DEA Surface Reflectance (Sentinel-2C MSI)

Version:: 3.2.1
Type:: Baseline, Raster
Resolution:: 10-60 m
Coverage:: 21 Jan 2025 to Present
Data updates:: Daily frequency, Ongoing

Overview

About

DEA Surface Reflectance Sentinel-2C Multispectral Instrument (MSI) is part of a suite of Digital Earth Australia’s (DEA) Surface Reflectance datasets that represent the vast archive of images which have been 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.

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Data sources

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Data sources

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Key specifications

For more specifications, see the Specifications tab.

Technical name	Geoscience Australia Sentinel-2C MSI Analysis Ready Data Collection 3
Bands	27 bands: nbart_coastal_aerosol, nbart_blue, and more
DOI	10.26186/150143
Collection	Geoscience Australia Sentinel-2 Collection 3
Licence	Creative Commons Attribution 4.0 International Licence

Publications

Li, F., Jupp, D. L. B., Reddy, S., Lymburner, L., Mueller, N., Tan, P., & Islam, A. (2010). An evaluation of the use of atmospheric and BRDF correction to standardize Landsat data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(3), 257–270. https://doi.org/10.1109/JSTARS.2010.2042281
Li, F., Jupp, D. L. B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., & Held, A. (2012). A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sensing of Environment, 124, 756–770. https://doi.org/10.1016/j.rse.2012.06.018

Description

Background

The European Space Agency (ESA) operates the Sentinel-2 series of medium-resolution satellites. These are the Sentinel-2A and Sentinel-2B satellites (since 2015) and Sentinel-2C (starting in 2025, to replace Sentinel-2A). The spectral bands and spatial resolution of Sentinel-2 are similar to those of the Landsat series, but Sentinel-2 has a higher revisit frequency and spatial coverage. A combination of Sentinel-2 and Landsat data can provide good spatial and temporal coverage of the Earth’s surface and provide useful information to monitor environmental resources over time, such as agricultural production and mining activities. However, the raw remotely sensed data received by these satellites in the solar spectral range do not directly characterise the underlying reflectance of surface objects. The data are modified by the atmosphere, variation of solar and sensor positions as well as surface anisotropic conditions. To make accurate comparisons of imagery acquired at different times, seasons and geographic locations, and detect the change of surface, it is necessary to remove/reduce these effects to ensure the data are consistent and can be compared over time.

What this product offers

This product takes Sentinel-2C imagery captured over the Australian continent and corrects for inconsistencies across land and coastal fringes. The result is accurate and standardised surface reflectance data, which is instrumental in identifying and quantifying environmental change.

The imagery is captured using the Multispectral Instrument (MSI) sensor aboard Sentinel-2C.

This product is a single, cohesive Analysis Ready Data (ARD) package, which allows the analysis of surface reflectance data as is, without the need to apply additional corrections.

It contains two sub-products that provide corrections or attribution information:

The resolution is a 10/20/60 m grid based on the ESA Level 1C archive. Note: DEA produces NBAR as part of the Landsat ARD. This product is not produced as part of the Sentinel-2 ARD.

This Collection 3 (C3) product and has been created by reprocessing Collection 1 (C1) and making improvements to the processing pipeline and packaging. See the History tab for more details.

The introduction of a maturity concept.

The Collection 3 product is comprised of data produced to varying degrees of maturity. The maturity of a dataset is dictated by the quality of the ancillary information, such as BRDF and atmospheric data, used to generate the product. The maturity levels are Near Real Time (NRT), Interim and Final. The maturity level is designated in the filename and in the metadata.

Near Real Time (NRT) is a rapid ARD product produced < 48 hours after image capture.
Interim ARD – If there are extended delays (>18 days) in delivery of inputs to the ARD model, interim production is utilised until the issue is resolved.
Final ARD - As the higher quality ancillary datasets become available, a “Final” version of the Sentinel 2 ARD data is produced, which replaces the NRT or interim product.

Applications

This product can be used for:

The development of derivative products to monitor land, inland waterways and coastal features, such as:
- urban growth
- coastal habitats
- mining activities
- agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping)
- water extent
The development of refined information products, such as:
- areal units of detected surface water
- areal units of deforestation
- yield predictions of agricultural parcels
Compliance surveys
Emergency management

Technical information

Multispectral Instrument (MSI)

MSI is a push-broom sensor with A Three-Mirror Anastigmat (TMA) telescope with a pupil diameter equivalent to 150 mm, isostatically mounted on the platform to minimise thermo-elastic distortions. Surface Reflectance values range between 0 and 10000. MSI collects data for visible, near infrared, and short wave infrared spectral bands.

The Analysis Ready Data concept

The Analysis Ready Data (ARD) package allows you to get up and running with your analysis as quickly as possible with minimal data preparation and additional input. This makes it simpler for you to develop applications and for the database to execute queries.

The satellite data has been processed to a minimum set of requirements and organised into a form that allows immediate analysis and interoperability through time and with other datasets. It has been adapted from CEOS Analysis Ready Data (CARD4L).

The technical report containing the data summary for the Phase 1 DEA Surface Reflectance Validation is available.

ARD sub-products

DEA Surface Reflectance NBART (Sentinel-2C MSI)

The sub-product produces standardised optical surface reflectance data using robust physical models which correct for variations and inconsistencies in the image of top atmospheric reflectance values. Corrections are performed using Nadir corrected Bidirectional reflectance distribution function Adjusted Reflectance (NBAR) with an additional terrain illumination correction applied (NBART).

DEA Surface Reflectance OA (Sentinel-2C MSI)

The NBART product depends upon the Observation Attributes (OA) product to provide accurate and reliable contextual information about the Sentinel-2C data. This ‘data provenance’ provides a chain of information which allows the data to be replicated or utilised by derivative applications. The OA takes a number of different forms, including satellite, solar and surface geometry and classification attribution labels.

Lineage

This product is derived from the ESA Sentinel-2C level 1C archive.

The Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A1 Version 6 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Model Parameters dataset was provided by the National Aeronautics and Space Administration (NASA). It was produced daily using 16 days of Terra and Aqua MODIS data at 500 m resolution. See USGS: MCD43A1, NASA: MODIS BRDF / Albedo Parameter, Schaaf et al. (2002)
The ozone data was provided by Environment Canada. See Environment Canada: Global Ozone Maps
The Aerosol Optical Thickness data was provided by the Commonwealth Scientific and Industrial Research Organisation (CSIRO). See Qin et al. (2015)
The Precipitable Water for Entire Atmosphere data was provided by the National Oceanic and Atmospheric Administration (NOAA) / Earth System Research Laboratory (ESRL) / Physical Sciences Division (PSD). See Kalnay et al. (1996)
The baseline Digital Surface Model (DSM) data produced from the Shuttle Radar Topography Mission (SRTM) was provided by the National Geospatial-Intelligence Agency (NGA). See NGA: SRTM, NASA: SRTM
Level 1C Collection 1 data was provided by the European Space agency’s Copernicus data hub, see https://scihub.copernicus.eu/

Processing steps

Software

References

Berk, A., Conforti, P., Kennett, R., Perkins, T., Hawes, F., & van den Bosch, J. (2014, June 13). MODTRAN6: A major upgrade of the MODTRAN radiative transfer code (M. Velez-Reyes & F. A. Kruse, Eds.). https://doi.org/10.1117/12.2050433

Dymond, J. R., & Shepherd, J. D. (1999). Correction of the topographic effect in remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 37(5), 2618–2619. https://doi.org/10.1109/36.789656

Hudson, S. R., Warren, S. G., Brandt, R. E., Grenfell, T. C., & Six, D. (2006). Spectral bidirectional reflectance of Antarctic snow: Measurements and parameterization. Journal of Geophysical Research, 111(D18), D18106. https://doi.org/10.1029/2006JD007290

Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., & Gandin, L. et al. (1996). The NCEP/NCAR 40-Year Reanalysis Project. Bulletin Of The American Meteorological Society, 77(3), 437-471. https://doi.org/10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2

Li, F., Jupp, D. L. B., Reddy, S., Lymburner, L., Mueller, N., Tan, P., & Islam, A. (2010). An evaluation of the use of atmospheric and brdf correction to standardize landsat data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(3), 257–270. https://doi.org/10.1109/JSTARS.2010.2042281

Li, F., Jupp, D. L. B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., & Held, A. (2012). A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sensing of Environment, 124, 756–770. https://doi.org/10.1016/j.rse.2012.06.018

Qin, Y., Mitchell, R., & Forgan, B. W. (2015). Characterizing the aerosol and surface reflectance over Australia using AATSR. IEEE Transactions on Geoscience and Remote Sensing, 53(11), 6163–6182. https://doi.org/10.1109/TGRS.2015.2433911

Schaaf, C., Gao, F., Strahler, A., Lucht, W., Li, X., & Tsang, T. et al. (2002). First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing Of Environment, 83(1-2), 135-148. https://www.doi.org/10.1016/s0034-4257(02)00091-3

SZA. (2011). Retrieved May 2019, from http://sacs.aeronomie.be/info/sza.php

Zhu, Z., Wang, S., & Woodcock, C. (2015). Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images. Remote Sensing Of Environment, 159, 269-277. https://doi.org/10.1016/j.rse.2014.12.014

Zhu, Z., & Woodcock, C. E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment, 118, 83–94. https://doi.org/10.1016/j.rse.2011.10.028

Quality

Accuracy

For detailed information on accuracy and limitations, refer to the sub-products’ pages

Quality assurance

For detailed information on quality assurance, refer to the sub-products’ pages

Specifications

Product ID

The Product ID is ga_s2cm_ard_3. This ID is used to load data from the Open Data Cube (ODC), for example dc.load(product="ga_s2cm_ard_3", ...)

Bands

Bands are distinct layers of data within a product that can be loaded using the Open Data Cube (on the DEA Sandbox or NCI) or DEA’s STAC API.

	Type	Units	Resolution	No-data	Aliases	Description
nbart_coastal_aerosol	int16	-	60	-999	nbart_band01 coastal_aerosol	NBART surface reflectance useful for shallow water and fine atmospheric particles like dust and smoke. Equivalent wavelength: 444.2 nm; Bandwidth: 21 nm.
nbart_blue	int16	-	10	-999	nbart_band02 blue	NBART surface reflectance for the blue spectral band. Equivalent wavelength: 489.0 nm; Bandwidth: 65 nm.
nbart_green	int16	-	10	-999	nbart_band03 green	NBART surface reflectance for the green spectral band. Equivalent wavelength: 560.6 nm; Bandwidth: 36 nm.
nbart_red	int16	-	10	-999	nbart_band04 red	NBART surface reflectance for the red spectral band. Equivalent wavelength: 666.5 nm; Bandwidth: 30 nm.
nbart_red_edge_1	int16	-	20	-999	nbart_band05 red_edge_1	NBART surface reflectance of the near-infrared (NIR) range useful for detecting vegetation. Equivalent wavelength: 707.1 nm; Bandwidth: 15 nm.
nbart_red_edge_2	int16	-	20	-999	nbart_band06 red_edge_2	NBART surface reflectance of the near-infrared range (NIR) useful for detecting vegetation. Equivalent wavelength: 741.1 nm; Bandwidth: 15 nm.
nbart_red_edge_3	int16	-	20	-999	nbart_band07 red_edge_3	NBART surface reflectance of the near-infrared (NIR) range useful for detecting vegetation. Equivalent wavelength: 784.7 nm; Bandwidth: 21 nm.
nbart_nir_1	int16	-	10	-999	nbart_band08 nir_1 nbart_common_nir	NBART surface reflectance of the near-infrared (NIR) range. Equivalent wavelength: 834.6 nm; Bandwidth: 114 nm.
nbart_nir_2	int16	-	20	-999	nbart_band8a nir_2	NBART surface reflectance of the near-infrared (NIR) range which is narrower than ‘nbart_nir_1’. Equivalent wavelength: 865.6 nm; Bandwidth: 20 nm.
nbart_swir_2	int16	-	20	-999	nbart_band11 swir_2 nbart_common_swir_1 swir2	NBART surface reflectance of the short-wave infrared (SWIR-2) range. Equivalent wavelength: 1612.0 nm; Bandwidth: 89 nm.
nbart_swir_3	int16	-	20	-999	nbart_band12 swir_3 nbart_common_swir_2	NBART surface reflectance of the short-wave infrared (SWIR-3) range. Equivalent wavelength: 2191.3 nm; Bandwidth: 182 nm.
oa_s2cloudless_mask	uint8	Classification	60	0	s2cloudless_mask	The s2cloudless cloud mask band identifies the presence of clouds. Classification values: `0` = No cloud; `1` = Cloud.
oa_s2cloudless_prob	float64	-	60	NaN	s2cloudless_prob	The s2cloudless cloud probabilities band provides the probabilities of cloud presence as values between 0.0 and 1.0.
oa_fmask	uint8	Classification	20	0	fmask	Fmask: A categorical classification layer produced using the automated Fmask (‘Function of mask’) algorithm, used to mask out unwanted observations in satellite imagery (e.g. cloud or shadow). Classification values: `0` = null; `1` = clear; `2` = cloud; `3` = cloud shadow; `4` = snow; `5` = water.
oa_nbart_contiguity	uint8	Classification	10	255	nbart_contiguity	NBART contiguity: A layer indicating whether each pixel is ‘spectrally contiguous’, meaning that it contains valid observations in every spectral band. Classification values: `0` = non-contiguous; `1` = contiguous.
oa_azimuthal_exiting	float32	Degrees	20	NaN	azimuthal_exiting	Azimuthal exiting: The angle between true north and the exiting direction in the slope geometry.
oa_azimuthal_incident	float32	Degrees	20	NaN	azimuthal_incident	Azimuthal incident: The angle between true north and the incident direction in the slope geometry.
oa_combined_terrain_shadow	uint8	Classification	20	255	combined_terrain_shadow	Combined terrain shadow: Terrain shadow. Classification values: `0` = terrain shadow; `1` = not terrain shadow.
oa_exiting_angle	float32	Degrees	20	NaN	exiting_angle	Exiting angle: The angle between a ray reflected from a surface and the line perpendicular to the surface at the point of emergence.
oa_incident_angle	float32	Degrees	20	NaN	incident_angle	Incident angle: The angle between a ray incident on a surface and the line perpendicular to the surface at the point of incidence.
oa_relative_azimuth	float32	Degrees	20	NaN	relative_azimuth	Relative azimuth: The relative azimuth angle between the sun and view directions.
oa_relative_slope	float32	Degrees	20	NaN	relative_slope	Relative slope: The relative azimuth angle between the incident and exiting directions in the slope geometry.
oa_satellite_azimuth	float32	Degrees	20	NaN	satellite_azimuth	Satellite azimuth: The angle of the satellite’s position from true north; i.e. the angle between true north and a vertical circle passing through the satellite and the point being imaged on Earth.
oa_satellite_view	float32	Degrees	20	NaN	satellite_view	Satellite view or satellite zenith: The angle between the zenith and the satellite. (The zenith is the point in the sky or celestial sphere directly above the point being imaged on Earth.)
oa_solar_azimuth	float32	Degrees	20	NaN	solar_azimuth	Solar azimuth: The angle of the sun’s position from true north; i.e. the angle between true north and a vertical circle passing through the sun and the point being imaged on Earth.
oa_solar_zenith	float32	Degrees	20	NaN	solar_zenith	Solar zenith: The angle between the zenith and the centre of the sun’s disc.
oa_time_delta	float32	Seconds	20	NaN	time_delta	Timedelta: The time from satellite apogee (the point of orbit at which the satellite is furthest from the Earth).

For all ‘nbart_’ bands, Surface Reflectance is scaled between 0 and 10,000.

Product information

This metadata provides general information about the product.

Product ID	ga_s2cm_ard_3	Used to load data from the Open Data Cube.
Short name	DEA Surface Reflectance (Sentinel-2C MSI)	The name that is commonly used to refer to the product.
Technical name	Geoscience Australia Sentinel-2C MSI Analysis Ready Data Collection 3	The full technical name that refers to the product and its specific provider, sensors, and collection.
Version	3.2.1	The version number of the product. See the History tab.
Lineage type	Baseline	Baseline products are produced directly from satellite data.
Spatial type	Raster	Raster data consists of a grid of pixels.
Spatial resolution	10-60 m	The size of the pixels in the raster.
Temporal coverage	21 Jan 2025 to Present	The time span for which data is available.
Update frequency	Daily	The expected frequency of data updates. Also called ‘Temporal resolution’.
Update activity	Ongoing	The activity status of data updates.
DOI	10.26186/150143	The Digital Object Identifier.
Catalogue ID	150143	The Data and Publications catalogue (eCat) ID.
Licence	Creative Commons Attribution 4.0 International Licence	See the Credits tab.

Product categorisation

This metadata describes how the product relates to other products.

Collection	Geoscience Australia Sentinel-2 Collection 3
Tags	geoscience_australia_sentinel_2_collection_3, analysis_ready_data, satellite_images, earth_observation, sentinel, european

Access

Access the data

DEA Explorer	Explore data availability	Learn how to use the DEA Explorer.
Data sources	Access the data on AWS Access the data on NCI	Learn how to access the data via AWS.
Code examples	View code examples	Learn how to use the DEA Sandbox.
Web services	Get via web service	Learn how to use DEA’s web services.

History

Version history

Versions are numbered using the Semantic Versioning scheme (Major.Minor.Patch). Note that this list may include name changes and predecessor products.

v3.2.1	-	Current version
v1.0.0	of	DEA Surface Reflectance NBAR (Sentinel-2 MSI)

Credits

Acknowledgments

This research was undertaken with the assistance of resources from the National Computational Infrastructure (NCI), which is supported by the Australian Government.

Contains modified Copernicus Sentinel data 2015-present.

The authors would like to thank the following organisations:

National Aeronautics and Space Administration (NASA)
Environment Canada
The Commonwealth Scientific and Industrial Research Organisation (CSIRO)
National Oceanic and Atmospheric Administration (NOAA) / Earth System Research Laboratories (ESRL) / Physical Sciences Laboratory (PSD)
The National Geospatial-Intelligence Agency (NGA)
The United States Geological Survey (USGS) / Earth Resources Observation and Science (EROS) Center
Spectral Sciences Inc.

License and copyright

Released under Creative Commons Attribution 4.0 International Licence.