DEA Surface Reflectance NBART (Sentinel-2A MSI)

Version:: 3.2.1
Type:: Baseline, Raster
Resolution:: 10-60 m
Coverage:: 12 Jul 2015 to Present
Data updates:: Daily frequency, Ongoing

../../../_images/surface_reflectance_2_NBARTa_1.png

Overview

About

DEA Surface Reflectance Nadir corrected Bidirectional reflectance distribution function Adjusted Reflectance Terrain corrected (NBART) Sentinel-2A Multispectral Instrument (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.

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For help accessing the data, see the Access tab.

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Data sources

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Data sources

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Code examples

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Web services

Key specifications

For more specifications, see the Specifications tab.

Technical name	Geoscience Australia Sentinel-2A MSI NBART Collection 3
Bands	27 bands of data (nbart_coastal_aerosol, nbart_blue, and more)
DOI	10.26186/146571
Currency	See currency and the latest update date
Collection	Geoscience Australia Sentinel-2 Collection 3
Tags	geoscience_australia_sentinel_2_collection_3, analysis_ready_data, satellite_images, earth_observation
Licence	Creative Commons Attribution 4.0 International Licence

Cite this product

Data citation

Geoscience Australia, 2022. Geoscience Australia Sentinel-2A MSI NBART Collection 3 - DEA Surface Reflectance NBART (Sentinel-2A MSI). Geoscience Australia, Canberra. https://dx.doi.org/10.26186/146571

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

Sub-product

This is a sub-product of DEA Surface Reflectance (Sentinel-2A MSI). See the parent product for more information.

Reflectance data at top of atmosphere (TOA) collected by Sentinel-2A MSI sensors can be affected by atmospheric conditions, sun position, sensor view angle, surface slope and surface aspect.

Surfaces with varying terrain can introduce inconsistencies to optical satellite images through irradiance and bidirectional reflectance distribution function (BRDF) effects. For example, slopes facing the sun appear brighter compared with those facing away from the sun. Likewise, many surfaces on Earth are anisotropic in nature, so the signal picked up by a satellite sensor may differ depending on the sensor’s position.

These inconsistencies need to be reduced or removed to ensure the data can be compared over time.

What this product offers

This product takes Sentinel-2A MSI imagery captured over the Australian continent and corrects the inconsistencies across the land and coastal fringe. It achieves this using Nadir corrected Bi-directional reflectance distribution function Adjusted Reflectance (NBAR).

In addition, this product applies terrain illumination correction to correct for varying terrain.

The resolution is a 10/20/60 m grid based on the ESA level 1C archive.

Technical information

Top of atmosphere reflectance measurements

Sentinel-2 series sensors measure top of atmospheric reflectance, which is a composite of:

surface reflectance
atmospheric condition
interaction between surface land cover, solar radiation and sensor view angle (BRDF effect)
land surface orientation relative to the imaging sensor (terrain illumination).

It has been traditionally assumed that satellite imagery displays negligible variation in sun and sensor view angles. However, these can vary significantly both within and between scenes, especially in different seasons and geographic regions (Li et al. 2010, 2012).

Surface reflectance correction models

This product represents standardised optical surface reflectance using robust physical models to correct for variations and inconsistencies in image radiance values.

It delivers modelled surface reflectance from Sentinel-2A MSI data using physical rather than empirical models. This ensures that the reflective value differences between imagery acquired at different times by different sensors will be primarily due to on-ground changes in biophysical parameters rather than artefacts of the imaging environment.

This product is created using a physics-based, coupled Bidirectional Reflectance Distribution Function (BRDF) and atmospheric correction model that can be applied to both flat and inclined surfaces (Li et al. 2012). The resulting surface reflectance values are comparable both within individual images and between images acquired at different times.

For more information on the BRDF/Albedo Model Parameters product, see NASA MODIS BRDF/Albedo parameter and MCD43A1 BRDF/Albedo Model Parameters Product.

Sentinel-2 archive

To improve access to Australia’s archive of Sentinel-2 data, several collaborative projects have been undertaken in conjunction with industry, government and academic partners. These projects have enabled implementation of a more integrated approach to image data correction that incorporates normalising models to account for atmospheric effects, BRDF and topographic shading (Li et al. 2012). The approach has been applied to Sentinel-2 imagery to create baseline surface reflectance products.

The advanced supercomputing facilities provided by the National Computational Infrastructure (NCI) at the Australian National University (ANU) have been instrumental in handling the considerable data volumes and processing complexities involved with the production of this product.

Image format specifications

band01, band02, band03, band04, band05, band06, band07, band08, band8A, band11, band12


Format	GeoTIFF
Resolution	10/20/60m based on Sentinel-2 original pixel resolution
Datatype	Int16
No data value	-999
Valid data range	[1,10000]
Tiled with X and Y block sizes	512x512
Compression	Deflate, Level 6, Predictor 2
Pyramids	Levels: [8,16,32] Compression: deflate Resampling: GDAL default (nearest) Overview X&Y block sizes: 512x512
Contrast stretch	None
Output CRS	As specified by source dataset; source is UTM with WGS84 as the datum

thumbnail


Format	JPEG
RGB combination	Red: band 4 Green: band 3 Blue: band 2
Resolution	X and Y directions each resampled to 10% of the original size
Compression	JPEG, Quality 75 (GDAL default) PHOTOMETRIC colour model: YCBCR
Contrast stretch	Linear Input minimum: 10 Input maximum: 3500 Output minimum: 0 Output maximum: 255
Output CRS	Geographics (Latitude/Longitude) WGS84

Processing steps

References

F. Li, D. L.B. Jupp & M. Thankappan (2015) Issues in the application of Digital Surface Model data to correct the terrain illumination effects in Landsat images, International Journal of Digital Earth, 8:3, 235-257, DOI: 10.1080/17538947.2013.866701

L. Wang, F. Li, I. Alam, D. Jupp, S. Oliver and M. Thankappan, “Analysis Ready Data Sensitivity Analyses,” IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019, pp. 5642-5645, doi: 10.1109/IGARSS.2019.8898667

Quality

Accuracy

Atmospheric correction accuracy depends on the quality of aerosol data and total column water vapour available to determine the atmospheric profile at the time of image acquisition (Wang et al., 2009).

BRDF correction is based on low resolution imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS), which is assumed to be relevant to medium resolution imagery such as that captured by Sentinel-2A MSI. A single BRDF shape is applied to each Sentinel-2A tile and it does not account for changes in land cover.

The algorithm assumes that BRDF effect for inclined surfaces is modelled by the surface slope and does not account for land cover orientation relative to gravity (as occurs for some broadleaf vegetation with vertical leaf orientation).

The accuracy of the terrain correction also depend on the quality, scale and spatial resolution of the DSM data used and the co-registration between the DSM and the satellite image (Li et al., 2013). At present, 30 m resolution SRTM DSM data were used for the correction.

The algorithm depends on several auxiliary data sources:

Availability of relevant MODIS BRDF data
Availability of relevant aerosol data
Availability of relevant water vapour data
Availability of relevant DSM data
Availability of relevant ozone data

Improved or more accurate sources for any of the above listed auxiliary dependencies will also improve the surface reflectance result.

Quality assurance

Results from the DEA Cal/Val workflow over 17 data takes from 9 field sites were created based on both BRDF Collections 5 and 6.

The results for each collection were averaged and then compared. The comparison showed small changes in individual field sites, but overall there was no significant difference in the average results over all field sites to within 1% at most.

The technical report containing the data summary for the Phase 1 DEA Surface Reflectance Validation is available: DEA Analysis Ready Data Phase 1 Validation Project: Data Summary

Specifications

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. Here are the bands of the product: ga_s2am_ard_3.

	Aliases	Resolution	No-data	Units	Type	Description
nbart_coastal_aerosol	nbart_band01 coastal_aerosol	60	-999	-	int16	-
nbart_blue	nbart_band02 blue	10	-999	-	int16	-
nbart_green	nbart_band03 green	10	-999	-	int16	-
nbart_red	nbart_band04 red	10	-999	-	int16	-
nbart_red_edge_1	nbart_band05 red_edge_1	20	-999	-	int16	-
nbart_red_edge_2	nbart_band06 red_edge_2	20	-999	-	int16	-
nbart_red_edge_3	nbart_band07 red_edge_3	20	-999	-	int16	-
nbart_nir_1	nbart_band08 nir_1 nbart_common_nir	10	-999	-	int16	-
nbart_nir_2	nbart_band8a nir_2	20	-999	-	int16	-
nbart_swir_2	nbart_band11 swir_2 nbart_common_swir_1 swir2	20	-999	-	int16	-
nbart_swir_3	nbart_band12 swir_3 nbart_common_swir_2	20	-999	-	int16	-
oa_fmask	fmask	20	0	-	uint8	-
oa_nbart_contiguity	nbart_contiguity	10	255	-	uint8	-
oa_azimuthal_exiting	azimuthal_exiting	20	NaN	-	float32	-
oa_azimuthal_incident	azimuthal_incident	20	NaN	-	float32	-
oa_combined_terrain_shadow	combined_terrain_shadow	20	255	-	uint8	-
oa_exiting_angle	exiting_angle	20	NaN	-	float32	-
oa_incident_angle	incident_angle	20	NaN	-	float32	-
oa_relative_azimuth	relative_azimuth	20	NaN	-	float32	-
oa_relative_slope	relative_slope	20	NaN	-	float32	-
oa_satellite_azimuth	satellite_azimuth	20	NaN	-	float32	-
oa_satellite_view	satellite_view	20	NaN	-	float32	-
oa_solar_azimuth	solar_azimuth	20	NaN	-	float32	-
oa_solar_zenith	solar_zenith	20	NaN	-	float32	-
oa_time_delta	time_delta	20	NaN	-	float32	-
oa_s2cloudless_mask	s2cloudless_mask	60	0	-	uint8	-
oa_s2cloudless_prob	s2cloudless_prob	60	NaN	-	float64	-

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_s2am_ard_3	Used to load data from the Open Data Cube.
Short name	DEA Surface Reflectance NBART (Sentinel-2A MSI)	The name that is commonly used to refer to the product.
Technical name	Geoscience Australia Sentinel-2A MSI NBART 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	12 Jul 2015 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.
Currency	See the Currency Report	Currency is a measure based on data publishing and update frequency.
Latest update date	Currency Report	See Table A of the report.
DOI	10.26186/146571	The Digital Object Identifier.
Catalogue ID	146571	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 DEA products.

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

Access

Access the data

DEA Maps	See it on a map	Learn how to use DEA Maps.
DEA Explorer	DEA Explorer	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 NBART (Sentinel-2 MSI)

Changelog

2024-02-26: Reprocessing complete

Reprocessing for the Sentinel-2 contiguity fix is complete. For a list of all scenes that were affected, download the CSV file below.

The first rows of the CSV file that lists all scenes that were affected. — A preview of the CSV file.

Download the list of affected scenes (CSV)

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.