Following the huge success of the 2019 event in Rome, the SAR Analytics Symposium 2022 will once again feature analytical thought leaders and will provide a unique meeting place for SAR service providers and applied SAR analytics consumers from across various industries.

Attendees will glean knowledge and ideas from other successful real-world analytical applications, all while sitting in a truly beautiful setting in the middle of Berlin, renowned for its exceptional variety of attractions, its flourishing cultural scene and a way of life that's both fast-paced and relaxed. Attendance for the symposium is limited to 120 people in order to provide high-quality interaction and participation. All the programme will be presented in English language.




Free and open access to SAR data from the European Space Agency combined with the recent launches of other SAR sensors underscores the enormous role SAR will play in the future of Earth Observation. For established SAR users, as well optical data users looking to add SAR derived information to their GIS, these launches serve notice that a deluge of complex new data will soon arrive, presenting many commercial and operational benefits.

As a community of users, analysts, and solution providers, we must continue to find innovative ways to collect, process, and analyze SAR data, but even more importantly to create solutions that deliver real value. The SAR Analytics Symposium provides the leading thought leadership venue for participants to connect with decisionmakers from across the community, explore new trends and ideas, and transform this fast-growing and dynamic technology ecosystem.

Topics will include:

  • The present and future of spaceborne SAR
  • Near real-time SAR applications
  • Leveraging SAR derived information for environment and sustainability
  • Detecting change over time with extreme levels of accuracy
  • Understanding infrastructure and land displacements
  • Machine learning and deep learning to enhance SAR data
  • Large-scale applications using SAR


We would like to thank the following sponsors for their support of the 2022 SAR Analytics Symposium:

Want to stand out by showcasing your analytical work?
Submit to speak at the SAR Analytics Symposium

Submission deadline is June 30, 2022



Please note, agenda and speakers are subject to change.




October 20, 2022



The requirements for remote sensing data providers in terms of spatial and temporal resolution are growing with the technical capabilities of modern small satellite constellations. Capella will provide a live demonstration of how easily, quickly, and effectively Capella VHR SAR data can be tasked and downloaded directly by the customer via their Image-Tasking platform Console. This service enables near-real-time tasking of the constellation with no human in the loop, translating into full automation of task scheduling, secure and private customer operations, and speedy data processing and delivery to enable access to global monitoring where and when you need it. We will in detail explain what we mean with: - High-Quality - Very high resolution and low noise leads to enhanced image clarity - Timely - Rapid fully-automated order-to-delivery means faster speed to insight - Frequent - Increasing high-cadence revisit timeframes as our constellation grows - Accessible - Intuitive online platform with self-serve catalog search, ordering and tasking Capella’s high-resolution SAR satellites are matched with unparalleled infrastructure to deliver reliable global insights that sharpen our understanding of the changing world – improving decisions about commerce, conservation, and security on Earth. Learn more at www.capellaspace.com.

There is an increasing need to mine the large amount of data generated by the new generation of satellites coming online, including for example the Copernicus system and New Space. Artificial Intelligence (AI) is certainly one important part of the full solution, enabling scalable exploration of big data and bringing new insight and predictive capabilities. However, it is important to note that AI remains just a tool that needs to be used together with physical principles and scientific interpretation. While today, the new boost of AI4EO is mainly related to Computer Vision applied to optical satellite imagery, there is an increasing use of Deep Learning (DL) with Synthetic Aperture Radar (SAR) data. However, the huge potential of Deep learning in SAR and InSAR remains locked. This talk aims to provide a status on the current use of Deep Learning for SAR data, focusing on the current portfolio of activities run by ESA philab.

SAR images are not necessarily very easy to visually interpret, and these difficulties can even increase in case of images of man-made objects and infrastructures. On the other hand, the exploitability of automated methods for spatial features’ identification and recognition deeply relies on the availability of enough reference images to train recognition systems, when based on Artificial Intelligence and Deep Learning methods. This presentation will introduce the results of the development of a SAR image simulator and of an Automatic Target Recognition system tightly linked to it. The focus of the first component is in generating simulated SAR images that provide a rigorous representation of how a 3D scene would look like if acquired from a given SAR sensor: the generated images can be exploited for the training of human operators and as support to visual interpretation, as well as for the training of the ATR component. This second system is providing accurate automated detection and classification of objects and spatial features in a SAR image.

The presentation introduces an operational AI/ML solution for very fast object detection and recognition in high resolution SAR imagery. Focus will be on the training aspects and on the discussion of capabilities and challenges.


Climate change is causing an increased occurrence of geohazards (e.g., landslides, sinkholes) with enormous economic impact and disruption, affecting infrastructure globally. We present the use of SAR combined with geotechnical data and AI for geohazard susceptibility assessment. This allows problem areas to be pinpointed early and trends predicted. This, in turn, leads to earlier maintenance interventions which are more economical, less disruptive and build greater resilience to climate change back into our infrastructure. As well as infrastructure, this is also being applied for the benefit of the construction, insurance, real estate, energy and mining sectors.

Traffic infrastructure plays a vital role in today's society. For security and economic reasons, it is essential to monitor traffic infrastructure, including roads, railways, and bridges. Assessing the health of traffic infrastructure with conventional geodetic approaches like levelling or GNSS observations is time-consuming, costly, and limited to sparse locations. In contrast, Earth observation data from satellite missions provide unique opportunities for spatially wide-scale and temporally high-resolution monitoring. In the scope of our project SAR4Infra we develop an automatic InSAR processing chain to generate a risk displacement map for traffic infrastructure in Schleswig-Holstein. We investigate the combination of different time series techniques to obtain a dense distribution of pixels on the traffic infrastructure. The reliable pixels consist of persistent and distributed scatterers. We improve the signal-to-noise ratio of distributed scatterers by phase-linking and subsequently process both persistent and distributed scatterers jointly in a persistent scatterers time series approach. To decrease the computational burden, we estimate the deformation parameters sequentially once a new SAR image is acquired without re-estimating the whole time series. We will present the current status and prospects of the SAR4Infra project and highlight the challenges and opportunities of Sentinel-1 InSAR for traffic infrastructure monitoring.

Satellite-based InSAR deformation measurements offer new capabilities in the context of Structural Health Monitoring (SHM). The presentation discusses a monitoring concept combining InSAR, geodetic measurements and structural simulations.




October 21, 2022



Illegal, Unreported and Unregulated (IUU) Fishing is one the most pressing issues facing our natural world and is estimated to cost the global economy in excess of $23 billion annually or about 20%-30% of the global fish catch depending on the market. This challenge is particularly difficult to address due to the remote areas where IUU Fishing is occurring. MDA is a leader in the use of Synthetic Aperture Radar to extract analytics about vessels on the high seas far from shore to tackle the challenge of IUU Fishing. MDA will present the latest research and development work it has operationalized for extraction of vessels from SAR, vessel velocity and vessel classifications. MDA will review the analytical and machine learning approaches employed to enable these new capabilities. Further, this presentation will provide insight on how MDA investments in SAR fusion with other sources such as RF, VIIRS and optical is enabling fisheries intelligence users to address their most difficult maritime domain awareness challenges such as tracking illicit dark vessel activity.

SAR for Maritime Situational Awareness (MSA) with examples of use cases in multinational trials and exercises with NATO and non-NATO partners. SAR is one element of the digitalisation of the oceans.

SAR provides unique opportunities and challenges for monitoring nuclear fuel cycles for nuclear safeguards purposes and research on various weapons of mass destruction (WMD) programmes around the world. This presentation illustrates some of these opportunities and challenges with case studies from the DPRK context.

Chadian population is suffering of the effect of climate change due to a severe water scarcity in African arid regions. Groundwater potential maps might contribute to the hydrogeological knowledge and support the water resources management to plan the exploitation of the aquifers in Chad. A groundwater potential map based on a machine learning approach is presented for the crystalline aquifer of the eastern Chad. The spatial-distributed explanatory variables are derived from multi-sensor data: multitemporal Landsat-8 and Sentinel-2 optical data, Sentinel 1 SAR data, Meteosat Second Generation (MSG) TAMSAT and GLO-30 Digital Elevation Model are used to generate seasonal and static products. Geological and hydrogeological fieldwork and knowledge-based information completed the analysis. A sample of 488 wells and boreholes are used to train and test the machine learning classifiers to define the presence of groundwater. Analysis on the performance of the supervised classification algorithms shows that Random Forest provides the higher test score, the analysis on the most relevant explanatory variables shows that fracture density, slope, SAR coherence (interferometric correlation), topographic wetness index, basement depth, and distance to ephemeral channels have the higher probability to predict the groundwater occurrence. The results allowed to identify the wadis and piedmont region in Chad as the most favourable area for groundwater exploitation.

In the last decades the need to effectively investigate deformation phenomena affecting wide areas of the Earth surface has fostered the exploitation of satellite SAR images and advanced Differential SAR Interferometry (DInSAR) techniques. In this framework, the Parallel Small BAseline Subset (P-SBAS) DInSAR approach has demonstrated, by exploiting HPC infrastructures also including GPU-based architectures, its capability to efficiently perform massive surface displacement analyses related to natural and anthropic hazard scenarios, by generating spatially dense displacement time series with millimeter accuracy and at different spatial resolutions. In this work, we analyze the effectiveness of the P-SBAS DInSAR approach to study, at different spatial scales, deformation phenomena affecting the natural and the built-up environment. To do this we first show the P-SBAS capability to investigate the built-up environment of some of the largest Italian cities by processing full resolution X-band stripmap SAR data stacks acquired by the Italian first and second generation COSMO-SkyMed constellation. Subsequently, we show some results achieved by exploiting large volumes of the C-band SAR data acquired through the TOPS mode of the European Sentinel-1 sensors, relevant to the natural environment of the Italian territory. The final analysis is focused on the results obtained on selected stacks, processed through the P-SBAS approach, of L-band stripmap SAR data acquired by the SAOCOM-1 Argentinian constellation.

Thanks to the wide availability of SAR satellite missions, Multitemporal Synthetic Aperture Radar Interferometry (MT-InSAR) are nowadays reliable techniques to measure the effects of natural phenomena (earthquakes, landslides, etc.) and anthropogenic activities (exploitation of groundwater, hydrocarbons, gas storage, etc.) on urban areas and infrastructures (railways, airports, bridges, etc.). INGV GEOSAR Lab. exploited several commercial and open-source softwares such as SARScape, GAMMA and StaMPS to generate MT-InSARtime series stemming from C-Band Sentinel-1 (S1) and X-band COSMO-SkyMed (CSK) datasets. Finally the European Union released the Programme for Critical Infrastructure Protection (EPCIP) defining the overall framework for activities aimed at improving the protection of critical infrastructure in Europe. EU started the European Infrastructure Simulation and Analysis Centre (EISAC) initiative, for supporting Operators and Public Authorities in better protecting assets and in enhancing their resilience with respect to all hazards. In Italy, EISAC.it results from a joint ENEA and INGV collaboration agreement established in 2018.

Picking up recent trends in high volume and large scale interferometric data analysis, basic ground deformation services were implemented on a national (Germany) and Pan European scale. As a service provider, GAF utilises a robust and validated processing approach deployed on its private cloud infrastructure. Concepts of our basic service operation plus interfaces for value adding and downstream applications will be presented.


The volcanic eruption on the island of La Palma (Canary Islands) started on 19.09.2021, specifically as a flank eruption at the Cumbre Vieja volcanic ridge comprising the southern half of the island. On 13.12.2021, volcanic activity stopped and was finally declared to have ended by 25.12.2021. With a duration of 85 days, it has been the longest known eruption on La Palma and the first on the island since the eruption of Teneguía in 1971. The eruption caused the evacuation of around 7,000 people and the lava flow covered an area of about 3.5 km in its widest point and 6.2 km long, affecting over 1,200 hectares. It reached the sea in two different locations forming two new peninsulas. During the eruption, approximately 3,000 buildings and 70 km of transportation infrastructure were destroyed. Towns such as Todoque or Los Campitos were significantly affected, as well as agricultural land, destroying 370ha of planted areas and affecting immensely the economic situation of local farmers.

In this talk, an overview of the emergency and main outcomes derived from the processing of SAR data will be presented. The results were produced by IABG in the context of the Copernicus Emergency Management Service in support of the Spanish authorities.

The COSMO-SkyMed Second Generation [CSG] is at the forefront of radar technologies and ensures improvements and guarantee continuity with the first generation satellites, preserving the high quality and the highest precision features, both required for the interferometric activities. The programme is funded by Agenzia Spaziale Italiana (ASI), the Italian Ministry of Defence and the Italian Ministry of Education, Universities and Scientific Research. Thales Alenia Space is the prime contractor responsible for the construction of two satellites, while Telespazio provides the ground segment and offers integrated logistics for operations. The present work focusses on the enhanced performances of second generation radar data and their new application potentials. In details, it will be showed how the polarimetric capabilities of the new generation radar sensors, added to the high frequency revisit of the constellation, enhance Earth Observation performances of the COSMO mission. e-GEOS, world-wide exclusive distributor of COSMO-SkyMed and operator, on behalf of ASI, of the IC-UGS (Italian Civilian User Ground Segment) at the Matera Space Center, is one of the most important satellite data providers on the market, providing also several Earth Observation based services. Mainly focusing on providing and using Synthetic Aperture Radar (SAR) images, e-GEOS is one of the major actors in the field of Emergency Services, Interferometric Analysis, Defense and Intelligence analysis, and many other services that have been developed during the years and that take advantage of the new missions available on the market.

In recent years, a new generation of Very High Resolution SAR satellites became operational like the Spanish PAZ, the German TerraSAR-X/TanDEM-X, the Italian Cosmo/Skymed, etc. The spatial resolution of such satellites achieves the meter domain or even below. InSAR (Interferometric Synthetic Aperture Radar) is a technique based on SAR data that allows monitoring tiny displacements of the Earth’s surface. It provides accuracy similar to the traditional or terrestrial techniques (e.g. levelling or GPS) without the need of in-situ observations or special equipment. The aim of this presentation is to illustrate the advantages of using Very High Resolution X-Band for InSAR purposes. The density of the measuring points and the accuracy on its location is of the utmost importance especially for civil engineering and critical infrastructure surveillance. The presentation discusses a study that aims at measuring potential surface deformation close to a rail track in the North of Spain. For that purpose, a series of 50 PAZ Very High Resolution images have been used combining Ascending and Descending passes.

Space shift is a Japanese company based in Tokyo develops SAR satellite data analytic software with AI/ML. Analysis of SAR data should not be limited to its amplitude images as it contains more information such as phase changes in lower products like SLC. We developed our own AI/ML method to utilize hidden features to improve its prediction accuracy to fit market requirements. In this presentation we will introduce our methodology to utilize all of available “Data” contained inside of SAR satellite signals to improve its capability for many type of civil applications and actual cases of our various customers.

SAR data is fragmented and spread across multiple provider platforms, which makes It hard to build and distribute algorithms, especially when you want to do this at scale. UP42 provides access to several SAR data providers, including Capella Space, TerraSAR-X and Sentinel-1. We also provide a workflow engine and scalable infrastructure, which means we enable you to bring your own algorithms to the platform, to process SAR data in our platform. You can build processing pipelines and use already existing SAR-processing algorithms, such as ship detection and ground displacement. In this presentation we want to demonstrate some examples of SAR data processing at scale.



Stay at the outstanding

Radisson Blu es. Hotel, Berlin


The SAR Analytics Symposium will be held at The Radisson Blu Hotel, one of the most exciting hotels in Berlin-Mitte. It is located in the historic centre directly on the bank of the river Spree and opposite to the Berlin Cathedral. Just a strolls away are restaurants, bars, boutiques, galleries and famous sights, such as Alexanderplatz, Museum Island, Boulevard Unter den Linden and the exclusive shops along Friedrichstrasse. A unique attraction is the AquaDom at the hotel lobby. It is the world’s largest cylindrical aquarium with a fascinating underwater world in one million litres of salt-water. 427 non-smoking guest rooms and suites combine timeless elegance with cutting edge comfort. The clear design in the puristic style reflects urban trends. The dark wood and warm tones of the high-class furniture create a homely atmosphere.

Discounted rates are available for the SAR Analytics Symposium through September 15th. Click here now to book your room online and save on the cost of your hotel stay. You can also send an e-mail to berlin@radissonblu.com or call +49 30 238 28 0.


Travel from Schönefeld Airport

From Schönefeld Airport, follow the covered walkway to the train station. Take the S9 train to S Hackescher Markt station; it runs every 20 minutes. From there, walk about 500 meters to the hotel.

Take either the RE 7 or the RB 14 Airport Express trains to Alexanderplatz station; they run twice an hour and take just under 30 minutes. From Alexanderplatz, head down Karl-Liebknecht-Strasse toward the cathedral/City Palace for a 10-minute walk. The hotel is on the right, just before the bridge. Alternatively, take the M4, M5, or M6 tram just one stop from S+U Alexanderplatz Bhf/Gontardstrasse to Spandauer Strasse/Marienkirche; the hotel is just around the corner on Karl-Liebknecht-Strasse.


Travel from Tegel Airport

Take the TXL bus outside Terminal A or B to Hauptbahnhof/Central Station. At Hauptbahnhof, take bus 245 toward Alexanderplatz and disembark at Lustgarten in front of the City Palace. The hotel lies just across the bridge toward the TV Tower on the other side of the street.

The quickest way to get from Tegel Airport to the hotel is by taxi. Expect a 30-minute journey, depending on traffic.