diff --git a/preprocessing/sparcs.py b/preprocessing/sparcs.py
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+"""Functions to preprocess the Sparcs dataset to work with pylandsat."""
+
+# !/usr/bin/env python
+# coding: utf-8
+
+# builtins
+import os
+import glob
+import shutil
+
+# externals
+import gdal
+import numpy as np
+
+# locals
+from pylandsat.core.untar import extract_data
+from pylandsat.core.calibration import landsat_radiometric_calibration
+
+
+def sparcs2pylandsat(source_path, target_path, overwrite=True):
+ """Convert the Sparcs dataset structure to the pylandsat standard.
+
+ Parameters
+ ----------
+ source_path : string
+ path to the Sparcs archive downloaded `here`_
+ target_path : string
+ path to save the preprocessed sparcs dataset
+ overwrite : bool
+ whether to overwrite existing files
+
+ Returns
+ -------
+ None.
+
+ .. _here:
+ https://www.usgs.gov/land-resources/nli/landsat/spatial-procedures-automated-removal-cloud-and-shadow-sparcs-validation
+
+ """
+ # create a directory for each scene
+ for dirpath, dirnames, filenames in os.walk(source_path):
+
+ # check if there are files in the current folder
+ if not filenames:
+ continue
+
+ # iterate over the files to modify
+ for file in filenames:
+
+ # get the path to the file
+ old_path = os.path.join(dirpath, file)
+
+ # get name of the scene
+ fname = file.split('_')[0]
+
+ # define the new path to the file
+ new_path = os.path.join(target_path, fname)
+
+ # check if file is the metadata file
+ if file.endswith('_mtl.txt'):
+
+ # add the collection number to the metadata file
+ with open(old_path, 'a') as mfile:
+ mfile.write('COLLECTION_NUMBER = 1')
+
+ # replace file ending
+ file = file.replace('mtl', 'MTL')
+
+ # move files to new directory
+ if os.path.isfile(new_path + os.sep + file) and not overwrite:
+ print('{} already exists.'.format(new_path + os.sep + file))
+ continue
+ else:
+ os.makedirs(new_path, exist_ok=True)
+ shutil.move(old_path, new_path + os.sep + file)
+
+ # remove old file location
+ shutil.rmtree(source_path)
+
+
+def destack_sparcs_raster(inpath, outpath=None, suffix='*_toa.tif'):
+ """Destack a TIFF with more than one band into a TIFF file for each band.
+
+ Parameters
+ ----------
+ inpath : string
+ path to a directory containing the TIFF file to destack
+ outpath : string, optional
+ path to save the output TIFF files. The default is None. If None,
+ ``outpath`` = ``inpath``.
+
+ Returns
+ -------
+ None.
+
+ """
+ # default: output directory is equal to the input directory
+ if outpath is None:
+ outpath = inpath
+
+ # check if output directory exists
+ if not os.path.exists(outpath):
+ os.makedirs(outpath)
+
+ # get the TIFF to destack
+ tif = glob.glob(inpath + os.sep + '*data.tif').pop()
+
+ # open the raster
+ img = gdal.Open(tif)
+
+ # check whether the current scene was already processed
+ processed = glob.glob(inpath + os.sep + suffix)
+ if len(processed) == img.RasterCount:
+ print('Scene: {} already processed.'.format(os.path.basename(inpath)))
+ img = None
+ os.unlink(tif)
+ return
+
+ # image driver
+ driver = gdal.GetDriverByName('GTiff')
+ driver.Register()
+
+ # output image type: digital numbers unsigned integer 16bit
+ codage = gdal.GDT_UInt16
+ nptype = np.uint16
+
+ # image size and tiles
+ cols = img.RasterXSize
+ rows = img.RasterYSize
+ bands = img.RasterCount
+
+ # print progress
+ imgname = os.path.basename(tif)
+ print('Processing: {}'.format(imgname))
+
+ # iterate the bands of the raster
+ for b in range(1, bands + 1):
+ # output file: replace for band name
+ fname = os.path.join(outpath, imgname.replace('data', 'B' + str(b)))
+ outDs = driver.Create(fname, cols, rows, 1, codage)
+
+ # read the data of band b
+ band = img.GetRasterBand(b)
+ data = band.ReadAsArray().astype(nptype)
+
+ # define output band
+ outband = outDs.GetRasterBand(1)
+
+ # write array to output band
+ outband.WriteArray(data)
+ outband.FlushCache()
+
+ # Set the geographic information
+ outDs.SetProjection(img.GetProjection())
+ outDs.SetGeoTransform(img.GetGeoTransform())
+
+ # clear memory
+ del outband, band, data, outDs
+
+ # remove old stacked GeoTIFF
+ img = None
+ os.unlink(tif)
+
+
+if __name__ == '__main__':
+
+ # define path to working directory
+ # wd = 'C:/Eurac/2020/'
+ wd = '/mnt/CEPH_PROJECTS/cci_snow/dfrisinghelli/'
+
+ # path to the downloaded sparcs archive
+ sparcs_archive = os.path.join(wd, '_Datasets/Archives/l8cloudmasks.zip')
+
+ # path to save preprocessed sparcs dataset
+ sparcs_path = os.path.join(wd, '_Datasets/Sparcs')
+
+ # extract the raw archive to the output path
+ location = extract_data(sparcs_archive, sparcs_path)
+
+ # transform SPARCS directory structure to pylandsat standard
+ sparcs2pylandsat(source_path=location, target_path=sparcs_path,
+ overwrite=False)
+
+ # destack the TIFF rasterstack to a single TIFF for each band and perform
+ # radiometric calibration
+ for scene in os.listdir(sparcs_path):
+ # path to the current scene
+ scene_path = os.path.join(sparcs_path, scene)
+
+ # build the GeoTIFFs for each band
+ destack_sparcs_raster(scene_path, suffix='*_toa.tif')
+
+ # convert the digital number format to top of atmosphere reflectance
+ landsat_radiometric_calibration(scene_path, exclude=[], suffix='_toa',
+ overwrite=False, remove_raw=True)