DEA Fractional Cover Percentiles (Landsat)

Geoscience Australia Landsat Fractional Cover Percentiles Collection 3

Version:: 4.0.0 (Latest)
Product types:: Derivative, Raster
Time span:: 1987 – Present
Update frequency:: Yearly
Product ID:: ga_ls_fc_pc_cyear_3

Overview

About

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 version includes breaking changes

All tile grid references have been changed to refer to a new origin point. Learn more in the Version 4.0.0 changelog.

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For help accessing the data, see the Access tab.

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Key details

Parent product(s)	DEA Fractional Cover (Landsat)
Collection	Geoscience Australia Landsat Collection 3
Persistent ID	145501
Licence	Creative Commons Attribution 4.0 International Licence

Cite this product

Data citation

Lymburner, L., 2021. Geoscience Australia Landsat Fractional Cover Percentiles Collection 3. Geoscience Australia, Canberra. https://pid.geoscience.gov.au/dataset/ga/145501

Paper citation

Scarth, P., Roder, A., 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. http://dx.doi.org/10.6084/M9.FIGSHARE.94250

Publications

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.

Details

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.

Fractional Cover Percentiles (Landsat) estimate the 10th, 50th, and 90th percentiles independently for the green vegetation, non-green vegetation, and bare soil fractions observed in each calendar year.

Percentiles provide an indicator of where an observation sits, relative to the rest of the observations for the pixel. For example, the 90th percentile is the value below which 90% of the observations fall. Because the percentiles are estimated independently for the three cover types, the 10th percentiles represent the low end of the measurements for the three covers, which may have been observed at different times of a year. Similarly, the 90th percentiles represent the high end of the measurements for the three covers, which may have occurred at different times.

The 10th, 50th, and 90th percentiles represent low, median and high values in a distribution that are robust against outliers. These values can be used separately or combined to understand the land cover dynamics. For example, the three percentiles for the green cover fraction can serve as proxies for the minimum, typical and maximum green cover for a given year. Difference between the 10th and 90th percentiles provides an estimate of the magnitude of change within a year. A large range of values may be observed in the agricultural land for all cover types while high green cover and a small difference between 10th and 90th percentiles are expected for forest cover.

A representative view of the landscape in a year can be obtained by combining the 50th percentiles, or the median values, for the three cover types.

What this product offers

It includes cloud and cloud shadow buffering with a size of 6 pixels. This buffering is applied to Landsat 5, Landsat 7, Landsat 8, and Landsat 9 data.

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

Technical information

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.

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 only
1999 : Landsat 5 and Landsat 7
2000-2002 : Landsat 7 only
2003 : Landsat 5 and Landsat 7
2004-2010 : Landsat 5 only
2011-2012 : Landsat 7 only
2013-2021 : Landsat 8 only
2022 onwards: Landsat 8 and Landsat 9

The values for this product are 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%

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

Family name : DEA Fractional Cover Percentiles

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

Quality Assurance:

This layer provides a breakdown of each FCP pixel between,

sufficient observations
insufficient observations dry
insufficient observations wet

For insufficient observations, these are pixels that have been masked out of the percentiles results e.g. NODATA, and provides an explanation as to why they have been masked out.

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

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 have a geometric quality assessment of greater than one, which occurs when there is poor geometric quality.
The DEA Water Observation has the following characteristics:
- It is contiguous (data for all bands is present and valid)
- 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

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.

It will have a directory structure of form:

/ga_ls_fc_pc_cyear_3/4-0-0/x25/y41/1999--P1Y/ga_ls_fc_pc_cyear_3_x25y41_1999--P1Y_final_bs_pc_10.tif

Lineage

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.

Processing steps

The Fractional Cover Percentile odc-statistician plugin can be found in Fractional Cover Percentiles Code Repository.

The processing steps are:

Fractional Cover and Water Observations Daily scenes are loaded for the calender year
Pixels for each time step are masked out that are not clear and dry or are wet, and a cloud and cloud shadow dilation of 6 pixels is applied
Fractional cover percentiles are calculated - noting results are not filtered by an unmixing error threshold

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.

Quality

Accuracy

Refer to DEA Fractional Cover for more information on the accuracy assessment of the daily scenes.

Quality assurance

QA enumeration

To assist with the downstream calculation of the DEA Mangroves 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 DEA Mangroves (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

Access

Access the data

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Get the data online	Digital Earth Australia - Public Data on AWS Digital Earth Australia - Public Data on NCI	Learn how to access the data via AWS
Code sample	Data explorer	Learn how to use the DEA Sandbox

History

Old versions

View previous versions of this data product.

3.0.0: DEA Fractional Cover Percentiles (Landsat)

2.2.1: DEA Fractional Cover Percentiles (Landsat)

Changelog

Version 4.0.0

Breaking change: Shift in grid origin point — The south-west origin point of the DEA Summary Product Grid has been shifted 18 tiles west and 15 tiles south. Therefore, all tile grid references have been changed. For instance, a tile reference of x10y10 has changed to x28y25. The tile grid references of all derivative products generated from 2024 onwards will also be changed; however, Analysis Ready Data products will not be affected.
Enhanced cloud masking to reduce noise — An enhancement to cloud masking has reduced cloud and shadow noise. This enhancement (known as ‘cloud buffering’) involved cleaning cloud masks using a 6-pixel dilation on cloud and shadows. Note that some areas of very high surface reflectance (e.g. sand dunes and ocean areas) may exhibit worsened noise or data gaps, but these are infrequent occurrences with low impact.
Landsat 9 product — Landsat 9 is processed from 2022 onwards.

Credits

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, the Australian Bureau of Agricultural and Resource Economics (ABARES) and State and Territory governments to collect additional calibration data has enabled the calibration to extend to the entire Australian continent. Fractional Cover 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.

License and copyright

Released under Creative Commons Attribution 4.0 International Licence.