Poster Session 1 Sponsored by ESA

There is an ongoing need to understand and quantify the state and dynamics of forest ecosystems at local scales to support operational research including land use/land cover change monitoring and sustainable forest management. Forest cover is one of the key biophysical parameters used in prediction models to assist with ecosystem monitoring & and in geospatial tools to assist with forest management. In a wide range of novel research studies data collected by Synthetic Aperture Radar (SAR) satellite systems have been used to enhance the identification & mapping of forest structure parameters including forest cover in remote areas where access is difficult, or with persistent cloud-cover. SAR data haven’t been used as widely in operational research to assist forest managers, geospatial practitioners, and forest scientists with decision making thus awareness needs to be raised in understanding the SAR data meaning & the processing flows required to use SAR data in information extraction systems. This poster is a key part of a European Space Agency (ESA) & Canadian Space Agency (CSA) sciences and operational application research (SOAR-2) project with the title ‘Studying Some Coniferous Forests' Characteristics with RadarSat-2 Data in Bulgaria’ which aims to assess the capability of backscatter data collected by the Canadian satellite RadarSat-2 to assist with forest cover mapping to support the sustainable management in two study areas; Parangalitza; United Nations Educational, Scientific and Cultural Organization (UNESCO) Man and Biosphere reserve, and Govedatzi, both located in the Rila mountain, Bulgaria.
Overall the ESA Cat-1 project has the following objectives:
1. Design & implement a SAR data collection plan to assist with dual-pol (HH, HV) RadarSat-2 (C-band) data collection during
dry periods to mitigate effects of precipitation to the SAR data, and using ascending & descending data collection modes to
support the mitigation of the extreme topographic relief found in Rila Mountain.
2. Pre-process & enhance the RadarSat-2 data to analysis level using the ESA Sentinel Application Platform (SNAP) and the
RadarSat-2 toolbox including a very high resolution Digital Elevation Model (DEM).
3. Using the RadarSat-2 backscatter data establish their sensitivity to forest cover as quantified by field measurements or a forest cover raster product (25m pixel spacing) which was derived using Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data.
In this poster we present the bespoke process flow devised & implemented during objective (1) which was used to order & collect the RadarSat-2 data to fit the purpose of analyzing radar backscatter data in an area with high topographic relief and precipitation, and we present & describe the RadarSat-2 backscatter data which will be used in objective (3) in future analyses.
The results presented in this poster will assist forest managers, geospatial experts, and forest modelers to gain insights on the SAR data design & collection workflows required for forested environments and on the meaning of the backscactter SAR data collected by RadarSat-2 to support information extraction.

Land-use/land-cover (LU/LC) change detection using satellite data has gained momentum in the past decades due to the need of detecting changes in Earth ecosystems caused by climate change or antropogenic drivers. With the advance of the Copernicus program, one of the greatest potentials of the large amount of earth observation data to be generated from the Sentinels, is studying global, regional, and local changes through time. The Compact High Resolution Imaging Spectrometer (CHRIS) mounted onboard the Project for OnBoard Autonomy (PROBA-1) spacecraft is a hyperspectral sensor which multi-angle viewing capability was found useful for vegetation structure assessment. The study area, “Bistrishko Branishte” UNESCO MAB reserve, is located in the upper part, between 1430 and 2282 m a.s.l., of Bistrica river basin in the North-East Vitosha Mountain. It was designated a biosphere reserve by UNESCO Man And Biosphere (MAB) Program in 1977. More than a half of the reserve territory is covered by an old-grove (120-150 years) Norway spruce (Picea abies L.) forest stands. Following a wind throw in 2001, an European Spruce Bark Beetle (Ips typographus) infestation outbreaked in the most affected areas by the wind throw.
The dead tree stands, which were not removed due to the strict regime of protection, were almost completely burned out in a wildfire occurred in the summer of 2012. Present study aims at studying the LU/LC change of “Bistrishko Branishte” UNESCO MAB reserve using CHRIS/PROBA Mode 1 satellite data acquired in 2012 and 2015. In this mode the satellite acquires images in five viewing angles, including nadir. The methods used in the study can be grouped into:

1) Pre-processing and data manipulation - CHRIS/PROBA satellite data were subject to data collection, noise correction, atmospheric and geometric correction, georeferencing, conversion to reflectance, cross-track illumination correction, terrain correction, spatial sub-setting, and design of a geodatabase in ArcGIS for subsequent spatial analysis;

2) Data analysis - LU/LC change detection is done using spectral difference images of nadir-looking mode CHRIS/PROBA Mode 1 images as well as difference between LU/LC maps produced after Maximum Likelihood Classification (MLC) method;

3) Data visualization – production of statistics (zonal), charts, and maps.

The results obtained show a significant shift of the reserve’s LU/LC classes between pre and post-wildfire event and a slow vegetation regrowth at the fire scar of 2012 wildfire, represented mainly by grassland and deciduous shrubs, detected on CHRIS/PROBA image acquired in 2015. Finally, the results are compared with outputs from previous studies done in the “Bistrishko Branishte” UNESCO MAB reserve.

The study is part of ESA Category-1 Third Party Mission (TPM) project (ID 8072) ‘Model for Assessment of Coniferous Vegetation Stress using Multispectral and Hyperspectral Satellite Data’.

In framework of the concept “citizen science” we investigate environmental changes in hot spots in Albania. The methodology is based in combination of gray-scale satellite bands, in false RGB images and identifying areas experiencing temporal environmental changes on basis of color variations. Also SAR differential interferometry experiments have shown traces of temporal environmental changes in specific areas.

The work is based on radar SAR images from Envisat and ERS missions, which offer the possibility of penetration cloud coverage and analysis of critical situations even in conditions of bad weather. Results from SAR images are compared with those obtained using Landsat visible and infrared images, as well as data from field studies.

The study is focused in two hot spots experiencing important environmental changes seriously correlated with human activities: Ohrid – Prespa Lakes area and lagoons at Adriatic sea shore of Semani.

For years now Prespa Lakes are experiencing significant negative changes characterized by low of water and sedimentation. Results from satellite imagery show a global view of segments of that area exposed from water loss, changes in ground and water vegetation, and evolution of sedimentary processes generated by wrong human intervention.

The phenomena in the whole extension of Aadriatic Sea shore bordering Preadriatic Depression are a combination of sedimentation, erosion, subsidence, and shifts of river deltas. Semani area of Adriatic Sea shore is experiencing significant sea transgression that has impacted seriously human activities. Contradictory hypotheses are thrown on causes of such transgression – erosion of the sandy beaches probably as result of changes in sediments transported by Shkumbini and Semani rivers, versus the hypothesis of subsidence. Signs of subsistence are visible also in Patoku – Lezha shores of Adriatic Sea in the north, with the Patoku beach converted in lagoon.

Analysis of satellite imagery permitted identification of variations of water lines, lagoons, and vegetation. Simple differential interferometry based on couples of SAR images was done to investigate environmental phenomena in Preadriatic Depression. Interferograms fringes were visible especially in hilly ranges in Lezha – Shkodra area and mountains around Shkodra Lake, probably related with seasonal vegetation variations. Further work using persistent backscatteres interferometry is necessary to fully understand the complexity of phenomena in Preadriatic Depression shores of Adriatic Sea.

The study aims to visualize volunteered data in three dimensions in a Web-based Geographic Information System (GIS), considering also the ease of use aspects for general public, using Free and Open Source Software (FOSS). This study reimplements the already existing application PoliCrowd 2.0, using the new Application Programming Interface (API) of NASA, Web World Wind. PoliCrowd 2.0 displays volunteered data submitted through ODK Collect mobile app and is based on NASA Java World Wind SDK (Software Development Kit). Web World Wind, written in JavaScript and based on Web Graphics Library (WebGL) is cross-platform and cross-browser, so that the virtual globe created using this API can be accessible through any WebGL supported browser on different operating systems and devices, as a result not requiring any installation or configuration on the client-side, making the collected data more usable to users, which is not the case with the World Wind for Java as installation and configuration of the Java Virtual Machine (JVM) is required.

The data displayed on the virtual globe comprises of data collected through various VGI (Volunteered Geographic Information) platforms. The project developed aims to visualize and query data collected through Open Data Kit (ODK) platform and a cross-platform application, where data is stored in an ODK Aggregate server backed with PostgreSQL database and NoSQL CouchDB database respectively. Moreover, the GIS developed is able to connect to the PoliCrowd server to display the data submitted (comments or multimedia content, such as images, audio and video) using PoliCrowd 2.0 platform, so that the displayed data is more comprehensive. The current state of the platform is available at http://viaregina3.como.polimi.it/WorldWind/.

The data are displayed on the virtual globe as markers, and upon clicking a marker the data of each POI (Point of Interest) is displayed inside a popup, where the data is in JSON (JavaScript Object Notation) format. The data involves the Via Regina project and the scope of Via Regina project (http://www.viaregina.eu/) is highlighted with red borders on the map through using a WMS (Web Map Service) layer. Moreover, the NASA Web World Wind API offers some base maps, such as Landsat imagery, Bing aerial imagery and OSM. It also has view controls and controls for compass, coordinates and geocoding.

The scope of this work evolved the coupling of different technologies and different type of data in order to extract flooded areas within the Evros River basin, in Greece, during the flooding events of December 2014.Initially, hydro meteorological data were retrieved by the literature, national databases and monitoring networks. The data were homogenized and were checked for errors and thereafter were statistically analyzed for the extraction of useful information. The second type of data that were processed for the accomplishment of this work, derived from the space assets sector. Particularly, Landsat images and SAR images were acquired from international databases, such as the Sentinel Data Hub which is a web based system designed to provide EO data users with distributed mirror archives and bulk dissemination capabilities for the Sentinel-1 products. After identifying the correct datasets, i.e. imageries that spatially cover the area of interest and imageries that their time reference is as close as possible to the dates of the flood event, the data were processed with the use of special software tools dedicated for remote sensing image analysis. As far the SAR data is concerned, the processing of the data engaged a sequence of pre-processing operations, namely Radiometric calibration, Remove thermal noise, De-burst, Multi-look, Speckle filtering, Slant Range to Ground Range (SRGR), Terrain correction, and Map projection, were applied in order to receive the final products. The third and final type of data that were used for extracting the final output were orthophotos images and Digital Terrain Model images. Both type of these data were obtained from the National Cadastre and Mapping Agency S.A. in Greece and were produced during the period 2006-2008. These data were used for digitization of the points of interest, e.g.  the river bed and the tributaries, at high resolution, as well as for representing the terrain formation and extracting useful information such as the contour lines. Finally, geographic Information system tools were routinely been used for the coupling of the different type of information as well as for the production of the final outputs. The sequential integration of all these technologies fostered the identification of the areas which had to confront excess water volumes as well as the calculation of the flooded areas. The aim of the study was accomplished using the free and open source Sentinel-1 Toolbox (S1TBX), developed by ESA, as well as the commercial remote sensing software ERDAS IMAGINE.

The scope of this presentation is to feature the G-POD SARvatore service to users for the exploitation of the CryoSat-2 and Sentinel-3 data, which was designed and developed by the Altimetry Team at ESA-ESRIN EOP-SER (Earth Observation – Exploitation, Research and Development).

The G-POD service coined SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research & Exploitation) is a web platform that allows any scientist to process on-line, on-demand and with user-selectable configuration CryoSat-2 SAR/SARIN data, from L1a (FBR) data products up to SAR/SARin Level-2 geophysical data products. The Processor takes advantage of the G-POD (Grid Processing On Demand) distributed computing platform (350 CPUs in _ 70 Working Nodes) to timely deliver output data products and to interface with ESA-ESRIN FBR data archive (328,827 SAR passes and 213,365 SARin passes). The output data products are generated in standard NetCDF format (using CF Convention), therefore being compatible with the multi-mission Broadview Radar Altimetry Toolbox (BRAT) and other NetCDF tools. By using the G-POD graphical interface, it is straightforward to select a geographical area of interest within the time-frame related to the Cryosat-2 SAR/SARin FBR data products availability in the service catalogue. The processor prototype is versatile, allowing users to customize and to adapt the processing, according to their specific requirements, by setting a list of configurable options. After the task submission, users can follow, in real time, the status of the processing. From the web interface, users can choose to generate experimental SAR data products as stack data and RIP (Range Integrated Power) waveforms.

The processing service, initially developed to support the development contracts awarded by confronting the deliverables to ESA’s computations, has been made available to the worldwide SAR Altimetry Community for research & development experiments, for hands-on demonstrations/training in training courses and workshops, for cross-comparison to third party products (e.g. CLS/CNES CPP or ESA SAR COP data products), and for the preparation of the Sentinel-3 Surface Topography Mission, by producing data and graphics for publications, etc. Initially, the processing was designed and uniquely optimized for open ocean studies. It was based on the SAMOSA model developed for the Sentinel-3 Ground Segment using CryoSat data (Cotton et al., 2008; Ray et al., 2014). However, since June 2015, a new retracker (SAMOSA+) is offered within the service as a dedicated retracker for coastal zone, inland water and sea-ice/ice-sheet. In view of the Sentinel-3 launch, a new flavor of the service will be initiated, exclusively dedicated to the processing of Sentinel-3 mission data products. The scope of this new service will be to maximize the exploitation of the upcoming Sentinel-3 Surface Topography Mission’s data over all surfaces.

The service is open, free of charge for worldwide scientific applications and available at https://gpod.eo.esa.int/services/CRYOSAT_SAR/ and https://gpod.eo.esa.int/services/CRYOSAT_SARIN.

The principles and methods for a future prototype Satellite Image Time Series (SITS) classifier are presented. The prototype can extract classes of pixels which experience similar evolution in time, offering also the possibility to assess the development of one scene based on alternative approaches. The solutions are provided by different integrated algorithms, which can be selected according to the needs of the application scenario. Visualization modes for the classification results are suggested.

The results presented in this poster derive from the ongoing ESA GSTP project: Data Mining for Analysis and exploitation of next generation of Time Series (DAMATS).

The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. According to the 2013 IBM Annual Report, 2.5 billion gigabytes of data are created every day, and 80 percent of it is “unstructured” data (everything from images, video, and audio, to social media and distributed devices) which are geo-referenced or can be geo-referenced. Specifically, geo-referenced Big Data or Big Geo Data, is produced every day mainly from fixed and mobile sensors such as satellites, aircrafts, webcams, UAVs, location-based social networks such as Twitter, Volunteered Geographic Information or even citizens through their normal activities.
These data is increasingly becoming Open Data (data that can be freely distributed) made public by the government, agencies, private enterprises and so forth. The exploitation of Open Data it has a significant potential. However, today, its applications are rather limited in size. With few exceptions, it mainly concerns a limited number of institutional users (civil protection, climatic issues and weather forecast, among others).
This contribution explores the effect of user-generated telecommunication traffic on weather conditions through the analysis of a large telecommunications dataset. The user-generated telecommunication traffic corresponds to the result of a computation over the Call Detail Records (CDRs) of Sent SMS, Received SMS, Incoming Calls, Outgoing Calls and Internet traffic; while weather conditions are characterized in terms of precipitation and temperature. ANOVA test is performed to find statistically significant differences between the behavior of telecommunications data in days with and without rain.
The used data corresponds to two months (November and December 2013) of telecommunications and Twitter activity of the city of Milan, issued by the Telecom Italia Big Data Challenge. The datasets are: a) user-generated telecommunication traffic, corresponding to the result of a computation over the Call Detail Records (CDRs) of Sent SMS, Received SMS, Incoming Calls, Outgoing Calls and Internet traffic; b) the level of interaction between the areas of the city of Milan and the Italian provinces in terms of number of calls issued; and c) data derived from an analysis of geo-referenced tweets (anonymized Twitter user, DBPedia entities, language, time stamp, etc). All Dataset have a temporal aggregation of ten minutes, and a spatial aggregation defined by a squared grid covering the city of Milan, with a square cell size of 235 meters.

The universal altimetry toolbox, BRAT (Broadview Radar Altimetry Toolbox) which can read all previous and current altimetry missions’ data, incorporates now the capability to read the upcoming Sentinel-3 L1 and L2 products.

ESA endeavoured to develop and supply this capability to support the users of the future Sentinel-3 SAR Altimetry Mission. BRAT is a collection of tools and tutorial documents designed to facilitate the processing of radar altimetry data.
This project started in 2005 from the joint efforts of ESA (European Space Agency) and CNES (Centre National d’Etudes Spatiales), and it is freely available at http://earth.esa.int/brat. The tools enable users to interact with the most common altimetry data formats. The BratGUI is the front-end for the powerful command line tools that are part of the BRAT suite. BRAT can also be used in conjunction with MATLAB/IDL (via reading routines) or in C/C++/Fortran via a programming API, allowing the user to obtain desired data, bypassing the data-formatting hassle. BRAT can be used simply to visualise data quickly, or to translate the data into other formats such as NetCDF, ASCII text files, KML (Google Earth) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas.

The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, shows its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also “use cases”, with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific “use-cases” for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome.

The Broadview Radar Altimetry Toolbox is a continuation of the Basic Radar Altimetry Toolbox. While developing the new toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific “use-cases” for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome.

The first Release of the new Radar Altimetry Toolbox was published in September 2015. It incorporates the capability to read S3 products as well as the new CryoSat-2 Baseline C.

The second Release of the Toolbox, planned for July 2016, will have a new graphical user interface and other visualisation improvements.

The ESA Research and Service Support (RSS) service has the mission to support the Earth Observation (EO) data exploitation, by an operational pilot of the new paradigm “bring users to data”. This approach dramatically lowers the barrier to make research activities, develop algorithms and downstream services by opening such possibility to new users and reducing effort and resources needed by the ones already involved in EO. This objective is achieved by: 1- offering tools and services to the EO community, granting a fast and easy data access (no need to transfer data to the scientist infrastructure) and real (offered by RSS) scalable processing resources access, and 2- supporting the researchers in developing new algorithms and also by enabling results visualization, verification, validation and sharing.

The RSS service offer is composed of several elements supporting different phases of the research process flow. The two processing environments offered are: (i) customised cloud toolboxes where scientists and developers alike can fine tune their algorithms on selected datasets and,(ii) on-demand processing environment where fine-tuned algorithms can be integrated and made available as EO applications for on-demand and/or massive processing, and results visualization tools.

As far as the algorithm development process is concerned, including the fine-tuning phase, the RSS CloudToolbox is the basic tool offered by RSS to EO researchers. Such tool is a customised virtual machine with pre-installed software powerful enough to speed-up the development phase. The algorithm can be successively integrated into the RSS processing environment, thus bringing it close to data, once it is deemed to be stable, either if the scientist plans to run it on massive datasets (big data processing) or to make it available to the scientific community as a web application.

In such environment high-performance computing resources, using Grid and Cloud technologies, provide the necessary flexibility to allow quick access to data and fast production of processing results. The RSS Grid/Cloud infrastructure counts over 90 processing nodes with an total of 2.3TB RAM memory and 490 CPU’s. This represents the RSS base capacity that is on average sufficient to satisfy users’ processing requirements. When the processing requests exceed the RSS base capacity, it is possible to scale up the resources by seamlessly federating additional clusters deployed on the Cloud.

In the big data era, started with the launch of Sentinel-1A in April 2014, data volume and processing requirements are becoming more and more challenging. Hence, the EO scientific community accessing and using RSS resources will experience even greater benefits for all the activities related to the EO research process, including algorithm development, data access, processing and results analysis.

WorldWind, open source virtual globe technology for Java, iOS, Android and Web, is provided by NASA and is architected as API-centric modular componentry. This enable it to be continually optimized and feature-enriched in ways that allow applications based on this SDK (Software Development Kit) to benefit Earth Observation, especially Open Science, with minimal or no adjustment for the decade ahead.

The next-generation National Airspace System (NAS) aviation management system for the U.S. Federal Aviation Administration, FAA, uses WorldWind, as do applications currently being developed by the European Space Agency, along with several other US and European government agencies and industry partners. This presentation will demonstrate several current use cases for WorldWind technology that also include advances being made to optimize access to NetCDF and HDF data via WebWorldWind.

I.MODI is an added value service, created via a European project funded through a H2020 initiative, that integrates EO observation technologies, aerial, ground based data and ICT to create visualized data easy accessible from all kind of users, also non EO professionals.

I.MODI uses DInSAR data to examine structural stability, performing an assessment on the level of damage suffered and evaluating its future evolution.

Monitoringstructuralstabilityin urbanareasand largeinfrastructurenetworksis emerging as one of the dominant socio-economical issuesfor the safety of the population.

The problem is accentuated by the ageoftheconstructions,exposed to increasing risks due to the material deterioration and loss of loading capacity.  This  becomes  a  civil  protection issue when the structures are threatened by the evolution of natural and man-made ground deformation processes. In the latter case, the monitoring system is strictly devoted to safeguarding the population and has a primary role in setting up mitigation and prevention actions, as well in the implementation of an alert system.

To date the evaluation of risks associated with the deformation of a structure used ground based methods, able to measure displacements at the surface or in boreholes, and on direct analyses such as in-situ inspections/investigations. These methods, although accurate at a local scale, require placing devices on the structures (destructive method) that are expensive and not always feasible due to accessibility and logistic constraints.

In addition, due to the extension, capillarity and frequency required for the monitoring of large urban areas, critical infrastructures (plants) and networks extended at a national scale (road, railway, airport), an approach based only on in-situ measurements would require huge resources, not available today.

To guaranteea systematic and comprehensive control of structural stability over large areas, satelliteremotesensingcan be effectively adopted. Among the different methods based on passive and active satellite sensors, the DifferentialInterferometrySARtechnology,the same technology chosen for I.MODI,today represents an adequate alternative solution in terms of providing data that, for precision, reliability and cost sustainability, can be fully assimilated within the monitoring approach based on in-situ data.

A web-based customized version of I.MODI is now in its developing stage with the aim to completely integrate the EO data within the standard procedures based on in-situ technologies (GNSS and ground surveying). EO and non-EO inputs will be linked and managed adopting open standards for data documentation and using ICT technology to furnish an added-value service to final users (companies, professional operators as well as private citizens).

More over the service foresees customized applications for different market segments and monitoring procedures.

The Space to Ground (S2G) Data Viewer [REF 1] is an extensible and flexible tool to inspect the contents of the communication data units exchanged between the satellites (including their instruments) and the payload data-processing ground system. The activity of Space to Ground testing for payload data as well as the related activity to generate data for testing the science data processors requires the analysis and visualisation of telemetry data files produced by satellites, ground equipment or simulators. This satellite house-keeping telemetry or science instruments data is transmitted to the ground sensor stations according to the CCSDS standard formats, consequently the data files on ground can be formatted as CADUs (Channel Access Data Units), TFs (Transfer Frames) or ISPs (Instrument Source Packets) and ad-hoc tools are usually developed every time for each mission by the ground test engineers and Level 1 processors developers.

The S2G Data Viewer was therefore developed as a generic tool supporting both the visualization and basic diagnostic of data generated on-board by current ESA Earth Observation Earth Explorer and Copernicus satellites, avoiding in this way the effort and cost of re-developing such tools for each mission. The S2G Data Viewer hence interprets binary files containing concatenated CADUs, TFs or ISPs, and presents them as hierarchical lists of available data units displaying the fields of header and content and the associated values in raw, engineering and binary format. The values are checked against user-specified constraints (e.g. correctness of Spacecraft ID, valid APID, data ranges), the sequences (e.g. SSC and Frame Counter) are checked for continuity and each data unit is also checked with respect to checksums and error correction fields.

The tool furthermore provides additional functionalities such as a hexadecimal viewer to allow direct low-level data inspection, searching, filtering and data transformation functions (CADU unscrambling and TFs/ISPs extraction). The tool stores all the data definition as pre-configured as files and includes mission configuration for Sentinel 1, 2, 3, 5p, SWARM, SMOS, Aeolus and EarthCARE. The configuration for parsing data of any other mission is possible by defining and importing new DFDL binary definition schemas within S2G.

To support flexible binary data parsing the S2G development uses of a generic binary data binding library based on the Data Format Description Language (DFDL). Published as an Open Grid Forum Proposed Recommendation [REF 2] DFDL is a modeling language evolved into an open standard for describing general text and binary data in a standard way. This language allows description of text, binary, and legacy data formats in a vendor-neutral declarative manner.

The DFDL for Space (DFDL4S, [REF 3]) is the underlying software library used by S2G Data Viewer. It comprises the capability to use DFDL schemas to read, write and interpret CADU, TF or ISP data files. This library can therefore be used to support in straightforward manner the generation of test data in any specified binary format (e.g. in simulators) and the reading of ISPs (e.g. in Level 1 Processors).

References

[REF 1] S2G website: http://eop-cfi.esa.int/index.php/applications/s2g-data-viewer

[REF 2] Michael J. Beckerle and Stephen M. Hanson, “Data Format Description Language (DFDL) v1.0 Specification” in Open Grid Forum (https://www.ogf.org/ogf/doku.php/standards/dfdl/dfdl), GFD-P-R-207, September 2014.

[REF 3] DFDL4S website: http://eop-cfi.esa.int/index.php/applications/dfdl4s

This paper presents the software applications for mission analysis and 3D visualization distributed by the ESA-ESTEC EOP System Support Division to users part of the ESA Earth Observation Earth Explorer and Copernicus satellites community.

These software tools can be used to perform mission analysis activities related to instrument swath coverage over regions of interest and ground station contact (ESOV NG [REF 1], EOMER [REF 2]) or to display high-resolution 3D satellite mission scenarios (SAMI [REF 3]). These tools can and have been used in the preparatory feasibility studies (e.g. to analyse coverage and revisit time), to support downlink and ground station visibility analysis as well as support to Calibration and Validation activities e.g. to plan on-ground campaigns during satellite commissioning or scheduling of ground transponders.

The Earth observation Swath and Orbit Visualization (ESOV NG) is a 2D orbit and swath visualization application, delivered with a predefined set of missions (Sentinel 1, 2, 3, 5p, 6, SWARM, Cryosat, SMOS, Aeolus, EarthCARE, MetOp-SG), although it is possible to configure user-defined satellites. This tool is multi-platform, available for Mac OS X, Linux and Windows.

EOMER (Earth Observation Mission Evaluation and Representation) is a Windows application for multi-satellite and swath visualization in 2D/3D, tailored to ESA Earth Observation missions (currently supporting Sentinel 1, 2, 3, 5p, MetOp-SG).

Both ESOV NG and EOMER applications allow the user to visualize satellite orbit ground-tracks and instrument swaths, and to calculate ground station visibility passes, times of overpass a given ground point and times when an instrument swath overlaps with a given region of interest.

In addition, with ESOV NG it is possible to calculate the visibility times between a LEO satellite (e.g. Sentinel-1A/B or Sentinel-2) and a Data Relay satellite in GEO orbit (EDRS), taking into account various link constraints and to obtain the viewing angles from a ground station to the satellite during a station pass.

EOMER provides as additional features, including the capability to animate the scenario within the user-selected time window and the visualization and highlight of events (including Gantt timeline representation).

The SAMIEdit (SAtellite Mission Editor & Player) application plays stunning high-resolution 3D and 2D animations and simulations of ESA Earth Observation satellite.  Real-time and endless loop simulation modes are also available. SAMIEdit displays the orbit ground-tracks and footprints of the instruments on-board, the entering in area of visibility between the satellite and the ground stations as well as solar arrays and antenna deployments and thruster firing events. With the editing capabilities of SAMIEdit, the user can drive the various camera views (camera attached to the Earth or to the satellite) and enable disable objects in the scene, generating standalone animation for kiosk type application and export it to HD video or series of snapshots. The missions currently supported are Sentinel 1,2,3, SWARM, Cryosat, SMOS and Aeolus. The application runs on desktop platforms (Mac OS X, Windows) and mobile platforms (iOS based, e.g. iPad).

The coherence and accuracy of the orbital and geometrical calculations within ESOV NG and SAMI applications is ensured by the use of embedded Earth Observation CFI Software libraries (EOCFI SW). In ESOV NG, the libraries are used to obtain orbit ground-track, instrument swaths, passes over selected area of interest or ground station while in SAMIEdit, the satellite position, orbit ground-track, attitude and swath footprint are calculated with the EOCFI SW libraries. The EOMER application instead makes use of the SatX and GanttX components developed by Taitus to support respectively the orbital calculations and its timeline visualisation.

The use of common interfaces (orbit files, swath files, SCF segments export format from ESOV NG, KML Google Earth) is a key point to facilitate sharing the input data and the comparison of the output results across the various software applications.

REFERENCES

[REF 1 ] ESOV website: http://eop-cfi.esa.int/index.php/applications/esov

[REF 2 ] EOMER website: http://eop-cfi.esa.int/index.php/applications/eomer

[REF 3 ]SAMI website: http://eop-cfi.esa.int/index.php/applications/sami

GLOBEWATCH is the multiplayer game where you are given the quest of becoming the sentinel of a given location or relevant event seen from space. A role-play game taking place on actual events in the planet, covering from natural disasters to humanitarian crises in a climate change triggered world phenomena. Unlock tasks and get awards, help ESA with satellite data and share your growing status on social media. Mastery your skills on glaciers retreats or become a proud rainforest guardian, from your bus stop bench. Take a leading role in watching your own planet with the power of your fingertips.

The GLOBEWATCH is a first draft of the application of game design elements to earth observation and citizen science tasks, striving to leverage people’s natural desire for socialising, learning and sharing, providing at the same time the sense of an active and meaningful cooperation with scientific research in space field. All comprised in a single and engaging phone/tablet game app.

The SNAP platform has been specifically designed for Earth Observation processing and analysis, formerly called BEAM. The open-source ESA toolbox can support a wide range of EO data formats, data products from various EO sensors.　

SNAP supports the toolboxes of Sentinel-1, Sentinel-2 and Sentinel-3, providing an optimal exploitation of the Sentinels data. The implementation language of SNAP  is Java and this means that its API is also in Java. The SNAP installation package provides a Python module called snappy that allows to access the Java API directly from Python. Using snappy enables to call any SNAP operator with a Python script or even to add new SNAP plugins coded in Python. The snappy module offers an interesting interface between the Python programming language and the desktop version of SNAP. However, this is not a common practice yet and we believe video tutorials and/or written tutorials based on Jupyter notebooks would be of great interest as a training material. A complete set of SNAP video tutorials already exists in the ESA website, but the interaction with Python can surely open to new developments. The idea to create a set of Jupyter notebooks, in which it is possible to mix explanatory text and live python code that can be run to visualize step by step the results of an exercise or a training lesson, would surely find interest in the Earth Observation community. Each video tutorial could guide the user through a notebook or invite him to personally modify some lines of code in it. According to the topics and the processing to implement, it could show some desktop SNAP operations interacting with the contents of a Jupyter notebook. This approach allows the user to learn how to handle the SNAP Java API while programming in Python and exploiting its scientific libraries. A more advanced objective could  be to explain how snappy can extend SNAP by adding new plugins coded in Python. This option has been clearly planned  by the SNAP development team, that has also provided some sample scripts about it, but they surely need further explanations so that a larger number of users can put them into practice. Furthermore,  SNAP developers actively give support about the SNAP API and Python in the

STEP forum.