If you don’t have an account use the Sign-Up option at the bottom of the login screen. If the application does not open, please ensure you are using an up to date web browser, and preferably use the Chrome Internet Browser for the application if this is not your default browser. Detailed instructions are provided in the sections below.
If the application does not open, please ensure you are using an up to date web browser, and preferably use a Chrome Internet Browser for the application if this is not your default browser.
Click on the sign up tab, enter your details and agree to the conditions.
Creating the MyFarmKey
Enter the property details and address.
Drag the location icon to the front gate location.
Select the land parcels that belong to your property. “click” again to remove parcels. Save when you are done and open the “My Properties” tab.
You can verify your property record against your LPA ID and Property Identification Code (PIC) which will allow your information to be linked together for future traceability and provenance applications that you may wish to undertake. You can complete the verification at any time.
If you choose to download your completed property MyFarmKey as geojson and/or kml files using the shopping cart prior to running a benchmark report the files will be placed in your download folder. Attach and email the 2 files to your service provider or collaborator for on-boarding. If you would like to view your MyFarmKey simply download Google Earth Pro and “drag” the kml file into the viewer. You can click on the MyFarmKey and see the records stored in the data file.
Displaying the Satellite Time Series Data
To display the Seasonal Ground Cover and Annual Woody Change data select the Time Series Data and simply set the time-slider for the date you want to look at.
Set the zoom level using the scroll wheel on your mouse. Alternatively, use the + or – button at the top left corner of the map.
Turn these layers off to select the parcels by clicking “X” in the Time Series Display.
Property Benchmarking and Reporting
Select the farm you want to analyse and the parcels you want to compare it to by selecting a search radius or selecting onscreen interactively.
Once payment is made the reports will be emailed to you.
Benchmark Report Content
You will receive the following files within a zip file via email. Simply download and unzip the attached file.
Annual Woody Vegetation Cover Change Reports
The woody vegetation trend analyses use data adapted from the Department of the Environment and Energy (2019). National forest and sparse woody vegetation data. Version 4.0. Commonwealth of Australia, Canberra.
Landsat satellite imagery is used to derive woody vegetation extent products that discriminate between forest, sparse woody and non-woody land cover across a time series from 1988 to 2019. A forest is defined as woody vegetation with a minimum 20% canopy cover (CC), potentially reaching 2 metres high and a minimum area of 0.2 hectares. Sparse woody (woodland) is defined as woody vegetation with a canopy cover between 5-19%.
Primary forest (>=20% CC) or woodland (5-19% CC) refers to woody vegetation that has been undisturbed since at least 1988. Secondary forest or woodland has been disturbed at anytime since 1988.
The Annual Woody Vegetation Cover Change Report provides information on the reported total extent of woodland and forest over time (the left axis and solid lines) and apparent annual loss rate (dotted lines and right axis) for primary and secondary woody vegetation (forest and woodland). The time-series display tool can be used to visualise where in the landscape these changes have occurred.
Figure 1. Example report showing annual changes in woody vegetation extent (solid lines) and apparent annual losses (dotted lines).
So what story does the above woody vegetation cover graph tell us?
The above graph shows a very low overall amount of woody cover starting with 4.5% of the report area in 1991 and a decrease in forest and woodland extent from 1991-2006 to about 2% of the reporting area with apparent losses of both primary and secondary woody vegetation. Since 2012 there has been a net increase in the extent of woody vegetation. The extent of woodland has remained relatively constant with most of the increase associated with forest. The greatest loss rate was in 2006 with over 20% of the woody cover being lost.
Seasonal Ground Cover Reports
Six time-series graphs are produced using median seasonal ground cover estimates based on Landsat satellite data using methods developed by the Joint Remote Sensing Research Program and adapted by Cibo Labs. Below these are the monthly gridded rainfall data sourced from the Bureau of Meteorology. The graphs provide the long term trends in ground cover over a property and allow the property to be compared to reference properties (e.g the adjacent properties within 5km) and the surrounding biogeographic region. If we can assume the comparison areas on similar land types have received similar rainfall, then differences in ground cover can generally be interpreted as land management effects.
Seasonal Ground Cover Percentiles.
Figure 2. Seasonal Ground Cover Percentiles and Monthly Rainfall – the graph above shows the seasonal ground cover levels achieved based on area percentiles of the property or reporting area, along with monthly rainfall. For example, the 99th percentile is highest seasonal ground cover achieved for 99% of the reporting area and the 50th percentile (median) is the seasonal ground cover achieved for 50% of the area.
So what story does the above seasonal ground cover graph tell us?
Generally ground cover across a property can be highly variable depending on land management practices and land condition. For example, a property might have generally high ground cover levels, but some localised areas with much lower ground cover levels that may be at risk of erosion. Using a single statistic such as the average or median seasonal ground cover for the entire property would potentially be very misleading. For the property in the example above, while drought conditions over the last 10 years has seen an overall decline in ground cover (as would be expected), this particular property has generally maintained greater than 75% seasonal ground cover levels over 75% of the area, (see the 25th percentile) except for the extreme drought year of 2020. The property has also generally had greater than 50% seasonal ground cover over 90% of the property (see the 10th percentile), and less than 1% of the property has been below 50% seasonal ground cover during 5 dry seasons in the last 10 drought years.
Seasonal Ground Cover Benchmarks (Compared to the Reference Area)
Figure 3. Seasonal Ground Cover Benchmarks compared to the Reference Area - The graph above compares the median (50th percentile) ground cover of the property to the 5th, 25th, 75th and 95th ground cover percentiles of the selected reference area (e.g. the properties within 5km). The blue line is near the 75th percentile of the reference area which means the median ground cover of the property is higher than around 75% of the selected reference property area.
Figure 4. Normalised Seasonal Ground Cover Benchmarks compared to the Reference Area - This graph compares the median seasonal ground cover of the property relative to the selected reference area seasonal ground cover (5th and 95th percentile are represented as the 0% & 100% respectively) . For example, if the median ground cover of the property is higher than the selected reference area it will be above the 50% line. In this example, in recent years the property has been around the 75th percentile and significantly improved relative to the neighbours.
So what story does the above seasonal ground cover benchmark graph tell us about the property?
The 2 graphs above tell a fantastic story about the positive impact of changing grazing management on ground cover, and overall productivity. The current owners took over the property around 2010 when ground cover levels were similar to or below neighboring properties. Despite drought conditions causing an overall drop in ground cover over the last 10 years, their ground cover levels relative to neighboring properties have improved due to infrastructure development and grazing management. Not only have their stocking rates increased, but ground cover levels are now around the top 25% compared to their neighbors.
Seasonal Ground Cover Benchmarks (compared to the IBRA Sub-Region)
Figure 5. Seasonal Ground Cover Benchmarks compared to the IBRA Sub Region - The graph above compares the median (50% percentile) ground cover of the property to the 5th, 25th, 75th and 95th ground cover percentiles of the surrounding IBRA Sub Region. If the blue line is near the 75th percentile it means the median ground cover of the property is higher than approximately 75% of the the surrounding IBRA Sub Region. If the blue line is below the 25th percentile the it means the median ground cover of the property is lower than approximately 75% (or the lowest 25% in terms of area) of the the surrounding IBRA Sub Region
Figure 6. Normalised Seasonal Ground Cover Benchmarks compared to the IBRA Sub Region - This graph compares the median seasonal ground cover of the property relative to the IBRA Sub Region seasonal ground cover (5th and 95th percentile are represented as the 0% & 100% respectively) . For example, if the median ground cover of the property is higher than the the IBRA Sub Region it will be above the 50% line.
So what story does the above seasonal ground cover benchmark graph tell us about the property?
Not only have the owners of this property improved the ground cover levels compared to their neighbors, but they have also dramatically improved ground cover compared to the district. Prior to 2010 ground cover levels on this property were generally well below others within the Banana-Auburn Ranges Biogeographic Region, and in some years below the 25th percentile. Importantly, there is a significant rainfall gradient across the region with this property receiving less than the long-term regional average rainfall. In recent years the property has generally been above the 50th percentile, suggesting the new property owners have significantly improved their ground cover.
Use Based Pricing
This is a commercial service and all FarmKey downloads and Benchmark Reports will incur a fee based on the pricing below or as specified in the application at the time of download.
The standard pricing model is as follows:
Access to the satellite mapping “time-slider” (ground cover, tree cover time-series)
$75.00 (inc GST) per property for a one-off perpetual licence
Property Benchmark Reports
$175.00 (inc GST) per property for a perpetual licence
12 month subscription for up to 20 reports for an individual property.