Combining production data such as yield and remote sensing is a popular method for creating zones or making new data layers.
PCT Agcloud Analytics takes this a step further by creating a correlation matrix to observe if the layers correlate before combining.
These correlations allow users to determine if data layers actually correlate and create a confidence level of low medium and high.
Combining data this way should always be carried out with caution.
There are two options for running Yield Analytics that are explained below. In both examples, Yield and Remote sensing layers can be used in the analysis.
Option 1 - Same Crop Over Multiple Years
Steps:
- In the analytics tool with the desired field selected, select the years to combine.
- Clicking Run Analysis will create the correlation scatterplots.
- Note that R Squares are shown at the bottom. R Squares <0.3 will be represented by the red line, >0.3 <0.6 will be represented by the orange line, and >0.6 will be represented by the green line.
- Clicking the combine maps tab will allow the user to save two types of maps.
- Average and Sum - these can be zoned but are not recommended as these layers can be used in further analysis applications.
Option 2 - Multiple Year Multiple Crops
Steps:
Note that when different crops are used the default is to normalise the data before combining. However, the user does have the ability to create {Crop} Yield Potential layers based on their local knowledge.
- Select the multiple crops and click run analysis.
- Check the correlations.
- The combined maps page will have some extra options as shown below.
- Select Crop and Yield Values - the user can take the combined yields and turn them into expected yields for other crops. For example, Barley Yield Potential could be saved as below but Chickpeas could range from 0.5 to 2.5t/ha.
- Select the crop type and values and hit Apply. Layers can also be zoned but it's not recommended. Other applications such as Rx and Zone Locate will zone the layers as needed on the fly.
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