Ag Productivity User Guide

Owned by John.Mcculloch (Unlicensed)
Feb 22, 2024
4 min read

Ag Productivity refers to the amount of carbon plants capture through photosynthesis and then store as above-ground plant mass. Ag Productivity provides an excellent indication of ecosystem productivity, pasture production and crop yield. As a biophysical variable, this data can be used to compare differences in productivity between locations and through time.

CSIRO generates Australia-wide grids of Ag Productivity data (pastures, crops and grasslands) at a 250 m spatial resolution and a 16-day timestep. These are derived from MODIS satellite imagery, which extends from 2001 up until the present. CSIRO continuously updates the Ag Productivity product approximately every three weeks as the latest imagery becomes available.  

Ag Productivity data are in units of grams of carbon per square metre per day (gC/m2/d). Valid values range from around -1 to 5. Ag Productivity can go negative – that is, when plants lose more carbon in keeping themselves alive (via respiration) than they gain through photosynthesis. Hence there is a net loss of carbon. This happens annually in many places that experience really dry or cold conditions seasonally, or during extended drought etc. Note that the Ag Productivity estimates do not discriminate between different types of crops, pastures or grasses.

Ag Productivity data have been derived using the CSP (C-Store Pastures) model1 which is built around the DIFFUSE Gross Primary Productivity (GPP) model2. Due to the scarcity of suitable data for validating Ag Productivity data nationally, we have not validated the Ag Productivity estimates. We have however validated the closely related, underlying GPP estimates at four grassland Australian flux tower sites. Our modelled GPP explained 83% of the tower GPP variability with an RMSE of 1.5 gC/m2/d.

Here Ag Productivity is modelled as the rate of accumulation of carbon mass. This is not the same as the total mass (that is, biomass) which is what is observed and measured on the ground. As a rule of thumb, biomass is about twice carbon mass. To convert these Ag Productivity data to biomass they need to be doubled. 

Ag Productivity data provide more powerful insights into productivity than the more commonly used Normalised Difference Vegetation Index (NDVI). NDVI is a spectral index and, while it is strongly related to foliage cover, has no inherent biophysical meaning. To derive meaningful information from the NDVI it must be related (calibrated) to some local, physical attribute, such as biomass or cover. Even when locally calibrated, the NDVI by itself is not always a good indicator of productivity because it saturates when cover is high (such as in the north’s wet season, the south’s dark winter months, and in the peak of the cropping season). NDVI usually needs to be calibrated at each location of interest. It is for these reasons that we have developed this new product, Ag Productivity .

How can I use these data?

Ag Productivity is a biophysical variable that provides an excellent indication of pasture, grassland and crop production.

As estimates are produced every few weeks, they provide detailed insights into how variable productivity has been and how it is currently changing. Uses can include:

  • Examine how the productivity of a given paddock has varied over the past 20 years, allowing for comparisons to made between current productivity and the average productivity for the same time of year.

  • Compare the progression of the current season to that of previous seasons to get a feel for possible trajectories of the coming months.

  • Gauge how well a given paddock is performing compared to surround paddocks in a region or further afield (even nationally). Such benchmarking can be useful in assessing the effectiveness of management strategies.

  • Understand how productivity relates to crop yield and grazing records

  • Assess at a regional level how the season is progressing to provide indicators of the likely production of livestock or grain in the region, or the demand for feed. This can further inform transport and processing requirements.



These Ag Productivity data can be converted from gC/m2/d into other commonly used units.  To convert to kilograms, divide by 1,000.  To convert to tonnes, divide by 1,000,000.  To convert to per-hectare, multiply by 10,000.  For example, to convert gC/m2/d to t/ha, multiply by 1,000,000 and then divide by 10,000 (which is the same as dividing the original Ag Productivity by 100). 

There are two methods that can be used to produce annual estimates.  One is to sum-up each 16-day value within a year and multiply by 16.  The other is to take the average of the year’s 16-day values and multiply by 365.25.  Both these give units of gC/m2/year.  Follow the above to convert this to kg, tonnes or per hectare to give, for example, t/ha/y.

Scientific literature

1 Donohue, R.J., Hume, I.H., Roderick, M.L., McVicar, T.R., Beringer, J., Hutley, L.B., Gallant, J.C., Austin, J.M., van Gorsel, E., Cleverly, J.R., Meyer, W.S., & Arndt, S.K. (2014). Evaluation of the remote-sensing-based DIFFUSE model for estimating photosynthesis of vegetation. Remote Sensing of Environment, 155, 349-365. https://doi.org/10.1016/j.rse.2014.09.007.

2 Donohue, R.J., & Renzullo, L.J. (2015). C-Store: an Australian remote-sensing and observation-driven carbon assessment system. In. Canberra: CSIRO. https://doi.org/10.4225/08/5a3953b0a4d5c.