def fmask(self):
'''-----\n
This method applies Fmask algorithm or its equivalent with the BQA band (default for Ecopotential)'''
os.chdir(self.ruta_escena)
print('Starting Cloud Mask')
try:
print('Starting Fmask')
t = time.time()
#Last value is the cloud confidence value
a = os.system(
'removethisisFmaskinstalled/usr/GERS/Fmask_4_0/application/run_Fmask_4_0.sh /usr/local/MATLAB/MATLAB_Runtime/v93 3 3 1 {}'
.format(self.umbral))
a
if a == 0:
self.cloud_mask = 'Fmask'
print('Cloud Mask (Fmask) generated in ' +
str(t - time.time()) + ' seconds')
else:
print('Starting Cloud Mask with BQA band')
outfile = os.path.join(
os.path.join(self.ruta_escena, self.escena + '_Fmask.tif'))
for i in os.listdir(self.ruta_escena):
if i.endswith('BQA.TIF'):
bqa = os.path.join(self.ruta_escena, i)
masker = LandsatMasker(bqa, collection=1)
conf = LandsatConfidence.high
cloud = masker.get_cloud_mask(conf)
cirrus = masker.get_cirrus_mask(conf)
shadow = masker.get_cloud_shadow_mask(conf)
MASCARA = cloud + cirrus + shadow
masker.save_tif(MASCARA, outfile)
self.cloud_mask = 'BQA'
print('Cloud Mask (BQA) generated in ' + str(t - time.time()) +
' seconds')
print('Calling get_water')
self.get_water()
except Exception as e:
print("Unexpected error:", type(e), e)
output_shadow_mask_path = "{0}/{1}/{1}_bqa_shadow_mask.TIF".format(
landsat_scenes_path, sceneID)
output_cloudshadow_mask_path = "{0}/{1}/{1}_bqa_cloudshadow_mask.TIF".format(
landsat_scenes_path, sceneID)
# load the QA band directly
#
# The "collection" parameter is required for landsat to specify the collection
# number. Acceptable number: 0 (pre-collection), 1 (collection-1)
masker = LandsatMasker(bqa_band_path, collection=1)
# algorithm has high confidence that this condition exists
# (67-100 percent confidence)
conf = LandsatConfidence.medium
# Get mask indicating cloud pixels with high confidence
cloud_mask = masker.get_cloud_mask(conf, cumulative=True)
# save the result
masker.save_tif(cloud_mask, output_cloud_mask_path)
if shadow:
# Get mask indicating cloud pixels with high confidence
cloud_shadow_mask = masker.get_cloud_shadow_mask(conf, cumulative=True)
masker.save_tif(cloud_shadow_mask, output_shadow_mask_path)
# Merge the Cloud and Cloud-Shadow mask
gdal_calc_string = "gdal_calc.py -A {} -B {} --outfile={} --calc='logical_or(A==1,B==1)'".format(
output_cloud_mask_path, output_shadow_mask_path,
output_cloudshadow_mask_path)
os.system(gdal_calc_string)
# Done
