Using pygeoprocessing to reclassify raster values

reclassify.md

Using pygeoprocessing to reclassify raster values

Here are some examples of how to use pygeoprocessing for reclassification. Note: tested with pygeoprocessing 2.3.2.

The reclassify_raster function

pygeoprocessing provides the reclassify_raster function which can handle basic cases. See the docstring for details.

Convert one valid value to another valid value

import pygeoprocessing
import numpy

##### EDIT THIS #################################
# replace these with your own paths

input_raster_path = '/path/to/your/input/raster.tif'
output_raster_path = '/path/to/your/output/raster.tif'
#################################################

raster_info = pygeoprocessing.get_raster_info(input_raster_path)
nodata = raster_info['nodata'][0]
unique_values = numpy.unique(pygeoprocessing.raster_to_numpy_array(input_raster_path))
value_map = {value: value for value in unique_values}

##### EDIT THIS #################################
# edit the value_map here to set your own value(s) to reclassify
# in this example, all pixels with value 2 will be reclassified to 4

value_map[2] = 4
#################################################

pygeoprocessing.reclassify_raster(
  (input_raster_path, 1),   # base raster (path, band) tuple
  value_map,
  output_raster_path,       # save the results to your desired output raster path
  raster_info['datatype'],  # give the output raster the same data type as the input raster has
  nodata                    # give the output raster the same nodata value as the input raster has
)

Convert nodata to a valid value

import pygeoprocessing
import numpy

##### EDIT THIS #################################
# replace these with your own paths

input_raster_path = '/path/to/your/input/raster.tif'
output_raster_path = '/path/to/your/output/raster.tif'
#################################################

raster_info = pygeoprocessing.get_raster_info(input_raster_path)
nodata = raster_info['nodata'][0]
unique_values = numpy.unique(pygeoprocessing.raster_to_numpy_array(input_raster_path))
value_map = {value: value for value in unique_values}

##### EDIT THIS #################################
# here we set the value(s) to reclassify
# in this example, all nodata pixels will be reclassified to 0
# replace 0 with the number that you want to reclassify to

value_map[nodata] = 0
#################################################

pygeoprocessing.reclassify_raster(
  (input_raster_path, 1),   # base raster (path, band) tuple
  value_map,
  output_raster_path,       # save the results to your desired output raster path
  raster_info['datatype'],  # give the output raster the same data type as the input raster has
  nodata                    # give the output raster the same nodata value as the input raster has
)

Convert a valid value to nodata

import pygeoprocessing
import numpy

##### EDIT THIS #################################
# replace these with your own paths

input_raster_path = '/path/to/your/input/raster.tif'
output_raster_path = '/path/to/your/output/raster.tif'
#################################################

raster_info = pygeoprocessing.get_raster_info(input_raster_path)
nodata = raster_info['nodata'][0]
unique_values = numpy.unique(pygeoprocessing.raster_to_numpy_array(input_raster_path))
value_map = {value: value for value in unique_values}

##### EDIT THIS #################################
# here we set the value(s) to reclassify
# in this example, all pixels with value 0 will be reclassified to nodata
# replace 0 with the number that you want to reclassify

value_map[0] = nodata
#################################################

pygeoprocessing.reclassify_raster(
  (input_raster_path, 1),   # base raster (path, band) tuple
  value_map,
  output_raster_path,       # save the results to your desired output raster path
  raster_info['datatype'],  # give the output raster the same data type as the input raster has
  nodata                    # give the output raster the same nodata value as the input raster has
)