def der_optical(dates):
client = Client(n_workers=12)
boi = ['red', 'blue', 'green', 'nir', 'swir1', 'swir2']
vars_loc = os.environ['WIN_SVR_DATA'] + 'Saldana/vars/'
files = list(filter(re.compile(r'^opt_.*').search, os.listdir(vars_loc)))
files = list(map(lambda x: vars_loc + x, files))
dataset = xr.open_mfdataset(files,
chunks={
'y': 1000,
'x': 750,
'time': -1
})
print('Concat Dataset\n')
print(dataset)
_location = os.environ['WIN_SVR_DATA'] + 'Saldana/features/'
itp.interpolate_dataset(dataset,
_location,
boi,
date_of_analysis=dates,
der=True)
print('Dataset interpolation done!\n')
def main_optical(dates):
saldana = regionstack.regionStack('Saldana', attrs=['S2', 'LC08'])
#saldana.harmonize_L8()
boi = ['red', 'blue', 'green', 'nir', 'swir1', 'swir2']
vars_loc = os.environ['WIN_SVR_DATA'] + 'Saldana/vars/'
for band in boi:
if not os.path.isfile(vars_loc + 'opt_' + band + '.nc'):
## TO-DO add isel for relevant dates
sentinel = saldana.S2[
band] #.isel(time=slice(min(dates)-120?D-security_margin, max(dates)+16D+security_margin))
landsat = saldana.LC08[
band] #.isel(time=slice(min(dates)-120?D, max(dates)+16D))
aligned = xr.align(sentinel, landsat, exclude={'time'})
da = xr.concat([aligned[0], aligned[1]], dim='time')
da.sortby('time').to_netcdf(vars_loc + 'opt_' + band + '.nc')
client = Client(n_workers=12)
client.upload_file('c_Class_Models/interpolatets.py')
files = list(filter(re.compile(r'^opt_.*').search, os.listdir(vars_loc)))
files = list(map(lambda x: vars_loc + x, files))
print('Reading concatenated Dataset')
dataset = xr.open_mfdataset(files,
chunks={
'y': 1000,
'x': 750,
'time': -1
})
print('Concat Dataset\n')
print(dataset)
_location = os.environ['WIN_SVR_DATA'] + 'Saldana/features/'
itp.interpolate_dataset(dataset,
_location,
boi,
date_of_analysis=dates,
der=False)
print('Dataset interpolation done!\n')
def main_radar_text(dates):
saldana = regionstack.regionStack(
'Saldana', attrs=['S1_ASCENDING_GLCM', 'S1_DESCENDING_GLCM'])
boi = [
'VV_ASM', 'VV_Contrast', 'VV_Dissimilarity', 'VV_Energy', 'VV_Entropy',
'VV_GLCMCorrelation', 'VV_GLCMMean', 'VV_GLCMVariance',
'VV_Homogeneity'
]
vars_loc = os.environ['WIN_SVR_DATA'] + 'Saldana/vars/'
for band in boi:
if not os.path.isfile(vars_loc + 'rad_' + band + '.nc'):
asc = saldana.S1_ASCENDING_GLCM[band]
dsc = saldana.S1_DESCENDING_GLCM[band]
da = xr.concat([asc, dsc], dim='time')
print('{} band was concatenated. Writing DataArray'.format(band))
da.to_netcdf(vars_loc + 'rad_' + band + '.nc')
client = Client(n_workers=12)
client.upload_file('b_Temporal_Stack/interpolatets.py')
files = list(filter(re.compile(r'^rad_.*').search, os.listdir(vars_loc)))
files = list(map(lambda x: vars_loc + x, files))
print('Reading concatenated Dataset')
dataset = xr.open_mfdataset(files,
chunks={
'y': 1000,
'x': 750,
'time': -1
})
print('Concat Dataset\n')
print(dataset)
_location = os.environ['WIN_SVR_DATA'] + 'Saldana/features/'
itp.interpolate_dataset(dataset, _location, boi, date_of_analysis=dates)
itp.interpolate_dataset(dataset,
_location,
boi,
date_of_analysis=dates,
der=True)