Create regression

The Create regression block allows you to input a dataset and create a new numeric band with predicted values based on training data. The training data can come from a dataset already in Earth Blox, or from your own data. 

To output a thematic band, use the Create supervised classification block.

Add the Create regression block to the workflow containing the input data. 

A table of results, and an accuracy assessment are automatically generated and are shown on the Dashboard.

Algorithm

Linear regression: predicts the value of one variable based on the value of another.

Training data

Choose a dataset to use as training data. Add a Save data for re-use block in the workflow you want to use as training data.

To use a feature collection as training data, use the Convert features to images block.

Band

Select the band of your image to use as training data. If your dataset has multiple bands, you will need to remove all other bands using the Remove bands block.

Band prefix

This is the name of the band containing your output.

Example: Predicting biomass using NDVI

In this example, we want to predict biomass (our ‘dependent variable’, contained in our training data) using NDVI (our ‘independent variable’, contained in our input variable).

Each point in the scatter plot below represents a pixel where we know both the NDVI (from our input data) and the biomass (from our training data).

Linear regression involves finding the line of best fit that best models the relationship between the two variables. The line of best fit has an ‘offset’ (intercept) and ‘scale’ (slope/gradient). 

Now we have this line, we can predict biomass for every other pixel of NDVI. This is our output, which is added as a new band.