Authors / CoAuthors
Abstract
DEA Surface Reflectance OA (Sentinel-2B MSI) is part of a suite of Digital Earth Australia's (DEA) Surface Reflectance datasets that represent the vast archive of images captured by the US Geological Survey (USGS) Landsat and European Space Agency (ESA) Sentinel-2 satellite programs, which have been validated, calibrated, and adjusted for Australian conditions — ready for easy analysis. <b>Background:</b> This is a sub-product of Geoscience Australia Sentinel-2B MSI Analysis Ready Data Collection 3 - DEA Surface Reflectance (Sentinel-2B MSI). See the parent product for more information. The contextual information related to a dataset is just as valuable as the data itself. This information, also known as data provenance or data lineage, includes details such as the data’s origins, derivations, methodology and processes. It allows the data to be replicated and increases the reliability of derivative applications. Data that is well-labelled and rich in spectral, spatial and temporal attribution can allow users to investigate patterns through space and time. Users are able to gain a deeper understanding of the data environment, which could potentially pave the way for future forecasting and early warning systems. The surface reflectance data produced by NBART requires accurate and reliable data provenance. Attribution labels, such as the location of cloud and cloud shadow pixels, can be used to mask out these particular features from the surface reflectance analysis, or used as training data for machine learning algorithms. Additionally, the capacity to automatically exclude or include pre-identified pixels could assist with emerging multi-temporal and machine learning analysis techniques. <b>What this product offers:</b> This product contains a range of pixel-level observation attributes (OA) derived from satellite observation, providing rich data provenance: - null pixels - clear pixels - cloud pixels - cloud shadow pixels - snow pixels - water pixels - spectrally contiguous pixels - terrain shaded pixels It also features the following pixel-level information pertaining to satellite, solar and sensing geometries: - solar zenith - solar azimuth - satellite view - incident angle - exiting angle - azimuthal incident - azimuthal exiting - relative azimuth - timedelta
Product Type
dataset
eCat Id
146570
Contact for the resource
Resource provider
Point of contact
- Contact instructions
- Space Division
Digital Object Identifier
Keywords
- theme.ANZRC Fields of Research.rdf
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- EARTH SCIENCES
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- analysis ready data
- ( Theme )
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- satellite images
- ( Theme )
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- Earth observation
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- observation attributes
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- cloud masking
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- Published_External
Publication Date
2022-05-11T04:37:17
Creation Date
2021-09-13T15:13:13+10:00
Security Constraints
Legal Constraints
Status
Purpose
This product provides pixel- and acquisition-level information that can be used in a variety of services and applications. This information includes: - data provenance, which: - denotes which inputs/parameters were used in running the algorithm - demonstrates how a particular result was achieved - can be used as evidence for the reasoning behind particular decisions - enables traceability - training data for input into machine learning algorithms, or additional likelihood metrics for image feature content, where pre-classified content includes: - cloud - cloud shadow - snow - water - additional pixel filtering (e.g. exclude pixels with high incident angles) - pre-analysis filtering based on image content (e.g. return acquisitions that have less than 10% cloud coverage) - input into temporal statistical summaries to produce probability estimates on classification likelihood This product allows you to screen your data for undesired anomalies that can occur during any phase: from the satellite’s acquisition, to the processing of surface reflectance, which relies on various auxiliary sources each having their own anomalies and limitations. Pixel-level information on satellite and solar geometries is useful if you wish to exclude pixels that might be deemed questionable based on their angular measure. This is especially useful if you are using the NBAR product, where pixels located on sloping surfaces can exhibit a lower than expected surface reflectance due to a higher incidence or solar zenith angle.
Maintenance Information
asNeeded
Topic Category
geoscientificInformation
Series Information
Lineage
This is a sub-product of Geoscience Australia Sentinel-2B MSI Analysis Ready Data Collection 3 - DEA Surface Reflectance (Sentinel-2B MSI). See the parent product for more information. Data sources: - SRTM DSM/DEM data - Ephemeris Data Processing steps: - Longitude and Latitude Calculation - Satellite and Solar Geometry Calculation - Elevation Retrieval and Smoothing - Slope and Aspect Calculation - Incidence and Azimuthal Incident Angles Calculation - Exiting and Azimuthal Exiting Angles Calculation - Relative Slope Calculation - Terrain Occlusion Mask - Function of Mask (Fmask) - Contiguous Spectral Data Mask Calculation
Parent Information
Extents
[-44.00, -9.00, 112.00, 154.00]
Reference System
GDA94 (geocentric) (EPSG:4348)
Spatial Resolution
Service Information
Associations
Association Type - crossReference
Geoscience Australia Sentinel-2B MSI NBART Collection 3 - DEA Surface Reflectance NBART (Sentinel-2B MSI)
eCat Identifier - 146569,
UUID - 9a28ebfd-3bc6-4e97-a9a5-0eb775a994f8
Association Type - largerWorkCitation
Geoscience Australia Sentinel-2B MSI Analysis Ready Data Collection 3 -
eCat Identifier - 146551,
UUID - 650e74ab-cd80-46e7-8f2f-6de5365705c8
Association Type - largerWorkCitation
DEA Surface Reflectance OA (Sentinel-2B MSI)
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Source Information
Please refer to the lineage section.