DEA Fractional Cover Percentiles (Landsat)

Background

The Fractional Cover (Landsat) product, developed by the Joint Remote Sensing Research Program, provides information about the the proportions of:

green vegetation
non-green vegetation (including deciduous trees during autumn and dry grass)
bare areas

for every 30m x 30m ground footprint.

It provides insight into how areas of dry vegetation and/or bare soil and green vegetation are changing over time.

It is important to be able to analyse and interpret fractional cover. For example, the 90th percentile of bare soil for a particular year will identify areas that have experienced a high portion of bare soil during that year.

What this product offers

This product is designed to make it easier to analyse and interpret fractional cover. It uses the Fractional Cover (Landsat) product and calculates the statistical summaries (10th, 50th and 90th percentile) of fractional cover per epoch (annual).

This product is available in the following form:

FC-PERCENTILE-ANNUAL-SUMMARY

This contains a (10th, 50th and 90th percentile) of bare, green and non-green vegetation of observations acquired in each full calendar year (1st of January - 31st December) from 1987 to the most recent full calendar year.

Applications

This product provides valuable information for a range of environmental and agricultural applications, including:

soil erosion monitoring
land surface process modelling
land management practices (e.g. crop rotation, stubble management, rangeland management)
vegetation studies
fuel load estimation
ecosystem modelling

Data access

Product ID	ga_ls_fc_pc_cyear_3
Link to data	Digital Earth Australia - Public Data
Link to maps	DEA Maps
eCat record	145501
CMI RESTful node ID	630
Security classification	Unclassified
Update frequency	asNeeded

Access notes

DEA Maps

To view and access the data interactively:

1) Visit DEA Maps.

2) Click 'Explore map data'.

3) Select 'Vegetation' > 'Fractional Cover'.

4) Select which Percentile products you would like to display (seasonal, annual, green, non-green, bare earth) and click 'Add'.

5) Chose the Percentile (10th, 50th, 90th) from the drop down Styles menu

Technical information

This product provides continental composites for each cover fraction.

The percentile ranges for each compositing period can be used to identify the 'greenest' observation i.e. 90th percentile of green cover and 'barest' observation i.e. 90th percentile of bare soil that occurred within the compositing period.

The 10th and 90th percentile are used in preference to the minimum and maximum values because they are less prone to residual noise associated with undetected cloud/cloud shadow. The 50th percentile (median) are used in preference to the mean as the median is less prone to being skewed by extreme values. It is worth noting that some undetected cloud and cloud shadow artefacts may still be present in the 10th and 90th percentiles, especially in areas with frequent cloud cover such as the wet tropics and Tasmania.

To account for satellite availability and status the statistics are calculated using the following satellites for the following periods of time:

1987-1998 : Landsat 5
1999 : Landsat 5 and Landsat 7
2000-2002 : Landsat 7
2003 : Landsat 5 and Landsat 7
2004-2010 : Landsat 5
2011-2012 : Landsat 7
2013 onward : Landsat 8

The values for this product are scaled as follows:
For the fractional cover bands (PV, NPV, BS)
0-100 = fractional cover values that range between 0 and 100%

Due to model uncertainties and the limitations of the training data, some areas may show cover values in excess of 100%. These areas can either be excluded or treated as equivalent to 100%

For the unmixing error (UE) band, the values are scaled between 0 and 127. High unmixing error values represent areas of high model uncertainty (areas of water, cloud, cloud shadow or soil types/colours that were not included in the model training data).

The DEA Landsat Collection 3 Fractional Cover Percentiles Summary products share the following attributes:

Each product will share the following name:

Family name : DEA Fractional Cover Percentiles

Each product will have the following bands: data type, nodata values, purpose

bs_pc_10 : uint8, nodata 255, bare soil 10th percentile
pv_pc_10 : uint8, nodata 255, photosynthetic veg 10th percentile
npv_pc_10 : uint8, nodata 255, non-photosynthetic veg, 10th percentile
bs_pc_50 : uint8, nodata 255, bare soil, 50th percentile
pv_pc_50 : uint8, nodata 255, photosynthetic veg, 50th percentile
npv_pc_50 : uint8, nodata 255, non-photosynthetic veg, 50th percentile
bs_pc_90 : uint8, nodata 255, bare soil, 90th percentile
pv_pc_90 : uint8, nodata 255, photosynthetic veg, 90th percentile
npv_pc_90 : uint8, nodata 255, non-photosynthetic veg, 90th percentile
qa : uint8, nodata 255, Quality Assurance enumeration - see below for details

Each product’s datasets will:

be divided into tiles of 3200 x 3200 pixels, with a pixel size of 30m^2
be presented in EPSG:3577

Percentiles

10th, 50th and 90th Percentiles are calculated per Fractional Cover measurement - Bare Soil, Photosynthetic Vegetation, Non-Photosynthetic Vegetation. DEA Fractional Cover C3 and DEA Water Observations C3 are used as the input to these products.

Fractional Cover Masking

DEA Water Observations are used to identify clear pixels from DEA Fractional Cover to be included in percentile calculation. A Fractional Cover observation is included if:

It has corresponding DEA Water Observation information. If an observation within DEA Fractional Cover has no corresponding Water Observation, it is discarded. This can happen for ARD scenes that do not meet the GQA threshold for Water Observation generation.
The DEA Water Observation has the following characteristics:
It is contiguous
It is not saturated
It is not cloud
It is not cloud shadow
It is not terrain shadow
It is not low solar angle
It can be high slope
It is not wet
There are at least 3 clear and dry observations for the time period.
Please note, no land/sea masking is applied
Observation dates for given percentiles are not captured

QA enumeration

To assist with the calculation of the Mangrove Canopy Cover product, each pixel has an additional enumeration associated with it:

0 - Not enough observations to calculate percentiles (less than 3 clear and dry observations), and there is at least one observation that has been identified as wet. Defined in ODC configuration as: insufficient observations wet.
1 - Not enough observations to calculate percentiles (less than 3 clear and dry observations), but never identified as wet. Defined in ODC configuration as: insufficient observations dry.
2 - There are sufficient observations to compute percentiles (3 or more clear and dry observations). Defined in ODC configuration as: sufficient observations

This enumeration assists in quantifying uncertainty within the Mangrove Canopy Cover product (see Mangrove Canopy Cover definition).

Side car files

Collection 3 Fractional Cover Percentiles will be accompanied by the following metadata, presentation and quality assurance side car files:

*.odc-metadata.yaml : EODatasets 3 compatible ODC dataset definition
*.odc-proc-info.yaml : Listing of python libraries and versions used by software to generate
*.sha1 : cryptographic hash of data to validate distributed data
*.thumbnail.jpg : quick look thumbnail of a scaled RGB rendering of R = bs_pc_50, G= pv_pc_50 and B = npv_pc_50
*.stac-item.json : STAC 1.0.0 STAC document

Geoscience Australia Landsat Fractional Cover Percentile Calendar Year Collection 3

Temporal period

Will be calculated from the 1st of January to the 31st of December (inclusive) for every available year of DEA Landsat Collection 3 Water Observations and DEA Landsat Collection 3 Fractional Cover observations.

Names

Geoscience Australia Landsat Fractional Cover Percentile Calendar Year Collection 3 will have the following names:

Full Product / Web service name

Geoscience Australia Landsat Fractional Cover Percentile Calendar Year Collection 3

ODC Product ID

ga_ls_fc_pc_cyear_3

Short name

Fractional Cover Percentiles Calendar Year (Landsat)

It will have a directory structure of form:

/ga_ls_fc_pc_cyear_3/3-0-0/x01/y02/2000--P1Y/ga_ls_fc_pc_cyear_3_x01y02_2000--P1Y_bs_pc_10.tif

References

Flood, N. (2014). Continuity of reflectance data between Landsat-7 ETM+ and Landsat-8 OLI, for both top-of-atmosphere and surface reflectance: A study in the Australian landscape. Remote Sensing, 6(9), 7952–7970. https://doi.org/10.3390/rs6097952

Muir, J., Schmidt, M., Tindall, D., Trevithick, R., Scarth, P. and Stewart, J.B. (2011). Guidelines for field measurement of fractional ground cover: a technical handbook supporting the Australian Collaborative Land Use and Management Program. Queensland Department of Environment and Resource Management for the Australian Bureau of Agricultural and Resource Economics and Sciences.

Scarth, P., Roder, A. and Schmidt, M. (2010). Tracking grazing pressure and climate interaction - the role of Landsat fractional cover in time series analysis. Proceedings of the 15th Australasian Remote Sensing & Photogrammetry Conference.

Schmidt, M., Denham, R. and Scarth, P. (2010), Fractional ground cover monitoring of pastures and agricultural areas in Queensland. Proceedings of the 15th Australasian Remote Sensing & Photogrammetry Conference.

Lineage

Nationally consistent information about fractional cover (FC) dynamics is essential to addressing a range of natural resource challenges. These include land management practices, air quality, soil erosion, rangeland condition and soil carbon dynamics.

The fractional cover algorithm was developed by the Joint Remote Sensing Research Program (JRSRP) and is described in Scarth et al. (2010). While originally calibrated in Queensland, a large collaborative effort between The Department of Agriculture - ABARES and State and Territory governments to collect additional calibration data has enabled the calibration to extend to the entire Australian continent.

FC was made possible by new scientific and technical capabilities, the collaborative framework established by the Terrestrial Ecosystem Research Network (TERN) through the National Collaborative Research Infrastructure Strategy (NCRIS), and collaborative effort between state and Commonwealth governments.

The long term acquisition plan supported by the Landsat program, in combination with Geoscience Australia's longstanding investment in the on-ground infrastructure required to capture Landsat imagery has made this product possible. Geoscience Australia's partnership with the National Computing Infrastructure (NCI) facilities in conjunction with the development of the Australian Geoscience Data Cube - a high performance data framework - makes it possible to analyse the continental archive of fractional cover data.

FC-PERCENTILE provides a consistent summary of fractional cover which will be an important foundation for land cover mapping and monitoring across Australia. It is a resource for natural resource managers, land surface process modellers, carbon modellers, rangeland managers, ecosystem scientists and policy makers.

Data sources

Processing steps

Fractional Cover Processing

Major algorithms

Fractional Cover Processing

Schema / spatial extent

Geoscience Australia Landsat Collection 3

Update frequency	asNeeded
Temporal extent	1987-01-01 00:00:01
Coordinate reference system	Universal Transverse Mercator (variable)
Cell size X	30.00
Cell size Y	30.00

Owner

Commonwealth of Australia (Geoscience Australia)

Subject matter experts

Leo Lymburner

License

CC BY Attribution 4.0 International License

Rights statement

Acknowledgments

Landsat data is provided by the United States Geological Survey (USGS) through direct reception of the data at Geoscience Australias satellite reception facility or download. The fractional cover algorithm was developed by the Joint Remote Sensing Research Program (JRSRP) and is described in Scarth et al. (2010). While originally calibrated in Queensland, a large collaborative effort between The Department of Agriculture & ABARES and State and Territory governments to collect additional calibration data has enabled the calibration to extend to the entire Australian continent. FC_25 was made possible by new scientific and technical capabilities, the collaborative framework established by the Terrestrial Ecosystem Research Network (TERN) through the National Collaborative Research Infrastructure Strategy (NCRIS), and collaborative effort between state and Commonwealth governments.

Basics