Australian
Reflectance Grid
(ARG25)
Product Information
Beta Release
V0 26 February 2013
Unclassified
ARG25 Product Information—Beta Release
Page 2 of 23
26 Feb 2013
Geoscience Australia
26 Feb 2013
ARG25 Product Information—Beta Release
Document History
Sheet A.2 Revisions
Revision
Number
0
Date
Nature of Change and Reason
26/02/2013 Minor edits
Geoscience Australia
Author/Approval
Adam Lewis
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ARG25 Product Information—Beta Release
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Table of Contents
A Description ............................................................................................................. 5
Sheet A.1 Definition and Usage ....................................................................................... 5
Sheet A.2 Revisions ......................................................................................................... 3
Sheet A.3 Further Information ......................................................................................... 8
B Specification ........................................................................................................... 9
Sheet B.1 Provenance and Algorithms ............................................................................ 9
Sheet B.2 Technical Characteristics .............................................................................. 12
Sheet B.2.1 Relevant Platforms ........................................................................................12
Sheet B.2.2 Relevant Sensors ...........................................................................................13
Sheet B.2.3 Product Details ..............................................................................................15
C Availability .......................................................................................................... 17
Sheet C.1 Licencing and Access .................................................................................... 17
Sheet C.2 Delivery Information ..................................................................................... 18
Sheet C.3a Pixel Quality Flag ......................................................................................... 19
Sheet C.3b Pixel Quality Flag (examples) ...................................................................... 20
Glossary
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26 Feb 2013
A
ARG25 Product Information—Beta Release
Description
Sheet A.1 Definition and Usage
Product
Name
Australian Reflectance Grid 251
Abbreviation
ARG25
Product Suite
The Australian Reflectance Grid (ARG) is a suite of new generation EO products from GA.
These standard data products deliver optical surface reflectance data across the Australian
landmass and its coastal fringes. The resulting datasets are effectively sensor agnostic and
future versions of products in this suite are intended to be readily comparable between scales.
The first product in this suite is the ARG25, a medium resolution (25 m) grid based on Landsat
imagery. A low resolution grid based on MODIS data is under development.
Key Features
of Product
Suite
The ARG product suite provides standardised optical surface reflectance datasets for Australia
using robust physical models to correct for variations in image radiance values due to
atmospheric properties, and sun and sensor geometry. These products also feature integrated
pixel quality flags to indicate whether the reflectance values in each grid cell are deemed to be
affected by band saturation, cloud or cloud shadow, or contain null values.
It is the intention of GA that this suite of products will be available within a more general
framework of nested grids. The grid cell sizes of products comprising this suite will be scalable
to facilitate easy data comparison between different products. This format will greatly simplify
comparison of image datasets acquired by different sensors at varying spatial scales.
The resulting stack of surface reflectance grids are effectively consistent over space and time,
and will be instrumental in identifying and quantifying environmental change.
The ARG25 is the first ARG product to be released by GA. It is based on the Landsat
TM/ETM+ archive and presents surface reflectance data in 25 m2 grid cells.
Product
Overview
Radiance measurements from EO sensors do not directly quantify the surface reflectance of the
Earth. Such measurements are modified by variations in atmospheric properties, sun position,
sensor view angle, surface slope and surface aspect. To obtain consistent and comparable
measures of Earth surface reflectance from EO, these variations need to be reduced or removed
from the radiance measurements (Li et al., 2010). This is especially important when comparing
imagery acquired in different seasons and geographic regions.
The ARG25 product is created using a physics-based coupled 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 and/or with different sensors3.
This product can be viewed as a data cube, with time as the third dimension. The surface
reflectance data for each imaged date and time are stacked in chronological order, with Landsat
TM/ETM+ sources being interleaved as appropriate to their acquisition time. Interrogation of
this data cube allows the time series for individual grid cells, as well as their heritage and data
quality, to be extracted and compared.
1
2
3
Formerly referred to as the Landsat Nadir BRDF-Adjusted Reflectance (NBAR) product.
In ARG25-V0.1 and ARG25-V1.0+, grid cell size will be 0.00025º, which approximates 25 m for most of Australia.
Notwithstanding differences due to variations in spectral bandwidth between sensors.
Geoscience Australia
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ARG25 Product Information—Beta Release
26 Feb 2013
Sheet A.1 Definition and Usage
Product
Background
Geometric Presentation
Current
Radiance Corrections
ARG25V0.0
Landsat TM/ETM+
archive from 2000 to
2010
Effects due to
Image scenes resampled to
atmospheric profile and
custom UTM grids
BRDF
ARG25V0.1
Landsat TM/ETM+
archive from 2000 to
2010
Effects due to
atmospheric profile and
BRDF
Geographic Grid derived
from
ARG25-V0.0
ARG25V1.0
Landsat TM/ETM+
archive plus Landsat
OLI
Effects due to
atmospheric profile and
BRDF
Gridded values
ARG25V2.0
Landsat
TM/ETM+/MSS
archive plus Landsat
OLI
Effects due to
atmospheric profile,
BRDF and topographic
shading
Gridded values
Future
Planned
Product
Versions
Features
Image Data Input
Interim
Version
Landsat Archive
GA has acquired Landsat TM/ETM+ imagery over Australia for several decades. While this
data has been used extensively for numerous land and coastal mapping studies, its utility for
accurate monitoring of environmental resources has been limited by the processing methods
that have been traditionally used to correct for inherent geometric and radiometric distortions in
EO imagery.
To improve access to Australia’s archive of Landsat TM/ETM+ 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 11 years of Landsat TM/ETM+ imagery (2000–2010) to
create the ARG25-V0.0 and ARG25-V0.1 products4. 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 5 and
processing complexities involved with production of this product. It is intended that the Landsat
archives from 1986 will be incrementally incorporated into the ARG25 product and released as
subsequent versions.
Surface Reflectance Correction Models
Image radiance values recorded by passive EO sensors are a composite of:
• surface reflectance;
• atmospheric condition;
• interaction between surface land cover, solar radiation and sensor view angle; and
• land surface orientation relative to the imaging sensor.
It has been traditionally assumed that Landsat imagery display 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).
The ARG25 product delivers an estimate of surface reflectance from Landsat TM/ETM+ data
using physical rather than empirical models. Accordingly, this product will ensure that
reflective value differences between imagery acquired at different times by different sensors 6
will be primarily due to on-ground changes in biophysical parameters rather than artefacts of
the imaging environment.
Integrated Time Series Data
Once consistent and comparable measures of surface reflectance have been retrieved from EO
data, it is possible to quantify changes in Earth surface features through time. This process is
further simplified when the surface reflectance data conforms to a sensor agnostic nested grid,
4
5
6
The ARG25-V0.0 and ARG25-V0.1 products do not include topographic shading correction nor the nested grid
structure.
110,000 Landsat 5/7 scenes totalling ~140 TB.
Notwithstanding differences due to variations in spectral bandwidth between sensors.
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Geoscience Australia
26 Feb 2013
ARG25 Product Information—Beta Release
Sheet A.1 Definition and Usage
as envisaged for future versions of the ARG25 product.
Given the growing time series of EO imagery, this landmark facility will streamline the process
of reliably monitoring long-term changes in Australian land and water resources.
Potential
Applications
ARG25 will significantly reduce pre-processing requirements for a wide range of land and
coastal monitoring applications and render more accurate results from these analyses,
particularly those utilising time series data. Such applications include various forms of change
detection, including monitoring of urban growth, coastal habitats, mining activities, and
agricultural production, as well as compliance surveys, scientific research and emergency
management.
Expected
Lifespan
Ongoing—while Medium Resolution Optical EO data stream is available for Australia.
Geoscience Australia
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ARG25 Product Information—Beta Release
26 Feb 2013
Sheet A.3 Further Information
References
Berk, A., Anderson, G.P., Acharya, P.K., Hoke, M.L., Chetwynd, J.H., Bernstein, L.S., Shettle, E.P.,
Matthew, M.W., and Adler-Golden, S.M. (2003) Modtran 4 Version 3 Revision 1 User's manual.
Airforce Research Laboratory, Hanscom, MA, USA.
Chander, G., Markham, B.L., and Helder, D.L. (2009) Summary of current radiometric calibration
coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment 113,
893–903.
Edberg, R., and Oliver, S. (2013) Projection-Independent Earth-Solar-Sensor Geometry for Surface
Reflectance Correction. Submitted to IGARSS 2013, Melbourne.
GA and CSIRO (2010) 1 second SRTM Derived Digital Elevation Models User Guide. Version 1.03. GA,
Canberra.
Forrest, R.B. (1981) Simulation of orbital image-sensor geometry, Photogrammetric Engineering and
Remote Sensing 47, 1187-93.
Irish, R. (2000) Landsat 7 Automatic Cloud Cover Assessment, sourced:
http://landsathandbook.gsfc.nasa.gov/pdfs/ACCA_SPIE_paper.pdf, last accessed 12/11/2012.
Irish, R.R., Barker, J.L., Goward, S.N., Arvidson, T. (2006) Characterization of the Landsat-7 ETM+
Automated Cloud –Cover Assessment (ACCA) Algorithm. Photogrammetric Engineering & Remote
Sensing 72 (10), 1179-88.
Kalnay, E. Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White,
G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski,
C., Wang, J., Leetmaa, A., Reynolds, R. Jenne, R., Joseph, D. (1996) The NCEP/NCAR 40-Year
Reanalysis Project. Bulletin of the American Meteorological Society 77, 437-71.
Li, F., Jupp, D.L.B., Reddy, S., Lymburner, L., Mueller, N., Tan, P., and Islam, A. (2010) An Evaluation
of the Use of Atmospheric and BRDF Correction to Standardize Landsat Data. IEEE J. Selected Topics
in Applied Earth Observations and Remote Sensing 3, 257–70.
Li, F., Jupp, D.L.B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., and Held, A. (2012) A
physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote
Sensing of Environment 124, 756–70.
Li, F. (2010) ARG25 Algorithm Theoretical Basis Document. GA, Canberra.
Lubke, M. (2012) Landsat Geometry Calibration/Validation Update. Presentation at LTWG #21, 25
September 2012, Sioux Falls. USGS, USA.
OGC (2006) OpenGIS® Web Map Server Implementation Specification (Ed: Jeff de la Beaujardiere) Ref.
OGC® 06–042. OGC
OGC (2010) OGC® WCS 2.0 Interface Standard – Core. (Ed: Peter Baumann) Ref. OGC 09–110r3.
OGC.
OGC (2013) CF-netCDF3 Data Model Extension Standard (Eds: Ben Domenico and Stefano Nativi) Ref.
OGC 11-165r2. OGC.
Strahler, A.H., and Muller, J.-P. (1999) MODIS BRDF/Albedo Product: Algorithm Theoretical Basis
Document Version 5.0. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod09.pdf
TM World Borders vector file: http://thematicmapping.org/downloads/world_borders.php
USGS (2012a) Landsat Thematic Mapper (TM) Level 1 (L1) Data Format Control Book (DFCB)
LS-DFCB-20 Version 4.0.. http://landsat.usgs.gov/documents/LS-DFCB-20.pdf
USGS (2012b) Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) Level 1 (L1) Data Format
Control Book (DFCB). LS-DFCB-04 Version 15.0.
http://landsat.usgs.gov/documents/LS-DFCB-04.pdf
Lubke, M. (2012) Landsat Geometry Calibration/Validation Update. Presentation at LTWG #21, 25
September 2012, Sioux Falls, USA.
Vincenty, T. (1975) Direct and Inverse Solutions of Geodesies on the Ellipsoid with Application of
Nested Equations. Survey Review 23, 88–93.
Zhu, Z. and Woodcock, C. E. (2012) Object-based cloud and cloud shadow detection in
Landsat imagery. Remote Sensing of Environment 118, 83–94.
Websites
Page 8 of 23
http://www.ga.gov.au/earth-observation/accessing-satellite-imagery/future-of-landsat-archive.html
landsathandbook.gsfc.nasa.gov
Geoscience Australia
26 Feb 2013
B
ARG25 Product Information—Beta Release
Specification
Sheet B.1 Provenance and Algorithms
Primary
Landsat TM (Landsat-5) Level 1 Systematic Terrain Correction Imagery
Landsat ETM+ (Landsat-7) Level 1 Systematic Terrain Correction Imagery
Landsat 5/7 Satellite
Ephemeris data7
Maximum view angle (degrees) 8
Acquisition day and time (in UTC) to compute sun
position
Metadata
Size (number of pixels and lines)
TM/ETM+ Image scene
Cell Size8
NW location
Centre location
Source
Data Sources
Ancillary
Derived Data
Earth rotational angular
velocity
0.000072722052 radians/second
Earth-sun distance LUT
Distance from image scene centre to the sun
Spectal filter
Sensor Response Function
Solar irradiance LUT
Sun position at image date/time
MODIS BRDF Shape
Function9
BRDF parameters for imagery acquired during
MODIS era
BRDF database derived
from 2001–2011 MODIS
archive10
BRDF parameters for imagery acquired before
MODIS era
DSM/DEM data from
1-second SRTM11
Height at image scene centre, plus slope and aspect
per pixel for topographic correction
Aerosol optical depth12
Monthly ozone image13
Total water vapour for
image date/time14
Atmospheric state in whole profile for
Modtran 5 Radiative Transfer Model
CO2 concentration for
image date/time15
Modtran Seasons for
atmospheric profiles
7
8
9
10
11
12
13
14
15
Tropical Summer: latitude < 23S
Mid-Latitude Summer: 23S < latitude < 50S
Based on NORAD daily Two Line Element (TLE) for Landsat 5/7
(http://landsat.usgs.gov/science_DEoption1.php) then adjusted to match image scene centre from scene metadata
and used to compute orbital parameters (semi-major axis, eccentricity and angular velocity).
See Table B.2.3 for numeric value.
Based on Ross-Li model—see Strahler and Muller (1999).
Under development.
GA and CSIRO (2010)—http:/www.ga.gov.au/image_cache/GA18067.pdf.
Ideally derived from same day AATSR data; else monthly composite AATSR data; else long term monthly average
aerosol data. Aerosol optical depth at 550nm is used to compute visibility (Berk et al., 2003).
Monthly average based on Canadian Ozone Map (http://exp-studies.tor.ec.gc.ca/cgi- bin/selectMap).
Ideally the WMO radiosonde network would be used but this does not offer continental coverage for Australia, so
the Total Precipitable Water Content product (NOAA NCEP; Kalnay et al., 1996) is used.
Set as constant=375 ppmv.
Geoscience Australia
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ARG25 Product Information—Beta Release
26 Feb 2013
Sheet B.1 Provenance and Algorithms
Major
Algorithms
ARG2516 uses a combined atmospheric, BRDF and topographic shading correction model based
on physical parameters to extract surface reflectance values from Landsat TM/ETM+ as
reported in Li et al. (2010) and Li et al. (2012).
For more details, see the Algorithm Theoretical Basis Document (Li, 2010).
Processing
Sequence
ARG25-V0.0, ARG25-V0.1 and ARG25-V1.0 (atmospheric and BRDF correction only):
1. Extract metadata from data sources.
2. Calculate sun and sensor angles for each pixel in image scene using satellite ephermis data
and a sampling-gridding procedure based on a geodesic path located with Vincenty’s
algorithm (Vincenty, 1975; Edberg and Oliver, 2013)17.
3. Determine values for six base atmosphere parameters 18 across each image scene:
a. divide scene into quarters and select the nine unique points which form the corners of
these quadrants;
b. compute the six parameters across optical spectrum at each of the nine points using
Radiative Transfer Model (Modtran 5) and atmospheric state data;
c. accumulate values for the six parameters at each of the nine points to correspond to
Landsat TM/ETM+ bands using Landsat spectral response function; and
d. interpolate accumulated values for the six parameters across image scene using bilinear
method.
4. Use interpolated, accumulated values for the six base atmosphere parameters 12 to compute
the atmospheric and BRDF correction for each pixel and output the normalised surface
reflectance for sun angle of 45.
ARG25-V2.0+ (correction for atmospheric, BRDF and topographic shading effects):
1. Extract metadata from data sources.
2. Pre-process Digital Surface Model (DSM) using modal filter and resample to match image
grid.
3. For each pixel in image scene, calculate:
a. sun and sensor angles using satellite ephermis data and a sampling-gridding procedure
based on a geodesic path located with Vincenty’s algorithm (Vincenty, 1975; Edberg
and Oliver, 2013)18;
b. slope, aspect, incident, exiting and their azimuth angles on sloping surface; and
c. cast shadow given sun and satellite directions.
4. Determine values for six base atmosphere parameters19 across each image scene:
a. divide scene into quarters and select the nine unique points which form the corners of
these quadrants;
b. compute six parameters across optical spectrum at each of the nine points using
Radiative Transfer Model (Modtran 5) and atmospheric state data;
c. accumulate values for six parameters at each of the nine points to correspond to Landsat
TM/ETM+ bands using Landsat spectral response function; and
d. interpolate accumulated values for six parameters across image scene using bilinear
method.
5. Compute atmospheric, BRDF and topographic shading corrected surface reflectance,
normalised for sun angle of 45.
16
17
18
The ARG25-V0.0 and ARG25-V0.1 products do not include topographic shading correction nor the nested grid
structure.
View angle calculations are based on method of Forrest (1981).
Tv—Total transmittance in view direction;
Ts—Total transmittance in sun direction;
fv—Fraction of diffuse radiation if sun were in view direction;
fs—Fraction of diffuse radiation if sun were in sun direction;
S—Reflectance of atmosphere from ground; and
0—Reflectance of atmosphere from satellite.
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ARG25 Product Information—Beta Release
Sheet B.1 Provenance and Algorithms
Validation of
Underlying
Algorithms
Accuracy and
Limitations
Atmospheric and BRDF Correction
As detailed in Li et al. (2010), the atmospheric and BRDF correction algorithm was validated in
three parts:
1. Validate combined atmospheric and surface BRDF correction using field reflectance
measurements at two very different sites, Gwydir, NSW, and Lake Frome, SA—correlation
(measured as r) between corrected image values and field data was > 0.95;
2. Validate surface BRDF correction using data from image overlap areas of adjacent paths
acquired one week apart in northeast Queensland—normalised reflectance factor was very
close in corrected images, but not in original images, and difference in reflectance factor
values between corrected and uncorrected images can be > 0.05; and
3. Cross-validate Landsat TM data for accuracy of spectral reflectance using the MODIS
reflectance product for Lake Frome—correlation (measured as r2) between corrected
Landsat TM image values and MODIS reflectance product was 0.93–0.97 in all bands
except Landsat TM band 5, which was 0.90.
The results clearly show that the algorithm can remove most of the BRDF effect without
empirical adjustment and that cross-calibration between the Landsat ETM+ and MODIS sensors
is achievable.
Topographic Correction
As detailed in Li et al. (2012), two high relief areas in southeast Australia (Australian Alps in
northeast Victoria and the Blue Mountains in NSW) were used to test the algorithm against
eight Landsat images with varying solar angles (seasons), and terrain types. Visual assessment
showed that the algorithm removed much of the topographic effect and detected deep shadows
in all eight images. An indirect validation based on the change in correlation between the data
and terrain slope showed that the correlation coefficient between the surface reflectance factor
and the cosine of the incident (sun) angle reduced dramatically after the topographic correction
algorithm was applied. The correlation coefficient typically reduced from 0.80–0.70 to 0.05 in
areas of significant relief. It was also shown how the corrected surface reflectance can provide
suitable input data for multi-temporal land cover classification in areas of high relief based on
spectral signatures and spectral albedo, while the products based only on BRDF and
atmospheric correction cannot. To provide comparison with previous work and to validate the
proposed algorithm, two empirical methods based on the C-correction were used as well as the
established SCS-method to provide benchmarks. The proposed method was found to achieve the
same measures of shade reduction without empirical regression.
1. Atmospheric correction accuracy is dependent on the quality of aerosol data available to
determine the atmospheric profile at time of image acquisition.
2. BRDF correction is based on low resolution imagery (MODIS) which is assumed to be
relevant to medium resolution imagery such as Landsat TM/ETM+. BRDF correction is
applied to each whole Landsat TM/ETM+ scenes and does not account for changes in land
cover. It also excludes effects due to topographic shading and local BRDF. This algorithm
is dependent on the availability of relevant MODIS BRDF data.
3. Topographic shading correction algorithm is designed for medium resolution imagery and
assumes that hill slopes are resolved by the sensor system (Li et al., 2012). The algorithm
assumes that:
a. 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 broad leaf vegetation
with vertical leaf orientation).
Geoscience Australia
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ARG25 Product Information—Beta Release
26 Feb 2013
Sheet B.2 Technical Characteristics
Sheet B.2.1 Relevant Platforms
Full Name
Landsat-5
Landsat-7
Abbreviation
Landsat-5
Landsat-7
Agency
NASA (USA) (launch and satellite maintenance)
USGS (USA) (ground stations and data handling)
Heritage
Landsat-1 launched in 1972; Landsat-7 last in series; Landsat Data Continuity
Mission (LDCM) due for launch in 2013
Application Areas
Land and Coastal Mapping
Land and Coastal Mapping;
hydrology
Launch Date
1 March 1984
15 April 1999
End of Life
18 November 2011
N/A
Orbit
Type
Sun-synchronous, near polar
Direction
Ascending
Altitude
705 Km
Inclination
98.2º
Period
99 minutes (~14.5 orbits/day)
Repeat Cycle
16 days (233 orbits/year)
Equatorial Crossing
Time
0945 (± 15 minutes) LST
1000 (± 15 minutes) LST
Multi-Spectral Scanner (MSS)
Enhanced Thematic Mapper Plus
(ETM+)
Sensors
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Thematic Mapper (TM)
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26 Feb 2013
ARG25 Product Information—Beta Release
Sheet B.2 Technical Characteristics (continued)
Sheet B.2.2 Relevant Sensors
Full Name
(Landsat) Thematic Mapper
(Landsat) Enhanced Thematic
Mapper Plus
Abbreviation
(Landsat) TM
Landsat ETM+
Platform
Landsat-4 and -5 satellites
Landsat-7 satellite
Heritage
MSS sensors carried on board
Landsat-1 and -5
Enhanced version of TM sensors
carried on board Landsat-4 and -5
Operational
No
Yes; Scan Line Correction (SLC)
fault since May 2003
GA Data Reception
September 1987–31 December 1999;
1 July 2003–18 November 2011
July 1999–present; small gaps from
31 May 2003 due to SLC fault
Sensing Mode
Passive
Passive
Scanning Method
Opto-mechanical
Opto-mechanical and Thermal
Infrared
Application Areas
Land and coastal mapping
Land and coastal mapping, hydrology
Spectral Bands
Band
Spectral
Range
(m)
1
0.45–
0.52
EM Region
Visible Blue
Band
Spectral
Range
(m)
1
0.45– 0.52
Visible Blue
2
0.52–0.60 Visible Green
2
0.52–0.60
Visible Green
3
0.63–0.69 Visible Red
3
0.63–0.69
Visible Red
4
0.76–0.90 Near Infrared
4
0.76–0.90
Near Infrared
5
1.55–1.75 Middle Infrared
5
1.55–1.75
Middle Infrared
6
10.40–
12.50
7
2.08–2.35
Middle Infrared
8
0.52–0.90
Panchromatic
6
7
10.40–
12.50
Thermal Infrared
2.08–2.35 Middle Infrared
Radiometric Quantisation
8 bit (256 levels)
Radiometric Quality
Radiometric Calibration Uncertainty ± 5%19
19
EM Region
Thermal
Infrared
Best 8 of 9 bits
Chander et al. (2009)—early years of Landsat 5 were less reliable.
See also http://landsathandbook.gsfc.nasa.gov/sysper/
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ARG25 Product Information—Beta Release
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Sheet B.2 Technical Characteristics (continued)
Sheet B.2.2 Relevant Sensors
Swath Width
185 Km
Ground Sampling Interval
(GSI or pixel size)
Maximum view angle
Geometric Quality
20
Band
Metres
Band
Metres
1-5 and 7
30
1-5 and 7
30
6
120
60
8
15 (theoretical),
18 (actual)
23.5
Absolute Error < 1 pixel
Absolute Error < 1 pixel
Relative Error < 1 pixel
Relative Error < 1 pixel
Band-to-Band Error < 0.31 pixel
Band-to-Band Error < 0.17 pixel
Repeat Coverage Interval
Once per repeat cycle of satellite platform
Stereo base-height ratio
N/A
Pointing angle
Vertical only
20
6
Based on Lubke (2012).
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ARG25 Product Information—Beta Release
Sheet B.2 Technical Characteristics (continued)
Sheet B.2.3 Product Details
Frequency
Based on available Landsat TM/ETM+ imagery
Temporal Extent
January 2000 to December 2010
Geographic Coverage
Spatial Extent21
Grid Dimensions
NW
10S latitude, 108E longitude
NE
45S latitude, 108E longitude
SW
10S latitude, 155E longitude
SE
45S latitude, 155E longitude
W–E
188,000 grid cells
N–S
140,000 grid cells
ITRF Epoch GDA94
Datum
GRS80
Ellipsoid
Mapping Base for
ARG25-V0.0
Image Grid for
ARG25-V0.0
Mapping Base for
ARG25-V0.1
Image Grid for
ARG25-V0.1
Grid Bit Depth
6,378,137 m
Inverse Flattening
(1/f)
298.25722210088
Eccentricity (e2)
0.0066943800229034
Map Co-ordinate
System
MGA94
Projection
Universal Transverse Mercator (UTM)
Origin
Centre of UTM zone
Cell Size
25 m
Type
Custom Grid
Specification
USGS (2012a, 2012b)
Pixel Origin
Top Left
Orientation
North Upwards
Resampling Method
Cubic Convolution
Datum
WGS84 (EPSG 4326)
Projection
Geographic
Cell Size
0.00025º
Type
Geographic Grid
Pixel Origin
Top Left
Orientation
North Upwards
Resampling Method
Nearest Neighbour from ARG25-V0.0
2 byte integer (16 bits)
Data
Spectral Bands
Quicklook
21
Semi-major axis (a)
Band 1
Surface Reflectance from Landsat TM/ETM+ bands 1
Band 2
Surface Reflectance from Landsat TM/ETM+ bands 2
Band 3
Surface Reflectance from Landsat TM/ETM+ bands 3
Band 4
Surface Reflectance from Landsat TM/ETM+ bands 4
Band 5
Surface Reflectance from Landsat TM/ETM+ bands 5
Band 6
Surface Reflectance from Landsat TM/ETM+ bands 7
Band 7
Pixel Quality Flag (see Sheet C.3)
Red
Landsat TM/ETM+ band 7
Green
Landsat TM/ETM+ band 4
Blue
Landsat TM/ETM+ band 1
For full Australian coverage.
Geoscience Australia
Page 15 of 23
ARG25 Product Information—Beta Release
26 Feb 2013
Sheet B.2 Technical Characteristics (continued)
Sheet B.2.3 Product Details
Data Range
Solar Zenith Angle
Surface Reflectance
1 to 10,000
Pixel Quality Flag*
Bit map of 16 binary tests (see Sheet C.3)
45
* Pixel quality flag not available in beta release of this product.
Page 16 of 23
Geoscience Australia
26 Feb 2013
C
ARG25 Product Information—Beta Release
Availability
Sheet C.1 Licencing and Access
Support
Supported
Licencing
Creative Commons 3.0 By Attribution
Search Tool
http://www.ga.gov.au/earth-observation/arg25.html
Preview Facility
Web Map Service 1.3.0 (WMS; OGC, 2006) for Quicklook Image
Web Coverage Service 2.0 (WCS; OGC, 2010) for all bands
Ordering and
Distribution
n/a
Geoscience Australia
Page 17 of 23
ARG25 Product Information—Beta Release
26 Feb 2013
Sheet C.2 Delivery Information
nnn_nnn_fff_ggg_hhh_ppp_rrr_yyyymmdd_x
where:
nnn_nnn: satellite and sensor ID
fff: product code
ggg: process code
hhh: process source/group
ppp: path
rrr: row
yyyymmdd: acquisition date
x: version number
File Name
Example file name: LS5_TM_NBAR_P54_GANBAR01-002_090_081_20090407_1
where
LS5—Landsat 5 (satellite ID)
TM—Thematic Mapper scene (sensor ID)
NBAR—Nadir BRDF Adjusted Reflectance (product code)
P54—Ortho NBAR product (process code)
GANBAR01—GA product code
002—Acquisition Ground Station ID (Alice Springs)
Path—090
Row—081
Acquistion Date—07/04/2009
Version Number—1
ARG25-V0.0
ARG25-V0.1
Data
GeoTIFF (7 bands)
GeoTIFF (7 bands)
NetCDF3/4 (OGC, 2013; Unidata,
2012)
Metadata
XML
XML
Quicklook
JPEG (3 bands)
Web Services (including
WMS 1.3.0 and WCS 2.0)
File Format
Data Volume
Page 18 of 23
Surface
Reflectance
Pixel Quality
Surface
Reflectance
Pixel Quality
Per Year
10 Tb
2.4 Tb
tbd
tbd
Per Grid
Block
tbd
tbd
tbd
tbd
Total
Product
110 Tb
26 Tb
tbd
tbd
Geoscience Australia
26 Feb 2013
ARG25 Product Information—Beta Release
Sheet C.3a Pixel Quality Flag
Test Condition
Bit Position
(right to
left)
Pixel Quality Flag Equals 0
if this pixel is
Pixel Quality Flag Equals
1 if this pixel is
Band 1 is saturated
0
Saturated in Band 1
Not saturated in Band 1
Band 2 is saturated
1
Saturated in Band 2
Not saturated in Band 2
Band 3 is saturated
2
Saturated in Band 3
Not saturated in Band 3
Band 4 is saturated
3
Saturated in Band 4
Not saturated in Band 4
Band 5 is saturated
4
Saturated in Band 5
Not saturated in Band 5
Band
6-122
is saturated
5
Saturated in Band 6-1
Not saturated in Band 6-1
Band
6-222
is saturated
6
Saturated in Band 6-2
Not saturated in Band 6-2
Band 7 is saturated
7
Saturated in Band 7
Not saturated in Band 7
Contiguity
8
Null value in at least one band
All bands for this pixel contain
non-null values
Land or Sea23
9
Sea
Land
Cloud (ACCA)24
10
Cloud
No Cloud
(Fmask)25
Cloud
22
23
24
25
26
27
28
29
11
Cloud
No Cloud
Cloud Shadow
(ACCA)26
12
Cloud Shadow
No Cloud Shadow
Cloud Shadow
(Fmask)27
13
Cloud Shadow
No Cloud Shadow
Topographic Shadow28
14
Topographic Shadow
No Topographic Shadow
To be determined29
15
N/A
N/A
This is designed to match Landsat 7 ETM+. The thermal band for Landsat 5 TM corresponds to Band 6-1 and this
value is duplicated in Band 6-2.
Land and sea masking is based on vector data from TM World Borders
(http://thematicmapping.org/downloads/world_borders.php) spliced with Australian Coastal Boundary using a
100m buffer into the sea.
Automatic Cloud Cover Assessment (ACCA) algorithm described in Irish (2000) and Irish et al., (2006).
Function of Mask (Fmask) uses TOAR rather than NBAR as input reflectance
(http://www.sciencedirect.com/science/article/pii/S0034425711003853).
Only computed for cloud detected by ACCA algorithm using in-house algorithm.
Only computed for cloud detected by Fmask algorithm using in-house algorithm.
This feature has not been implemented yet so bit 14 is set to value 0.
Default untested value currently set to 0.
Geoscience Australia
Page 19 of 23
ARG25 Product Information—Beta Release
26 Feb 2013
Sheet C.3b Pixel Quality Flag (examples)
Binary Code (for bits 0 to 15)
15 14 13 12 11 10 9
0
0
0
0
1
0
1
0
0
1
0
1
1
1
8
1
1
7
1
1
6
1
1
5
1
1
4
0
1
3
1
1
2
1
1
1
1
1
0
0
1
Equivalen
t Decimal
value
Code Interpretation
13294
Bands 1 and 5 are saturated (bits 0
and 4 = 0)
No null values (bit 8 = 1)
Land pixel (bit 9 = 1)
Clouds detected by ACCA and
Fmask (bits 10 and 11 = 0)
No cloud shadow
(bits 12 and 13 = 1)
4095
No saturated bands (bits 0–7=1)
No null values (bit 8 = 1)
Land pixel (bit 9 = 1)
No cloud detected
(bits 10 and 11 = 1)
Cloud shadow detected by ACCA
and Fmask
(bits 12 and 13 = 0)
0
0
1
1
0
0
1
1
0
1
1
0
1
1
1
0
13166
Bands 1, 5 and 7 are saturated
(bits 0, 4 and 7 = 0)
No null values (bit 8 = 1)
Land pixel (bit 9 = 1)
Clouds detected by ACCA and
Fmask (bits 10 and 11 = 0)
No cloud shadow
(bits 12 and 13 = 1)
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
16383
Clear Land Pixel—
no saturation, null values, cloud,
or cloud shadow
Page 20 of 23
Geoscience Australia
26 Feb 2013
ARG25 Product Information—Beta Release
Glossary
AATSR
ACCA
ALOS
AMG
ANZLIC
ANU
ARG
ARG25
ARG25PI
Aqua
ASCII
ASTER
ATBD
AVHRR
AVNIR-2
BIL
BSQ
BoM
BRDF
CalVal
CCBY
CF
CRCSI
Advanced Along-Track Scanning Radiometer
Automatic Cloud Cover Assessment (Irish et al., 2006)
Advanced Land Observing Satellite (JAXA, Japan)
Australian Map Grid
Australian and New Zealand Land Information Council
Australian National University
Australian Reflectance Grid
Australian Reflectance Grid 25
ARG25 Product Information
NASA satellite collecting data on Earth's water cycle (USA)
American Standard Code for Information Interchange
Advanced Space-borne Thermal Emission and Reflection Radiometer
Algorithm Theoretical Basis Document
Advanced Very High Resolution Radiometer (NOAA)
Advance Visible and Near Infrared Radiometer type 2
Band Interleaved with Line
Band Sequential
Bureau of Meteorology (Australia)
Bidirectional Reflectance Distribution Function
Calibration and Validation of EO data
Creative Commons By Attribution
Climate and Forecast metadata (for NetCDF)
Cooperative Research Centre for Spatial Information
Commonwealth Scientific and Industrial Research Organisation
CSIRO
(Australia)
DEM
Digital Elevation Model
DSM
Digital Surface Model
ECW
ER Mapper Enhanced Compressed Wavelet
EO
Earth Observation
EOS
Earth Observing System (NASA)
EPSG
European Petroleum Survey Group
ER Mapper ERDAS Image Processing System
ERS
ER Mapper ASCII format for extended metadata in raster header files
ESA
European Space Agency
ETM+
Enhanced Thematic Mapper Plus sensor on board Landsat-7
Fmask
Function of Mask algorithm (see Sheet B.4)
GA
Geoscience Australia
GB
Gigabyte (106 KB)
Geoscience Australia
Page 21 of 23
ARG25 Product Information—Beta Release
26 Feb 2013
GeoTIFF
GSI
IRS-P6
ITRF
JAXA
KB
TIFF with geo-referencing
Ground Sampling Interval
Indian Remote Sensing satellite, also known as RESOURCESAT-1
International Terrestrial Reference Frame
Japan Aerospace Exploration Agency
Kilobyte (210 bytes)
WA Statutory Authority responsible for Land Information and
Landgate
Geographic Data (Australia)
Originally known as the Earth Resource Technology Satellite, renamed in
Landsat
1975 (USA)
LDCM
Landsat Data Continuity Mission (USA)
LUT
Look-Up Table
MB
Megabyte (103 KB)
MGA
Map Grid of Australia
MODIS
MODerate-Resolution Imaging Spectroradiometer (NASA)
Modtran
Atmospheric radiative transfer model
MSS
Multispectral Scanner
NASA
National Aeronautics and Space Administration (USA)
NaviGAtor GA data archive and access facility
NBAR
Nadir BRDF-Adjusted Reflectance
NCEP
National Centres for Environmental Prediction (NOAA, USA)
NCI
National Computational Infrastructure (at ANU)
National Earth Observation group within Geoscience Australia (formerly
NEO
the Australian Centre for Remote Sensing, ACRES)
NetCDF
Network Common Data Form
NNG
National Nested Grid (ANZLIC, 2012)
NOAA
National Oceanic and Atmospheric Administration (USA)
NORAD
North American Aerospace Defence Command (USA)
NPP
National Polar-orbiting Partnership (USA)
OGRE
Optical, Geospatial, Radar and Elevation Supplies and Services Panel
PALSAR
Phased Array type L-band Synthetic Aperture Radar
PRISM
Panchromatic Remote-sensing Instrument for Stereo Mapping
RADAR
RAdio Detection And Ranging
Radarsat
Pair of satellites providing C-band radar data (Canada)
SAR
Synthetic Aperture Radar
SLC
Scan Line Corrector
SRTM
Shuttle RADAR Topography Mission (USA)
SUOMI
Satellite mission replacing EOS satellites (NASA)
NPP
TOAR
Top Of Atmosphere Reflectance
TB
Terabyte (109 KB)
Page 22 of 23
Geoscience Australia
26 Feb 2013
Terra
TIFF
TLE
TM
TOAR
USGS
UTC
UTM
VIIRS
VPAC
WCS
WGS
WMO
WMS
XML
ARG25 Product Information—Beta Release
NASA satellite collecting data on Earth's land processes (USA)
Tagged Image File Format
Two Line Element
Thematic Mapper
Top Of Atmosphere Reflectance
United States Geological Survey (USA)
Universal Time Coordinated
Universal Transverse Mercator
Visible Infrared Imaging Radiometer Suite
Victorian Partnership for Advanced Computing
Web Coverage Service
World Geodetic System
World Meteorological Organisation (UN)
Web Map Service
Extensible Mark-up Language
Geoscience Australia
Page 23 of 23