Hi,
though be prepared that converting large images into shape is quite
slow. I would go opposite way: convert a shape to a raster [0, 1];
extract band from the image as another raster [2]; and then extract
statistics using Numpy [e.g. 3].
[0] http://stackoverflow.com/questions/2220749/rasterizing-a-gdal-layer
[1]
http://trac.osgeo.org/gdal/wiki/FAQRaster#HowcanIcreateablankrasterbasedonavectorfilesextentsforusewithgdal_rasterizeGDAL1.8.0
[2] http://gdal.org/gdal_tutorial.html#gdal_tutorial_read
[3] zoneMean = rasterFromBand[rasterFromShape = zoneIndex].mean()
Good luck!
Anton
On 06/19/2012 07:15 PM, Alexander Bruy wrote:
Hi,
you can use GDAL Python bindigs for this [0, 1]. The process may look
as open shape and raster, then convert pixel coordinates into map (shape)
coordinates and process only pixels inside your polygon.
[0] http://gdal.org/gdal_tutorial.html
[1] http://gdal.org/ogr/ogr_apitut.html
2012/6/19 jdmorgan<[email protected]>:
Hello,
Is there a way to do something along the lines of zonal statistics with
gdal. Basically, I have a county shape file and a classified raster
dataset. I would like to count the number of raster pixels/county (FIPS).
Is this possible with GDAL/OGR? If so can someone point me in the right
direction? If so, awesome as I plan to do some automation with python.
Thanks,
Derek
Hope this helps
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