<!-- language-all: lang-r -->

You can use this R script. For example for a map called "Prodes1":

    library(rgdal)
    library(raster)

    Prodes1<-readOGR(dsn="E:/PRODES/PDigital2014_22768_shp", layer="PDigital2014_22768__pol", dropNULLGeometries=TRUE)
    
    Prodes1$Grd_ranks<-rank(Prodes1$mainclass) #Creating a numeric column for rasterize
    
    i<-1
    Prodes1$value<-rank(Prodes1$mainclass)
    for (i in 1:(length(Prodes1$mainclass))) {
      if (Prodes1$mainclass[i]=="DESFLORESTAMENTO") Prodes1$value[i]<-0 else 
        if (Prodes1$mainclass[i]=="FLORESTA") Prodes1$value[i]<-1 else
          if (Prodes1$mainclass[i]=="HIDROGRAFIA") Prodes1$value[i]<-2 else
            if (Prodes1$mainclass[i]=="NAO_FLORESTA") Prodes1$value[i]<-3 else
              if (Prodes1$mainclass[i]=="NUVEM") Prodes1$value[i]<-4 else
                if (Prodes1$mainclass[i]=="RESIDUO") Prodes1$value[i]<-5 else Prodes1$mainclass[i]<-Prodes1$classe[i])
    }                            
    
    #Creating a ROI to receive the raster data
    ROI2=raster() 
    extent(ROI2)<-extent(Prodes1)
    res(ROI2)<-0.002232143
    proj4string(ROI2)<-CRS(proj4string(Prodes1))
    r<-rasterize(Prodes1, ROI2, "value", fun="first")
    
    #Saving the raster TIFF
    
    writeRaster(r, filename="Prodes.tiff")