The reclass rules are read from standard input (i.e., from the keyboard, redirected from a file, or piped through another program).
Before using r.reclass the user must know the following:
r.reclass only works on an integer input raster map; if the input map is instead floating point data, you must multiply the input data by some factor to achieve whole number input data, otherwise r.reclass will round the raster values down to the next integer.
Also note that although the user can generate a r.reclass map which is based on another r.reclass map, the new r.reclass map will be stored in GRASS as a reclass of the original raster map on which the first reclassed map was based. Therefore, while GRASS allows the user to provide r.reclass map layer information which is based on an already reclassified map (for the user's convenience), no r.reclass map layer (i.e., reclass table) will ever be stored as a r.reclass of a r.reclass.
To convert a reclass map to a regular raster map layer, set your geographic region settings to match the settings in the header for the reclass map (with "g.region raster=reclass_map", or viewable by running r.info) and then run r.resample.
r.mapcalc can be used to convert a reclass map to a regular raster map layer as well:
r.mapcalc "raster_map = reclass_map"
where raster_map is the name to be given to the new raster map, and reclass_map is an existing reclass map.
Because r.reclass generates internally simply a table by referencing some original raster map layer rather than creating a full new reclassed raster map layer, a r.reclass map layer will no longer be accessible if the original raster map layer, upon which it was based, is later removed. Therefore, attempting to remove a raster map layer from which a r.reclass has been derived is only possible if the original map is removed first. Alternatively, a r.reclass map can be removed including its base map by using
g.remove's -b flag.
A r.reclass map is not a true raster map layer. Rather, it is a table of reclassification values which reference the input raster map layer. Therefore, users who wish to retain reclassified map layers must also save the original input raster map layers from which they were generated. Alternatively r.recode can be used.
Category values which are not explicitly reclassified to a new value by the user will be reclassified to NULL.
where each line of input specifies the category values in the input raster map layer to be reclassified to the new output_category category value. Specification of a label to be associated with the new output map layer category is optional. If specified, it is recorded as the category label for the new category value. The equal sign = is required. The input_category(ies) may consist of single category values or a range of such values in the format "low thru high." The word "thru" must be present.
To include all (remaining) values the asterix "*" can be used. This rule has to be set as last rule. No further rules are accepted after setting this rule. The special rule "* = *" specifies that all categories not explicitly set by one of the above rules should be passed through unaltered instead of being set to NULL.
Categories to become no data are specified by setting the output category value to "NULL".
A line containing only the word end terminates the input.
The first example reclassifies categories 1, 2 and 3 in the input raster map layer "roads" to category 1 with category label "good quality" in the output map layer, and reclassifies input raster map layer categories 4 and 5 to category 2 with the label "poor quality" in the output map layer.
1 2 3 = 1 good quality 4 5 = 2 poor quality
The following example reclassifies categories 1, 3 and 5 in the input raster map layer to category 1 with category label "poor quality" in the output map layer, and reclassifies input raster map layer categories 2, 4, and 6 to category 2 with the label "good quality" in the output map layer. All other values are reclassified to NULL.
1 3 5 = 1 poor quality 2 4 6 = 2 good quality * = NULL
The following example reclassifies input raster map layer categories 1 thru 10 to output map layer category 1, input map layer categories 11 thru 20 to output map layer category 2, and input map layer categories 21 thru 30 to output map layer category 3, all without labels. The range from 30 to 40 is reclassified as NULL.
1 thru 10 = 1 11 thru 20 = 2 21 thru 30 = 3 30 thru 40 = NULL
The following example shows overlapping rules. Subsequent rules override previous rules. Therefore, the below example reclassifies input raster map layer categories 1 thru 19 and 51 thru 100 to category 1 in the output map layer, input raster map layer categories 20 thru 24 and 26 thru 50 to the output map layer category 2, and input raster map layer category 25 to the output category 3.
1 thru 100 = 1 poor quality 20 thru 50 = 2 medium quality 25 = 3 good quality
The previous example could also have been entered as:
1 thru 19 51 thru 100 = 1 poor quality 20 thru 24 26 thru 50 = 2 medium quality 25 = 3 good quality
1 thru 19 = 1 poor quality 51 thru 100 = 1 20 thru 24 = 2 26 thru 50 = 2 medium quality 25 = 3 good quality
The final example was given to show how the labels are handled. If a new category value appears in more than one rule (as is the case with new category values 1 and 2), the last label which was specified becomes the label for that category. In this case the labels are assigned exactly as in the two previous examples.
r.category landuse96_28m 0 not classified 1 High Intensity Developed 2 Low Intensity Developed 3 Cultivated [...] 20 Water Bodies 21 Unconsolidated Sediment # use this command or save rules with editor in textfile "landuserecl.txt" echo "0 = NULL 1 2 = 1 developed 3 = 2 agriculture 4 6 = 3 herbaceous 7 8 9 = 4 shrubland 10 thru 18 = 5 forest 20 = 6 water 21 = 7 sediment" > landuserecl.txt r.reclass input=landuse96_28m output=landclass96_recl \ rules=landuserecl.txt \ title="Simplified landuse classes 1996" # verify result r.category landuse96_recl 1 developed 2 agriculture 3 herbaceous 4 shrubland 5 forest 6 water 7 sediment
Available at: r.reclass source code (history)
Latest change: Wednesday Nov 27 22:53:26 2024 in commit: b90ce69e88409469369ec1edb86fde8ec822af8b
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