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Product pages » Fractional cover - MODIS, CSIRO Land and Water algorithm, Australia and global coverage

Fractional cover - MODIS, CSIRO Land and Water algorithm, Australia and global coverage

Last modified by Matt Paget on 2016/08/12 17:38

Fractional cover - MODIS, CSIRO Land and Water algorithm, Australia and global coverage

Fig 1. Australia coverage Fractional cover, Total cover and monthly Anomaly for January 2016.

Fig 2. Global coverage Fractional cover, Total cover and monthly Anomaly for January 2016.

Link to the data


DescriptorData link
Persistent URL
GeoNetwork record - Australia
HTTP (netCDF and Geotiff)
FTP (netCDF and Geotiff)


DescriptorData link
Persistent URL
GeoNetwork record - global
HTTP (netCDF and Geotiff)
FTP (netCDF and Geotiff)

Data licence and Access rights

RightsCopyright 2008-2016 CSIRO. Rights owned by the Commonwealth Scientific and Industrial Research Organisation (CSIRO). Rights licensed subject to Creative Commons Attribution (CC BY).
LicenceCreative Commons Attribution 4.0 License,
AccessThese data can be freely downloaded and used subject to the CC BY licence. Attribution and citation is required as described at We ask that you send us citations and copies of publications arising from work that use these data.

Abstract or Summary

Vegetation fractional cover represents the exposed proportion of Photosynthetic Vegetation (PV), Non-Photosynthetic Vegetation (NPV) and Bare Soil (BS) within each pixel. In forested canopies the photosynthetic or non-photosynthetic portions of trees may obscure those of the grass layer and/or bare soil. The MODIS Fractional Cover product is derived from the MODIS Nadir BRDF-Adjusted Reflectance (NBAR) product (MCD43A4, collection 5). A suite of derivative products are also produced including total vegetation cover (PV+NPV), monthly fractional cover and total vegetation cover, monthly anomaly of total cover against the time series, and monthly ground cover as total cover minus an estimate of tree cover. MODIS fractional cover has been validated for Australia. A global product is also produced with the same algorithm using the global NBAR product MCD43C1 (collection 5, 0.05 degrees spatial resolution).

Spatial and Temporal extents


Spatial resolution (metres)500 m
Spatial coverage (degrees)110 to 155 E, -10 to -45 N
Temporal resolution8 day, 1 month
Temporal coverage2000-02 to ongoing
Sensor & platformMODIS Terra & Aqua
Spatial representation typegrid
Spatial reference systemWGS84


Spatial resolution (metres)0.05 deg
Spatial coverage (degrees)-180 to 180 E, -90 to 90 N
Temporal resolution8 day, 1 month
Temporal coverage2000-02 to ongoing
Sensor & platformMODIS Terra & Aqua
Spatial representation typegrid
Spatial reference systemMODIS Sinusoidal

Point of contact

NameDr. Juan Guerschman
OrganisationCSIRO Land and Water


This dataset has been developed by the Environmental Earth Observation Group, CSIRO Land and Water. This work has been partially supported by a NASA Earth Science Enterprise Carbon Cycle Science research program (NRA04-OES-01).


FoREnvironmental Sciences > Ecological Applications = 0501

There are three main thesauri that AusCover recommends:

  1. Global Change Master Directory (
  2. Climate and Forecast (CF) convention standard names (
  3. Fields of Research codes (

Data quality

The quality of the fractional cover product is dependant on the quality of the MODIS NBAR data, and subject to uncertainties and bias as described in Guerschman et al. (2009). The phased production strategy (i.e. producing a 16-day composite every 8 days, for collection 5) and the combination of the Terra and Aqua sensors enhances the chances of obtaining enough cloud-free data for each pixel in each date compared to the MODIS NBAR collection 4 product. However, there are still areas with poor data availability, notably in the tropical areas during the monsoonal rains (November to April). 

Validation status

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. 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). 

Related products

ItemProduct link
MODIS Land Products for Australia
Australian Ground Cover Reference Sites


ItemDetail or link
PublicationJuan Pablo Guerschman, Michael J. Hill, Luigi J. Renzullo, Damian J. Barrett, Alan S. Marks, Elizabeth J. Botha (2009). Estimating fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil in the Australian tropical savanna region upscaling the EO-1 Hyperion and MODIS sensors Remote Sensing of Environment, Volume 113, Issue 5, pp. 928-945.
Validation reportGuerschman, JP, Oyarzabal, M, Malthus, TJ, McVicar, TM, Byrne, G, Randall, LA and Stewart, JB (2012), Validation of the MODIS-based vegetation fractional cover product, CSIRO Land and Water Science Report, Canberra, April 2012.
PublicationJuan P. Guerschman, Peter F. Scarth, Tim R. McVicar, Luigi J. Renzullo, Tim J. Malthus, Jane B. Stewart, Jasmine E. Rickards, Rebecca Trevithick (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, Volume 161, pp. 12–26.
Data ReferencePaget, M.J., & King, E.A. (2008). MODIS Land data sets for the Australian region. CSIRO Marine and Atmospheric Research Internal Report No. 004. 96pp. In. Canberra, Australia: CSIRO.
Method ReferenceFlood, N. (2013). Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median). Remote Sensing, 5(12), pp6481–6500.

Algorithm summary

Source data are derived from the MODIS Nadir BRDF-Adjusted Reflectance product (MCD43A4, collection 5), referred to as MODIS NBAR, as described at

The combined Terra-Aqua MODIS NBAR provides 500-meter reflectance data adjusted using a bidirectional reflectance distribution function (BRDF) to model the values as if they were taken from nadir view. MODIS NBAR data are 16-day composites in a phased production strategy: Produced every 8 days with 16 days of acquisition (i.e., production period 2001001 includes acquisition between Days 001 and 016, production period 2001009 includes acquisition between Days 009 and 024). Both Terra and Aqua data are used in the generation of this product, providing the highest probability for quality input data.

The MODIS NBAR data for the Australian Continent were downloaded from the LPDAAC site, mosaicked and reprojected into a geographical projection, as described in Paget and King (2008).

Variants and methods summary

MonthlyA multidimensional median (“medoid”, Flood 2013) was used for aggregating the 16-day composites into monthly.
AnomaliesDifference between monthly total vegetation cover and mean vegetation cover for the month (full series mean), recalculated for all years for that month when a new month is produced.
3 month differenceReference month minus 3 months prior
Global FC5 km CMG LPDAAC data
Global monthlymedoids as above
Global anomalymonthly difference as above
NRM statsexperimental, aggregation of FC 8-day and month over predefined spatial areas, produced as a comma-separated file (csv).

Product version history

Version labelDetail
Version 1Data produced using the method and the data as described in Guerschman et al. (2009). It uses MOD43A4 collection 4, with a 1km spatial resolution. 
Version 2Created using the MCD43A4 collection 5 data, applying the same algorithm as version 1. The main improvements as compared to Version 1 are in the spatial resolution (500m instead of 1000m) and the phased production strategy (16-days composites produced every 8 days).
Version 2.1 (June 2010)

Differs to Version 2 in:

  • Fractional cover values for areas where unmixing was constrained (FLAG=2) were set to 254 (0 in V2.0). This avoids the possibility that the user will use the value of 0 when the fractional cover should be ignored altogether.
  • Algorithm only applied to pixels over Australian Land (ocean and PNG ignored and set to 255).
Version 2.2 (November 2011)

Differs to Version 2.1 in:

  • Location of endmembers was redefined following a validation exercise reported in Guerschman et al. (2012).
  • The main effect of that change was an overall decrease in the fractions of bare soil (BS) and an increase in the fractions of non-photosynthetic vegetation (NPV). The estimates of photosynthetic vegetation (PV) had very low changes.
  • The changes in the endmember locations decreased the RMSE of the three cover fractions from 17% to 14.7% (PV), 25% to 20.6% (NPV) and from 26% to 17% (BS).
  • The reader is referred to Guerschman et al. (2012) for more details on these changes.
Version 3.0 (September 2014)The algorithm was changed substantially from previous versions. It uses three endmembers which were obtained form field measurements. The spectral unmixing is performed using all 7 MODIS bands. The RMSE was 12.9%, 18.1% and 16.6% for the PV, NPV and BS fractions respectively [percentage cover]. The reader is referred to Guerschman et al (2015) for more details on these changes. 

Directory, filename and data formats

Filenames of individual data files have the following format:
    vvvv    version (V3.0.1 most recent)
    YYYY    Year (2000 to 2008)
    DDD     Day of year corresponding to the first day of the 16-day composite
    xxxx    aust corresponds to Australia and is 500m (source MCD43A4)
            glob is the global product and is 0.05 degrees (source MCD43C4)
    FF      PV is fraction of Photosynthetic Vegetation
            NPV is fraction of non-Photosynthetic Vegetation
            BS is fraction of Bare Soil
            FLAG is a flag that indicates the processing type (V2 only)
            RNORM is the residual in the spectral unmixing (in reflectance values) 

For example: FractCover.V3.0.1.2000.049.aust.005.BS.img corresponds to the fraction of Bare Soil for the 16-day period starting on the day 49 of the year 2000 (i.e. 18 February to 4 March 2000). Each file is stored in GEOTIF format with values ranging from 0 to 100 (corresponding to the fraction * 100). Pixels with no information in the MODIS NBAR images have a value of 255.

V3: RNORM is a measure of disagreement between the estimated reflectance for the pixel, given the estimated endmembers and the observed fraction. It is provided as a possible metric of model error. The units of RNORM are in reflectance.

A quicklook, with the same name as the data files and suffix png, has been generated. It contains a false color composite of each image with NPV, PV and BS in red, green and blue respectively. In the quicklook images white colours correspond to areas where MODIS NBAR data were not available (FLAG= 255) and ocean. Black areas correspond to areas where FLAG= 2.

Metadata history

2009Metadata creation date
2012-08-31Added Version 2.2 info.
2012-12-10Reformatted to new template.
Added Filename and Product version sections. Added Validation reference.
2016-05-04New record for version 3
(old version 2 metadata record available at Fractional Cover MODIS CLW to v2)
2016-05-30Updated author list of Guerschman et al (2015)
Created by Matt Paget on 2012/12/10 16:47

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