{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T23:41:46Z","timestamp":1778542906495,"version":"3.51.4"},"reference-count":49,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,7,5]],"date-time":"2019-07-05T00:00:00Z","timestamp":1562284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>This study aims at assessing the feasibility of automatically producing analysis-ready radiometrically terrain-corrected (RTC) Synthetic Aperture Radar (SAR) gamma nought backscatter data for ingestion into a data cube for use in a large spatio-temporal data environment. As such, this study investigates the analysis readiness of different openly available digital elevation models (DEMs) and the capability of the software solutions SNAP and GAMMA in terms of overall usability as well as backscatter data quality. To achieve this, the study builds on the Python library pyroSAR for providing the workflow implementation test bed and provides a Jupyter notebook for transparency and future reproducibility of performed analyses. Two test sites were selected, over the Alps and Fiji, to be able to assess regional differences and support the establishment of the Swiss and Common Sensing Open Data cubes respectively.<\/jats:p>","DOI":"10.3390\/data4030093","type":"journal-article","created":{"date-parts":[[2019,7,5]],"date-time":"2019-07-05T11:44:16Z","timestamp":1562327056000},"page":"93","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":70,"title":["Towards Sentinel-1 SAR Analysis-Ready Data: A Best Practices Assessment on Preparing Backscatter Data for the Cube"],"prefix":"10.3390","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7259-101X","authenticated-orcid":false,"given":"John","family":"Truckenbrodt","sequence":"first","affiliation":[{"name":"Department for Earth Observation, Friedrich-Schiller-University Jena, 07743 Jena, Germany"},{"name":"Institute for Data Science, German Aerospace Center DLR, 07745 Jena, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3716-5891","authenticated-orcid":false,"given":"Terri","family":"Freemantle","sequence":"additional","affiliation":[{"name":"Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chris","family":"Williams","sequence":"additional","affiliation":[{"name":"Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom","family":"Jones","sequence":"additional","affiliation":[{"name":"Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1440-364X","authenticated-orcid":false,"given":"David","family":"Small","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratories, Dept. of Geography, University of Zurich, 8057 Zurich, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cl\u00e9mence","family":"Dubois","sequence":"additional","affiliation":[{"name":"Department for Earth Observation, Friedrich-Schiller-University Jena, 07743 Jena, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5144-8145","authenticated-orcid":false,"given":"Christian","family":"Thiel","sequence":"additional","affiliation":[{"name":"Institute for Data Science, German Aerospace Center DLR, 07745 Jena, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cristian","family":"Rossi","sequence":"additional","affiliation":[{"name":"Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asimina","family":"Syriou","sequence":"additional","affiliation":[{"name":"Satellite Applications Catapult, Harwell Campus, Didcot OX11 0QR, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1825-8865","authenticated-orcid":false,"given":"Gregory","family":"Giuliani","sequence":"additional","affiliation":[{"name":"Institute for Environmental Sciences, University of Geneva, 1205 Geneva, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Onoda, M., and Young, O.R. (2017). Satellite Earth Observations and Their Impact on Society and Policy, Springer.","DOI":"10.1007\/978-981-10-3713-9"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1080\/10095020.2017.1333230","article-title":"Earth observation in service of the 2030 agenda for sustainable development","volume":"20","author":"Anderson","year":"2017","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1038\/513030a","article-title":"Satellites: Make earth observations open access","volume":"513","author":"Wulder","year":"2014","journal-title":"Nature"},{"key":"ref_4","unstructured":"COPE-SERCO (2019). Sentinel Data Access Annual Report 2019, COPE-SERCO. COPE-SERCO-RP-19-0389."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1080\/20964471.2017.1398903","article-title":"Building an earth observations data cube: Lessons learned from the swiss data cube (sdc) on generating analysis ready data (ard)","volume":"1","author":"Giuliani","year":"2017","journal-title":"Big Earth Data"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.rse.2017.03.015","article-title":"The australian geoscience data cube \u2014 foundations and lessons learned","volume":"202","author":"Lewis","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_7","unstructured":"Swiss Data Cube (2019, April 09). First Sentinel-1 Analysis Ready Data Ingested. Available online: https:\/\/www.swissdatacube.org\/index.php\/2018\/12\/05\/first-sentinel-1-analysis-ready-data-ingested\/."},{"key":"ref_8","unstructured":"Haarpaintner, J., Killough, B., Ofori-Ampofo, S., and Boamah, E.O. (2018, January 5). Advanced sentinel-1 analysis ready data for the ghana open data cube and environmental monitoring. Proceedings of the International Workshop on Retrieval of Bio- & Geo-physical Parameters from SAR Data for Land Applications, Oberpfaffenhofen, Germany."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1080\/20964471.2017.1402490","article-title":"Digital earth australia \u2013 unlocking new value from earth observation data","volume":"1","author":"Dhu","year":"2017","journal-title":"Big Earth Data"},{"key":"ref_10","unstructured":"Veci, L., Lu, J., Foumelis, M., and Engdahl, M. (2017, January 23\u201328). Esa\u2019s multi-mission sentinel-1 toolbox. Proceedings of the EGU, Vienna, Austria."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Geudtner, D., Torres, R., Snoeij, P., Davidson, M., and Rommen, B. (2014, January 13\u201318). Sentinel-1 system capabilities and applications. Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada.","DOI":"10.1109\/IGARSS.2014.6946711"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ariza-Porras, C., Bravo, G., Villamizar, M., Moreno, A., Castro, H., Galindo, G., Cabera, E., Valbuena, S., and Lozano, P. (2017, January 19\u201322). Cdcol: A geoscience data cube that meets colombian needs. Proceedings of the Colombian Conference on Computing, Cali, Colombia.","DOI":"10.1007\/978-3-319-66562-7_7"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Mathieu, P.-P., and Aubrecht, C. (2018). Fostering cross-disciplinary earth science through datacube analytics. Earth Observation Open Science and Innovation, Springer International Publishing.","DOI":"10.1007\/978-3-319-65633-5"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kreiser, Z., Killough, B., and Rizvi, S.R. (2018, January 22\u201327). Water across synthetic aperture radar data (wasard): Sar water body classification for the open data cube. Proceedings of the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517447"},{"key":"ref_15","unstructured":"CEOS (2018). Analysis Ready Data for Land: Normalized Radar Backscatter, CEOS."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3081","DOI":"10.1109\/TGRS.2011.2120616","article-title":"Flattening gamma: Radiometric terrain correction for sar imagery","volume":"49","author":"Small","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wicks, D., Jones, T., and Rossi, C. (2018, January 22\u201327). Testing the interoperability of sentinel 1 analysis ready data over the united kingdom. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518120"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Giuliani, G., Chatenoux, B., Honeck, E., and Richard, J.-P. (2018, January 22\u201327). Towards sentinel-2 analysis ready data: A swiss data cube perspective. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517954"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Killough, B. (2018, January 22\u201327). Overview of the open data cube initiative. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517694"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Frau, L., Rizvi, S.R., Chatenoux, B., Poussin, C., Richard, J., and Giuliani, G. (2018, January 22\u201327). Snow observations from space: An approach to map snow cover from three decades of landsat imagery across switzerland. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518394"},{"key":"ref_21","unstructured":"Small, D., Miranda, N., Ewen, T., and Jonas, T. (2013, January 9\u201313). Reliably flattened backscatter for wet snow mapping from wide-swath sensors. Proceedings of the ESA Living Planet Symposium, Edinburgh, UK."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"R\u00fcetschi, M., Schaepman, M.E., and Small, D. (2017). Using multitemporal sentinel-1 c-band backscatter to monitor phenology and classify deciduous and coniferous forests in northern switzerland. Remote Sens., 10.","DOI":"10.3390\/rs10010055"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"R\u00fcetschi, M., Small, D., and Waser, L. (2019). Rapid detection of windthrows using sentinel-1 c-band sar data. Remote Sens., 11.","DOI":"10.3390\/rs11020115"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.rse.2019.04.031","article-title":"Estimating melt onset over arctic sea ice from time series multi-sensor sentinel-1 and radarsat-2 backscatter","volume":"229","author":"Howell","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_25","unstructured":"Soille, P., Loekken, S., and Albani, S. (2019, January 19\u201320). Pyrosar: A framework for large-scale sar satellite data proessing. Proceedings of the Big Data from Space, Munich, Germany."},{"key":"ref_26","unstructured":"Truckenbrodt, J., Baris, I., Cremer, F., and Kidd, R. (2019, July 05). Pyrosar Version 0.9.1 Online Documentation. Available online: https:\/\/pyrosar.readthedocs.io\/en\/v0.9.1\/."},{"key":"ref_27","unstructured":"Truckenbrodt, J., Baris, I., and Cremer, F. (2019, April 09). Spatialist: A Python Module for Spatial Data Handling. Available online: https:\/\/github.com\/johntruckenbrodt\/spatialist."},{"key":"ref_28","unstructured":"ESA (2019, April 09). Snap\u2014Esa Sentinel Application Platform. Available online: http:\/\/step.esa.int\/."},{"key":"ref_29","unstructured":"Gamma Remote Sensing (2019, April 09). Gamma Software. Available online: https:\/\/www.gamma-rs.ch\/."},{"key":"ref_30","unstructured":"GDAL\/OGR Contributors (2019, April 09). Gdal\/ogr Geospatial Data Abstraction Software Library. Available online: http:\/\/gdal.org."},{"key":"ref_31","unstructured":"Barrilero, O., Peters, M., Cara, C., Veci, L., Engdahl, M., Ramoino, F., and Volden, E. (2019, January 13\u201317). Evolutions and roadmap of snap and the sentinel toolboxes. Proceedings of the ESA Living Planet Symposium, Milan, Italy."},{"key":"ref_32","unstructured":"Kluyver, T., Ragan-Kelley, B., Perez, F., Granger, B., Brussonnier, M., Frederic, J., Kelley, K., Hamrick, J., Grout, J., and Corlay, S. (2016, January 7\u20139). Jupyter notebooks\u2014A publishing format for reproducible computational workflows. Proceedings of the International Conference on Electronic Publishing, G\u00f6ttingen, Germany."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MCSE.2011.37","article-title":"The numpy array: A structure for efficient numerical computation","volume":"13","author":"Colbert","year":"2011","journal-title":"Comput. Sci. Eng."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/MCSE.2007.55","article-title":"Matplotlib: A 2d graphics environment","volume":"9","author":"Hunter","year":"2007","journal-title":"Comput. Sci. Eng."},{"key":"ref_35","unstructured":"Jones, E., Oliphant, T., and Peterson, P. (2019, April 14). Scipy: Open Source Scientific Tools for Python. Available online: http:\/\/www.scipy.org\/."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"A33","DOI":"10.1051\/0004-6361\/201322068","article-title":"Astropy: A community python package for astronomy","volume":"558","author":"Robitaille","year":"2013","journal-title":"Astron. Astrophys."},{"key":"ref_37","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1080\/13658810601169899","article-title":"An evaluation of void-filling interpolation methods for srtm data","volume":"21","author":"Reuter","year":"2007","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"237","DOI":"10.14358\/PERS.72.3.237","article-title":"The srtm data \u201cfinishing\u201d process and products","volume":"72","author":"Slater","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Farr, T.G., Rosen, P.A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., and Roth, L. (2007). The shuttle radar topography mission. Rev. Geophys., 45.","DOI":"10.1029\/2005RG000183"},{"key":"ref_41","unstructured":"JAXA (2019). Alos Global Digital Surface Model (DSM) Product Description, JAXA."},{"key":"ref_42","unstructured":"DLR (2018). Tandem-x Ground Segment Dem Products Specification Document, DLR."},{"key":"ref_43","unstructured":"Wegm\u00fcller, U., Werner, C., and Magnard, C. (2017). Geocode_Back; Gamma Diff&Geo: Reference Manual."},{"key":"ref_44","unstructured":"Miranda, N., and Hajduch, G. (2018). Masking \"no-value\" Pixels on Grd Products Generated by the Sentinel-1 Esa Ipf, CLS."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1179\/caj.1993.30.1.46","article-title":"Line generalisation by repeated elimination of points","volume":"30","author":"Visvalingam","year":"1993","journal-title":"Cartogr. J."},{"key":"ref_46","unstructured":"Schreier, G. (1993). Precise terrain corrected geocoded images. Sar Geocoding: Data and Systems, Herbert Wichmann Verlag GmbH."},{"key":"ref_47","unstructured":"B\u00fcttner, G., Kosztra, B., Soukup, T., Sousa, A., and Langanke, T. (2017). Clc2018 Technical Guidelines, European Environment Agency."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.isprsjprs.2015.01.007","article-title":"The kennaugh element framework for multi-scale, multi-polarized, multi-temporal and multi-frequency sar image preparation","volume":"102","author":"Schmitt","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Vreugdenhil, M., Wagner, W., Bauer-Marschallinger, B., Pfeil, I., Teubner, I., R\u00fcdiger, C., and Strauss, P. (2018). Sensitivity of sentinel-1 backscatter to vegetation dynamics: An austrian case study. Remote Sens., 10.","DOI":"10.3390\/rs10091396"}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/4\/3\/93\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:03:02Z","timestamp":1760187782000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/4\/3\/93"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,5]]},"references-count":49,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["data4030093"],"URL":"https:\/\/doi.org\/10.3390\/data4030093","relation":{},"ISSN":["2306-5729"],"issn-type":[{"value":"2306-5729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,5]]}}}