I am new to the software EnMap Box that incorporates Random Forest (RF) as one of its capability. To learn the Enmap, I followed the RF tutorial provided online.
My goal is to use RF as a tool to classify Landsat images using more than 100 explanatory variables.
In the EnMap tutorial (link provided above), under the "Parameterization of RFC/RFR Models", it only says "Select the Image to be classified...." But what image in particular? Am I going to use the image that stacked all 100 variables that I want in the analysis? In other words, how would I input the various explanatory variables into EnMap, so that I could then apply the tool "Variable Importance" to select important layers for classification?
Is there anyone familiar with EnMap and could guide me through this?