The Copernicus Programme is a joint European initiative developed by the European Commission (EC) and the European Space Agency (ESA) to provide accurate, up-to-date, and comprehensive Earth observation data for environmental monitoring, climate change analysis, disaster management, and security. The Copernicus program comprises a series of dedicated satellite missions i.e., the Sentinels spanning a wide range of the electromagnetic spectrum with different sensing techniques.Sentinel-1 [1] is the radar imaging component of Copernicus. It is a two-satellites constellation placed in the same orbit and spaced 180º apart. The Sentinels are providing systematically data to the Copernicus service component and scientific users.The Copernicus operational services are covering key operational applications tailored to support the definition and monitoring of European policies such as:–Observation of the marine environment and sea-ice monitoring–Surveillance of maritime transport zones–Land surface mapping, e.g., vegetation cover and surface deformation,–Polar environment monitoring (e.g., ice shelves and glaciers)–Climate Change–Emergency Response and ManagementThe Sentinel-1 first generation comprises four satellite units developed in two batches. The first two (A and B) have been already launched and two recurrent (C&D) ones planned for launch ensuring continuity of measurement throughout the 2020’s. Sentinel-1C and D will overlap with other Copernicus SAR mission in development like ROSE-L [2] and the Sentinel-1 Next Generation [3].In this paper we discuss the status and evolution of the Sentinel-1 first generation.

ESA BIOMASS will be the first spaceborne P-band SAR, and is designed to produce annual, near-global maps of forest biomass. Biomass-independent scene properties can be mitigated by interferometric pre-processing of the acquisitions, after which backscatter is inverted by a model to estimate biomass, relying on some external reference biomass. The model is simple enough to be invertible, while still representing the spatiotemporal variability of parameters in a global scenario. However, it requires a reliable, global reference biomass dataset, with enough coverage to reflect the variability of the chosen model. The global algorithm is also computationally efficient, so can be deployed in the ground segment. In this paper we briefly discuss the design of the global estimation algorithm for BIOMASS and propose a reference biomass dataset for the algorithm. Then, we discuss the robustness of the proposed algorithm using some reference biomass data for three different parameter variability setups.

This paper introduces the extended timing annotation dataset (ETAD) product for Sentinel-1 (S-1) which was developed in a joint effort of German Aerospace Center (DLR) and the European Space Agency (ESA). It allows to correct range and azimuth timing of S-1 images for geophysical effects as well as for inaccuracies in synthetic aperture radar (SAR) image focusing. In combination with the precise orbit solution, these effects determine the absolute geolocation accuracy of S-1 SAR images and the relative collocation accuracy of repeat pass image stacks. ETAD contains the gridded timing corrections for the tropospheric and ionospheric path delays, the tidal-based surface displacements, and the SAR processing effects, all of which are computed for each data take using standard models from geodesy and auxiliary atmospheric data. The ETAD product helps S-1 users to significantly improve the geolocation accuracy of the S-1 SAR products to better than 0.2 m and offers a potential solution for correcting large scale interferometric phase variations. The product layout and the product generation are described schematically. The paper also reports first results for different SAR techniques: first, the improvement in geolocation accuracy down to a few centimeters by verification of accurately surveyed corner reflector positions in the range-azimuth plane; second, the well-established offset-tracking technique, that is used for systematic ice velocity monitoring of ice sheets and glaciers, where ETAD can reduce velocity biases down to sub-centimetric values; and third, the correction of atmospheric phase contributions in wide-area interferograms used for national and European ground motion services. These early results proof the added value of the ETAD corrections and that the product design is well suited to be integrated into the processing flows of established SAR applications such as absolute ranging of targets, speckle/feature tracking and interferometry.

An updated algorithm for removal of thermal noise in Sentinel-1 synthetic aperture radar (SAR) Level-1 Ground Range Detected (GRD) data in cross-polarization is presented. The algorithm is comprised of two steps: correction of the annotated thermal noise magnitude (previously proposed in park2018) and a novel correction of the annotated thermal noise range dependence. The magnitude of the annotated thermal noise is corrected by applying scale and offset coefficients tuned on a few hundred of Sentinel-1 data acquired over surfaces with low backscatter in Interferometric Wide and Extra Wide swath modes in HV and VH polarizations. The values of coefficients for all modes and polarizations for data processed with Instrument Processing Facility (IPF) version 3.1 -3.3 are provided. The range dependence is corrected by minimizing a cost function between the annotated range profiles of thermal noise and antenna pattern gain (APG). An objective validation metric based on comparison of averaged backscatter at inter-swath boundaries is proposed. Validation is performed on hundreds of Sentinel-1 scenes acquired over open ocean, doldrums, deserts and sea ice. It shows that the new algorithm outperforms the standard thermal noise removal algorithm proposed by European Space Agency in almost all cases. Analysis shows that the new algorithm worsens noise correction in cases when the range dependence of the annotated APG does not match with the observed signal, indicating either problems with signal processing on IPF or imprecise annotation of APG.

The benefits of composite products are well known to users of data from optical sensors: cloud-cleared composite reflectance or index products are commonly used as an analysis-ready data (ARD) layer. No analogous composite products are currently in widespread use that is based on spaceborne radar satellite backscatter signals. Here, we present a methodology to produce wide-area ARD composite backscatter images. They build on the existing heritage of geometrically and radiometrically terrain corrected level 1 products. By combining backscatter measurements of a single region seen from multiple satellite tracks (incl. ascending and descending), they are able to provide wide-area coverage with low latency. The analysis-ready composite backscatter maps provide flattened backscatter estimates that are geometrically and radiometrically corrected for slope effects. A mask layer annotating the local quality of the composite resolution is introduced. Multiple tracks are combined by weighting each observation by its local resolution, generating seamless wide-area backscatter maps suitable for applications ranging from wet snow monitoring to land cover classification or short-term change detection.

In order to help scientists in the above ground biomass community and to support the science behind the upcoming BIOMASS satellite missions, ESA is building a cloud-computing platform called Multi-Mission Algorithm and Analysis Platform (MAAP). The MAAP is jointly developed and implemented with NASA and will include not only data (satellite, airborne, in situ data and products), but also high performing computing capabilities and tools and algorithms developed to support this specific field of research. To best ensure that users are able to collaborate across the platform and to access needed resources, the MAAP requires all data, algorithms, and software to conform to open access and open-source policies. As one such example of best collaborative and open-source practices, the BIOMASS data processing algorithms are developed on MAAP under the umbrella of an open-source scientific software project called BioPAL. In addition to aiding researchers, the MAAP will focus on sharing data, science algorithms and compute resources in order to foster and accelerate scientific research.

The Biomass mission is the 7th Earth Explorer Mission within the frame of the ESA Earth Observation Programme. The primary objective of Biomass is to determine the worldwide distribution of forest above-ground biomass in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere. To meet these objectives Biomass will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR) supporting also interferometric acquisitions. This paper provides an overview of the Biomass system design and development status.

Radio Frequency Interference (RFI) is a well-known issue since the early days of telecommunications. Traditionally considered an occasional event in the Earth Observation domain, RFI is becoming a severe problem due to the surge of wireless LANs and the increasing number of operational EO missions. In the near future, RFI will eventually be treated as an additional source of noise, to be addressed not only for mitigation, but also during mission design. Sentinel-1 (S-1) is a constellation of two spaceborne C-band synthetic aperture radar (SAR) sensors developed and operated by the European Space Agency under the Copernicus programme. In this paper, S-1 thermal noise measurements are used to create an automatic monitoring system generating world RFI maps with a periodicity of 12 days. For tuning the system, the RFI power is calibrated against a radiometer operating at the same range of frequencies. Analysing the strength and geographical distribution of the RFI, the most affected regions are identified and probability maps are extracted.

In the framework of the EU/ESA co-funded Copernicus program [RD-1] (formerly known as Global Monitoring for Environment and Security - GMES). ESA is developing and operating a series of Sentinel missions with the objective to provide routinely Earth Observation data for supporting the implementation of operational Copernicus services and for existing or future national service initiatives.

This article shows how the array of corner reflectors (CRs) in Queensland, Australia, together with highly accurate geodetic synthetic aperture radar (SAR) techniques-also called imaging geodesy-can be used to measure the absolute and relative geometric fidelity of SAR missions. We describe, in detail, the end-to-end methodology and apply it to TerraSAR-X Stripmap (SM) and ScanSAR (SC) data and to Sentinel-1 interferometric wide swath (IW) data. Geometric distortions within images that are caused by commonly used SAR processor approximations are explained, and we show how to correct them during postprocessing. Our results, supported by the analysis of 140 images across the different SAR modes and using the 40 reflectors of the array, confirm our methodology and achieve the limits predicted by theory for both Sentinel-1 and TerraSAR-X. After our corrections, the Sentinel-1 residual errors are 6 cm in range and 26 cm in azimuth, including all error sources. The findings are confirmed by the mutual independent processing carried out at University of Zurich (UZH) and German Aerospace Center (DLR). This represents an improvement of the geolocation accuracy by approximately a factor of four in range and a factor of two in azimuth compared with the standard Sentinel-1 products. The TerraSAR-X results are even better. The achieved geolocation accuracy now approaches that of the global navigation satellite system (GNSS)-based survey of the CRs positions, which highlights the potential of the end-to-end SAR methodology for imaging geodesy.

As part of the European Copernicus programme, the Sentinel-1 mission, based on a constellation of two SAR satellites, ensures continuity for C-band SAR observations for Europe. Both satellites have been launched from Kourou on a Soyuz rocket, Sentinel-1A on 3rdApril 2014, Sentinel-1B on 25thApril 2016. Following the completion of the constellation operational qualification phase, the routine operations of the constellation are on-going and performed at the full mission and system capacity. The mission is characterized by large-scale, frequent and repetitive observations, systematic production and a free and open data distribution policy.The paper provides high-level information on the ongoing mission operations. It describes at high level the system operations, incl. the basics of the Sentinel-1 observation scenario and the satellite and ground segment operational activities. It presents few examples of Sentinel-1 mission exploitation activities in the domain of disaster management and geohazards monitoring, ones of the main thematic of IGARSS 2019.

The thermal noise-induced distortions in a Sentinel-1 terrain observation with progressive scans synthetic aperture radar image cannot be corrected by the noise equivalent sigma nought (NESZ) subtraction only. Since the thermal noise is scaled during synthetic aperture radar processing, it resides not only as an additive noise in each pixel but also as a multiplicative noise in the interpixel contrast. In this paper, we investigate the noise characteristics and propose an efficient method for the multiplicative textural noise correction. The core ideas are to find the optimal coefficient of the noise-induced standard deviation (SD) and model the noise contribution to the local SD as a function of the NESZ and the signal-to-noise ratio. Denoising is accomplished by a subwindow-wise adaptive rescaling of the pixel values. The improvements in the first- and second-order statistical textural features demonstrate the effectiveness of the proposed method.

Synthetic Aperture Radar (SAR) satellites observe range and azimuth geometric accuracies at the low centimeter level. The accuracy of geolocation is driven by several aspects, e.g. orbit determination, SAR image processing, or atmospheric error correction. Our paper concentrates on the Sentinel-1 mission and the compensation of the platform motion effects in the geolocation, which were found to limit the best possible geolocation capabilities of Sentinel-1. The key to advance the geolocation results is the rigorous compensation of the bistatic effect in azimuth, and the correction of the Doppler-induced shifts in range. First results for Sentinel-1 at the Australian reflector array consisting of 40 Corner Reflector (CR) show consistent improvement in the geolocation$(1\sigma)$to 6 cm in range and 28 cm in azimuth for both spacecrafts when using the Interferometric Wide swath (IW) product.

For many land monitoring applications using remote sensing, lack of data is no longer an issue, as it may have been in the past. Programs, such as Copernicus by the European Commission and the Landsat Missions by the United States Geological Survey, have adopted systematic acquisition strategies, and distribute vast amounts of satellite data under open licenses. In parallel, storage and computing capability have evolved to make it cost-effective and practical to process and analyze these data at various scales. Data architecture solutions, such as the Open Data Cube (ODC) and the Copernicus Data and Information Access Services (DIAS), are providing frameworks that make [scientific] analysis much simpler and straightforward. However, enabling non-expert users without the expertise and/or computation resources to pre-process and store low-level data products in order to exploit these capabilities, has proven more challenging. The Committee on Earth Observation Satellites (CEOS1) is working to address this challenge through the CEOS Analysis Ready Data for Land (CARD4L) initiative [1]. CARD4 L is foreseen to enable users to access satellite data products that are `ready to use' for a wide range of land applications. Moreover, CARD4L aims to enable non-expert users access to products that have been processed `far enough' to be suitable for immediate analysis for a range of applications, while ensuring they are not too specific to only be used for particular topics or areas. CARD4L will be an important enabler of the Open Data Cube (ODC) initiative [2]. Through CARD4L, users will be able to easily locate products that are suitable for ingestion into Data Cubes [3], and will have confidence that these different CARD4 L products will limit as far as possible barriers to interoperability.

Sentinel-1 (S-1) is a constellation of two C-band SAR satellites [1] whose development is co-funded by the European Space Agency (ESA) and the European Commission (EC) as part of the Copernicus space program. S-1A was launched in May 2014 followed by the S-1B unit two years after. The constellation is operational since September 2016 after the successful commissioning of the second unit. This paper provides an update of the constellation performance and recalls the last result achieved in terms of radiometric and geometric accuracy.

As part of the European Copernicus programme, the Sentinel-1 mission, based on a constellation of two SAR satellites, ensures continuity for C-band SAR observations for Europe. Both satellites have been launched from Kourou on a Soyuz rocket, Sentinel-1A on 3rd April 2014, Sentinel-1B on 25 April 2016. Following the completion of the constellation operational qualification phase, the routine operations of the constellation are on-going and performed close to the full mission and system capacity. The mission is characterized by large-scale, frequent and repetitive observations, systematic production and a free and open data distribution policy. The paper provides high-level information on the ongoing mission operations. It describes at high level the system operations, incl. ground segment operational activities, as well as some user data access statistics. It presents few examples of mission results achieved since the operations of Sentinel-1A, in some key application domains.

The Sentinel-1 constellation provides high resolution radiometrically calibrated SAR images with 6 days revisit and global coverage. The radiometric calibration was established during the Commissioning Phase exploiting transponders and natural targets. The paper describes the elevation antenna pattern verification based on the S-1 Antenna Model and the necessary refinements performed to achieve the requested radiometric accuracy.

This paper addresses the results of the instrument and product performance verification, radiometric and geometric calibration achieved since the end of the respective Sentinel-1 A and B commissioning phases.

Sentinel-1A and Sentinel-1B have been launched from Kourou on a Soyuz rocket on 3rd April 2014 and 25 April 2016 respectively. Data opening was made early October 2014 for Sentinel-1A and end-September 2016 for Sentinel-1B. At the time of writing this paper, the so-called mission operational qualification phase is on-going, with a gradual increase of the capacity of the overall system, including the use of the European Data Relay Satellite System (EDRS). The Full Operation Capacity (FOC) of the mission will be reached indicatively by Q2 2017. The paper provides high-level information on the on-going mission operations. It describes at high level the system operations, incl. ground segment operational activities, as well as some user data access statistics. It presents few examples of mission results achieved since the operations of Sentinel-1A, in some key application domains.

This paper addresses the results of the instrument and product performance verification, radiometric and geometric calibration achieved during the since commissioning and routine phase.

Sentinel-1A has been launched from Kourou on a Soyuz rocket on 3rd April 2014. The second satellite Sentinel-1B is planned to be launched first half of 2016. The In-Orbit Commissioning phase was completed on 23 September 2014, followed by the so-called operational qualification phase (ramp-up). This ramp-up operations phase is a phase during which the capacity of the overall system, including the ground segment operations, is progressively increased, together with the gradual release of the operationally qualified products. The ramp-up phase is being completed at the time of writing this paper (end May 2015); at this stage the routine operations are starting. The Full Operation Capacity (FOC) of the mission will be reached once the In-Orbit Commissioning phase of Sentinel-1B and the subsequent constellation operational qualification phase will have been completed, indicatively by end 2016. The paper provides high-level information on the ongoing mission operations, at the time of the ramp-up phase completion. It described at high level the system operations, incl. ground segment operational activities, as well as some user data access statistics. It presents few examples of mission results achieved during the first year of Sentinel-1A in orbit, in some key application domains.

Sentinel-1A (S1A), launched by the European Space Agency (ESA) on April 3, 2014, is a state-of-the-art spaceborne Synthetic Aperture Radar (SAR) Earth observation platform. S1A products are expected to provide high and consistent geolocation accuracy. As of the end of May, 2014, the satellite has not yet reached its reference orbit. However, estimation of product geolocation accuracy is ongoing, and improvements are continually being made. The results reported here represent the early situation, with continued progress expected.

This paper proposes a set of tests that provide necessary and, as far as possible, sufficient conditions for verifying the phase preservation of synthetic aperture radar (SAR) processors. This paper discusses two different test families composed of self-consistency and point-target-based tests. The set of self-consistent tests extends the well-known CEOS-OFFSET to very different acquisition modes, namely, StripMAP, ScanSAR, TopSAR, and SPOTLIGHT, and introduces a new complementary test to check the consistency of the space-variant implementation of a processor. The set of point target tests, based on the analysis of point target simulated data, completes the self-consistent tests by providing a verification of phase accuracy between different bursts and swaths.

The Sentinel-1 Instrument Processing Facility (IPF) is the sub-system of the Sentinel-1 Payload Data Ground Segment (PDGS) [1] responsible for the generation of the Level-1 and Level-2 products. This paper provides an overview of the Sentinel-1 IPF architecture, processing algorithms and the output products.

This paper provides an overview of the Senitnel-1 Ground Segment and its main operations concepts. It presents the Sentinel-1 Payload data Ground Segment (PDGS), responsible during the Sentinel-1 mission operations for the Sentinel-1 mission planning, X-Band data downlink, data processing, quality performance, data dissemination, archiving activities and user interface, with the main objective to make the core ground segment products available to the Sentinel-1 users within the expected timeliness and quality. The paper describes as well the Sentinel- 1 operational user product family and their characteristics.

A refinement technique of the antenna model considered to compute Synthetic Aperture Radar (SAR) data pattern is proposed in this work. The accurate knowledge of the antenna patterns of a SAR sensor is of main importance for precise SAR image processing. This requirement, coupled with tight needs for a short duration of the calibration process, have made necessary the investigation of innovative methods to calibrate complex SAR systems. When considering active arrays, the antenna patterns computed from homogeneous SAR data is often in disagreement with those obtained from a mathematical model (the antenna model). In this paper a correction factor is introduced within the antenna model, in order to overcome this discrepancy. This parameter is expressed as a corrected version of the matrix indicating the working status of the antenna. It is estimated through inversion by exploiting the patten information of SAR data, and it can be used for effective antenna model calibration. The effectiveness of the proposed method is assessed by considering ENVISAT ASAR rain forest-images.

In this paper a method for calculating the antenna contribution to the Doppler Centroid is presented. The Antenna Doppler Contribution (ADC) is originated by the non idealities affecting the TR modules of the active antenna arrays. It is an undesired effect for SAR applications requiring stringent performances on the Doppler Centroid control capability. The first part of this paper introduces the problem and shows how it is possible to predict the ADC by exploiting a suitable Antenna Model. The second part of the paper presents a comparison between the ADC calculated with an Antenna Model and the ADC retrieved from real ASAR data.

Improved geometric accuracy in SAR sensors implies that more complex models of the Earth may be used not only to geometrically rectify imagery, but also to more robustly calibrate their radiometry. Current beta, sigma, and gamma nought SAR radiometry conventions all assume a simple ¿flat as Kansas¿ Earth ellipsoid model. We complement these simple models with improved radiometric calibration that accounts for local terrain variations. In the era of ERS-1 and RADARSAT-1, image geolocation accuracy was in the order of multiple samples, and tiepoint-free establishment of the relationship between radar and map geometries was not possible. Newer sensors such as ASAR, PALSAR, and TerraSAR-X all support accurate geolocation based on product annotations alone. We show that high geolocation accuracy, combined with availability of high-resolution accurate elevation models, enables a more robust radiometric calibration standard for modern SAR sensors that is based on gamma nought normalised using an Earth terrain-model.

The Stable Point Network (SPN) is a persistent scatterer interferometric technique developed by ALTAMIRA INFORMATION in 2001. The technique makes use of both ERS SAR and/or ASAR differential phase measurements to generate long term terrain movement and precise height maps with the same resolution as the original SAR images. The algorithm is capable to use all the available phase information even in conditions of large baselines or platform instabilities giving place to large Doppler centroid variations. Such behaviour is handled by precise location estimate of the scatterer within the pixel and accurate elevation extraction which permits the exact location of the radar measurement in ground geometry. However not all the SPN interferometric measurements within a pixel have a direct correspondence in the real scene. Some points presented as measurement points may not be related to existing structures on ground but directly generated by the processing itself. For instance, several artifacts can be created in the Synthetic Aperture Radar images due to the signal acquisition system. Azimuth ambiguities are one of them. They may appears as strong targets in low backscattering areas like forest or water. Secondary lobes of strong targets are also an issue. Since low level signals can be masked by the side lobes of higher level signals. They cannot be handled like standard scatterers and present completely different geometric behaviour not related to their position in the radar image. This paper discusses the way to identify those artifacts and analyses their impact on SPN measurements compared to their reference points (centre of the main lobe).