Hi,

The reason for this is that ESA Worldcover data and sampleType is not the same as a vegetation index. The ESA World Cover classes are discrete values (e.g. 1,2,3,4), whereas a vegetation index consists of continuous data in a range (e.g. 0.0 - 1.0). This is why the histogram option is not enabled.

What are you trying to measure using the histograms for the dataset? The sum of pixels for each land cover class?

Hi,, many thanks for your reply.

Is there a way to convert it to an index with a custom script to enable histogram ?

My goal is indeed to evaluate the proportion of each class (by counting the pixels). Then do it for another year and see the evolution. For instance: forest cover went from 40% in 2018 to 30% in 2021 in this area.

Hi,

As I said, with this kind of data (discrete and not continuous), converting to an index does not make sense.

I would recommend downloading the data and then visualising the histogram classes using Python to achieve your desired goal.

ESA world cover classes integer values range from 10 to 100 with increments of 10 (or 5).

If index is the only way to display a histogram, it could make sense to convert discrete data to an index where integer values ranging from 0 to 100 would be converted to float values within the 0-1 range. For instance class 20 would become the value 0,2.

Can this operation be performed ?