Fractional Cover - MODIS, CSIRO algorithm
Vegetation Fractional Cover represents the exposed proportion of Photosynthetic Vegetation (PV), Non-Photosynthetic Vegetation (NPV) and Bare Soil (BS) within each pixel. The sum of the three fractions is 100% (+/- 3%) and shown in Red/Green/Blue colors. In forested canopies the photosynthetic or non-photosynthetic portions of trees may obscure those of the grass layer and/or bare soil. This product is derived from the MODIS Nadir BRDF-Adjusted Reflectance product (MCD43A4) collection 6 and has 500 meters spatial resolution. A suite of derivative products are also produced including monthly fractional cover, total vegetation cover (PV+NPV), and anomaly of total cover against the time series. Monthly: The monthly product is aggregated from the 8-day composites using the medoid method. Anomaly: represents the difference between total vegetation cover (PV+NPV) in a given month and the mean total vegetation cover for that month in all years available, expressed in units of cover. For example, if the mean vegetation cover in January (2001-current year) was 40% and the vegetation cover for the pixel in January 2018 was 30%, the anomaly for the pixel in Jan 2018 would be -10%. Decile: represents the ranking (in ten value intervals) for the total vegetation cover in a given month in relation to the vegetation cover in that month for all years in the time-series. MODIS fractional cover has been validated for Australia.
Simple
Identification info
- Date (Creation)
- 2019-11-11
- Date (Publication)
- 2020-03-10
- Date (Revision)
- 2025-12-10
- Edition
- 1.0
Publisher
Author
CSIRO Land and Water (2014-2022) - Guerschman, Juan Pablo (Senior Research Scientist)
147 Underwood Avenue, Floreat, Western Australia, 6014, Australia
Floreat
Western Australia
6014
Australia
- Website
- https://www.tern.org.au/
- Purpose
- This project will bring the enhancements to the ground cover monitoring tool (the RaPP Map) needed to assist in enabling the NRM agencies and individuals to undertake monthly reporting on ground cover level change. Proposed enhancements include: Continuity of the tool data quality increase the number of outputs required by NRMs improve the functionality as determined by the users This project is closely aligned with the Ground cover training and target setting (GTTS) project being proposed by John Leys from the NSW OEH which focuses on the training in the use of the tool to NRM agencies. This project is also contributing to the international engagement via the GEOGLAM initiative which aims at improving the information on agricultural productivity.
- Credit
- We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
- Credit
- Funding was provided by CSIRO (Australia), Terrestrial Ecosystem Research Network (TERN) (Australia), and the Australian Government Department of Agriculture.
- Status
- On going
Point of contact
CSIRO Land and Water (2014-2022) - Guerschman, Juan Pablo (Senior Research Scientist)
147 Underwood Avenue, Floreat, Western Australia, 6014, Australia
147 Underwood Avenue
Floreat
Western Australia
6014
Australia
- Topic category
-
- Imagery base maps earth cover
Extent
- Description
- Global dataset on fractional cover, CSIRO algorithm.
N
S
E
W
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Temporal extent
- Time period
- 2001-01-01
- Title
- Guerschman, J. P., & Hill, M. J. (2018). Calibration and validation of the Australian fractional cover product for MODIS collection 6. Remote Sensing Letters, 9(7), 696–705.
- Website
-
Guerschman, J. P., & Hill, M. J. (2018). Calibration and validation of the Australian fractional cover product for MODIS collection 6. Remote Sensing Letters, 9(7), 696–705.
Related documentation
- Title
- Guerschman et al (2015). Assessing the effects of site heterogeneity and soil properties when unmixing photosynthetic vegetation, non-photosynthetic vegetation and bare soil fractions from Landsat and MODIS data. Remote Sensing of Environment
- Website
-
Guerschman et al (2015). Assessing the effects of site heterogeneity and soil properties when unmixing photosynthetic vegetation, non-photosynthetic vegetation and bare soil fractions from Landsat and MODIS data. Remote Sensing of Environment
Related documentation
- Title
- Gill, T., Heidenreich, S. and Guerschman, J (2014). MODIS monthly fractional cover: product creation and distribution. The Joint Remote Sensing Research Program Publication Series. St. Lucia, QLD, Australia: The University of Queensland.
- Website
-
Gill, T., Heidenreich, S. and Guerschman, J (2014). MODIS monthly fractional cover: product creation and distribution. The Joint Remote Sensing Research Program Publication Series. St. Lucia, QLD, Australia: The University of Queensland.
Related documentation
- Title
- Flood, N. (2013). Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median). Remote Sensing 5, 6481–6500.
- Website
-
Flood, N. (2013). Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median). Remote Sensing 5, 6481–6500.
Related documentation
- Title
- README file - additional detail including the naming convention for the data files
- Website
-
README file - additional detail including the naming convention for the data files
Related documentation
- Maintenance and update frequency
- Monthly
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Platform Vocabulary
- TERN Instrument Vocabulary
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Temporal Resolution Ranges
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}.
Resource constraints
- Classification
- Unclassified
Distribution Information
- Distribution format
-
Distributor
Distributor
National Computational Infrastructure, Australian National University
10 East Road, Acton, 2601, Australian Capital Territory, Australia
Acton
Australian Capital Territory
2601
Australia
- OnLine resource
- NCI Thredds Server
- OnLine resource
-
modis_tot_cov_monthly
WMS Service for Total Fractional Cover
Distribution Information
- Distribution format
-
Distributor
Distributor
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
- OnLine resource
- GEOGLAM RAPP map (includes WMS sources)
- OnLine resource
- CSIRO Project Site
- OnLine resource
- ro-crate-metadata.json
Data quality info
- Hierarchy level
- Dataset
- Other
- Version 3.0: Fractional cover was derived using a linear unmixing methodology (Guerschman et al. 2015). The method uses all 7 MODIS bands and adds log transforms and band interaction terms to account for non-linearities in the spectral mixing. A cross-validation step was also included to select the optimal number of singular values to avoid over-fitting. The calibration and validation steps used 1171 field observations across Australia.
Report
Result
- Statement
- Overall, the model fitted and applied to MCD43A4 fractional cover has a root mean square error (RMSE) of 12.9%, 18.1% and 16.6% for the PV, NPV and BS fractions respectively (percentage cover) Version 3.1: ("v310") Same as Version 3.0 with the following modifications: 1- input data changed to MODIS Collection 6.0 (MCD43A4.006) (see source). 2- calibration dataset expanded to include ~3022 field measurement sites accross Australia. 3- overall accuracy improved to an RMSE of 11.3%, 16.1% and 14.7% for the PV, NPV and BS fractions respectively.
Resource lineage
- Statement
- Monthly vegetation cover is calculated from the 8-day composites using a medoid method as described in Gill et al. Monthly anomalies show the difference between total vegetation cover (PV+NPV) in a given month and the mean total vegetation cover for that month in all years available\nMonthly deciles show the decile (ranking) for the total vegetation cover in a given month in relation to the vegetation cover in that month for all years in the time series. Version 3.0: Fractional cover was derived using a linear unmixing methodology (Guerschman et al. 2015). Version 3.1: ("v310") Same as Version 3.0 with the following modifications: 1- input data changed to MODIS Collection 6.0 (MCD43A4.006) (see source). 2- calibration dataset expanded to include ~3022 field measurement sites accross Australia. 3- overall accuracy improved to an RMSE of 11.3%, 16.1% and 14.7% for the PV, NPV and BS fractions respectively.
- Hierarchy level
- Dataset
Process step
- Description
- Time Period Composition Mediod Method: The medoid is a multi-dimensional analogue of the median. It can be applied to creating a time-period composite of images, for example a seasonal composite, by selecting a single date for each pixel that minimizes the sum of the distances to the band pixel values of all other dates in the set. Source: Flood, N. (2013). Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median). https://doi.org/10.3390/rs5126481
Process step
- Description
- Linear Spectral Unmixing Method: Spectral unmixing is the process of decomposing the spectral signature of a mixed pixel into a set of endmembers representing the types of objects present in the pixel, and their corresponding abundances. Source: Shi, C., & Wang, L. (2014). Incorporating spatial information in spectral unmixing: A review. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2014.03.034
Reference System Information
- Reference system identifier
- EPSG/EPSG:4326
- Reference system type
- Geodetic Geographic 2D
Metadata
- Metadata identifier
-
urn:uuid/a6ef2480-e397-4c42-9706-3865dd6ca380
- 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/a6ef2480-e397-4c42-9706-3865dd6ca380
Point-of-truth metadata URL
- Date info (Creation)
- 2019-11-11T00:00:00.000000+00:00
- Date info (Revision)
- 2025-12-10T10:32:18.693357+00:00
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
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Provided by
Associated resources
Not available