Classification

To generate suitable fertilizer maps from vegetation index maps, it is necessary to group these values into zones with similar characteristics. You can choose the number of zones to be created and determine how they should be grouped, which we explained in more detail:

Jenks Natural Breaks

The classification method Jenks natural breaks is a data clustering method designed to determine the best arrangement of values into different classes. The method seeks to reduce the variance within classes and maximize the variance between classes.

How it works

The method requires an iterative process. Calculations must be repeated using different breaks in the dataset to determine which set of breaks has the smallest in-class variance. The process is started by dividing the ordered data into classes in some way, which may be arbitrary. Two steps must be repeated:

1. Calculate the sum of squared deviations from the class means.

2. Choose a new way of dividing the data into classes, perhaps by moving one or more data points from one class to a different one.

New class deviations are then calculated, and the process is repeated until the sum of the within class deviations reaches a minimal value.

Equal index distance

The classification method equal index distance is a data clustering method designed to classify values into different classes, which have the same dividing distance.

How it works

From the smallest and the biggest values, the difference is calculated. The difference is then divided by the number of classes and each value is classified into a specific class.

Equal zone size

The classification method equal zone size is a data clustering method designed to classify values into different classes, which have the same number of values in them.

How it works

The number of classes divides the number of values. Then each value is classified into a specific class.