remotior_sensus.tools.band_sieve module
Band sieve.
This tool allows for performing the sieve of raster bands removing patches having size lower than a threshold (i.e. number of pixels).
Typical usage example:
>>> # import Remotior Sensus and start the session
>>> import remotior_sensus
>>> rs = remotior_sensus.Session()
>>> # start the process
>>> sieve = rs.band_sieve(input_bands=['file1.tif', 'file2.tif'],size=2,
... output_path='directory_path',connected=False,prefix='sieve_')
- remotior_sensus.tools.band_sieve.band_sieve(input_bands: list | int | BandSet, size: int, output_path: list | str | None = None, connected: bool | None = None, overwrite: bool | None = False, prefix: str | None = '', extent_list: list | None = None, n_processes: None | int = None, available_ram: None | int = None, bandset_catalog: BandSetCatalog | None = None, virtual_output: bool | None = None) OutputManager
Perform band sieve.
This tool allows for performing the sieve of raster bands removing patches having size lower than a threshold (i.e. number of pixels).
- Parameters:
input_bands – input of type BandSet or list of paths or integer number of BandSet.
output_path – string of output path directory or list of paths.
overwrite – if True, output overwrites existing files.
size – size of dilation in pixels.
virtual_output – if True (and output_path is directory), save output as virtual raster of multiprocess parts
connected – if True, consider 8 pixel connection; if False, consider 4 pixel connection.
prefix – optional string for output name prefix.
extent_list – list of boundary coordinates left top right bottom.
n_processes – number of parallel processes.
available_ram – number of megabytes of RAM available to processes.
bandset_catalog – optional type BandSetCatalog for BandSet number
- Returns:
- Object
OutputManager()
with paths = output list
- Object
Examples
- Perform the sieve of size 3 with connected pixel (8 connection)
>>> sieve = band_sieve(input_bands=['file1.tif', 'file2.tif'],size=3,output_path='directory_path',connected=True,prefix='sieve_')