{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T18:34:10Z","timestamp":1781289250551,"version":"3.54.1"},"reference-count":63,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000122681\/17\/NL\/MP"],"award-info":[{"award-number":["4000122681\/17\/NL\/MP"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000128485\/19\/I-DT"],"award-info":[{"award-number":["4000128485\/19\/I-DT"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["776242"],"award-info":[{"award-number":["776242"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["776242"],"award-info":[{"award-number":["776242"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004955","name":"Austrian Research Promotion Agency","doi-asserted-by":"publisher","award":["878946"],"award-info":[{"award-number":["878946"]}],"id":[{"id":"10.13039\/501100004955","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004955","name":"Austrian Research Promotion Agency","doi-asserted-by":"publisher","award":["873658"],"award-info":[{"award-number":["873658"]}],"id":[{"id":"10.13039\/501100004955","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Sentinel-1 Synthetic Aperture Radar (SAR) satellites allow global monitoring of the Earth\u2019s land surface with unprecedented spatio-temporal coverage. Yet, implementing large-scale monitoring capabilities is a challenging task given the large volume of data from Sentinel-1 and the complex algorithms needed to convert the SAR intensity data into higher-level geophysical data products. While on-demand processing solutions have been proposed to cope with the petabyte-scale data volumes, in practice many applications require preprocessed datacubes that permit fast access to multi-year time series and image stacks. To serve near-real-time as well as offline land monitoring applications, we have created a Sentinel-1 backscatter datacube for all continents (except Antarctica) that is constantly being updated and maintained to ensure consistency and completeness of the data record over time. In this technical note, we present the technical specifications of the datacube, means of access and analysis capabilities, and its use in scientific and operational applications.<\/jats:p>","DOI":"10.3390\/rs13224622","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T09:16:11Z","timestamp":1637140571000},"page":"4622","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["A Sentinel-1 Backscatter Datacube for Global Land Monitoring Applications"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7704-6857","authenticated-orcid":false,"given":"Wolfgang","family":"Wagner","sequence":"first","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien, Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"},{"name":"EODC Earth Observation Data Centre for Water Resources Monitoring, Franz-Grill-Stra\u00dfe 9, 1030 Wien, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7356-7516","authenticated-orcid":false,"given":"Bernhard","family":"Bauer-Marschallinger","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien, Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5701-9509","authenticated-orcid":false,"given":"Claudio","family":"Navacchi","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien, Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3867-7397","authenticated-orcid":false,"given":"Felix","family":"Reu\u00df","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien, Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2002-4467","authenticated-orcid":false,"given":"Senmao","family":"Cao","sequence":"additional","affiliation":[{"name":"EODC Earth Observation Data Centre for Water Resources Monitoring, Franz-Grill-Stra\u00dfe 9, 1030 Wien, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3554-7332","authenticated-orcid":false,"given":"Christoph","family":"Reimer","sequence":"additional","affiliation":[{"name":"EODC Earth Observation Data Centre for Water Resources Monitoring, Franz-Grill-Stra\u00dfe 9, 1030 Wien, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5913-8600","authenticated-orcid":false,"given":"Matthias","family":"Schramm","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien, Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Briese","sequence":"additional","affiliation":[{"name":"EODC Earth Observation Data Centre for Water Resources Monitoring, Franz-Grill-Stra\u00dfe 9, 1030 Wien, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2011.05.028","article-title":"GMES Sentinel-1 mission","volume":"120","author":"Torres","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1080\/07038992.2015.1104633","article-title":"Overview of the RADARSAT Constellation Mission","volume":"41","author":"Thompson","year":"2015","journal-title":"Can. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Woodhouse, I.H. (2017). Introduction to Microwave Remote Sensing, CRC Press.","DOI":"10.1201\/9781315272573"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gao, Q., Zribi, M., Escorihuela, M., Baghdadi, N., and Segui, P. (2018). Irrigation Mapping Using Sentinel-1 Time Series at Field Scale. Remote Sens., 10.","DOI":"10.3390\/rs10091495"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"111814","DOI":"10.1016\/j.rse.2020.111814","article-title":"Sentinel-1 time series data for monitoring the phenology of winter wheat","volume":"246","author":"Schlund","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Dost\u00e1lov\u00e1, A., Lang, M., Ivanovs, J., Waser, L.T., and Wagner, W. (2021). European Wide Forest Classification Based on Sentinel-1 Data. Remote Sens., 13.","DOI":"10.3390\/rs13030337"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kopp, S., Becker, P., Doshi, A., Wright, D.J., Zhang, K., and Xu, H. (2019). Achieving the Full Vision of Earth Observation Data Cubes. Data, 4.","DOI":"10.3390\/data4030094"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Wagner, W., Bauer-Marschallinger, B., Navacchi, C., Reuss, F., Cao, S., Reimer, C., Schramm, M., and Briese, C. (2021, January 18\u201320). A Sentinel-1 Data Cube For Global Land Monitoring Applications. Proceedings of the 2021 Conference on Big Data from Space (BiDS\u201921), Online Conference.","DOI":"10.3390\/rs13224622"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"81","DOI":"10.5194\/isprsannals-II-7-81-2014","article-title":"Addressing Grand Challenges in Earth Observation Science: The Earth Observation Data Centre for Water Resources Monitoring","volume":"II-7","author":"Wagner","year":"2014","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_11","unstructured":"EODC (2021, September 22). EODC Cloud. Available online: https:\/\/eodc.eu\/services\/cloud."},{"key":"ref_12","unstructured":"(2021, September 29). OpenStack. Available online: https:\/\/www.openstack.org\/."},{"key":"ref_13","unstructured":"EODC (2021, September 22). High Performance Computing. Available online: https:\/\/eodc.eu\/services\/hpc."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ticehurst, C., Zhou, Z.S., Lehmann, E., Yuan, F., Thankappan, M., Rosenqvist, A., Lewis, B., and Paget, M. (2019). Building a SAR-Enabled Data Cube Capability in Australia Using SAR Analysis Ready Data. Data, 4.","DOI":"10.3390\/data4030100"},{"key":"ref_15","unstructured":"Knowelden, R., and Castriotta, A.G. (2021, September 22). Copernicus Sentinel Data Access\u20142019 Annual Report. Available online: https:\/\/sentinels.copernicus.eu\/web\/sentinel\/news\/-\/asset_publisher\/xR9e\/content\/copernicus-sentinel-data-access-annual-report-2019;jsessionid=4DC08B0ABC1B60CB9A889CD1AF2B53B1.jvm2?redirect=https%3A%2F%2Fsentinels.copernicus.eu%2Fweb%2Fsentinel%2Fnews%3Bjsessionid%3D4DC08B0ABC1B60CB9A889CD1AF2B53B1.jvm2%3Fp_p_id%3D101_INSTANCE_xR9e%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26p_p_col_id%3Dcolumn-1%26p_p_col_count%3D1%26_101_INSTANCE_xR9e_keywords%3D%26_101_INSTANCE_xR9e_advancedSearch%3Dfalse%26_101_INSTANCE_xR9e_delta%3D20%26_101_INSTANCE_xR9e_andOperator%3Dtrue."},{"key":"ref_16","unstructured":"SkyWatch, German Aerospace Center (DLR), Brockmann Consult, and OceanDataLab (2021, September 29). Sentinel-1 Toolbox. Available online: https:\/\/step.esa.int\/main\/toolboxes\/sentinel-1-toolbox\/."},{"key":"ref_17","unstructured":"OSGeo (2021, September 27). GDAL. Available online: https:\/\/gdal.org\/."},{"key":"ref_18","unstructured":"Anaconda (2021, September 27). Numba. Available online: http:\/\/numba.pydata.org\/."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Truckenbrodt, J., Freemantle, T., Williams, C., Jones, T., Small, D., Dubois, C., Thiel, C., Rossi, C., Syriou, A., and Giuliani, G. (2019). Towards Sentinel-1 SAR Analysis-Ready Data: A Best Practices Assessment on Preparing Backscatter Data for the Cube. Data, 4.","DOI":"10.3390\/data4030093"},{"key":"ref_20","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_21","doi-asserted-by":"crossref","unstructured":"Small, D., Rohner, C., Miranda, N., R\u00fcetschi, M., and Schaepman, M.E. (2021). Wide-Area Analysis-Ready Radar Backscatter Composites. IEEE Trans. Geosci. Remote Sens., 1\u201314.","DOI":"10.1109\/TGRS.2021.3055562"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Bruggisser, M., Dorigo, W., Dost\u00e1lov\u00e1, A., Hollaus, M., Navacchi, C., Schlaffer, S., and Pfeifer, N. (2021). Potential of Sentinel-1 C-Band Time Series to Derive Structural Parameters of Temperate Deciduous Forests. Remote Sens., 13.","DOI":"10.3390\/rs13040798"},{"key":"ref_23","unstructured":"Fahrland, E. (2021, November 16). Copernicus Digital Elevation Model Product Handbook, Available online: https:\/\/spacedata.copernicus.eu\/documents\/20126\/0\/GEO1988-CopernicusDEM-SPE-002_ProductHandbook_I1.00.pdf."},{"key":"ref_24","unstructured":"Peters, M. (2021, September 29). Creating a GPF Graph. Available online: https:\/\/senbox.atlassian.net\/wiki\/spaces\/SNAP\/pages\/70503590\/Creating+a+GPF+Graph."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1109\/JSTARS.2017.2787650","article-title":"Methods to Remove the Border Noise From Sentinel-1 Synthetic Aperture Radar Data: Implications and Importance For Time-Series Analysis","volume":"11","author":"Ali","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.cageo.2014.07.005","article-title":"Optimisation of global grids for high-resolution remote sensing data","volume":"72","author":"Sabel","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1038\/s41597-020-0479-6","article-title":"Geomorpho90m, empirical evaluation and accuracy assessment of global high-resolution geomorphometric layers","volume":"7","author":"Amatulli","year":"2020","journal-title":"Sci. Data"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1080\/2150704X.2016.1212419","article-title":"Best practices for the reprojection and resampling of Sentinel-2 Multi Spectral Instrument Level 1C data","volume":"7","author":"Roy","year":"2016","journal-title":"Remote Sens. Lett."},{"key":"ref_29","unstructured":"TU Wien GEO Department (2021, September 22). Equi7Grid\u2014GitHub. Available online: https:\/\/github.com\/TUW-GEO\/Equi7Grid."},{"key":"ref_30","unstructured":"Elefante, S., Wagner, W., Briese, C., Cao, S., and Naeimi, V. (2016, January 15\u201317). High-performance computing for soil moisture estimation. Proceedings of the 2016 Conference on Big Data from Space (BiDS\u201916), Santa Cruz de Tenerife, Spain."},{"key":"ref_31","unstructured":"Ali, I., Naeimi, V., Cao, S., Elefante, S., Le, T., Bauer-Marschallinger, B., and Wagner, W. (2017, January 28\u201330). Sentinel-1 data cube exploitation: Tools, products, services and quality control. Proceedings of the 2017 Conference on Big Data from Space (BiDS\u201917), Toulouse, France."},{"key":"ref_32","unstructured":"Copernicus-ESA (2021, September 27). The Copernicus Services Data Hub. Available online: https:\/\/colhub.copernicus.eu\/."},{"key":"ref_33","unstructured":"Copernicus-ESA (2021, September 27). The Sentinels Collaborative Data Hub. Available online: https:\/\/colhub.copernicus.eu\/."},{"key":"ref_34","unstructured":"EODC (2021, September 22). CSW. Available online: https:\/\/eodc.eu\/services\/pycsw."},{"key":"ref_35","unstructured":"TU Wien GEO Department (2021, September 22). yeoda\u2014GitHub. Available online: https:\/\/github.com\/TUW-GEO\/yeoda."},{"key":"ref_36","unstructured":"ODC (2021, September 22). Open Data Cube. Available online: https:\/\/www.opendatacube.org\/."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Killough, B. (2018, January 22\u201327). Overview of the Open Data Cube Initiative. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517694"},{"key":"ref_38","unstructured":"TU Wien GEO Department (2021, September 22). yeoda\u2014Read the Docs. Available online: https:\/\/yeoda.readthedocs.io\/en\/latest\/index.html."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Nguyen, D.B., and Wagner, W. (2017). European Rice Cropland Mapping with Sentinel-1 Data: The Mediterranean Region Case Study. Water, 9.","DOI":"10.3390\/w9060392"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Vreugdenhil, M., Navacchi, C., Bauer-Marschallinger, B., Hahn, S., Steele-Dunne, S., Pfeil, I., Dorigo, W., and Wagner, W. (2020). Sentinel-1 Cross Ratio and Vegetation Optical Depth: A Comparison over Europe. Remote Sens., 12.","DOI":"10.3390\/rs12203404"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1109\/TGRS.2018.2858004","article-title":"Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets and Overcoming Obstacles","volume":"57","author":"Freeman","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"112128","DOI":"10.1016\/j.rse.2020.112128","article-title":"National-scale mapping of building height using Sentinel-1 and Sentinel-2 time series","volume":"252","author":"Frantz","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1038\/s41597-021-01059-7","article-title":"The normalised Sentinel-1 Global Backscatter Model, mapping Earth\u2019s land surface with C-band microwaves","volume":"8","author":"Cao","year":"2021","journal-title":"Sci. Data"},{"key":"ref_44","unstructured":"Copernicus Programme (2021, September 21). Copernicus Land Monitoring Service. Available online: https:\/\/land.copernicus.eu\/."},{"key":"ref_45","unstructured":"Copernicus Programme (2021, September 21). Copernicus Emergency Management Service. Available online: https:\/\/emergency.copernicus.eu\/."},{"key":"ref_46","first-page":"123","article-title":"An automatic change detection approach for rapid flood mapping in Sentinel-1 SAR data","volume":"73","author":"Li","year":"2018","journal-title":"Int. J. Appl. Earth Observ. Geoinf."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"4629","DOI":"10.1038\/s41467-019-12566-y","article-title":"Snow depth variability in the Northern Hemisphere mountains observed from space","volume":"10","author":"Lievens","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"El Hajj, M., Baghdadi, N., Wigneron, J.P., Zribi, M., Albergel, C., Calvet, J.C., and Fayad, I. (2019). First Vegetation Optical Depth Mapping from Sentinel-1 C-band SAR Data over Crop Fields. Remote Sens., 11.","DOI":"10.3390\/rs11232769"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"112554","DOI":"10.1016\/j.rse.2021.112554","article-title":"Sentinel-1 soil moisture at 1 km resolution: A validation study","volume":"263","author":"Balenzano","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_50","unstructured":"Matgen, P., Martinis, S., Wagner, W., Freeman, V., Zeil, P., and McCormick, N. (2019). Feasibility Assessment of an Automated, Global, Satellite-Based Flood Monitoring Product for the Copernicus Emergency Management Service, European Commission Joint Research Centre. Technical Report JRC116163."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"641","DOI":"10.5194\/isprs-annals-V-3-2020-641-2020","article-title":"Data processing architectures for monitoring floods using Sentinel-1","volume":"V-3-2020","author":"Wagner","year":"2020","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_52","unstructured":"(2021, September 27). Rasdaman. Available online: http:\/\/www.rasdaman.org\/."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Baumann, P., Misev, D., Merticariu, V., Huu, B.P., and Bell, B. (2018, January 6\u20139). rasdaman: Spatio-temporal datacubes on steroids. Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, USA.","DOI":"10.1145\/3274895.3274988"},{"key":"ref_54","unstructured":"Project Jupyter (2021, September 27). JupyterHub. Available online: https:\/\/jupyter.org\/hub."},{"key":"ref_55","unstructured":"OSGeo (2021, September 27). GeoServer. Available online: http:\/\/geoserver.org\/."},{"key":"ref_56","unstructured":"EODC (2021, September 27). Austrian Data Cube. Available online: https:\/\/acube.eodc.eu\/."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Schramm, M., Pebesma, E., Milenkovi\u0107, M., Foresta, L., Dries, J., Jacob, A., Wagner, W., Mohr, M., Neteler, M., and Kadunc, M. (2021). The openEO API\u2013Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities. Remote Sens., 13.","DOI":"10.3390\/rs13061125"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Mullissa, A., Vollrath, A., Odongo-Braun, C., Slagter, B., Balling, J., Gou, Y., Gorelick, N., and Reiche, J. (2021). Sentinel-1 SAR Backscatter Analysis Ready Data Preparation in Google Earth Engine. Remote Sens., 13.","DOI":"10.3390\/rs13101954"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Canty, M.J., Nielsen, A.A., Conradsen, K., and Skriver, H. (2020). Statistical Analysis of Changes in Sentinel-1 Time Series on the Google Earth Engine. Remote Sens., 12.","DOI":"10.3390\/rs12010046"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Greifeneder, F., Notarnicola, C., and Wagner, W. (2021). A Machine Learning-Based Approach for Surface Soil Moisture Estimations with Google Earth Engine. Remote Sens., 13.","DOI":"10.3390\/rs13112099"},{"key":"ref_61","unstructured":"Committee on Earth Observation Satellites (2021, September 22). CEOS Analysis Ready Data. Available online: https:\/\/ceos.org\/ard\/."},{"key":"ref_62","unstructured":"European Space Agency (2021, September 22). openEO Platform. Available online: https:\/\/docs.openeo.cloud\/."},{"key":"ref_63","unstructured":"Copernicus (2021, September 22). Copernicus and Sentinel Data at your Fingertips. Available online: https:\/\/www.wekeo.eu\/."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/22\/4622\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:31:27Z","timestamp":1760167887000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/22\/4622"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,17]]},"references-count":63,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13224622"],"URL":"https:\/\/doi.org\/10.3390\/rs13224622","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,17]]}}}