I have 120 or so geotiff files that I'd like to build and export the raster attribute table to something a little more friendly (e.g. csv).

I'm curious if there is an open source way to do this. The files are rather large 36001 X 36001 pixels so brute force solutions may be out. Ideally, I'm looking to do this in gdal commandline/OSGEO4w or Qgis. Grass in a pinch.

Some additions in response to comments:

  • I am somewhat familiar with python. If anyone has a solution in that vein, I'd love to hear it. Same thing goes with R and windows command line.

-The table would look something like this:

Value | # of Cells
0 | 100000
1 | 3214
2 | 25125
98 | 2214213

Basically, I'm looking for a non-ArcGIS way to recreate the ArcGIS raster attribute table. The reason I want CSV is because I have some other mathematical operations I'd like to run, and a csv or some sort of text file works best for my workflow. Its a bit anti-dramatic, but all I really need at this stage is the number of cells for each value in the raster.

  • Show a few lines about such table as an example and tell us for what purpose you think csv to be more friendly than data as raster files.
    – user30184
    Oct 6 '14 at 5:38
  • are you python friendly? Oct 6 '14 at 6:16
  • I've adjusted the posting in response to comments. Thanks for your interest thus far. @user1269942 Oct 7 '14 at 14:38
  • This link might help: gis.stackexchange.com/questions/40958/…
    – Joseph
    Oct 7 '14 at 14:54
  • so you want one row per raster in your exported file? that'll be a big file. Also, can you elaborate on your format...I don't quite understand what your numbers are, thanks! Oct 8 '14 at 5:00

Ok, I'm still fuzzy on what exactly your export file is but I'll assume "#of cells" is simply the number of pixes for each raster and "Value" is some identifier for each raster (parse the file name??). In absence of how to get "Value", I just put an incremented variable. This script will require gdal.

import glob
from osgeo import gdal
import numpy as np

def get_raster_data(raster_file_name, band):
    r = gdal.Open(raster_file_name)
    return np.array(r.GetRasterBand(band).ReadAsArray())

fp = open('export.txt', 'w+')
fp.write('Value | # of Cells\n')

#what is Value?? I will just put an incremented number. 
#if Value is the raster number, parse yourself.
val = 1
for fname in glob.glob('*.tif'):
    arr = get_raster_data(fname, 1)
    num_cells = arr.shape[0] * arr.shape[1]
    fp.write('%i|%i\n' % (val, num_cells))
    val += 1

Thanks for all the response. Turns out the Count Raster Cells tool from the LecoS plug-in is what I needed.

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