The Copernicus Sentinel App offers a comprehensive access to information about and data from the Copernicus Sentinel missions for both the general public and expert users on iOS and Android. It has been the most popular ESA mobile application since a couple of years. The newer features further increase its usefulness for more advanced users such as EO scientists and professionals involved in the operations of the Sentinel missions.

The presentation will provide a quick overview of the functionality before digging into the more advanced features enjoyed by EO professionals. The most relevant sections are the tracking, statistics, and acquisition sections. The tracking section provides general awareness of the status of the missions in a 3D environment. Further, the statistics section gives an overview of the performance of the missions and long-term data availability. Last, the acquisition section offers tools to discover future acquisitions and available products in an intuitive manner. This section contains powerful features for quickly:
- Looking at future acquisitions;
- Browsing the products available at a particular location;
- Monitoring particular areas for the availability of new products, and;
- Sending products of interest to your computer or servers directly from the app.
Stories from users will be presented in order to exemplify the potential of these features.

Moreover, the Copernicus Sentinel App can be a useful means to teachers, and educators in general, which can rely on its features to explain how Earth Observation missions work and why they are so useful to our society.

The functionality provided to both the general public and expert users requires interacting with a multitude of openly available data sources. The presentation will thus not stop at the features of the app, but explore the systems involved in making them possible. This will notably include the simple data access and monitoring systems used by the app. These can be leveraged by anybody working with the Sentinel data.

Decision makers need accessible robust evidence in order to introduce new policies in an effort to mitigate and adapt to climate change. There is an increasing amount of environmental information available to policy makers concerning recent observations and trends relating to the climate. However, this data is hosted on a plethora of websites often with inconsistent metadata and little information relating to the quality of the data to determine any differences in parameters due to processing algorithms, definitions and assumptions. Subsequently, the task of comparing datasets to decide which is the most appropriate for a certain purpose is very complex and often infeasible.

The Copernicus Climate Change Service hosts a Climate Data Store (CDS) where numerous data products are catalogued with associated standardised metadata and substantial quality information. When the store is fully established, it will provide a means to access hundreds of Essential Climate Variable (ECV) data products derived from satellite and in situ observations as well as climate projections, seasonal forecasts and reanalysis. The CDS will have an integrated Evaluation and Quality Control (EQC) function which will be responsible for the provision of user-driven information related to quality for each ECV data product. This includes interactive multi-level traceability chains which provide data users with a quick overview of the processing algorithms used, detailed Quality Assurance Reports as well as an evaluation matrix which grades the product on the provision of quality information provided.

The Quality Assurance Reports will include comprehensive information on the product generation, quality information provided by the data producer (quality flags, quality control, known issues etc.) as well as information on their uncertainty characterisation and their validation and inter-comparison activities. Independent evaluation of the quality of the data products by a QA administration of experts will ensure the information is robust and sufficient for users to judge the fitness for purpose of the dataset for their application. The evaluation matrix will present the scores achieved by the product based on two factors: the quality of information provided by the producer in the report and if best practice have been followed. This evaluation matrix will soon be shown publicly on the CDS website as a QA product summary through which the detailed report can then be accessed.

A key feature of the EQC function will be the ability to compare data products by their quality information enabled by the standardisation of the information captured. The EQC function will act as a tool to directly compare several products based on the matters a user deems most important. The evaluation matrix lists around 30 key factors which end-users should consider in choosing a product. Users will be able to compare multiple matrices and then discover further information in the quality report so that they can make an informed decision on which product may be most useful for their application.

This presentation will demonstrate how the EQC function could be used by end-users of Earth Observation data and will highlight how increased quality information can be extremely beneficial to scientific users and policy makers.

Climate Change is impacting our lives, tomorrow as well as today. Understanding Climate Change requires data, people, and enabling technologies. The European Space Agency (ESA) is running the Climate Change Initiative (CCI+), to provide an adequate, comprehensive, and timely response to the extremely challenging set of requirements for long-term satellite-based products for climate. One element of this programme is the CCI Toolbox, called Cate, which is an enabling technology to connect scientists, but potentially also wide climate data users such as decision makers and the knowledgable public to climate data. CATE is a software environment for ingesting, operating on and visually analysing all ESA CCI datasets as well as other climate data from various sources. The toolbox works by mashing data into a common data model , manipulate them and letting users visualise the results of their investigations in various ways for understanding, knowledge exchange and ideas sharing.

CATE is open source (climatetoolbox.io.), and its backend, operating on the data, is fully implemented in python to allow users to modify and extend it with own code. The graphical user interface (GUI) frontend is using web technologies (TypeScript, html5) with powerful visualisation capabilities (React, Blueprint). The GUI is designed as a native desktop application, using Electron technology for the desktop operating system integration. This brings full computing power to CATE operations. The GUI uses a Python (RESTful) web server providing the CCI Toolbox’ WebAPI service to the GUI. The split of backend and frontend with communication via Web Service makes CATE ready for deployment in cloud environments. In addition to the GUI, CATE provides two additional user interfaces for programmatic application, namely a command line interface (CLI) and an application programming interface (API). Workflows can be developed interactively in the GUI, and executed for automation, large batch processing and near-real time processing in these interfaces. All three user interfaces communicate with the Python core via its WebAPI. This design allows for later extensions towards a web application with possibly multiple remote WebAPI services.

But CATE is more than the software and also fosters collaboration between climate scientists through its collaboration tools and the climatetoolbox.io presence. CCI is a long-term programme assuring sustainability of CATE.

The Sentinel Application Platform (SNAP), host for the Sentinel-1, Sentinel-2 and Sentinel-3 Toolboxes, has become the reference tool for the Sentinel’s data exploitation. Based on BEAM and NEST, and funded by ESA, SNAP has demonstrated to be ideal for Earth Observation processing and analysis. Thanks to the great acceptance that it has had among the remote sensing community, it has been possible to carry out a constant evolution from early versions. During the already released six first major versions, the growing number of users is allowing to improve the tool having into account their feedback, suggestions and needs.
The release of the coming major version (SNAP 7.0) will have a focus on performance improvements for processing. Python interface to SNAP (snappy) has gained great acceptance among the scientific SNAP users and is widely used. However, it will be enhanced by a dedicated pythonic interface which will make easier to use the API. Furthermore, the documentation especially for developers will be extended.
On the other hand, this version will focus also on a better support for multi-size products (specially Sentinel-2), on the homogenization of metadata and readers in order to make easier the use of some processors and on the fixing of some known limitations in the use of the graph builder tool.
Further down the road new feature are planned like Product Groups, Fusion and Change Detection processors, Time series exploration and direct access of cloud resources.
At toolboxes level there will be improvements and new features during the contract runtime till end of 2020. The S1TBX will support new sensors (ALOS-2, PAZ, RISAT-1…) and will improve some processors like the stack generation or the coherence estimator.
The S2TBX will add, similarly, product readers for more high resolution optical sensors and will also add support for Landsat products in the biophysical processor. New processors for atmospheric corrections and cloud detection will be available.
The Sentinel-3 Toolbox will provide new pre-processing tools for improving the radiometric calibration and derive reflectance values from OLCI data. Also, processors to derive water quality indices are on the feature list. Beside the afore mentioned processors a tool will be developed which will allow to create L1C synergy data products from OLCI and SLSTR data.

The objective of this paper is to make a general presentation of the very new version of the ESA PolSARpro software toolbox which is now named : PolSARpro-Biomass Edition software.
In order to prepare for the scientific exploitation of BIOMASS and SAOCOM missions, ESA wishes to develop a new toolbox version called PolSARpro-Bio Edition adding appropriate and state-of-the-art algorithms for advanced processing of polarimetric data (including polarimetry, Pol-InSAR and tomography) and new readers and functionality while improving the user support elements and performance.
PolSARpro-Bio Edition will pursue the philosophy of ESA Toolboxes by offering an open source scientific toolbox readily available to exploit data from the first fully polarimetric ESA missions (BIOMASS) and new (like the SAOCOM or the GF-3 Chinese missions) or upcoming third party missions.
In addition PolSARpro-Biomass Edition will also provide the new generation students with basic and advanced training for the scientific exploitation of polarimetric SAR data and showcase some applications where fully polarimetric data brings unique benefits.
For this, the PolSARpro project provides educational software that offers a tool for self-education in the field of Polarimetric SAR data analysis and a comprehensive suite of functions for the scientific exploitation of fully and partially polarimetric data sets. The PolSARpro software establishes a foundation for the exploitation of polarimetric techniques for scientific developments and stimulates research and applications developments using Pol-SAR (Polarimetric SAR), Pol-InSAR (Polarimetric – Interferometric SAR), Pol-TomoSAR (Polarimetric – Tomographic SAR) and Pol-TimeSAR (Polarimetric – Time Series SAR) data.
The PolSARpro-Biomass Edition activity falls under action line 2 and 1 of the SEOM program (Scientific Exploitation of Operational Missions) which is a new program element within the fourth period (2013-2017) of ESA Earth Ob-servation Envelope Programme (EOEP-4).
The PolSARpro-Biomass Edition Software will be released in January 2019 and will be avalaible for free download. A global overview of the objectives and functionalities of the PolSARpro-Biomass Edition Software, the new scientific toolbox for ESA & third party fully polarimetric SAR missions, will be presented during the ESA Living Planet Symposium.

Orfeo ToolBox is an open-source project for state-of-the-art remote sensing. It is designed for processing and analyzing large remote sensing datasets and it provides a range of image corrections algorithms, filtering and classification tools as well as data extraction utilities for optical and radar data. It is shipped with a set of extensible ready-to-use tools for classical remote sensing tasks, as well as a fully integrated, end-users oriented software called Monteverdi. OTB algorithms can also be used from Python, from the Quantum GIS processing module or as a processor in the ESA Sentinel-2 toolbox.

With more than 10 years of development, Orfeo ToolBox has evolved from a very-high-resolution specific toolbox driven by the CNES Pleiades mission to a multi-sensor, multi-purpose remote sensing toolbox. Thanks to its modular architecture, OTB allows fast prototyping and covers the full spectrum of algorithms for remote sensing image processing from pre-processing to advanced feature extractions methods allowing one to go from raw data to value added products. On top of the existing modules, there is a collection of remote modules, developped and maintained by different teams, to supply new features for the base library.

Orfeo ToolBox is now a core building block in several image processing chains, supplying the different algorithmic operations, while the orchestration and the handling of input products is mostly done in Python. This strategy allows to efficiently write complex processing chains in Python, while using streamed and mutli-threaded algorithmic operations on large datasets. Some of these chains are also open-source : Let It Snow (Snow cover detection), iota2 (Large Scale Land Surface Classification), WASP (Multitemp images fusion), S1Tiling (Sentinel-1 calibration)...

This presentation will highlight new features included in the latest versions of OTB and it will also further show the current and future directions of the project and opportunities for interested developers and users. The presentation will also illustrate how ORFEO ToolBox is used at CNES to process data from the ESA Sentinel missions to derive country-scale operational products, such as annual Land Cover Map or snow cover products of France.