TU Wien Research Data

Published August 23, 2021 | Version 1.0
Dataset Open

The Sentinel-1 Global Backscatter Model (S1GBM) - Mapping Earth's Land Surface with C-Band Microwaves

  • 1. ROR icon TU Wien
  • 2. Earth Observation Data Centre for Water Resources Monitoring, Vienna, Austria
  • 3. Spire Global, Luxembourg
  • 4. ROR icon European Space Agency
  • 5. Airbus Defense and Space, Leiden, The Netherlands
  • 6. European Space Agency, Noordwijk, The Netherlands

Description

This dataset was generated by the Remote Sensing Group of the TU Wien Department of Geodesy and Geoinformation (https://mrs.geo.tuwien.ac.at/), within a dedicated project by the European Space Agency (ESA). Rights are reserved with ESA. Open use is granted under the CC BY 4.0 license.

With this dataset publication, we open up a new perspective on Earth's land surface, providing a normalised microwave backscatter map from spaceborne Synthetic Aperture Radar (SAR) observations. The Sentinel-1 Global Backscatter Model (S1GBM) describes Earth for the period 2016-17 by the mean C-band radar cross section in VV- and VH-polarization at a 10 m sampling, giving a high-quality impression on surface- structures and -patterns.

At TU Wien, we processed 0.5 million Sentinel-1 scenes totaling 1.1 PB and performed semi-automatic quality curation and backscatter harmonisation related to orbit geometry effects. The overall mosaic quality excels (the few) existing datasets, with minimised imprinting from orbit discontinuities and successful angle normalisation in large parts of the world. Supporting the designand verification of upcoming radar sensors, the obtained S1GBM data potentially also serve land cover classification and determination of vegetation and soil states, as well as water body mapping.

We invite developers from the broader user community to exploit this novel data resource and to integrate S1GBM parameters in models for various variables of land cover, soil composition, or vegetation structure.

Please be referred to our peer-reviewed article at Nature Scientific Data for details, generation methods, and an in-depth dataset analysis. In this publication, we demonstrate – as an example of the S1GBM's potential use – the mapping of permanent water bodies and evaluate the results against the Global Surface Water (GSW) benchmark.

Dataset Record

The VV and VH mosaics are sampled at 10 m pixel spacing, georeferenced to the Equi7Grid and divided into six continental zones (Africa, Asia, Europe, North America, Oceania, South America), which are further divided into square tiles of 100 km extent ("T1"-tiles). With this setup, the S1GBM consists of 16071 tiles over six continents, for VV and VH each, totaling to a compressed data volume of 2.67 TB.

The tiles' file-format is a LZW-compressed GeoTIFF holding 16-bit integer values, with tagged metadata on encoding and georeference. Compatibility with common geographic information systems as QGIS or ArcGIS, and geodata libraries as GDAL is given.

In this repository, we provide each mosaic as tiles that are organised in a folder structure per continent. With this, twelve zipped dataset-collections per continent are available for download.

Web-Based Data Viewer

In addition to this data provision here, there is a web-based data viewer set up at the facilities of the Earth Observation Data Centre (EODC) under http://s1map.eodc.eu/. It offers an intuitive pan-and-zoom exploration of the full S1GBM VV and VH mosaics. It has been designed to quickly browse the S1GBM, providing an easy and direct visual impression of the mosaics.

Code Availability

We encourage users to use the open-source Python package yeoda, a datacube storage access layer that offers functions to read, write, search, filter, split and load data from the S1GBM datacube. The yeoda package is openly accessible on GitHub at https://github.com/TUW-GEO/yeoda.

Furthermore, for the usage of the Equi7Grid we provide data and tools via the python package available on GitHub at https://github.com/TUW-GEO/Equi7Grid. More details on the grid reference can be found in https://www.sciencedirect.com/science/article/pii/S0098300414001629.

Acknowledgements

This study was partly funded by the project "Development of a Global Sentinel-1 Land Surface Backscatter Model", ESA Contract No. 4000122681/17/NL/MP for the European Union Copernicus Programme. The computational results presented have been achieved using the Vienna Scientific Cluster (VSC). We further would like to thank our colleagues at TU Wien and EODC for supporting us on technical tasks to cope with such a large and complex data set. Last but not least, we appreciate the kind assistance and swift support of the colleagues from the TU Wien Center for Research Data Management.

Files

preview.png
Files (2.6 TiB)
Name Size
md5:0fd58d48993baea7cf2f75046acfee80
1.7 MiB Preview Download
md5:56ae0a0f5a53476a470c0cc91ea2e352
316.1 GiB Preview Download
md5:b1f817252d3c45ff6d6be462c4d0c793
374.2 GiB Preview Download
md5:b008190ed96588b2fea1d19a191c30e4
98.9 GiB Preview Download
md5:4ff9ac6651326b29a876c71cd00d9756
220.7 GiB Preview Download
md5:745c4d04b2512a15f2c813e7c4f760ca
141.8 GiB Preview Download
md5:3fbe373fcbdcef6ee428bf5f36e7c5eb
166.8 GiB Preview Download
md5:756666cc46731878d99e4f03b6cb1b0f
332.1 GiB Preview Download
md5:91947cf64bc65834265386c3a946d174
375.0 GiB Preview Download
md5:6797865b5f5508a7e3784f88afedd5fa
96.5 GiB Preview Download
md5:9d47b878a70bfdc189942962ad66c45f
212.2 GiB Preview Download
md5:c132331bc94ea14cb9f3946b91358a94
136.8 GiB Preview Download
md5:046f4e28277c28b44688211555bd82ac
167.0 GiB Preview Download

Additional details

Created:
December 11, 2020
Modified:
July 20, 2022