Scientific Data · 2021 · 98 citations · 40 references
Natural SciencesEarth SciencesGeoinformaticsGlobal Navigation Satellite SystemsRemote SensingSoil SensingLand Cover ClassificationLand Cover MappingLand Surface MonitoringRemote Sensing ImagerySatellite SensorsGeometry EffectsLand Cover Classification SchemesRadar Backscatter AnalysisRadar Cross-sectionSatellite Remote Sensing DataSynthetic Aperture RadarSynthetic Aperture Radar SensorsThermal Noise
We present 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-polarisation at a 10 m sampling. We processed 0.5 million Sentinel-1 scenes totalling 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. Regions covered by only one or two Sentinel-1 orbits remain challenging, owing to insufficient angular variation and not yet perfect sub-swath thermal noise correction. Supporting the design and verification of upcoming radar sensors, the obtained S1GBM data potentially also serve land cover classification and determination of vegetation and soil states. Here, we demonstrate, as an example of its potential use, the mapping of permanent water bodies and evaluate against the Global Surface Water benchmark.
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