On 13/02/14 18:48, manuel.martin wrote:
So I looked closer at the data and it is ESRI's binary ArcInfo Grid
format with vat.adf files in the layer directory. These tables may be
accessed outside of ArcGIS using for instance gdalinfo, and the R raster
library seem to do it as well. However these tables seem to contain some
binary codes so they cannot easily be read from automatic processing.
If you can export the information with gdalinfo, you should be able to
treat it automatically to create the necessary input files for r.reclass
or r.category. I don't have any sample files here, so I can't test for
myself. If you want to send me a sample file, I can try to see what is
possible.
BTW: I just added to the GRASS wiki page on Corine Land Cover [2] the
input necessary for r.reclass to transform a raster with generic 0-255
categories to a raster with the CLC codes as categories and the
description of each class as a label.
Unfortunately, CLC is not the only categorical layer I need to process,
and manually linking the imported rasters values (within GRASS) to
manually extracted codes (which again may be also strings) is not really
an option. (or maybe is there a way to automate the process?)
If you have access to ArcGIS, you can apparently export the raster data
table [3]. You should then be able to input that table into r.reclass or
r.category depending on your needs and on the data.
So I am now thinking to convert these ArcGIS layers to another format
using the gdal library (function gdal_translate for instance) for latter
importing these converted layers to grass. I am thus facing two new
questions.
1) which format is the best suited for carrying such categorical data on
larger rasters among supported gdal formats and
2) will this format be supported by grass?
GRASS raster format does not store attributes for rasters (or maximum
one in the form of labels). So if you want to store the information
contained in several fields in an attribute table, you have to create as
many raster maps as there are attributes (assuming that these attributes
are numerical). So I think you best bet is to try to get the attribute
data in text form and then extract from that the inputs to
r.reclass/r.category.
Moritz
[1]
http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/Raster_dataset_attribute_tables/009t00000009000000/
[2] http://grasswiki.osgeo.org/wiki/CORINE_Land_Cover#Legend
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