The Normalised Radar Backscatter (NRB) for Copernicus Sentinel-1 is a new product currently being developed by ESA (with University of Jena and ACRI-ST as contractors). It is designed to be high-quality Analysis Ready Data (ARD) compliant with the CEOS ARD for Land (CARD4L) NRB specification.
The product aims to complement the existing family of Copernicus Sentinel-1 products, which currently contains Level-1 Single Look Complex (SLC) and Ground Range Detected (GRD) products , by providing a flexible and easy to use data source particularly suited for non-expert users and easily exploitable for automated time series analysis in the context of modern cloud-based analysis platforms.
According to the CARD4L definition , the products are “processed to a minimum set of requirements and organized into a form that allows immediate analysis with a minimum of additional user effort. These products would be resampled onto a common geometric grid (for a given product) and would provide baseline data for further interoperability both through time and with other datasets.”
The S1-NRB product contains radiometrically terrain corrected (RTC) gamma nought backscatter (γ0) processed from Single Look Complex (SLC) Level-1A data acquired in Stripmap (SM), Interferometric Wide Swath (IW) or Extra Wide Swath (EW) mode. Each acquired polarization is stored in an individual binary image file. In addition to the actual backscatter data, annotation image datasets (e.g., local incident angle) are included to enable better interpretation of the backscatter data as well as to convert it to sigma-nought RTC.
All images are projected and gridded into the United States Military Grid Reference System (US-MGRS). Hence, the data is projected to Universal Polar Stereographic (UPS) at the poles and to Universal Transverse Mercator (UTM) otherwise. Tiling is applied to structure data into (1) UTM zones and (2) 100 x 100 km granules. The pixel spacing is 10 m for SM and IW, and 20 m for EW.
The use of the US-MGRS tile grid ensures a very high level of interoperability with Sentinel-2 Level-2A ARD products making it easy to also set-up complex analysis systems that exploit both SAR and optical data.
It should be noted that while speckle is inherent in SAR acquisitions, speckle filtering is not applied to the S1-NRB product in order to preserve spatial resolution. Some applications (or processing methods) may require spatial or temporal filtering for stationary backscatter estimates.
Accurate Radiometric Terrain Correction (RTC) and Geometric Terrain Correction (GTC) is achieved utilising state-of-the-art algorithms . Their accuracy is further enhanced by using high-resolution data sources like the Copernicus DEM . The processing also includes the removal of background noise to ensure an extremely good quality of the data also in areas with very low backscatter.
Finally, the product uses modern technologies and standards like Cloud Optimized GeoTIFF (COG) , Limited Error Raster Compression (LERC) , and the provision of SpatioTemporal Asset Catalogue (STAC)  metadata to maximise the accessibility and ease of use of the product, especially in cloud computing infrastructure like data cubes, while keeping the data volume as low as possible.
A summary of the product characteristics is reported in the following table.
|Spatial Reference system||UTM/UPS (according to US-MGRS)|
|Gridding and tiling system||US-MGRS|
|Number of looks (rg x az)||6x6||5x1||3x1|
|Measured variables||Gamma-nought (linear scale) (*, **)|
|Units||m2 / m2|
109.8 x 109.8 km
|Number of samples per tile||10980 x 10980|
|Data type of data layers||Floating point|
|Number of polarisations||1 or 2|
|Polarisations||HH or VV or HH+HV or VV+VH|
|Number of annotation datasets||8-9 (2 integer layers, 6-7 float layers) (***)|
Average data volume per tile
(*) additional virtual layers for representation in logarithmic scale (dB), for sigma-nought conversion, and for colour composition are included in the product as GDAL VRT files .
(**) annotation layers are available in the metadata folder to allow an easy conversion to sigma-nought and beta-nought (see below).
(***) the number of layers depends on the number of polarizations.
The product is generated starting from Sentinel-1 SLC products (L1A) and the following processing steps and corrections are applied:
- Application of Extended Timing Annotation Dataset (ETAD)  corrections (to improve the geolocation accuracy)
- Conversion from digital numbers (DN)
- Detection (conversion form complex values to intensity)
- Thermal noise removal
- De-bursting (for TOPSAR products only)
- Application of precise orbits
- Radiometric terrain correction (RTC)
- Geometric terrain correction (GTC) and geo-coding
The product is organised as a folder containing:
- The main metadata file in XML format compliant with the OGC Earth Observation Metadata profile of Observations & Measurements  containing all relevant metadata of the product and its source products, as well as a manifest of the product contents.
- The metadata files in JSON format compliant with the STAC specification .
- The annotation folder containing image files providing information supporting the backscatter measurements.
- The measurement folder containing the backscatter image files, one for each polarization, as well as virtual raster files for logarithmic scaling and conversion to sigma nought RTC.
- The support folder containing XSD files for validation of XML metadata files.
The development of a processor prototype is currently ongoing.
The approach to provide this potential new product in the course of 2023-2024 (on the fly or systematically) is under definition and will be communicated after agreement with the European Commission.
Contact: Clément Albinet
 CLS, Sentinel-1 Product Specification, Version 3.9, 2021, https://sentinel.esa.int/documents/247904/1877131/Sentinel-1-Product-Specification-18052021.pdf
 CEOS, Analysis Ready Data For Land: Normalized Radar Backscatter, Version 5.5, 2021, https://ceos.org/ard/files/PFS/NRB/v5.5/CARD4L-PFS_NRB_v5.5.pdf
 Small, D. (2011). Flattening Gamma: Radiometric Terrain Correction for SAR Imagery. IEEE Transactions on Geoscience and Remote Sensing, 49, 3081-3093. https://doi.org/10.1109/Tgrs.2011.2120616
 Copernicus DEM, https://spacedata.copernicus.eu/web/cscda/dataset-details?articleId=394198
 Cloud Optimized GeoTIFF (COG), https://www.cogeo.org
 Limiter Error Raster Compression (LERC), https://github.com/esri/lerc
 SpatioTemporal Asset Catalogs (STAC), https://stacspec.org
 Geospatial Data Abstraction Library (GDAL) Virtual Format (VRT), https://gdal.org/drivers/raster/vrt.html
 Extended Timing Annotation Dataset (ETAD), https://sentinels.copernicus.eu/ja/web/sentinel/missions/sentinel-1/data-products/etad-dataset
 Open Geo-spatial Consortium (OGC) Earth Observation Metadata profile of Observations & Measurements, https://docs.opengeospatial.org/is/10-157r4/10-157r4.html