Briefly, the steps to get the data.frame are:
1. Read a image as a data.frame with readGDAL - this is the first loop.
2. Dataframe is classified with a predict(lda())
3. It's back converted to a SPDF called pixID
4. Pixels (regions) of a specific class of the SPDF pixID is dissolved into
single reg
How are you creating the dataframes? You did not provide an example
of the code. Can you use 'lapply' instead of a 'for' loop and then
use 'do.call(rbind, lappy_result)' to create your dataframe? Adding
each time through the loop can get resource consuming if the
dataframes are large, but you ga
I'm not sure if there are better methods to create objects such as
dataframes with other than rbind function.
II usually combine a data.frames created at each loop with a rbind(),
specially when I don't know the dimension of the data.frame that will be
created.
Binding the new to an existing data.
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