DEA Surface Reflectance NBART (Landsat 7 ETM+)

DEA Surface Reflectance NBART (Landsat 7 ETM+)

ga_ls7e_ard_3

Version:

3.0.0

Type:

Baseline, Raster

Resolution:

15-30 m

Coverage:

28 May 1999 to 6 Apr 2022

Data updates:

No further updates (Previously: Daily frequency)

../../../_images/surface_reflectance_2_NBARTa_0.png

About

DEA Surface Reflectance NBART (Landsat 7 ETM+) is part of a suite of Digital Earth Australia (DEA)’s 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, validated, calibrated, and adjusted for Australian conditions — ready for easy analysis.

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Data sources

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Data sources

View code examples

Code examples

Key specifications

For more specifications, see the Specifications tab.

Technical name

Geoscience Australia Landsat 7 ETM+ NBART Collection 3

Bands

21 bands of data (nbart_blue, nbart_green, and more)

Catalogue ID

132310

Collection

Geoscience Australia Landsat Collection 3

Tags

geoscience_australia_landsat_collection_3, analysis_ready_data, satellite_images, earth_observation

Licence

Creative Commons Attribution 4.0 International Licence

Cite this product

Data citation

Fuqin, Li., Jupp, D.L.B., Sixsmith, J., Wang, L., Dorj, P., Vincent, A., Alam, I., Hooke, J., Oliver, S., Thankappan, M. 2019. GA Landsat 7 ETM+ Analysis Ready Data Collection 3. Geoscience Australia, Canberra. https://pid.geoscience.gov.au/dataset/ga/132310

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

Background

Sub-product

This is a sub-product of DEA Surface Reflectance (Landsat 7 ETM+). See the parent product for more information.

Radiance data collected by Landsat 7 Enhanced Thematic Mapper Plus (ETM+) 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 need to be reduced or removed to ensure the data is consistent and can be compared over time.

What this product offers

This product takes Landsat 7 ETM+ imagery captured over the Australian continent and corrects the inconsistencies across land and coastal fringe. It achieves this using Nadir corrected Bi-directional reflectance distribution function Adjusted Reflectance (NBAR).

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

The resolution is a 30 m grid based on the USGS Landsat Collection 1 archive.

Technical information

Radiance measurements

Landsat’s Earth Observation (EO) sensors measure radiance (brightness of light), which is a composite of:

  • surface reflectance

  • atmospheric condition

  • interaction between surface land cover, solar radiation and sensor view angle

  • land surface orientation relative to the imaging sensor

It has been traditionally assumed that Landsat 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. 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 Landsat 7 ETM+ 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.

Landsat archive

To improve access to Australia’s archive of Landsat TM/ETM+/OLI 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 Landsat TM/ETM+ and OLI 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, band07

Format

GeoTIFF

Resolution

30m

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

band08

Format

GeoTIFF

Resolution

15m

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

None

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 3
Green: band 2
Blue: band 1

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

  1. Longitude and Latitude Calculation

  2. Satellite and Solar Geometry Calculation

  3. Aerosol Optical Thickness Retrieval

  4. BRDF Shape Function Retrieval

  5. Ozone Retrieval

  6. Elevation Retrieval and Smoothing

  7. Slope and Aspect Calculation

  8. Incidence and Azimuthal Incident Angles Calculation

  9. Exiting and Azimuthal Exiting Angles Calculation

  10. Relative Slope Calculation

  11. Terrain Occlusion Mask

  12. MODTRAN

  13. Atmospheric Correction Coefficients Calculation

  14. Bilinear Interpolation of Atmospheric Correction Coefficients

  15. Surface Reflectance Calculation (NBAR)

Accuracy

Atmospheric correction accuracy depends on the quality of aerosol data available to determine the atmospheric profile at the time of image acquisition.

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 Landsat 7 ETM+. BRDF correction is applied to each whole Landsat 7 ETM+ scene and does not account for changes in land cover. It also excludes effects due to topographic shading and local BRDF.

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 algorithm also 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 DEM 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 were compared with data gathered at two field sites, Lake Frome and Gwydir. The average RMSD was found to be 0.027 reflectance units.

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

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_ls7e_ard_3.

Aliases

Resolution

No-data

Units

Type

Description

nbart_blue

nbart_band01
blue

30

-999

-

int16

-

nbart_green

nbart_band02
green

30

-999

-

int16

-

nbart_red

nbart_band03
red

30

-999

-

int16

-

nbart_nir

nbart_band04
nir
nbart_common_nir

30

-999

-

int16

-

nbart_swir_1

nbart_band05
swir_1
nbart_common_swir_1
swir1

30

-999

-

int16

-

nbart_swir_2

nbart_band07
swir_2
nbart_common_swir_2
swir2

30

-999

-

int16

-

nbart_panchromatic

nbart_band08
panchromatic

15

-999

-

int16

-

oa_fmask

fmask

30

0

-

uint8

-

oa_nbart_contiguity

nbart_contiguity

30

255

-

uint8

-

oa_azimuthal_exiting

azimuthal_exiting

30

NaN

-

float32

-

oa_azimuthal_incident

azimuthal_incident

30

NaN

-

float32

-

oa_combined_terrain_shadow

combined_terrain_shadow

30

255

-

uint8

-

oa_exiting_angle

exiting_angle

30

NaN

-

float32

-

oa_incident_angle

incident_angle

30

NaN

-

float32

-

oa_relative_azimuth

relative_azimuth

30

NaN

-

float32

-

oa_relative_slope

relative_slope

30

NaN

-

float32

-

oa_satellite_azimuth

satellite_azimuth

30

NaN

-

float32

-

oa_satellite_view

satellite_view

30

NaN

-

float32

-

oa_solar_azimuth

solar_azimuth

30

NaN

-

float32

-

oa_solar_zenith

solar_zenith

30

NaN

-

float32

-

oa_time_delta

time_delta

30

NaN

-

float32

-

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_ls7e_ard_3

Used to load data from the Open Data Cube.

Short name

DEA Surface Reflectance NBART (Landsat 7 ETM+)

The name that is commonly used to refer to the product.

Technical name

Geoscience Australia Landsat 7 ETM+ NBART Collection 3

The full technical name that refers to the product and its specific provider, sensors, and collection.

Version

3.0.0

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

15-30 m

The size of the pixels in the raster.

Temporal coverage

28 May 1999 to 6 Apr 2022

The time span for which data is available.

Update frequency

Daily (Inactive)

Previously, when data updates were active, this was their expected frequency. Also called ‘Temporal resolution’.

Update activity

No further updates

The activity status of data updates.

Catalogue ID

132310

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 Landsat Collection 3

Tags

geoscience_australia_landsat_collection_3, analysis_ready_data, satellite_images, earth_observation

Access the data

DEA Maps

Learn how to use DEA Maps.

DEA Explorer

Learn how to use the DEA Explorer.

Data sources

Learn how to access the data via AWS.

Code examples

Learn how to use the DEA Sandbox.

Version history

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

v3.0.0

-

Current version

v2.0.0

of

DEA Surface Reflectance NBART (Landsat)

Frequently asked questions

Why doesn’t DEA make Landsat thermal bands available to users?

Landsat satellite sensors not only collect data in the short-wave spectrum but also collect data into the thermal infrared bands. The USGS makes this data available in the form of a surface temperature and emissivity product: Landsat Collection 2 Surface Temperature. It provides this separately to the surface reflectance products.

This USGS Surface Temperature product is a global product that uses global datasets to perform corrections on the data that are collected by the satellite sensors. The land surface temperature outputs are very sensitive to the atmospheric profile data that is used to perform the correction. For the global analysis, the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA) atmospheric data is used to provide values for height, air temperature, and humidity. While this dataset works well for a global correction, studies over Australia have shown that the correction can be improved when higher resolution datasets are considered (Li et al, 2015).

DEA’s ARD product provides high-quality data corrections for Australian conditions. At present, we do not produce a custom land surface temperature dataset for Australia, and so we have not included the thermal bands in our ARD package.

If you would like to use USGS Landsat thermal data directly, we provide a Jupyter notebook that shows you how to combine DEA ARD data with USGS thermal data.

Acknowledgments

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

Landsat level 0 and level 1 data courtesy of the U.S. Geological Survey.

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.