def getAuxdata(datasets, scenes):
auxDataPath = os.path.join(expanduser("~"), '.snap/auxdata')
scenes = [identify(scene) if isinstance(scene, str) else scene for scene in scenes]
sensors = list(set([scene.sensor for scene in scenes]))
for dataset in datasets:
if dataset == 'SRTM 1Sec HGT':
files = [x.replace('hgt', 'SRTMGL1.hgt.zip') for x in
list(set(dissolve([scene.getHGT() for scene in scenes])))]
for file in files:
infile = os.path.join('http://step.esa.int/auxdata/dem/SRTMGL1', file)
outfile = os.path.join(auxDataPath, 'dem/SRTM 1Sec HGT', file)
if not os.path.isfile(outfile):
print(infile)
try:
input = urlopen(infile)
except HTTPError:
print('-> not available')
continue
with open(outfile, 'wb') as output:
output.write(input.read())
input.close()
elif dataset == 'POEORB':
for sensor in sensors:
if re.search('S1[AB]', sensor):
dates = [(scene.start[:4], scene.start[4:6]) for scene in scenes]
years = list(set([x[0] for x in dates]))
remote_contentVersion = urlopen(
'http://step.esa.int/auxdata/orbits/Sentinel-1/POEORB/remote_contentVersion.txt')
versions_remote = getOrbitContentVersions(remote_contentVersion)
for year in years:
dir_orb = os.path.join(auxDataPath, 'Orbits/Sentinel-1/POEORB', year)
if not os.path.isdir(dir_orb):
os.makedirs(dir_orb)
contentVersionFile = os.path.join(dir_orb, 'contentVersion.txt')
if os.path.isfile(contentVersionFile):
contentVersion = open(contentVersionFile, 'r+')
versions_local = getOrbitContentVersions(contentVersion)
else:
contentVersion = open(contentVersionFile, 'w')
versions_local = {}
combine = dict(set(versions_local.items()) & set(versions_remote.items()))
dates_select = [x for x in dates if x[0] == year]
months = list(set([x[1] for x in dates_select]))
orb_ids = sorted(
[x for x in ['{}-{}.zip'.format(year, month) for month in months] if not x in combine])
if len(orb_ids) > 0:
contentVersion.write('#\n#{}\n'.format(strftime('%a %b %d %H:%M:%S %Z %Y', gmtime())))
for orb_id in orb_ids:
orb_remote = urlopen(
'http://step.esa.int/auxdata/orbits/Sentinel-1/POEORB/{}'.format(orb_id))
orb_remote_stream = zf.ZipFile(StringIO(orb_remote.read()), 'r')
orb_remote.close()
targets = [x for x in orb_remote_stream.namelist() if
not os.path.isfile(os.path.join(dir_orb, x))]
orb_remote_stream.extractall(dir_orb, targets)
orb_remote_stream.close()
versions_local[orb_id] = versions_remote[orb_id]
for key, val in versions_local.iteritems():
contentVersion.write('{}={}\n'.format(key, val))
contentVersion.close()
remote_contentVersion.close()
else:
print('not implemented yet')
elif dataset == 'Delft Precise Orbits':
path_server = 'dutlru2.lr.tudelft.nl'
subdirs = {'ASAR:': 'ODR.ENVISAT1/eigen-cg03c', 'ERS1': 'ODR.ERS-1/dgm-e04', 'ERS2': 'ODR.ERS-2/dgm-e04'}
ftp = FTP(path_server)
ftp.login()
for sensor in sensors:
if sensor in subdirs.keys():
path_target = os.path.join('pub/orbits', subdirs[sensor])
path_local = os.path.join(auxDataPath, 'Orbits/Delft Precise Orbits', subdirs[sensor])
ftp.cwd(path_target)
for item in ftp.nlst():
ftp.retrbinary('RETR ' + item, open(os.path.join(path_local, item), 'wb').write)
ftp.quit()
else:
print('not implemented yet')
def test_identify_fail(testdir, testdata):
with pytest.raises(OSError):
pyroSAR.identify(os.path.join(testdir, 'foobar'))
with pytest.raises(RuntimeError):
pyroSAR.identify(testdata['tif'])
def test_filter_processed(tmpdir, testdata):
scene = pyroSAR.identify(testdata['s1'])
assert len(pyroSAR.filter_processed([scene], str(tmpdir))) == 1
def gpt(xmlfile, groups=None, cleanup=True, gpt_exceptions=None):
"""
wrapper for ESA SNAP's Graph Processing Tool GPT.
Input is a readily formatted workflow XML file as
created by function :func:`~pyroSAR.snap.util.geocode`.
Additional to calling GPT, this function will
* execute the workflow in groups as defined by `groups`
* encode a nodata value into the output file if the format is GeoTiff-BigTIFF
* convert output files to GeoTiff if the output format is ENVI
Parameters
----------
xmlfile: str
the name of the workflow XML file
groups: list
a list of lists each containing IDs for individual nodes
cleanup: bool
should all files written to the temporary directory during function execution be deleted after processing?
gpt_exceptions: dict
a dictionary to override the configured GPT executable for certain operators;
each (sub-)workflow containing this operator will be executed with the define executable;
- e.g. ``{'Terrain-Flattening': '/home/user/snap/bin/gpt'}``
Returns
-------
"""
workflow = Workflow(xmlfile)
write = workflow['Write']
outname = write.parameters['file']
suffix = workflow.suffix
format = write.parameters['formatName']
dem_name = workflow.tree.find('.//demName').text
if dem_name == 'External DEM':
dem_nodata = float(
workflow.tree.find('.//externalDEMNoDataValue').text)
else:
dem_nodata = 0
if 'Remove-GRD-Border-Noise' in workflow.ids:
xmlfile = os.path.join(outname,
os.path.basename(xmlfile.replace('_bnr', '')))
if not os.path.isdir(outname):
os.makedirs(outname)
# border noise removal is done outside of SNAP and the node is thus removed from the workflow
del workflow['Remove-GRD-Border-Noise']
# remove the node name from the groups
i = 0
while i < len(groups) - 1:
if 'Remove-GRD-Border-Noise' in groups[i]:
del groups[i][groups[i].index('Remove-GRD-Border-Noise')]
if len(groups[i]) == 0:
del groups[i]
else:
i += 1
# identify the input scene, unpack it and perform the custom border noise removal
read = workflow['Read']
scene = identify(read.parameters['file'])
print('unpacking scene')
scene.unpack(outname)
print('removing border noise..')
scene.removeGRDBorderNoise()
# change the name of the input file to that of the unpacked archive
read.parameters['file'] = scene.scene
# write a new workflow file
workflow.write(xmlfile)
print('executing node sequence{}..'.format(
's' if groups is not None else ''))
if groups is not None:
subs = split(xmlfile, groups)
for sub in subs:
execute(sub, cleanup=cleanup, gpt_exceptions=gpt_exceptions)
else:
execute(xmlfile, cleanup=cleanup, gpt_exceptions=gpt_exceptions)
if format == 'ENVI':
print('converting to GTiff')
translateoptions = {
'options': ['-q', '-co', 'INTERLEAVE=BAND', '-co', 'TILED=YES'],
'format': 'GTiff'
}
for item in finder(outname, ['*.img'], recursive=False):
if re.search('[HV]{2}', item):
pol = re.search('[HV]{2}', item).group()
name_new = outname.replace(suffix,
'{0}_{1}.tif'.format(pol, suffix))
else:
base = os.path.splitext(os.path.basename(item))[0] \
.replace('elevation', 'DEM')
name_new = outname.replace(suffix, '{0}.tif'.format(base))
nodata = dem_nodata if re.search('elevation', item) else 0
translateoptions['noData'] = nodata
gdal_translate(item, name_new, translateoptions)
# by default the nodata value is not registered in the GTiff metadata
elif format == 'GeoTiff-BigTIFF':
ras = gdal.Open(outname + '.tif', GA_Update)
for i in range(1, ras.RasterCount + 1):
ras.GetRasterBand(i).SetNoDataValue(0)
ras = None
if cleanup:
shutil.rmtree(outname)
print('done')
'polarizations': ['HH', 'HV'],
'product': '1.5',
'samples': 12870,
'sensor': 'PSR2',
'spacing': (6.25, 6.25),
'start': '20140909T043342',
'stop': '20140909T043352'
}
}
return cases
@pytest.fixture
def scene(testcases, testdata, request):
case = testcases[request.param]
case['pyro'] = pyroSAR.identify(testdata[request.param])
return case
class Test_Metadata():
@pytest.mark.parametrize('scene', ['s1', 'psr2'], indirect=True)
def test_attributes(self, scene):
assert scene['pyro'].acquisition_mode == scene['acquisition_mode']
assert scene['pyro'].compression == scene['compression']
assert scene['pyro'].getCorners() == scene['corners']
assert scene['pyro'].lines == scene['lines']
assert scene['pyro'].outname_base() == scene['outname']
assert scene['pyro'].orbit == scene['orbit']
assert scene['pyro'].polarizations == scene['polarizations']
assert scene['pyro'].product == scene['product']
assert scene['pyro'].samples == scene['samples']
def split(xmlfile, groups):
"""
split a workflow file into groups and write them to separate workflows including source and write target linking.
The new workflows are written to a sub-directory `temp` of the target directory defined in the input's `Write` node.
Each new workflow is parameterized with a `Read` and `Write` node if they don't already exist. Temporary outputs are
written to `BEAM-DIMAP` files named after the workflow suffix sequence.
Parameters
----------
xmlfile: str
the workflow to be split
groups: list
a list of lists each containing IDs for individual nodes
Returns
-------
list of str
the names of the newly written temporary workflows
Raises
------
RuntimeError
"""
workflow = Workflow(xmlfile)
write = workflow['Write']
out = write.parameters['file']
tmp = os.path.join(out, 'temp')
if not os.path.isdir(tmp):
os.makedirs(tmp)
# the temporary XML files
outlist = []
# the names and format of temporary products
prod_tmp = {}
prod_tmp_format = {}
for position, group in enumerate(groups):
node_lookup = {}
log.debug('creating new workflow for group {}'.format(group))
new = parse_recipe('blank')
nodes = [workflow[x] for x in group]
for node in nodes:
id_old = node.id
sources = node.source
if sources is None:
sources = []
resetSuccessorSource = False
elif isinstance(sources, list):
resetSuccessorSource = False
else:
resetSuccessorSource = True
sources = [sources]
reset = []
for source in sources:
if source not in group:
read = new.insert_node(
parse_node('Read'),
void=False,
resetSuccessorSource=resetSuccessorSource)
reset.append(read.id)
read.parameters['file'] = prod_tmp[source]
read.parameters['formatName'] = prod_tmp_format[source]
node_lookup[read.id] = source
else:
reset.append(source)
if isinstance(sources, list):
sources_new_pos = [
list(node_lookup.values()).index(x) for x in sources
]
sources_new = [
list(node_lookup.keys())[x] for x in sources_new_pos
]
newnode = new.insert_node(node.copy(),
before=sources_new,
void=False,
resetSuccessorSource=False)
else:
newnode = new.insert_node(node.copy(),
void=False,
resetSuccessorSource=False)
node_lookup[newnode.id] = id_old
if not resetSuccessorSource:
newnode.source = reset
# if possible, read the name of the SAR product for parsing names of temporary files
# this was found necessary for SliceAssembly, which expects the names in a specific format
products = [x.parameters['file'] for x in new['operator=Read']]
try:
id = identify(products[0])
filename = os.path.basename(id.scene)
except (RuntimeError, OSError):
filename = os.path.basename(products[0])
basename = os.path.splitext(filename)[0]
basename = re.sub(r'_tmp[0-9]+', '', basename)
# add a Write node to all dangling nodes
counter = 0
for node in new:
dependants = [
x for x in workflow.successors(node.id)
if not x.startswith('Write') and not x in group
]
if node.operator != 'Read' and len(dependants) > 0:
write = parse_node('Write')
new.insert_node(write,
before=node.id,
resetSuccessorSource=False)
id = str(position) if counter == 0 else '{}-{}'.format(
position, counter)
tmp_out = os.path.join(tmp,
'{}_tmp{}.dim'.format(basename, id))
prod_tmp[node_lookup[node.id]] = tmp_out
prod_tmp_format[node_lookup[node.id]] = 'BEAM-DIMAP'
write.parameters['file'] = tmp_out
write.parameters['formatName'] = 'BEAM-DIMAP'
counter += 1
if not is_consistent(new):
message = 'inconsistent group:\n {}'.format(' -> '.join(group))
raise RuntimeError(message)
outname = os.path.join(tmp, '{}_tmp{}.xml'.format(basename, position))
new.write(outname)
outlist.append(outname)
return outlist
def geocode(infile, outdir, t_srs=4326, tr=20, polarizations='all', shapefile=None, scaling='dB',
geocoding_type='Range-Doppler', removeS1BorderNoise=True, removeS1BorderNoiseMethod='pyroSAR',
removeS1ThermalNoise=True, offset=None, allow_RES_OSV=False,
externalDEMFile=None, externalDEMNoDataValue=None, externalDEMApplyEGM=True, terrainFlattening=True,
basename_extensions=None, test=False, export_extra=None, groupsize=1, cleanup=True,
gpt_exceptions=None, gpt_args=None, returnWF=False, nodataValueAtSea=True,
demResamplingMethod='BILINEAR_INTERPOLATION', imgResamplingMethod='BILINEAR_INTERPOLATION',
speckleFilter=False, refarea='gamma0'):
"""
wrapper function for geocoding SAR images using ESA SNAP
Parameters
----------
infile: str or ~pyroSAR.drivers.ID or list
the SAR scene(s) to be processed; multiple scenes are treated as consecutive acquisitions, which will be
mosaicked with SNAP's SliceAssembly operator
outdir: str
The directory to write the final files to.
t_srs: int, str or osr.SpatialReference
A target geographic reference system in WKT, EPSG, PROJ4 or OPENGIS format.
See function :func:`spatialist.auxil.crsConvert()` for details.
Default: `4326 <http://spatialreference.org/ref/epsg/4326/>`_.
tr: int or float, optional
The target resolution in meters. Default is 20
polarizations: list or str
The polarizations to be processed; can be a string for a single polarization, e.g. 'VV', or a list of several
polarizations, e.g. ['VV', 'VH']. With the special value 'all' (default) all available polarizations are
processed.
shapefile: str or :py:class:`~spatialist.vector.Vector`, optional
A vector geometry for subsetting the SAR scene to a test site. Default is None.
scaling: {'dB', 'db', 'linear'}, optional
Should the output be in linear or decibel scaling? Default is 'dB'.
geocoding_type: {'Range-Doppler', 'SAR simulation cross correlation'}, optional
The type of geocoding applied; can be either 'Range-Doppler' (default) or 'SAR simulation cross correlation'
removeS1BorderNoise: bool, optional
Enables removal of S1 GRD border noise (default).
removeS1BorderNoiseMethod: str
the border noise removal method to be applied, See :func:`pyroSAR.S1.removeGRDBorderNoise` for details; one of the following:
- 'ESA': the pure implementation as described by ESA
- 'pyroSAR': the ESA method plus the custom pyroSAR refinement
removeS1ThermalNoise: bool, optional
Enables removal of S1 thermal noise (default).
offset: tuple, optional
A tuple defining offsets for left, right, top and bottom in pixels, e.g. (100, 100, 0, 0); this variable is
overridden if a shapefile is defined. Default is None.
allow_RES_OSV: bool
(only applies to Sentinel-1) Also allow the less accurate RES orbit files to be used?
The function first tries to download a POE file for the scene.
If this fails and RES files are allowed, it will download the RES file.
The selected OSV type is written to the workflow XML file.
Processing is aborted if the correction fails (Apply-Orbit-File parameter continueOnFail set to false).
externalDEMFile: str or None, optional
The absolute path to an external DEM file. Default is None.
externalDEMNoDataValue: int, float or None, optional
The no data value of the external DEM. If not specified (default) the function will try to read it from the
specified external DEM.
externalDEMApplyEGM: bool, optional
Apply Earth Gravitational Model to external DEM? Default is True.
terainFlattening: bool
apply topographic normalization on the data?
basename_extensions: list of str
names of additional parameters to append to the basename, e.g. ['orbitNumber_rel']
test: bool, optional
If set to True the workflow xml file is only written and not executed. Default is False.
export_extra: list or None
a list of image file IDs to be exported to outdir. The following IDs are currently supported:
- incidenceAngleFromEllipsoid
- localIncidenceAngle
- projectedLocalIncidenceAngle
- DEM
groupsize: int
the number of workers executed together in one gpt call
cleanup: bool
should all files written to the temporary directory during function execution be deleted after processing?
gpt_exceptions: dict
a dictionary to override the configured GPT executable for certain operators;
each (sub-)workflow containing this operator will be executed with the define executable;
- e.g. ``{'Terrain-Flattening': '/home/user/snap/bin/gpt'}``
gpt_args: list or None
a list of additional arguments to be passed to the gpt call
- e.g. ``['-x', '-c', '2048M']`` for increased tile cache size and intermediate clearing
returnWF: bool
return the full name of the written workflow XML file?
nodataValueAtSea: bool
mask pixels acquired over sea? The sea mask depends on the selected DEM.
demResamplingMethod: str
one of the following:
- 'NEAREST_NEIGHBOUR'
- 'BILINEAR_INTERPOLATION'
- 'CUBIC_CONVOLUTION'
- 'BISINC_5_POINT_INTERPOLATION'
- 'BISINC_11_POINT_INTERPOLATION'
- 'BISINC_21_POINT_INTERPOLATION'
- 'BICUBIC_INTERPOLATION'
imgResamplingMethod: str
the resampling method for geocoding the SAR image; the options are identical to demResamplingMethod
speckleFilter: str
one of the following:
- 'Boxcar'
- 'Median'
- 'Frost'
- 'Gamma Map'
- 'Refined Lee'
- 'Lee'
- 'Lee Sigma'
refarea: str
one of the following:
- 'beta0'
- 'gamma0'
- 'sigma0'
Returns
-------
str or None
either the name of the workflow file if `returnWF == True` or None otherwise
Note
----
If only one polarization is selected and not extra products are defined the results are directly written to GeoTiff.
Otherwise the results are first written to a folder containing ENVI files and then transformed to GeoTiff files
(one for each polarization/extra product).
If GeoTiff would directly be selected as output format for multiple polarizations then a multilayer GeoTiff
is written by SNAP which is considered an unfavorable format
.. figure:: figures/snap_geocode.png
:scale: 25%
:align: center
Workflow diagram for function geocode for processing a Sentinel-1 Ground Range
Detected (GRD) scene to radiometrically terrain corrected (RTC) backscatter.
An additional Subset node might be inserted in case a vector geometry is provided.
Examples
--------
geocode a Sentinel-1 scene and export the local incidence angle map with it
>>> from pyroSAR.snap import geocode
>>> filename = 'S1A_IW_GRDH_1SDV_20180829T170656_20180829T170721_023464_028DE0_F7BD.zip'
>>> geocode(infile=filename, outdir='outdir', tr=20, scaling='dB',
>>> export_extra=['DEM', 'localIncidenceAngle'], t_srs=4326)
See Also
--------
:class:`pyroSAR.drivers.ID`,
:class:`spatialist.vector.Vector`,
:func:`spatialist.auxil.crsConvert()`
"""
if isinstance(infile, pyroSAR.ID):
id = infile
elif isinstance(infile, str):
id = pyroSAR.identify(infile)
elif isinstance(infile, list):
ids = pyroSAR.identify_many(infile, verbose=False, sortkey='start')
id = ids[0]
else:
raise TypeError("'infile' must be of type str, list or pyroSAR.ID")
if id.is_processed(outdir):
print('scene {} already processed'.format(id.outname_base()))
return
# print(os.path.basename(id.scene))
if not os.path.isdir(outdir):
os.makedirs(outdir)
############################################
# general setup
if id.sensor in ['ASAR', 'ERS1', 'ERS2']:
formatName = 'ENVISAT'
elif id.sensor in ['S1A', 'S1B']:
id.getOSV()
if id.product == 'SLC':
raise RuntimeError('Sentinel-1 SLC data is not supported yet')
formatName = 'SENTINEL-1'
else:
raise RuntimeError('sensor not supported (yet)')
######################
# print('- assessing polarization selection')
if isinstance(polarizations, str):
if polarizations == 'all':
polarizations = id.polarizations
else:
if polarizations in id.polarizations:
polarizations = [polarizations]
else:
raise RuntimeError('polarization {} does not exists in the source product'.format(polarizations))
elif isinstance(polarizations, list):
polarizations = [x for x in polarizations if x in id.polarizations]
else:
raise RuntimeError('polarizations must be of type str or list')
format = 'GeoTiff-BigTIFF' if len(polarizations) == 1 and export_extra is None else 'ENVI'
# print(polarizations)
# print(format)
bandnames = dict()
bandnames['int'] = ['Intensity_' + x for x in polarizations]
bandnames['beta0'] = ['Beta0_' + x for x in polarizations]
bandnames['gamma0'] = ['Gamma0_' + x for x in polarizations]
bandnames['sigma0'] = ['Sigma0_' + x for x in polarizations]
############################################
############################################
# parse base workflow
# print('- parsing base workflow')
workflow = parse_recipe('base')
############################################
# Read node configuration
# print('-- configuring Read Node')
read = workflow['Read']
read.parameters['file'] = id.scene
read.parameters['formatName'] = formatName
readers = [read.id]
if isinstance(infile, list):
for i in range(1, len(infile)):
readn = parse_node('Read')
readn.parameters['file'] = ids[i].scene
readn.parameters['formatName'] = formatName
workflow.insert_node(readn, before=read.id, resetSuccessorSource=False)
readers.append(readn.id)
sliceAssembly = parse_node('SliceAssembly')
sliceAssembly.parameters['selectedPolarisations'] = polarizations
workflow.insert_node(sliceAssembly, before=readers)
read = sliceAssembly
############################################
# Remove-GRD-Border-Noise node configuration
# print('-- configuring Remove-GRD-Border-Noise Node')
if id.sensor in ['S1A', 'S1B'] and removeS1BorderNoise:
bn = parse_node('Remove-GRD-Border-Noise')
workflow.insert_node(bn, before=read.id)
bn.parameters['selectedPolarisations'] = polarizations
############################################
# ThermalNoiseRemoval node configuration
# print('-- configuring ThermalNoiseRemoval Node')
if id.sensor in ['S1A', 'S1B'] and removeS1ThermalNoise:
for reader in readers:
tn = parse_node('ThermalNoiseRemoval')
workflow.insert_node(tn, before=reader)
tn.parameters['selectedPolarisations'] = polarizations
############################################
# orbit file application node configuration
# print('-- configuring Apply-Orbit-File Node')
orbit_lookup = {'ENVISAT': 'DELFT Precise (ENVISAT, ERS1&2) (Auto Download)',
'SENTINEL-1': 'Sentinel Precise (Auto Download)'}
orbitType = orbit_lookup[formatName]
if formatName == 'ENVISAT' and id.acquisition_mode == 'WSM':
orbitType = 'DORIS Precise VOR (ENVISAT) (Auto Download)'
if formatName == 'SENTINEL-1':
match = id.getOSV(osvType='POE', returnMatch=True)
if match is None and allow_RES_OSV:
id.getOSV(osvType='RES')
orbitType = 'Sentinel Restituted (Auto Download)'
orb = workflow['Apply-Orbit-File']
orb.parameters['orbitType'] = orbitType
orb.parameters['continueOnFail'] = False
############################################
# calibration node configuration
# print('-- configuring Calibration Node')
cal = workflow['Calibration']
cal.parameters['selectedPolarisations'] = polarizations
cal.parameters['sourceBands'] = bandnames['int']
if terrainFlattening:
if refarea != 'gamma0':
raise RuntimeError('if terrain flattening is applied refarea must be gamma0')
cal.parameters['outputBetaBand'] = True
else:
refarea_options = ['sigma0', 'beta0', 'gamma0']
if refarea not in refarea_options:
message = '{0} must be one of the following:\n- {1}'
raise ValueError(message.format('refarea', '\n- '.join(refarea_options)))
cal.parameters['output{}Band'.format(refarea[:-1].capitalize())] = True
last = cal.id
############################################
# terrain flattening node configuration
# print('-- configuring Terrain-Flattening Node')
if terrainFlattening:
tf = parse_node('Terrain-Flattening')
workflow.insert_node(tf, before=last)
if id.sensor in ['ERS1', 'ERS2'] or (id.sensor == 'ASAR' and id.acquisition_mode != 'APP'):
tf.parameters['sourceBands'] = 'Beta0'
else:
tf.parameters['sourceBands'] = bandnames['beta0']
if externalDEMFile is None:
tf.parameters['reGridMethod'] = True
else:
tf.parameters['reGridMethod'] = False
last = tf.id
############################################
# speckle filtering node configuration
speckleFilter_options = ['Boxcar',
'Median',
'Frost',
'Gamma Map',
'Refined Lee',
'Lee',
'Lee Sigma']
if speckleFilter:
message = '{0} must be one of the following:\n- {1}'
if speckleFilter not in speckleFilter_options:
raise ValueError(message.format('speckleFilter', '\n- '.join(speckleFilter_options)))
sf = parse_node('Speckle-Filter')
workflow.insert_node(sf, before=last)
sf.parameters['sourceBands'] = bandnames[refarea]
sf.parameters['filter'] = speckleFilter
last = sf.id
############################################
# configuration of node sequence for specific geocoding approaches
# print('-- configuring geocoding approach Nodes')
if geocoding_type == 'Range-Doppler':
tc = parse_node('Terrain-Correction')
workflow.insert_node(tc, before=last)
tc.parameters['sourceBands'] = bandnames[refarea]
elif geocoding_type == 'SAR simulation cross correlation':
sarsim = parse_node('SAR-Simulation')
workflow.insert_node(sarsim, before=last)
sarsim.parameters['sourceBands'] = bandnames[refarea]
workflow.insert_node(parse_node('Cross-Correlation'), before='SAR-Simulation')
tc = parse_node('SARSim-Terrain-Correction')
workflow.insert_node(tc, before='Cross-Correlation')
else:
raise RuntimeError('geocode_type not recognized')
############################################
# Multilook node configuration
try:
image_geometry = id.meta['image_geometry']
incidence = id.meta['incidence']
except KeyError:
raise RuntimeError('This function does not yet support sensor {}'.format(id.sensor))
rlks, azlks = multilook_factors(sp_rg=id.spacing[0],
sp_az=id.spacing[1],
tr_rg=tr,
tr_az=tr,
geometry=image_geometry,
incidence=incidence)
if azlks > 1 or rlks > 1:
workflow.insert_node(parse_node('Multilook'), before='Calibration')
ml = workflow['Multilook']
ml.parameters['nAzLooks'] = azlks
ml.parameters['nRgLooks'] = rlks
ml.parameters['sourceBands'] = None
# if cal.parameters['outputBetaBand']:
# ml.parameters['sourceBands'] = bandnames['beta0']
# elif cal.parameters['outputGammaBand']:
# ml.parameters['sourceBands'] = bandnames['gamma0']
# elif cal.parameters['outputSigmaBand']:
# ml.parameters['sourceBands'] = bandnames['sigma0']
############################################
# specify spatial resolution and coordinate reference system of the output dataset
# print('-- configuring CRS')
tc.parameters['pixelSpacingInMeter'] = tr
try:
t_srs = crsConvert(t_srs, 'epsg')
except TypeError:
raise RuntimeError("format of parameter 't_srs' not recognized")
# the EPSG code 4326 is not supported by SNAP and thus the WKT string has to be defined;
# in all other cases defining EPSG:{code} will do
if t_srs == 4326:
t_srs = 'GEOGCS["WGS84(DD)",' \
'DATUM["WGS84",' \
'SPHEROID["WGS84", 6378137.0, 298.257223563]],' \
'PRIMEM["Greenwich", 0.0],' \
'UNIT["degree", 0.017453292519943295],' \
'AXIS["Geodetic longitude", EAST],' \
'AXIS["Geodetic latitude", NORTH]]'
else:
t_srs = 'EPSG:{}'.format(t_srs)
tc.parameters['mapProjection'] = t_srs
############################################
# (optionally) add node for conversion from linear to db scaling
# print('-- configuring LinearToFromdB Node')
if scaling not in ['dB', 'db', 'linear']:
raise RuntimeError('scaling must be a string of either "dB", "db" or "linear"')
if scaling in ['dB', 'db']:
lin2db = parse_node('lin2db')
workflow.insert_node(lin2db, before=tc.id)
lin2db.parameters['sourceBands'] = bandnames[refarea]
############################################
# (optionally) add subset node and add bounding box coordinates of defined shapefile
# print('-- configuring Subset Node')
if shapefile:
# print('--- read')
shp = shapefile.clone() if isinstance(shapefile, Vector) else Vector(shapefile)
# reproject the geometry to WGS 84 latlon
# print('--- reproject')
shp.reproject(4326)
ext = shp.extent
shp.close()
# add an extra buffer of 0.01 degrees
buffer = 0.01
ext['xmin'] -= buffer
ext['ymin'] -= buffer
ext['xmax'] += buffer
ext['ymax'] += buffer
# print('--- create bbox')
with bbox(ext, 4326) as bounds:
# print('--- intersect')
inter = intersect(id.bbox(), bounds)
if not inter:
raise RuntimeError('no bounding box intersection between shapefile and scene')
# print('--- close intersect')
inter.close()
# print('--- get wkt')
wkt = bounds.convert2wkt()[0]
# print('--- parse XML node')
subset = parse_node('Subset')
# print('--- insert node')
workflow.insert_node(subset, before=read.id)
subset.parameters['region'] = [0, 0, id.samples, id.lines]
subset.parameters['geoRegion'] = wkt
############################################
# (optionally) configure subset node for pixel offsets
if offset and not shapefile:
subset = parse_node('Subset')
workflow.insert_node(subset, before=read.id)
# left, right, top and bottom offset in pixels
l, r, t, b = offset
subset_values = [l, t, id.samples - l - r, id.lines - t - b]
subset.parameters['region'] = subset_values
subset.parameters['geoRegion'] = ''
############################################
# parametrize write node
# print('-- configuring Write Node')
# create a suffix for the output file to identify processing steps performed in the workflow
suffix = workflow.suffix
basename = os.path.join(outdir, id.outname_base(basename_extensions))
extension = suffix if format == 'ENVI' else polarizations[0] + '_' + suffix
outname = basename + '_' + extension
write = workflow['Write']
write.parameters['file'] = outname
write.parameters['formatName'] = format
############################################
############################################
if export_extra is not None:
options = ['incidenceAngleFromEllipsoid',
'localIncidenceAngle',
'projectedLocalIncidenceAngle',
'DEM']
write = parse_node('Write')
workflow.insert_node(write, before=tc.id, resetSuccessorSource=False)
write.parameters['file'] = outname
write.parameters['formatName'] = format
for item in export_extra:
if item not in options:
raise RuntimeError("ID '{}' not valid for argument 'export_extra'".format(item))
key = 'save{}{}'.format(item[0].upper(), item[1:])
tc.parameters[key] = True
############################################
############################################
# select DEM type
# print('-- configuring DEM')
dempar = {'externalDEMFile': externalDEMFile,
'externalDEMApplyEGM': externalDEMApplyEGM}
if externalDEMFile is not None:
if os.path.isfile(externalDEMFile):
if externalDEMNoDataValue is None:
with Raster(externalDEMFile) as dem:
dempar['externalDEMNoDataValue'] = dem.nodata
if dempar['externalDEMNoDataValue'] is None:
raise RuntimeError('Cannot read NoData value from DEM file. '
'Please specify externalDEMNoDataValue')
else:
dempar['externalDEMNoDataValue'] = externalDEMNoDataValue
dempar['reGridMethod'] = False
else:
raise RuntimeError('specified externalDEMFile does not exist')
dempar['demName'] = 'External DEM'
else:
# SRTM 1arcsec is only available between -58 and +60 degrees.
# If the scene exceeds those latitudes SRTM 3arcsec is selected.
if id.getCorners()['ymax'] > 60 or id.getCorners()['ymin'] < -58:
dempar['demName'] = 'SRTM 3Sec'
else:
dempar['demName'] = 'SRTM 1Sec HGT'
dempar['externalDEMFile'] = None
dempar['externalDEMNoDataValue'] = 0
for key, value in dempar.items():
workflow.set_par(key, value)
# download the EGM lookup table if necessary
if dempar['externalDEMApplyEGM']:
get_egm96_lookup()
############################################
############################################
# configure the resampling methods
options = ['NEAREST_NEIGHBOUR',
'BILINEAR_INTERPOLATION',
'CUBIC_CONVOLUTION',
'BISINC_5_POINT_INTERPOLATION',
'BISINC_11_POINT_INTERPOLATION',
'BISINC_21_POINT_INTERPOLATION',
'BICUBIC_INTERPOLATION']
message = '{0} must be one of the following:\n- {1}'
if demResamplingMethod not in options:
raise ValueError(message.format('demResamplingMethod', '\n- '.join(options)))
if imgResamplingMethod not in options:
raise ValueError(message.format('imgResamplingMethod', '\n- '.join(options)))
workflow.set_par('demResamplingMethod', demResamplingMethod)
workflow.set_par('imgResamplingMethod', imgResamplingMethod)
############################################
############################################
# additional parameter settings applied to the whole workflow
workflow.set_par('nodataValueAtSea', nodataValueAtSea)
############################################
############################################
# write workflow to file and optionally execute it
# print('- writing workflow to file')
workflow.write(outname + '_proc')
# execute the newly written workflow
if not test:
try:
groups = groupbyWorkers(outname + '_proc.xml', groupsize)
gpt(outname + '_proc.xml', groups=groups, cleanup=cleanup,
gpt_exceptions=gpt_exceptions, gpt_args=gpt_args,
removeS1BorderNoiseMethod=removeS1BorderNoiseMethod)
except RuntimeError as e:
print(str(e))
with open(outname + '_error.log', 'w') as log:
log.write(str(e))
if returnWF:
return outname + '_proc.xml'
def test_filter_processed():
scene = pyroSAR.identify(testfile1)
outdir = 'pyroSAR/tests'
assert len(pyroSAR.filter_processed([scene], outdir)) == 1
def gpt(xmlfile,
groups=None,
cleanup=True,
gpt_exceptions=None,
gpt_args=None,
removeS1BorderNoiseMethod='pyroSAR',
basename_extensions=None):
"""
wrapper for ESA SNAP's Graph Processing Tool GPT.
Input is a readily formatted workflow XML file as
created by function :func:`~pyroSAR.snap.util.geocode`.
Additional to calling GPT, this function will
* execute the workflow in groups as defined by `groups`
* encode a nodata value into the output file if the format is GeoTiff-BigTIFF
* convert output files to GeoTiff if the output format is ENVI
Parameters
----------
xmlfile: str
the name of the workflow XML file
groups: list
a list of lists each containing IDs for individual nodes
cleanup: bool
should all files written to the temporary directory during function execution be deleted after processing?
gpt_exceptions: dict
a dictionary to override the configured GPT executable for certain operators;
each (sub-)workflow containing this operator will be executed with the define executable;
- e.g. ``{'Terrain-Flattening': '/home/user/snap/bin/gpt'}``
gpt_args: list or None
a list of additional arguments to be passed to the gpt call
- e.g. ``['-x', '-c', '2048M']`` for increased tile cache size and intermediate clearing
removeS1BorderNoiseMethod: str
the border noise removal method to be applied, See :func:`pyroSAR.S1.removeGRDBorderNoise` for details; one of the following:
- 'ESA': the pure implementation as described by ESA
- 'pyroSAR': the ESA method plus the custom pyroSAR refinement
basename_extensions: list of str
names of additional parameters to append to the basename, e.g. ['orbitNumber_rel']
Returns
-------
Raises
------
RuntimeError
"""
workflow = Workflow(xmlfile)
read = workflow['Read']
write = workflow['Write']
scene = identify(read.parameters['file'])
outname = write.parameters['file']
suffix = workflow.suffix
format = write.parameters['formatName']
dem_name = workflow.tree.find('.//demName')
if dem_name is not None:
if dem_name.text == 'External DEM':
dem_nodata = float(
workflow.tree.find('.//externalDEMNoDataValue').text)
else:
dem_nodata = 0
if 'Remove-GRD-Border-Noise' in workflow.ids \
and removeS1BorderNoiseMethod == 'pyroSAR' \
and scene.meta['IPF_version'] < 2.9:
if 'SliceAssembly' in workflow.operators:
raise RuntimeError(
"pyroSAR's custom border noise removal is not yet implemented for multiple scene inputs"
)
xmlfile = os.path.join(outname,
os.path.basename(xmlfile.replace('_bnr', '')))
os.makedirs(outname, exist_ok=True)
# border noise removal is done outside of SNAP and the node is thus removed from the workflow
del workflow['Remove-GRD-Border-Noise']
# remove the node name from the groups
i = 0
while i < len(groups) - 1:
if 'Remove-GRD-Border-Noise' in groups[i]:
del groups[i][groups[i].index('Remove-GRD-Border-Noise')]
if len(groups[i]) == 0:
del groups[i]
else:
i += 1
# unpack the scene if necessary and perform the custom border noise removal
print('unpacking scene')
if scene.compression is not None:
scene.unpack(outname)
print('removing border noise..')
scene.removeGRDBorderNoise(method=removeS1BorderNoiseMethod)
# change the name of the input file to that of the unpacked archive
read.parameters['file'] = scene.scene
# write a new workflow file
workflow.write(xmlfile)
print('executing node sequence{}..'.format(
's' if groups is not None else ''))
try:
if groups is not None:
subs = split(xmlfile, groups)
for sub in subs:
execute(sub,
cleanup=cleanup,
gpt_exceptions=gpt_exceptions,
gpt_args=gpt_args)
else:
execute(xmlfile,
cleanup=cleanup,
gpt_exceptions=gpt_exceptions,
gpt_args=gpt_args)
except RuntimeError as e:
if cleanup and os.path.exists(outname):
shutil.rmtree(outname, onerror=windows_fileprefix)
raise RuntimeError(str(e) + '\nfailed: {}'.format(xmlfile))
if format == 'ENVI':
print('converting to GTiff')
translateoptions = {
'options': ['-q', '-co', 'INTERLEAVE=BAND', '-co', 'TILED=YES'],
'format': 'GTiff'
}
for item in finder(outname, ['*.img'], recursive=False):
if re.search('[HV]{2}', item):
pol = re.search('[HV]{2}', item).group()
name_new = outname.replace(suffix,
'{0}_{1}.tif'.format(pol, suffix))
else:
base = os.path.splitext(os.path.basename(item))[0] \
.replace('elevation', 'DEM')
name_new = outname.replace(suffix, '{0}.tif'.format(base))
nodata = dem_nodata if re.search('elevation', item) else 0
translateoptions['noData'] = nodata
gdal_translate(item, name_new, translateoptions)
# by default the nodata value is not registered in the GTiff metadata
elif format == 'GeoTiff-BigTIFF':
ras = gdal.Open(outname + '.tif', GA_Update)
for i in range(1, ras.RasterCount + 1):
ras.GetRasterBand(i).SetNoDataValue(0)
ras = None
###########################################################################
# write the Sentinel-1 manifest.safe file as addition to the actual product
readers = workflow['operator=Read']
for reader in readers:
infile = reader.parameters['file']
try:
id = identify(infile)
if id.sensor in ['S1A', 'S1B']:
manifest = id.getFileObj(id.findfiles('manifest.safe')[0])
basename = id.outname_base(basename_extensions)
basename = '{0}_{1}_manifest.safe'.format(basename, suffix)
outdir = os.path.dirname(outname)
outname_manifest = os.path.join(outdir, basename)
with open(outname_manifest, 'wb') as out:
out.write(manifest.read())
except RuntimeError:
continue
###########################################################################
if cleanup and os.path.exists(outname):
shutil.rmtree(outname, onerror=windows_fileprefix)
print('done')
def test_infile_type(self, tmpdir, testdata):
scene = testdata['s1']
with pytest.raises(TypeError):
geocode(infile=123, outdir=str(tmpdir), test=True)
id = identify(scene)
geocode(infile=id, outdir=str(tmpdir), test=True)
def geocode(infile, outdir, t_srs=4326, tr=20, polarizations='all', shapefile=None, scaling='dB',
geocoding_type='Range-Doppler', removeS1BoderNoise=True, offset=None, externalDEMFile=None,
externalDEMNoDataValue=None, externalDEMApplyEGM=True, test=False):
"""
wrapper function for geocoding SAR images using ESA SNAP
Parameters
----------
infile: str or ~pyroSAR.drivers.ID
the SAR scene to be processed
outdir: str
The directory to write the final files to.
t_srs: int, str or osr.SpatialReference
A target geographic reference system in WKT, EPSG, PROJ4 or OPENGIS format.
See function :func:`spatialist.auxil.crsConvert()` for details.
Default: `4326 <http://spatialreference.org/ref/epsg/4326/>`_.
tr: int or float, optional
The target resolution in meters. Default is 20
polarizations: list or {'VV', 'HH', 'VH', 'HV', 'all'}, optional
The polarizations to be processed; can be a string for a single polarization e.g. 'VV' or a list of several
polarizations e.g. ['VV', 'VH']. Default is 'all'.
shapefile: str or :py:class:`~spatialist.vector.Vector`, optional
A vector geometry for subsetting the SAR scene to a test site. Default is None.
scaling: {'dB', 'db', 'linear'}, optional
Should the output be in linear or decibel scaling? Default is 'dB'.
geocoding_type: {'Range-Doppler', 'SAR simulation cross correlation'}, optional
The type of geocoding applied; can be either 'Range-Doppler' (default) or 'SAR simulation cross correlation'
removeS1BoderNoise: bool, optional
Enables removal of S1 GRD border noise (default).
offset: tuple, optional
A tuple defining offsets for left, right, top and bottom in pixels, e.g. (100, 100, 0, 0); this variable is
overridden if a shapefile is defined. Default is None.
externalDEMFile: str or None, optional
The absolute path to an external DEM file. Default is None.
externalDEMNoDataValue: int, float or None, optional
The no data value of the external DEM. If not specified (default) the function will try to read it from the
specified external DEM.
externalDEMApplyEGM: bool, optional
Apply Earth Gravitational Model to external DEM? Default is True.
test: bool, optional
If set to True the workflow xml file is only written and not executed. Default is False.
Note
----
If only one polarization is selected the results are directly written to GeoTiff.
Otherwise the results are first written to a folder containing ENVI files and then transformed to GeoTiff files
(one for each polarization).
If GeoTiff would directly be selected as output format for multiple polarizations then a multilayer GeoTiff
is written by SNAP which is considered an unfavorable format
See Also
--------
:class:`pyroSAR.drivers.ID`,
:class:`spatialist.vector.Vector`,
:func:`spatialist.auxil.crsConvert()`
"""
id = infile if isinstance(infile, pyroSAR.ID) else pyroSAR.identify(infile)
if id.is_processed(outdir):
print('scene {} already processed'.format(id.outname_base()))
return
############################################
# general setup
if id.sensor in ['ASAR', 'ERS1', 'ERS2']:
formatName = 'ENVISAT'
elif id.sensor in ['S1A', 'S1B']:
if id.product == 'SLC':
raise RuntimeError('Sentinel-1 SLC data is not supported yet')
formatName = 'SENTINEL-1'
else:
raise RuntimeError('sensor not supported (yet)')
if polarizations == 'all':
polarizations = id.polarizations
else:
polarizations = [x for x in polarizations if x in id.polarizations]
print("Polarizations:", polarizations)
format = 'GeoTiff-BigTIFF' if len(polarizations) == 1 else 'ENVI'
############################################
# parse base workflow
workflow = parse_recipe('geocode')
############################################
# Read node configuration
read = workflow.find('.//node[@id="Read"]')
read.find('.//parameters/file').text = id.scene
read.find('.//parameters/formatName').text = formatName
############################################
# Remove-GRD-Border-Noise node configuration
if id.sensor in ['S1A', 'S1B'] and removeS1BoderNoise:
insert_node(workflow, 'Read', parse_node('Remove-GRD-Border-Noise'))
bn = workflow.find('.//node[@id="Remove-GRD-Border-Noise"]')
bn.find('.//parameters/selectedPolarisations').text = ','.join(polarizations)
############################################
# orbit file application node configuration
orbit_lookup = {'ENVISAT': 'DELFT Precise (ENVISAT, ERS1&2) (Auto Download)',
'SENTINEL-1': 'Sentinel Precise (Auto Download)'}
orbitType = orbit_lookup[formatName]
if formatName == 'ENVISAT' and id.acquisition_mode == 'WSM':
orbitType = 'DORIS Precise VOR (ENVISAT) (Auto Download)'
orb = workflow.find('.//node[@id="Apply-Orbit-File"]')
orb.find('.//parameters/orbitType').text = orbitType
############################################
# calibration node configuration
cal = workflow.find('.//node[@id="Calibration"]')
cal.find('.//parameters/selectedPolarisations').text = ','.join(polarizations)
cal.find('.//parameters/sourceBands').text = ','.join(['Intensity_' + x for x in polarizations])
############################################
# terrain flattening node configuration
tf = workflow.find('.//node[@id="Terrain-Flattening"]')
if id.sensor in ['ERS1', 'ERS2'] or (id.sensor == 'ASAR' and id.acquisition_mode != 'APP'):
tf.find('.//parameters/sourceBands').text = 'Beta0'
else:
tf.find('.//parameters/sourceBands').text = ','.join(['Beta0_' + x for x in polarizations])
############################################
# configuration of node sequence for specific geocoding approaches
if geocoding_type == 'Range-Doppler':
insert_node(workflow, 'Terrain-Flattening', parse_node('Terrain-Correction'))
tc = workflow.find('.//node[@id="Terrain-Correction"]')
tc.find('.//parameters/sourceBands').text = ','.join(['Gamma0_' + x for x in polarizations])
elif geocoding_type == 'SAR simulation cross correlation':
insert_node(workflow, 'Terrain-Flattening', parse_node('SAR-Simulation'))
insert_node(workflow, 'SAR-Simulation', parse_node('Cross-Correlation'))
insert_node(workflow, 'Cross-Correlation', parse_node('SARSim-Terrain-Correction'))
tc = workflow.find('.//node[@id="SARSim-Terrain-Correction"]')
sarsim = workflow.find('.//node[@id="SAR-Simulation"]')
sarsim.find('.//parameters/sourceBands').text = ','.join(['Gamma0_' + x for x in polarizations])
else:
raise RuntimeError('geocode_type not recognized')
tc.find('.//parameters/pixelSpacingInMeter').text = str(tr)
try:
t_srs = spatial.crsConvert(t_srs, 'epsg')
except TypeError:
raise RuntimeError("format of parameter 't_srs' not recognized")
if t_srs == 4326:
t_srs = 'GEOGCS["WGS84(DD)",' \
'DATUM["WGS84",' \
'SPHEROID["WGS84", 6378137.0, 298.257223563]],' \
'PRIMEM["Greenwich", 0.0],' \
'UNIT["degree", 0.017453292519943295],' \
'AXIS["Geodetic longitude", EAST],' \
'AXIS["Geodetic latitude", NORTH]]'
else:
t_srs = 'EPSG:{}'.format(t_srs)
tc.find('.//parameters/mapProjection').text = t_srs
############################################
# add node for conversion from linear to db scaling
if scaling not in ['dB', 'db', 'linear']:
raise RuntimeError('scaling must be a string of either "dB", "db" or "linear"')
if scaling in ['dB', 'db']:
lin2db = parse_node('lin2db')
sourceNode = 'Terrain-Correction' if geocoding_type == 'Range-Doppler' else 'SARSim-Terrain-Correction'
insert_node(workflow, sourceNode, lin2db)
lin2db = workflow.find('.//node[@id="LinearToFromdB"]')
lin2db.find('.//parameters/sourceBands').text = ','.join(['Gamma0_' + x for x in polarizations])
############################################
# add subset node and add bounding box coordinates of defined shapefile
if shapefile:
shp = shapefile if isinstance(shapefile, spatial.vector.Vector) else spatial.vector.Vector(shapefile)
bounds = spatial.bbox(shp.extent, shp.wkt)
bounds.reproject(id.projection)
intersect = spatial.intersect(id.bbox(), bounds)
if not intersect:
raise RuntimeError('no bounding box intersection between shapefile and scene')
wkt = bounds.convert2wkt()[0]
subset = parse_node('Subset')
insert_node(workflow, 'Read', subset)
subset = workflow.find('.//node[@id="Subset"]')
subset.find('.//parameters/region').text = ','.join(map(str, [0, 0, id.samples, id.lines]))
subset.find('.//parameters/geoRegion').text = wkt
############################################
# configure subset node for pixel offsets
if offset and not shapefile:
subset = parse_node('Subset')
insert_node(workflow, 'Read', subset)
# left, right, top and bottom offset in pixels
l, r, t, b = offset
subset = workflow.find('.//node[@id="Subset"]')
subset.find('.//parameters/region').text = ','.join(map(str, [l, t, id.samples - l - r, id.lines - t - b]))
subset.find('.//parameters/geoRegion').text = ''
############################################
# parametrize write node
# create a suffix for the output file to identify processing steps performed in the workflow
suffix = parse_suffix(workflow)
if format == 'ENVI':
outname = os.path.join(outdir, id.outname_base() + '_' + suffix)
else:
outname = os.path.join(outdir, '{}_{}_{}'.format(id.outname_base(), polarizations[0], suffix))
write = workflow.find('.//node[@id="Write"]')
write.find('.//parameters/file').text = outname
write.find('.//parameters/formatName').text = format
############################################
############################################
# select DEM type
if externalDEMFile is not None:
if os.path.isfile(externalDEMFile):
if externalDEMNoDataValue is None:
dem = spatial.raster.Raster(externalDEMFile)
if dem.nodata is not None:
externalDEMNoDataValue = dem.nodata
else:
raise RuntimeError('Cannot read NoData value from DEM file. Please specify externalDEMNoDataValue')
else:
raise RuntimeError('specified externalDEMFile does not exist')
demname = 'External DEM'
else:
# SRTM 1arcsec is only available between -58 and +60 degrees.
# If the scene exceeds those latitudes SRTM 3arcsec is selected.
if id.getCorners()['ymax'] > 60 or id.getCorners()['ymin'] < -58:
demname = 'SRTM 3Sec'
else:
demname = 'SRTM 1Sec HGT'
externalDEMFile = None
externalDEMNoDataValue = 0
for demName in workflow.findall('.//parameters/demName'):
demName.text = demname
for externalDEM in workflow.findall('.//parameters/externalDEMFile'):
externalDEM.text = externalDEMFile
for demNodata in workflow.findall('.//parameters/externalDEMNoDataValue'):
demNodata.text = str(externalDEMNoDataValue)
for egm in workflow.findall('.//parameters/externalDEMApplyEGM'):
egm.text = str(externalDEMApplyEGM).lower()
############################################
############################################
# write workflow to file
write_recipe(workflow, outname + '_proc')
# execute the newly written workflow
if not test:
try:
gpt(outname + '_proc.xml')
except RuntimeError:
os.remove(outname + '_proc.xml')
def test_identify_fail():
with pytest.raises(IOError):
pyroSAR.identify(os.path.join(testdir, 'foobar'))
def main(s1_archive,
out_path,
t_srs='utm',
tr=10,
polarization='all',
bbox=None,
shapefile=None,
scaling='db',
geocoding_type='Range-Doppler',
remove_s1_border_noise=True,
remove_s1_thermal_noise=False,
offset_left=None,
offset_right=None,
offset_top=None,
offset_bottom=None,
external_dem_file=None,
external_dem_no_data_value=None,
external_dem_apply_egm=True,
terrain_flattening=True,
basename_extension=None,
test=False,
export_extra=None,
group_size=2,
cleanup=True,
return_wf=False):
# identify the scene from input archive
print("Identifying S1 scene from input archive.")
scene = pyroSAR.identify(s1_archive)
print("Success")
# deal with offsets
offset = (offset_left, offset_right, offset_top, offset_bottom)
if set(offset) == set([None]):
offset = None
if t_srs.lower() == 'utm':
# get the bbox
scene_extent = scene.bbox().extent
scene_bbox = box(scene_extent['xmin'], scene_extent['ymin'],
scene_extent['xmax'], scene_extent['ymax'])
# get the lat and long from the aoi centroid
long = scene_bbox.centroid.x
lat = scene_bbox.centroid.y
# use the longitude to get the utm zone (3rd element in returned list
c = utm.from_latlon(lat, long)
utm_zone = c[2]
# build the epsg code
if lat >= 0.0:
t_srs = int("326%s" % (str(utm_zone)))
else:
t_srs = int("327%s" % (str(utm_zone)))
else:
# try to convert to an integer -- if it doesn't work, leave as is
try:
t_srs = int(t_srs)
except ValueError:
pass
# deal with basename extensions
if basename_extension is None:
basename_extensions = None
else:
basename_extensions = [basename_extension]
# deal with export_extra
if export_extra is not None:
export_extra = list(map(str, export_extra.split(',')))
# make the output directory if it doesn't exist
if os.path.exists(out_path) is False:
os.mkdir(out_path)
# if bbox is provided, convert to format expected by pyroSAR
if bbox is not None:
bbox = map(float, bbox.split(','))
shapefile = spatialist.bbox(
dict(zip(['xmin', 'ymin', 'xmax', 'ymax'], bbox)),
crs=spatialist.auxil.crsConvert(4326, 'epsg'))
print("Geocoding image according to input options.")
geocode(infile=scene,
outdir=out_path,
t_srs=t_srs,
tr=tr,
polarizations=[polarization],
shapefile=shapefile,
scaling=scaling,
geocoding_type=geocoding_type,
removeS1BoderNoise=remove_s1_border_noise,
removeS1ThermalNoise=remove_s1_thermal_noise,
offset=offset,
externalDEMFile=external_dem_file,
externalDEMNoDataValue=external_dem_no_data_value,
externalDEMApplyEGM=external_dem_apply_egm,
terrainFlattening=terrain_flattening,
basename_extensions=basename_extensions,
test=test,
export_extra=export_extra,
groupsize=group_size,
cleanup=cleanup,
returnWF=return_wf)
print("Processing completed successfully.")
def geocode(infile,
outdir,
t_srs=4326,
tr=20,
polarizations='all',
shapefile=None,
scaling='dB',
geocoding_type='Range-Doppler',
removeS1BoderNoise=True,
removeS1ThermalNoise=True,
offset=None,
externalDEMFile=None,
externalDEMNoDataValue=None,
externalDEMApplyEGM=True,
basename_extensions=None,
test=False,
export_extra=None,
groupsize=2,
cleanup=True):
"""
wrapper function for geocoding SAR images using ESA SNAP
Parameters
----------
infile: str or ~pyroSAR.drivers.ID
the SAR scene to be processed
outdir: str
The directory to write the final files to.
t_srs: int, str or osr.SpatialReference
A target geographic reference system in WKT, EPSG, PROJ4 or OPENGIS format.
See function :func:`spatialist.auxil.crsConvert()` for details.
Default: `4326 <http://spatialreference.org/ref/epsg/4326/>`_.
tr: int or float, optional
The target resolution in meters. Default is 20
polarizations: list or {'VV', 'HH', 'VH', 'HV', 'all'}, optional
The polarizations to be processed; can be a string for a single polarization e.g. 'VV' or a list of several
polarizations e.g. ['VV', 'VH']. Default is 'all'.
shapefile: str or :py:class:`~spatialist.vector.Vector`, optional
A vector geometry for subsetting the SAR scene to a test site. Default is None.
scaling: {'dB', 'db', 'linear'}, optional
Should the output be in linear or decibel scaling? Default is 'dB'.
geocoding_type: {'Range-Doppler', 'SAR simulation cross correlation'}, optional
The type of geocoding applied; can be either 'Range-Doppler' (default) or 'SAR simulation cross correlation'
removeS1BoderNoise: bool, optional
Enables removal of S1 GRD border noise (default).
removeS1ThermalNoise: bool, optional
Enables removal of S1 thermal noise (default).
offset: tuple, optional
A tuple defining offsets for left, right, top and bottom in pixels, e.g. (100, 100, 0, 0); this variable is
overridden if a shapefile is defined. Default is None.
externalDEMFile: str or None, optional
The absolute path to an external DEM file. Default is None.
externalDEMNoDataValue: int, float or None, optional
The no data value of the external DEM. If not specified (default) the function will try to read it from the
specified external DEM.
externalDEMApplyEGM: bool, optional
Apply Earth Gravitational Model to external DEM? Default is True.
basename_extensions: list of str
names of additional parameters to append to the basename, e.g. ['orbitNumber_rel']
test: bool, optional
If set to True the workflow xml file is only written and not executed. Default is False.
export_extra: list or None
a list of image file IDs to be exported to outdir. The following IDs are currently supported:
* incidenceAngleFromEllipsoid
* localIncidenceAngle
* projectedLocalIncidenceAngle
* DEM
groupsize: int
the number of workers executed together in one gpt call
cleanup: bool
should all files written to the temporary directory during function execution be deleted after processing?
Note
----
If only one polarization is selected and not extra products are defined the results are directly written to GeoTiff.
Otherwise the results are first written to a folder containing ENVI files and then transformed to GeoTiff files
(one for each polarization/extra product).
If GeoTiff would directly be selected as output format for multiple polarizations then a multilayer GeoTiff
is written by SNAP which is considered an unfavorable format
Examples
--------
geocode a Sentinel-1 scene and export the local incidence angle map with it
>>> from pyroSAR.snap import geocode
>>> filename = 'S1A_IW_GRDH_1SDV_20180829T170656_20180829T170721_023464_028DE0_F7BD.zip'
>>> geocode(infile=filename, outdir='outdir', tr=20, scaling='dB',
>>> export_extra=['DEM', 'localIncidenceAngle'], t_srs=4326)
See Also
--------
:class:`pyroSAR.drivers.ID`,
:class:`spatialist.vector.Vector`,
:func:`spatialist.auxil.crsConvert()`
"""
id = infile if isinstance(infile, pyroSAR.ID) else pyroSAR.identify(infile)
if id.is_processed(outdir):
print('scene {} already processed'.format(id.outname_base()))
return
# print(os.path.basename(id.scene))
if not os.path.isdir(outdir):
os.makedirs(outdir)
############################################
# general setup
if id.sensor in ['ASAR', 'ERS1', 'ERS2']:
formatName = 'ENVISAT'
elif id.sensor in ['S1A', 'S1B']:
if id.product == 'SLC':
raise RuntimeError('Sentinel-1 SLC data is not supported yet')
formatName = 'SENTINEL-1'
else:
raise RuntimeError('sensor not supported (yet)')
######################
# print('- assessing polarization selection')
if isinstance(polarizations, str):
if polarizations == 'all':
polarizations = id.polarizations
else:
if polarizations in id.polarizations:
polarizations = [polarizations]
else:
raise RuntimeError(
'polarization {} does not exists in the source product'.
format(polarizations))
elif isinstance(polarizations, list):
polarizations = [x for x in polarizations if x in id.polarizations]
else:
raise RuntimeError('polarizations must be of type str or list')
format = 'GeoTiff-BigTIFF' if len(
polarizations) == 1 and export_extra is None else 'ENVI'
# print(polarizations)
# print(format)
bands_int = ['Intensity_' + x for x in polarizations]
bands_beta = ['Beta0_' + x for x in polarizations]
bands_gamma = ['Gamma0_' + x for x in polarizations]
############################################
############################################
# parse base workflow
# print('- parsing base workflow')
workflow = parse_recipe('geocode')
############################################
# Read node configuration
# print('-- configuring Read Node')
read = workflow['Read']
read.parameters['file'] = id.scene
read.parameters['formatName'] = formatName
############################################
# Remove-GRD-Border-Noise node configuration
# print('-- configuring Remove-GRD-Border-Noise Node')
if id.sensor in ['S1A', 'S1B'] and removeS1BoderNoise:
bn = parse_node('Remove-GRD-Border-Noise')
workflow.insert_node(bn, before='Read')
bn.parameters['selectedPolarisations'] = polarizations
############################################
# ThermalNoiseRemoval node configuration
# print('-- configuring ThermalNoiseRemoval Node')
if id.sensor in ['S1A', 'S1B'] and removeS1ThermalNoise:
tn = parse_node('ThermalNoiseRemoval')
workflow.insert_node(tn, before='Read')
tn.parameters['selectedPolarisations'] = polarizations
############################################
# orbit file application node configuration
# print('-- configuring Apply-Orbit-File Node')
orbit_lookup = {
'ENVISAT': 'DELFT Precise (ENVISAT, ERS1&2) (Auto Download)',
'SENTINEL-1': 'Sentinel Precise (Auto Download)'
}
orbitType = orbit_lookup[formatName]
if formatName == 'ENVISAT' and id.acquisition_mode == 'WSM':
orbitType = 'DORIS Precise VOR (ENVISAT) (Auto Download)'
orb = workflow['Apply-Orbit-File']
orb.parameters['orbitType'] = orbitType
############################################
# calibration node configuration
# print('-- configuring Calibration Node')
cal = workflow['Calibration']
cal.parameters['selectedPolarisations'] = polarizations
cal.parameters['sourceBands'] = bands_int
############################################
# terrain flattening node configuration
# print('-- configuring Terrain-Flattening Node')
tf = workflow['Terrain-Flattening']
if id.sensor in ['ERS1', 'ERS2'] or (id.sensor == 'ASAR'
and id.acquisition_mode != 'APP'):
tf.parameters['sourceBands'] = 'Beta0'
else:
tf.parameters['sourceBands'] = bands_beta
############################################
# configuration of node sequence for specific geocoding approaches
# print('-- configuring geocoding approach Nodes')
if geocoding_type == 'Range-Doppler':
tc = parse_node('Terrain-Correction')
workflow.insert_node(tc, before='Terrain-Flattening')
tc.parameters['sourceBands'] = bands_gamma
elif geocoding_type == 'SAR simulation cross correlation':
sarsim = parse_node('SAR-Simulation')
workflow.insert_node(sarsim, before='Terrain-Flattening')
sarsim.parameters['sourceBands'] = bands_gamma
workflow.insert_node(parse_node('Cross-Correlation'),
before='SAR-Simulation')
tc = parse_node('SARSim-Terrain-Correction')
workflow.insert_node(tc, before='Cross-Correlation')
else:
raise RuntimeError('geocode_type not recognized')
############################################
# Multilook node configuration
try:
image_geometry = id.meta['image_geometry']
incidence = id.meta['incidence']
except KeyError:
raise RuntimeError(
'This function does not yet support sensor {}'.format(id.sensor))
rlks, azlks = multilook_factors(sp_rg=id.spacing[0],
sp_az=id.spacing[1],
tr_rg=tr,
tr_az=tr,
geometry=image_geometry,
incidence=incidence)
if azlks > 1 or rlks > 1:
workflow.insert_node(parse_node('Multilook'), after=tf.id)
ml = workflow['Multilook']
ml.parameters['sourceBands'] = bands_beta
ml.parameters['nAzLooks'] = azlks
ml.parameters['nRgLooks'] = rlks
############################################
# specify spatial resolution and coordinate reference system of the output dataset
# print('-- configuring CRS')
tc.parameters['pixelSpacingInMeter'] = tr
try:
t_srs = crsConvert(t_srs, 'epsg')
except TypeError:
raise RuntimeError("format of parameter 't_srs' not recognized")
# the EPSG code 4326 is not supported by SNAP and thus the WKT string has to be defined;
# in all other cases defining EPSG:{code} will do
if t_srs == 4326:
t_srs = 'GEOGCS["WGS84(DD)",' \
'DATUM["WGS84",' \
'SPHEROID["WGS84", 6378137.0, 298.257223563]],' \
'PRIMEM["Greenwich", 0.0],' \
'UNIT["degree", 0.017453292519943295],' \
'AXIS["Geodetic longitude", EAST],' \
'AXIS["Geodetic latitude", NORTH]]'
else:
t_srs = 'EPSG:{}'.format(t_srs)
tc.parameters['mapProjection'] = t_srs
############################################
# (optionally) add node for conversion from linear to db scaling
# print('-- configuring LinearToFromdB Node')
if scaling not in ['dB', 'db', 'linear']:
raise RuntimeError(
'scaling must be a string of either "dB", "db" or "linear"')
if scaling in ['dB', 'db']:
lin2db = parse_node('lin2db')
sourceNode = 'Terrain-Correction' if geocoding_type == 'Range-Doppler' else 'SARSim-Terrain-Correction'
workflow.insert_node(lin2db, before=sourceNode)
lin2db.parameters['sourceBands'] = bands_gamma
############################################
# (optionally) add subset node and add bounding box coordinates of defined shapefile
# print('-- configuring Subset Node')
if shapefile:
# print('--- read')
shp = shapefile.clone() if isinstance(shapefile,
Vector) else Vector(shapefile)
# reproject the geometry to WGS 84 latlon
# print('--- reproject')
shp.reproject(4326)
ext = shp.extent
shp.close()
# add an extra buffer of 0.01 degrees
buffer = 0.01
ext['xmin'] -= buffer
ext['ymin'] -= buffer
ext['xmax'] += buffer
ext['ymax'] += buffer
# print('--- create bbox')
with bbox(ext, 4326) as bounds:
# print('--- intersect')
inter = intersect(id.bbox(), bounds)
if not inter:
raise RuntimeError(
'no bounding box intersection between shapefile and scene')
# print('--- close intersect')
inter.close()
# print('--- get wkt')
wkt = bounds.convert2wkt()[0]
# print('--- parse XML node')
subset = parse_node('Subset')
# print('--- insert node')
workflow.insert_node(subset, before='Read')
subset.parameters['region'] = [0, 0, id.samples, id.lines]
subset.parameters['geoRegion'] = wkt
############################################
# (optionally) configure subset node for pixel offsets
if offset and not shapefile:
subset = parse_node('Subset')
workflow.insert_node(subset, before='Read')
# left, right, top and bottom offset in pixels
l, r, t, b = offset
subset_values = [l, t, id.samples - l - r, id.lines - t - b]
subset.parameters['region'] = subset_values
subset.parameters['geoRegion'] = ''
############################################
# parametrize write node
# print('-- configuring Write Node')
# create a suffix for the output file to identify processing steps performed in the workflow
suffix = workflow.suffix
basename = os.path.join(outdir, id.outname_base(basename_extensions))
extension = suffix if format == 'ENVI' else polarizations[0] + '_' + suffix
outname = basename + '_' + extension
write = workflow['Write']
write.parameters['file'] = outname
write.parameters['formatName'] = format
############################################
############################################
if export_extra is not None:
options = [
'incidenceAngleFromEllipsoid', 'localIncidenceAngle',
'projectedLocalIncidenceAngle', 'DEM'
]
write = parse_node('Write')
workflow.insert_node(write, before=tc.id, resetSuccessorSource=False)
write.parameters['file'] = outname
write.parameters['formatName'] = format
for item in export_extra:
if item not in options:
raise RuntimeError(
"ID '{}' not valid for argument 'export_extra'".format(
item))
key = 'save{}{}'.format(item[0].upper(), item[1:])
tc.parameters[key] = True
############################################
############################################
# select DEM type
# print('-- configuring DEM')
dempar = {
'externalDEMFile': externalDEMFile,
'externalDEMApplyEGM': externalDEMApplyEGM
}
if externalDEMFile is not None:
if os.path.isfile(externalDEMFile):
if externalDEMNoDataValue is None:
with Raster(externalDEMFile) as dem:
dempar['externalDEMNoDataValue'] = dem.nodata
if dempar['externalDEMNoDataValue'] is None:
raise RuntimeError(
'Cannot read NoData value from DEM file. '
'Please specify externalDEMNoDataValue')
else:
dempar['externalDEMNoDataValue'] = externalDEMNoDataValue
else:
raise RuntimeError('specified externalDEMFile does not exist')
dempar['demName'] = 'External DEM'
else:
# SRTM 1arcsec is only available between -58 and +60 degrees.
# If the scene exceeds those latitudes SRTM 3arcsec is selected.
if id.getCorners()['ymax'] > 60 or id.getCorners()['ymin'] < -58:
dempar['demName'] = 'SRTM 3Sec'
else:
dempar['demName'] = 'SRTM 1Sec HGT'
dempar['externalDEMFile'] = None
dempar['externalDEMNoDataValue'] = 0
for node in workflow.nodes():
for key, value in dempar.items():
if key in node.parameters.keys():
node.parameters[key] = value
############################################
############################################
# write workflow to file and optionally execute it
# print('- writing workflow to file')
workflow.write(outname + '_proc')
# execute the newly written workflow
if not test:
try:
groups = groupbyWorkers(outname + '_proc.xml', groupsize)
gpt(outname + '_proc.xml', groups=groups, cleanup=cleanup)
except RuntimeError:
if cleanup:
os.remove(outname + '_proc.xml')
