TERN Geospatial Catalogue
Monthly blended fractional cover - Landsat and Sentinel-2, JRSRP algorithm, Queensland coverage
The monthly fractional cover product shows representative values for the proportion of bare ground, green and non-green ground cover across a month. It is a spatially explicit raster product, which predicts vegetation cover at medium resolution (30 m per-pixel) for each month. This dataset consists of medoid-composited monthly fractional cover created from a combined Landsat 8 and Sentinel-2 time series.
Simple
Identification info
- Date (Creation)
- 2017-01-31
- Date (Publication)
- 2021-04-15
- Date (Revision)
- 2021-03-30
- Edition
- 1.0.0
Publisher
Author
Rights holder
- Website
- https://www.tern.org.au/
- Purpose
- This product captures variability in fractional cover at monthly time scales, forming a consistent time series from 2015 - present. It is useful for investigating more rapid changes than the three-month seasonal products. For example, the monthly dataset is used by the Queensland pastoral industry for improved monitoring of drought conditions. The green and non-green fractions may include a mix of woody and non-woody vegetation. For applications investigating long-term dynamics, the three-month seasonal product may be more appropriate. Note: A new fractional cover algorithm will be implemented during 2021, based on additional field validation and a new machine learning approach.
- Credit
- This dataset was produced by the Joint Remote Sensing Research Program using data sourced from US Geological Survey and the European Space Agency.
- Status
- On going
Point of contact
Department of Environment and Science, Queensland Government - van den Berg, Deanna ()
Ecosciences Precinct, 41 Boggo Road
GPO Box 378
Dutton Park
QLD
4102
Australia
Spatial resolution
- Level of detail
- 30 meters - < 100 meters
- Topic category
-
- Environment
Extent
- Description
- Queensland, Australia
N
S
E
W
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Temporal extent
- Time period
- 2015-12-01
- Title
- Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500; doi:10.3390/rs5126481
- Website
-
Flood, N. (2013) Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-dimensional Median). Remote Sens. 2013, 5(12), 6481-6500; doi:10.3390/rs5126481
Related documentation
- Title
- Zhu, Z. and Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery Remote Sensing of Environment 118.
- Website
-
Zhu, Z. and Woodcock, C.E. (2012). Object-based cloud and cloud shadow detection in Landsat imagery Remote Sensing of Environment 118.
Related documentation
- Title
- Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013) An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sens. 2013
- Website
-
Flood, N., Danaher, T., Gill, T. and Gillingham, S. (2013) An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sens. 2013
Related documentation
- Title
- Beutel Terrence S. et al (2019) VegMachine.net. online land cover analysis for the Australian rangelands. The Rangeland Journal 41
- Website
-
Beutel Terrence S. et al (2019) VegMachine.net. online land cover analysis for the Australian rangelands. The Rangeland Journal 41
Related documentation
- Title
- Sentinel 2 Level 1C Processing
- Website
-
Sentinel 2 Level 1C Processing
Related documentation
- Title
- Flood, N. (2017) Comparing Sentinel-2A and Landsat 7 and 8 Using Surface Reflectance over Australia. Remote Sens. 9, no. 7
- Website
-
Flood, N. (2017) Comparing Sentinel-2A and Landsat 7 and 8 Using Surface Reflectance over Australia. Remote Sens. 9, no. 7
Related documentation
- Title
- Sentinel 2 Data Product Quality Reports
- Website
-
Sentinel 2 Data Product Quality Reports
Related documentation
- Title
- Fractional vegetation cover from Sentinel-2
- Website
-
Fractional vegetation cover from Sentinel-2
Related documentation
- Maintenance and update frequency
- Monthly
- TERN Platform Vocabulary
- TERN Instrument Vocabulary
- Keywords
- Keywords
- Keywords
- Keywords
- GCMD Earth Science and Earth Science Services Keywords
- Temporal Resolution
- ANZSRC Fields of Research
- Keywords (dataResolution)
Resource constraints
- Use limitation
- The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/
- File name
- 88x31.png
- File description
- CCBy Logo from creativecommons.org
- File type
- png
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 4.0
- Access constraints
- License
- Use constraints
- Other restrictions
- Other constraints
- TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure. <br/>Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN. <br /><br />Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting
- Other constraints
- Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.
- Other constraints
- It is not recommended that these data sets be used at scales more detailed than 1:100,000.
Resource constraints
- Classification
- Unclassified
Distribution Information
Distributor
Distributor
- OnLine resource
-
aus:monthly_fractional_cover
Web Map Service
Distribution Information
Distributor
Distributor
- OnLine resource
-
Vegmachine Timeseries Viewer
Vegmachine Timeseries Viewer
Distribution Information
Distributor
Distributor
- OnLine resource
-
Monthly fractional cover for Queensland
Monthly fractional cover for Queensland
Distribution Information
Distributor
Distributor
- OnLine resource
-
band_descriptions_and_filenaming_convention-v01.txt
Information
Data quality info
- Hierarchy level
- Dataset
- Other
- 1) All the data described here has been generated from the analysis of Level 1A Landsat OLI and Sentinel Level 1C (see Publications: Flood (2017)). 2) The seasonal fractional cover model output was compared to 1500 field sites.
Report
Result
- Statement
- 1) The Sentinel-2 Data Quality Report from ESA indicates that positional accuracy is on the order of 12 m. The USGS aims to provide Landsat image-to-image registration with an accuracy of 12m. 2) The fractional cover model (based on Landsat) achieved an overall model Root Mean Squared Error (RMSE) of 11.6% against field reference sites.
Resource lineage
- Statement
- Summary of processing: Landsat 8/Sentinel-2 surface reflectance data > multiple single-date fractional cover datasets > monthly composite of fractional cover <br />Further details are provided in the Methods section.
- Hierarchy level
- Dataset
Process step
- Description
- Landsat 8 imagery rated as less than 80% cloud cover was downloaded from the USGS EarthExplorer website as level L1T imagery. Sentinel-2A data was downloaded from the ESA as Level 1C (version 02.04 system). Masks for cloud, cloud shadow, topographic shadow and water were applied as described in Flood (2017).
- Title
- Image preprocessing
Process step
- Description
- The bare soil, green vegetation and non-green vegetation endmembers for the blended Landsat 8 and Sentinel 2 are calculated using models developed for seasonal fractional cover across Australia. Values are reported as percentages of cover plus 100. The fractions stored in the 4 image layers are: Band1 - bare (bare ground, rock, disturbed), Band2 - green vegetation, Band3 - non green vegetation (litter, dead leaf and branches), Band4 - Model fitting error.
- Title
- Fractional Cover Model
Process step
- Description
- The method of compositing used selection of representative pixels through the determination of the medoid (multi-dimensional equivalent of the median) of at least three observations of fractional cover imagery. The medoid is the point which minimises the total distance between the selected point and all other points. Thus the selected point is “in the middle” of the set of points. It is robust against extreme values, inherently avoiding the selection of outliers, such as occurs when cloud or cloud shadow goes undetected. Unfortunately, due to the high level of cloud cover in some areas, often three cloud free pixels are not available, resulting in data gaps in the seasonal fractional cover image. For further details on this method see Flood (2013).
- Title
- Data compositing
Reference System Information
- Reference system identifier
- EPSG/GDA94 / Australian Albers (EPSG:3577)
Metadata
- Metadata identifier
-
urn:uuid/2d52273c-115a-41ca-88f3-d70fb7b8e831
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/2d52273c-115a-41ca-88f3-d70fb7b8e831
Point-of-truth metadata URL
- Date info (Creation)
- 2008-11-12T00:00:00
- Date info (Revision)
- 2021-04-15T03:59:33
Metadata standard
- Title
- ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
- Edition
- 1
Metadata standard
- Title
- ISO/TS 19115-3:2016
- Edition
- 1.0
Metadata standard
- Title
- ISO/TS 19157-2:2016
- Edition
- 1.0
- Title
- Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
- Date (published)
- 2021
- Edition
- 1.0
Identifier
Overviews
Spatial extent
N
S
E
W
Provided by
Associated resources
Not available