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Technical Note

An Operational Analysis Ready Radar Backscatter Dataset for the African Continent

1
Geoscience Australia, GPO Box 378, Canberra 2601, Australia
2
Sinergise, Cvetkova Ulica 29, SI-1000 Ljubljana, Slovenia
3
solo Earth Observation (soloEO), Tokyo 104-0054, Japan
*
Author to whom correspondence should be addressed.
Academic Editors: Gregory Giuliani, Daniel Wicks, Ioannis Manakos, Olivier Hagolle, Jose Gomez-Dans and Cristian Rossi
Remote Sens. 2022, 14(2), 351; https://doi.org/10.3390/rs14020351
Received: 26 November 2021 / Revised: 7 January 2022 / Accepted: 7 January 2022 / Published: 13 January 2022
(This article belongs to the Special Issue Sentinel Analysis Ready Data (Sentinel ARD))
Digital Earth Africa is now providing an operational Sentinel-1 normalized radar backscatter dataset for Africa. This is the first free and open continental scale analysis ready data of this kind that has been developed to be compliant with the CEOS Analysis Ready Data for Land (CARD4L) specification for normalized radar backscatter (NRB) products. Partnership with Sinergise, a European geospatial company and Earth observation data provider, has ensured this dataset is produced efficiently in the cloud infrastructure and can be sustained in the long term. The workflow applies radiometric terrain correction (RTC) to the Sentinel-1 ground range detected (GRD) product, using the Copernicus 30 m digital elevation model (DEM). The method is used to generate data for a range of sites around the world and has been validated as producing good results. This dataset over Africa is made available publicly as a AWS public dataset and can be accessed through the Digital Earth Africa platform and its Open Data Cube API. We expect this dataset to support a wide range of applications, including natural resource monitoring, agriculture, and land cover mapping across Africa. View Full-Text
Keywords: synthetic aperture radar; Sentinel-1; analysis ready data; normalized radar backscatter; Open Data Cube synthetic aperture radar; Sentinel-1; analysis ready data; normalized radar backscatter; Open Data Cube
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MDPI and ACS Style

Yuan, F.; Repse, M.; Leith, A.; Rosenqvist, A.; Milcinski, G.; Moghaddam, N.F.; Dhar, T.; Burton, C.; Hall, L.; Jorand, C.; Lewis, A. An Operational Analysis Ready Radar Backscatter Dataset for the African Continent. Remote Sens. 2022, 14, 351. https://doi.org/10.3390/rs14020351

AMA Style

Yuan F, Repse M, Leith A, Rosenqvist A, Milcinski G, Moghaddam NF, Dhar T, Burton C, Hall L, Jorand C, Lewis A. An Operational Analysis Ready Radar Backscatter Dataset for the African Continent. Remote Sensing. 2022; 14(2):351. https://doi.org/10.3390/rs14020351

Chicago/Turabian Style

Yuan, Fang, Marko Repse, Alex Leith, Ake Rosenqvist, Grega Milcinski, Negin F. Moghaddam, Tishampati Dhar, Chad Burton, Lisa Hall, Cedric Jorand, and Adam Lewis. 2022. "An Operational Analysis Ready Radar Backscatter Dataset for the African Continent" Remote Sensing 14, no. 2: 351. https://doi.org/10.3390/rs14020351

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