Toolboxes 1

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 March 2016, will have a new graphical user interface and other visualisation improvements.

The ESA Atmospheric Toolbox (BEAT) is one of the ESA earth observation end user toolboxes. Since its inception in 2002 it has brought data reading, analysis and visualization support for products from a wide range of atmospheric missions such as ENVISAT, ERS, Metop, Aura, ACE, Odin, GOSAT, NPP-Suomi, Atmospheric CII, and Sentinel-5P. The toolbox consists of three main components: CODA, HARP, and VISAN.

CODA is the core data reading interface allowing direct product access to a wide range of products using a single interface.

HARP is the data harmonization and inter-comparison interface which brings all data to a harmonized data format and then provides operations such as filtering, collocation, unit conversion, quantity conversion (e.g. vmr to nd), vertical integration/smoothing, and uncertainty propagation.

VISAN is a python-based basic analysis and visualization environment with advanced interactive plotting for 2D and geographical data.

All components of the toolbox are freely available and fully open source.

The user community of SAR data for land applications is still small compared to its optical counterpart. One of the reasons might be that the pre-processing of the data is quite complex and a limited amount of data was available in the past. With the availability of archived mission data from ESA (i.e. ERS, Envisat) and JAXA (ALOS PALSAR) as well as the vast amount of SAR imagery provided by the Copernicus Sentinel-1 mission, general interest in the use of the data is massively growing.

Open Foris SARKit represents an extension to the collection of Free and Open Source Software (FOSS) tools developed under the Open Foris Initiative of the Food and Agriculture Organization (FAO) of the United Nations. It is a meta-software, which bundles algorithms and functions of already available FOSS GIS and Remote Sensing software tools in order to simplify and automate radar data processing from single raw data to large scale mosaics within bash scripts. The main aim is that users without a deep previous knowledge about SAR data processing can use standardized processing chains with as little interaction as possible. On the other hand, the command-line interface allows for an easy interaction on cloud-based computing platforms even with limited internet connection. Furthermore, the implementation into potential WPS service frameworks is straight-forward.

Supported sensors are ERS, ENVISAT ASAR, ALOS-1 PALSAR, RADARSAT-1 & 2, as well as SENTINEL-1. Apart from standard UNIX/Linux tools, the scripts access functions of the SNAP Toolbox, ASF MapReady, RSGISLIB as well as GDAL-tools and SAGA GIS. The functionality ranges from inventory and download scripts to single scene pre-processing, mosaicking, derivation of texture measures, stacking and image segmentation procedures. Intermediate results are written to KMZ files, so that a quality assessment from remote machines is possible without having to deal with large traffic volume.

First results, which already have been processed by the toolbox, include nationwide ALOS PALSAR FBD wall-to-wall mosaics from Zambia, Bangladesh, Philippines, Paraguay and numerous other UN-REDD countries, whereby the SAR stacks have been combined with optical Landsat data for land cover classification as well as biophysical parameter estimation. Those examples serve as the introduction to the standard processing workflow of the Open Foris SARKit within the presented work and are going to demonstrate the potential of SAR data alone and in combination with optical data sources for land applications. If operationally feasible to be produced by developing countries themselves, these products can be of great help for better management of land on national scale in the context of the international climate conventions.

The Sentinel-2 Toolbox is a project kicked off by ESA in early 2014, under the umbrella of the ESA SEOM programme with the aim to provide a tool for visualizing, analysing, and processing the Sentinel-2 datasets.

The toolbox is an extension of the Sentinel Application Platform (SNAP), a project resulting from the effort of the developers of the Sentinel-1, Sentinel-2 and Sentinel-3 toolbox to provide a single common application framework suited for the mixed exploitation of SAR, high resolution optical and medium resolution optical datasets. All three development teams collaborate to drive the evolution of the common SNAP framework in a developer forum.

In this triplet, the Sentinel-2 toolbox is dedicated to enhance SNAP support for high resolution optical imagery. It is a multi-mission toolbox, already providing support for Sentinel-2, RapidEye, Deimos, SPOT 1 to SPOT 5 datasets.

In terms of processing algorithms, the Sentinel-2 toolbox provides tools specific to the Sentinel-2 mission :

An atmospheric correction module, Sen2Cor, is integrated into the toolbox, and provides scene classification, atmospheric correction, cirrus detection and correction. The output L2A products can be opened seamlessly in the toolbox.

A multitemporal synthesis processor (L3)

A biophysical products processor (L2B)

A water processor

A deforestation detector

along with a set of more generic tools, among which the seamless integration of Orfeo Toolbox tools to further extend the processing capabilities : supervised classification, segmentation will soon be available in the Sentinel-2 Toolbox.

Together with the generic functionnalities of SNAP this provides an ideal environment for designing multi-missions processing chains and producing value-added products from raw datasets.

The use of SNAP and the Sentinel Toolboxes is manyfold. The desktop tools provides a rich application for interactive visualization, analysis and processing of data. But all tools available from SNAP can be accessed via command-line through the Graph Processing Framework (GPT), the kernel of the SNAP processing engine. This makes it a perfect candidate for driving the processing of data on servers for bulk processing.

The SENTINEL-1 Toolbox is a new open source software for scientific learning, research and exploitation of the large archives of SENTINEL and heritage missions. The Toolbox is based on the proven BEAM/NEST architecture inheriting all current NEST functionality including multi-mission support for most civilian satellite SAR missions. The Toolbox will also be compatible with the SENTINEL-2 and SENTINEL-3 Toolboxes incorporating tools for multispectral optical products.

The project is funded through ESA's Scientific Exploitation of Operational Missions (SEOM). The SENTINEL-1 Toolbox will strive to serve the SEOM mandate by providing leading-edge software to the science and application users in support of ESA's operational SAR mission as well as by educating and growing a SAR user community.

The Toolbox consists of a collection of processing tools, data product readers and writers and a display and analysis application.  A common architecture for all Sentinel Toolboxes is being jointly developed by Brockmann Consult, Array Systems Computing and C-S called the Sentinel Application Platform (SNAP). The SNAP architecture is ideal for Earth Observation processing and analysis due the following technological innovations: Extensibility, Portability, Modular Rich Client Platform, Generic EO Data Abstraction, Tiled Memory Management, and a Graph Processing Framework.

The project has developed new tools for working with SENTINEL-1 data in particular for working with the new Interferometric TOPSAR mode. TOPSAR Complex Coregistration and a complete Interferometric processing chain has been implemented for SENTINEL-1 TOPSAR data. To accomplish this, a coregistration following the Spectral Diversity[4] method has been developed as well as special azimuth handling in the coherence, interferogram and spectral filter operators.

The Toolbox includes reading of L0, L1 and L2 products in SAFE format, calibration and de-noising, slice product assembling, TOPSAR deburst and sub-swath merging, terrain flattening radiometric normalization, and visualization for L2 OCN products.  The Toolbox also provides several new tools for exploitation of polarimetric data including speckle filters, decompositions, and classifiers. The Toolbox will also include tools for large data stacks, supervised and unsupervised classification, improved vector handling and change detection.

Architectural improvements such as smart memory configuration, task queuing, and optimizations for complex data will provide better support and performance for very large products and stacks.

In addition, a Cloud Exploitation Platform Extension (CEP) has been developed to add the capability to smoothly utilize a cloud computing platform where EO data repositories and high performance processing capabilities are available. The extension to the SENTINEL Application Platform would facilitate entry into cloud processing services for supporting bulk processing on high performance clusters.