Exporting Raster Attribute Table using Open Source software

Question

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.

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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.

Answer 1

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
fp.close()

Answer 2

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