewing geometry dependent, it is proportional to the ground target brightness temperature. In this paper the noise signal measured by C-band scatterometers on-board ERS-2 and Metop-A satellites is analyzed. It was found that the noise signal carries valuable geophysical information, which is worth to be exploited. It is shown that the noise signal varies spatially, temporally and with viewing geometry. Thus, different targets (ocean, sea ice, land) could be easily identified. A comparison was carried out between the scatterometer noise and AMSR-E radiometer brightness temperature and high correlation was found. The noise signal processing (mainly noise subtraction) is discussed, including the assessment of the Noise Equivalent Sigma Zero and the Signal-to-noise ratio. This analysis leads to a better understanding of the noise signal and its impact on the backscatter processing.