def wkt2shp(wkt, srs, outname):
"""
convert a well-known text string geometry to a shapefile.
Parameters
----------
wkt: str
the well-known text description
srs: int, str
the spatial reference system; see :func:`spatialist.auxil.crsConvert` for options.
outname: str
the name of the shapefile to write
Returns
-------
"""
geom = ogr.CreateGeometryFromWkt(wkt)
geom.FlattenTo2D()
srs = crsConvert(srs, 'osr')
layername = os.path.splitext(os.path.basename(outname))[0]
with Vector(driver='Memory') as bbox:
bbox.addlayer(layername, srs, geom.GetGeometryType())
bbox.addfield('area', ogr.OFTReal)
bbox.addfeature(geom, fields={'area': geom.Area()})
bbox.write(outname, format='ESRI Shapefile')
geom = None
def main():
# define a shapefile for the study area
shp = '/.../testsite.shp'
# define the output name of the DEM (no file extension like .tif etc.!)
outname = '/path/to/demfile'
# define a buffer around the study area boundaries (in degrees)
buffer = 0.01
# load the defined shapefile
with Vector(shp) as site:
# reproject the shapefile to latlon (in-memory, no file written or modified)
site.reproject(4326)
# create the DEM mosaic in Gamma format including tile download, warping to arbitrary CRS and resolution,
# and conversion from geoid to ellipsoid heights
# documentation: https://pyrosar.readthedocs.io/en/latest/pyroSAR.html#pyroSAR.gamma.dem.dem_autocreate
dem_autocreate(
geometry=site,
outfile=outname,
buffer=buffer,
demType='SRTM 1Sec HGT',
t_srs=32632, # WGS84, UTM 32N
tr=(20, 20), # 20 m target resolution in both x and y
geoid_mode=
'gamma', # convert from EGM96 geoid to WGS84 ellipsoid heights using Gamma
resampling_method='bilinear')
def test_archive_postgres(tmpdir, testdata):
pguser = os.environ.get('PGUSER')
pgpassword = os.environ.get('PGPASSWORD')
id = pyroSAR.identify(testdata['s1'])
db = pyroSAR.Archive('test',
postgres=True,
port=5432,
user=pguser,
password=pgpassword)
db.insert(testdata['s1'], verbose=False)
assert all(isinstance(x, str) for x in db.get_tablenames())
assert all(isinstance(x, str) for x in db.get_colnames())
assert db.is_registered(testdata['s1']) is True
assert len(db.get_unique_directories()) == 1
assert db.select_duplicates() == []
assert db.select_duplicates(outname_base='S1A__IW___A_20150222T170750',
scene='scene.zip') == []
assert len(db.select(mindate='20141001T192312',
maxdate='20201001T192312')) == 1
assert len(db.select(polarizations=['VV'])) == 1
assert len(db.select(vectorobject=id.bbox())) == 1
assert len(
db.select(sensor='S1A',
vectorobject='foo',
processdir=str(tmpdir),
verbose=True)) == 1
assert len(
db.select(sensor='S1A', mindate='foo', maxdate='bar',
foobar='foobar')) == 1
out = db.select(vv=1, acquisition_mode=('IW', 'EW'))
assert len(out) == 1
assert isinstance(out[0], str)
db.add_tables(mytable)
assert 'mytable' in db.get_tablenames()
with pytest.raises(IOError):
db.filter_scenelist([1])
db.close()
with pyroSAR.Archive('test',
postgres=True,
port=5432,
user=pguser,
password=pgpassword) as db:
assert db.size == (1, 0)
shp = os.path.join(str(tmpdir), 'db.shp')
db.export2shp(shp)
db.drop_database()
assert Vector(shp).nfeatures == 1
with pytest.raises(OSError):
with pyroSAR.Archive('test',
postgres=True,
port=5432,
user=pguser,
password=pgpassword) as db:
db.import_outdated(testdata['archive_old'])
db.drop_database()
with pytest.raises(SystemExit) as pytest_wrapped_e:
pyroSAR.Archive('test', postgres=True, user='******', port=7080)
assert pytest_wrapped_e.type == SystemExit
def test_archive2(tmpdir, testdata):
dbfile = os.path.join(str(tmpdir), 'scenes.db')
with pyroSAR.Archive(dbfile) as db:
db.insert(testdata['s1'], verbose=False)
assert db.size == (1, 0)
shp = os.path.join(str(tmpdir), 'db.shp')
db.export2shp(shp)
os.remove(dbfile)
assert not os.path.isfile(dbfile)
assert Vector(shp).nfeatures == 1
with pytest.raises(OSError):
with pyroSAR.Archive(dbfile) as db:
db.import_outdated(testdata['archive_old'])
def test_archive(tmpdir, testdata):
id = pyroSAR.identify(testdata['s1'])
dbfile = os.path.join(str(tmpdir), 'scenes.db')
db = pyroSAR.Archive(dbfile)
db.insert(testdata['s1'], verbose=False)
assert all(isinstance(x, str) for x in db.get_tablenames())
assert all(isinstance(x, str) for x in db.get_colnames())
assert db.is_registered(testdata['s1']) is True
assert len(db.get_unique_directories()) == 1
assert db.select_duplicates() == []
assert db.select_duplicates(outname_base='S1A__IW___A_20150222T170750',
scene='scene.zip') == []
assert len(db.select(mindate='20141001T192312',
maxdate='20201001T192312')) == 1
assert len(db.select(polarizations=['VV'])) == 1
assert len(db.select(vectorobject=id.bbox())) == 1
assert len(
db.select(sensor='S1A',
vectorobject='foo',
processdir=str(tmpdir),
verbose=True)) == 1
assert len(
db.select(sensor='S1A', mindate='foo', maxdate='bar',
foobar='foobar')) == 1
out = db.select(vv=1, acquisition_mode=('IW', 'EW'))
assert len(out) == 1
assert isinstance(out[0], str)
db.insert(testdata['s1_3'], verbose=False)
db.insert(testdata['s1_4'], verbose=False)
db.drop_element(testdata['s1_3'])
assert db.size == (2, 0)
db.drop_element(testdata['s1_4'])
db.add_tables(mytable)
assert 'mytable' in db.get_tablenames()
with pytest.raises(IOError):
db.filter_scenelist([1])
db.close()
with pyroSAR.Archive(dbfile) as db:
assert db.size == (1, 0)
shp = os.path.join(str(tmpdir), 'db.shp')
db.export2shp(shp)
pyroSAR.drop_archive(db)
assert not os.path.isfile(dbfile)
assert Vector(shp).nfeatures == 1
with pytest.raises(OSError):
with pyroSAR.Archive(dbfile) as db:
db.import_outdated(testdata['archive_old'])
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,
demName='SRTM 1Sec HGT',
externalDEMFile=None,
externalDEMNoDataValue=None,
externalDEMApplyEGM=True,
terrainFlattening=True,
basename_extensions=None,
test=False,
export_extra=None,
groupsize=1,
cleanup=True,
tmpdir=None,
gpt_exceptions=None,
gpt_args=None,
returnWF=False,
nodataValueAtSea=True,
demResamplingMethod='BILINEAR_INTERPOLATION',
imgResamplingMethod='BILINEAR_INTERPOLATION',
alignToStandardGrid=False,
standardGridOriginX=0,
standardGridOriginY=0,
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` or dict or None
A vector geometry for subsetting the SAR scene to a test site.
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).
demName: str
the name of the auto-download DEM. Default is 'SRTM 1Sec HGT'. Is ignored when `externalDEMFile` is not None.
externalDEMFile: str or None, optional
The absolute path to an external DEM file. Default is None. Overrides `demName`.
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.
terrainFlattening: bool
apply topographic normalization on the data?
basename_extensions: list of str or None
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
- layoverShadowMask
- scatteringArea
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?
tmpdir: str or None
path of custom temporary directory, useful to separate output folder and temp folder. If `None`, the `outdir`
location will be used. The created subdirectory will be deleted after processing.
gpt_exceptions: dict or None
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 or list
'sigma0', 'gamma0' or a list of both
alignToStandardGrid: bool
align all processed images to a common grid?
standardGridOriginX: int or float
the x origin value for grid alignment
standardGridOriginY: int or float
the y origin value for grid alignment
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']:
if id.product == 'SLC':
raise RuntimeError('Sentinel-1 SLC data is not supported yet')
formatName = 'SENTINEL-1'
else:
raise RuntimeError('sensor not supported (yet)')
# several options like resampling are modified globally for the whole workflow at the end of this function
# this list gathers IDs of nodes for which this should not be done because they are configured individually
resampling_exceptions = []
######################
# 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')
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 isinstance(refarea, str):
refarea = [refarea]
if terrainFlattening:
if 'gamma0' not in refarea:
raise RuntimeError(
'if terrain flattening is applied refarea must be gamma0')
cal.parameters['outputBetaBand'] = True
if 'sigma0' in refarea:
cal.parameters['outputSigmaBand'] = True
else:
refarea_options = ['sigma0', 'gamma0']
for opt in refarea:
if opt 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(opt[:-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 'reGridMethod' in tf.parameters.keys():
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'] = None
sf.parameters['filter'] = speckleFilter
last = sf.id
############################################
# configuration of node sequence for specific geocoding approaches
bands = dissolve([bandnames[opt] for opt in refarea])
if geocoding_type == 'Range-Doppler':
tc = parse_node('Terrain-Correction')
workflow.insert_node(tc, before=last)
tc.parameters['sourceBands'] = bands
elif geocoding_type == 'SAR simulation cross correlation':
sarsim = parse_node('SAR-Simulation')
workflow.insert_node(sarsim, before=last)
sarsim.parameters['sourceBands'] = bands
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')
tc.parameters['alignToStandardGrid'] = alignToStandardGrid
tc.parameters['standardGridOriginX'] = standardGridOriginX
tc.parameters['standardGridOriginY'] = standardGridOriginY
############################################
# 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
############################################
# merge sigma0 and gamma0 bands to pass them to Terrain-Correction
if len(refarea) > 1 and terrainFlattening:
bm = parse_node('BandMerge')
workflow.insert_node(bm, before=[tf.source, tf.id])
sources = bm.source
gamma_index = sources.index('Terrain-Flattening')
sigma_index = abs(gamma_index - 1)
s1_id = os.path.basename(os.path.splitext(id.scene)[0])
bands_long = []
for band in bands:
comp = [band + '::']
if shapefile is not None:
comp.append('Subset_')
comp.append(s1_id)
if band.startswith('Gamma'):
comp.append('_' + workflow.suffix(stop=sources[gamma_index]))
else:
comp.append('_' + workflow.suffix(stop=sources[sigma_index]))
bands_long.append(''.join(comp))
bm.parameters['sourceBands'] = bands_long
bm.parameters['geographicError'] = 0.0
############################################
# 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('LinearToFromdB')
workflow.insert_node(lin2db, before=tc.id)
lin2db.parameters['sourceBands'] = bands
############################################
# (optionally) add subset node and add bounding box coordinates of defined shapefile
# print('-- configuring Subset Node')
if shapefile:
# print('--- read')
if isinstance(shapefile, dict):
ext = shapefile
else:
if isinstance(shapefile, Vector):
shp = shapefile.clone()
elif isinstance(shapefile, str):
shp = Vector(shapefile)
else:
raise TypeError(
"argument 'shapefile' must be either a dictionary, a Vector object or a string."
)
# reproject the geometry to WGS 84 latlon
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')
inter.close()
wkt = bounds.convert2wkt()[0]
subset = parse_node('Subset')
workflow.insert_node(subset, before=read.id)
subset.parameters['region'] = [0, 0, id.samples, id.lines]
subset.parameters['geoRegion'] = wkt
subset.parameters['copyMetadata'] = True
############################################
# (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()
if tmpdir is None:
tmpdir = outdir
basename = os.path.join(tmpdir, id.outname_base(basename_extensions))
outname = basename + '_' + suffix
write = workflow['Write']
write.parameters['file'] = outname
write.parameters['formatName'] = 'ENVI'
############################################
############################################
if export_extra is not None:
tc_options = [
'incidenceAngleFromEllipsoid', 'localIncidenceAngle',
'projectedLocalIncidenceAngle', 'DEM'
]
tc_write = None
tc_selection = []
for item in export_extra:
if item in tc_options:
if tc_write is None:
tc_write = parse_node('Write')
workflow.insert_node(tc_write,
before=tc.id,
resetSuccessorSource=False)
tc_write.parameters['file'] = outname
tc_write.parameters['formatName'] = 'ENVI'
key = 'save{}{}'.format(item[0].upper(), item[1:])
tc.parameters[key] = True
tc_selection.append(item)
elif item == 'layoverShadowMask':
sarsim = parse_node('SAR-Simulation')
sarsim.parameters['saveLayoverShadowMask'] = True
workflow.insert_node(sarsim,
after=tc.id,
resetSuccessorSource=False)
sarsim_select = parse_node('BandSelect')
sarsim_select.parameters['sourceBands'] = 'layover_shadow_mask'
workflow.insert_node(sarsim_select,
before=sarsim.id,
resetSuccessorSource=False)
sarsim_tc = parse_node('Terrain-Correction')
workflow.insert_node(sarsim_tc, before=sarsim_select.id)
sarsim_tc.parameters[
'alignToStandardGrid'] = alignToStandardGrid
sarsim_tc.parameters[
'standardGridOriginX'] = standardGridOriginX
sarsim_tc.parameters[
'standardGridOriginY'] = standardGridOriginY
sarsim_tc.parameters[
'imgResamplingMethod'] = 'NEAREST_NEIGHBOUR'
resampling_exceptions.append(sarsim_tc.id)
sarsim_write = parse_node('Write')
sarsim_write.parameters['file'] = outname
sarsim_write.parameters['formatName'] = 'ENVI'
workflow.insert_node(sarsim_write,
before=sarsim_tc.id,
resetSuccessorSource=False)
elif item == 'scatteringArea':
area_select = parse_node('BandSelect')
workflow.insert_node(area_select,
before=tf.source,
resetSuccessorSource=False)
area_select.parameters['sourceBands'] = bandnames['beta0']
area_merge1 = parse_node('BandMerge')
workflow.insert_node(area_merge1,
before=[tf.id, area_select.id],
resetSuccessorSource=False)
math = parse_node('BandMaths')
math.element.attrib[
'class'] = '"com.bc.ceres.binding.dom.XppDomElement"'
workflow.insert_node(math,
before=area_merge1.id,
resetSuccessorSource=False)
# math = parse_node('BandMaths')
# workflow.insert_node(math, before=[tf.id, area_select.id], resetSuccessorSource=False)
math.parameters.clear_variables()
exp = math.parameters['targetBands'][0]
exp['name'] = 'scatteringArea_VV'
exp['type'] = 'float32'
exp['expression'] = 'Beta0_VV / Gamma0_VV'
exp['noDataValue'] = 0.0
area_merge2 = parse_node('BandMerge')
workflow.insert_node(area_merge2,
before=[tf.id, math.id],
resetSuccessorSource=False)
tc.source = area_merge2.id
# modify Terrain-Correction source bands
tc_bands = tc.parameters['sourceBands'] + ',scatteringArea_VV'
tc.parameters['sourceBands'] = tc_bands
# add scattering Area to list of band directly written from Terrain-Correction
tc_selection.append('scatteringArea_VV')
else:
raise RuntimeError(
"ID '{}' not valid for argument 'export_extra'".format(
item))
if len(tc_selection) > 0:
tc_select = parse_node('BandSelect')
workflow.insert_node(tc_select, after=tc_write.id)
tc_select.parameters['sourceBands'] = tc_selection
############################################
############################################
# 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:
dempar['demName'] = demName
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,
exceptions=resampling_exceptions)
############################################
############################################
# 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')
wf_name = outname.replace(tmpdir, outdir) + '_proc.xml'
workflow.write(wf_name)
# execute the newly written workflow
if not test:
try:
groups = groupbyWorkers(wf_name, groupsize)
gpt(wf_name,
groups=groups,
cleanup=cleanup,
gpt_exceptions=gpt_exceptions,
gpt_args=gpt_args,
removeS1BorderNoiseMethod=removeS1BorderNoiseMethod,
outdir=outdir)
except RuntimeError as e:
print(str(e))
with open(wf_name.replace('_proc.xml', '_error.log'), 'w') as log:
log.write(str(e))
if returnWF:
return wf_name
def geocode(infile, outdir, t_srs=4326, tr=20, polarizations='all', shapefile=None, scaling='dB',
geocoding_type='Range-Doppler', removeS1BorderNoise=True, removeS1ThermalNoise=True, offset=None,
externalDEMFile=None, externalDEMNoDataValue=None, externalDEMApplyEGM=True, terrainFlattening=True,
basename_extensions=None, test=False, export_extra=None, groupsize=2, cleanup=True,
gpt_exceptions=None, returnWF=False,
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
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'
removeS1BorderNoise: 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.
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'}``
returnWF: bool
return the full name of the written workflow XML file?
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()`
"""
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)
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
############################################
# 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')
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'] = 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')
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
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)
############################################
############################################
# 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)
############################################
############################################
# 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)
except RuntimeError as e:
if cleanup:
if os.path.isdir(outname):
shutil.rmtree(outname)
elif os.path.isfile(outname):
os.remove(outname)
os.remove(outname + '_proc.xml')
with open(outname + '_error.log', 'w') as log:
log.write(str(e))
if returnWF:
return outname + '_proc.xml'
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, basename_extensions=None, 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.
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.
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
# 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 else 'ENVI'
# print(polarizations)
# print(format)
bands_int = ','.join(['Intensity_' + x for x in polarizations])
bands_beta = ','.join(['Beta0_' + x for x in polarizations])
bands_gamma = ','.join(['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.find('.//node[@id="Read"]')
read.find('.//parameters/file').text = id.scene
read.find('.//parameters/formatName').text = formatName
############################################
# Remove-GRD-Border-Noise node configuration
# print('-- configuring Remove-GRD-Border-Noise Node')
if id.sensor in ['S1A', 'S1B'] and removeS1BoderNoise:
insert_node(workflow, parse_node('Remove-GRD-Border-Noise'), before='Read')
bn = workflow.find('.//node[@id="Remove-GRD-Border-Noise"]')
bn.find('.//parameters/selectedPolarisations').text = ','.join(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.find('.//node[@id="Apply-Orbit-File"]')
orb.find('.//parameters/orbitType').text = orbitType
############################################
# calibration node configuration
# print('-- configuring Calibration Node')
cal = workflow.find('.//node[@id="Calibration"]')
cal.find('.//parameters/selectedPolarisations').text = ','.join(polarizations)
cal.find('.//parameters/sourceBands').text = bands_int
############################################
# terrain flattening node configuration
# print('-- configuring Terrain-Flattening Node')
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 = bands_beta
############################################
# configuration of node sequence for specific geocoding approaches
# print('-- configuring geocoding approach Nodes')
if geocoding_type == 'Range-Doppler':
insert_node(workflow, parse_node('Terrain-Correction'), before='Terrain-Flattening')
tc = workflow.find('.//node[@id="Terrain-Correction"]')
tc.find('.//parameters/sourceBands').text = bands_gamma
elif geocoding_type == 'SAR simulation cross correlation':
insert_node(workflow, parse_node('SAR-Simulation'), before='Terrain-Flattening')
insert_node(workflow, parse_node('Cross-Correlation'), before='SAR-Simulation')
insert_node(workflow, parse_node('SARSim-Terrain-Correction'), before='Cross-Correlation')
tc = workflow.find('.//node[@id="SARSim-Terrain-Correction"]')
sarsim = workflow.find('.//node[@id="SAR-Simulation"]')
sarsim.find('.//parameters/sourceBands').text = bands_gamma
else:
raise RuntimeError('geocode_type not recognized')
############################################
# specify spatial resolution and coordinate reference system of the output dataset
# print('-- configuring CRS')
tc.find('.//parameters/pixelSpacingInMeter').text = str(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.find('.//parameters/mapProjection').text = 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'
insert_node(workflow, lin2db, before=sourceNode)
lin2db = workflow.find('.//node[@id="LinearToFromdB"]')
lin2db.find('.//parameters/sourceBands').text = bands_gamma
############################################
# (optionally) add subset node and add bounding box coordinates of defined shapefile
# print('-- configuring Subset Node')
if shapefile:
# print('--- read')
shp = shapefile if isinstance(shapefile, Vector) else Vector(shapefile)
# reproject the geometry to WGS 84 latlon
# print('--- reproject')
shp.reproject(4326)
ext = shp.extent
# 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, shp.srs) as bounds:
# print('--- intersect')
print(shapefile.srs)
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]
if isinstance(shapefile, str):
shp.close()
# print('--- parse XML node')
subset = parse_node('Subset')
# print('--- insert node')
insert_node(workflow, subset, before='Read')
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
############################################
# (optionally) configure subset node for pixel offsets
if offset and not shapefile:
subset = parse_node('Subset')
insert_node(workflow, subset, before='Read')
# left, right, top and bottom offset in pixels
l, r, t, b = offset
subset = workflow.find('.//node[@id="Subset"]')
subset_values = ','.join(map(str, [l, t, id.samples - l - r, id.lines - t - b]))
subset.find('.//parameters/region').text = subset_values
subset.find('.//parameters/geoRegion').text = ''
############################################
# parametrize write node
# print('-- configuring Write Node')
# create a suffix for the output file to identify processing steps performed in the workflow
suffix = parse_suffix(workflow)
basename = os.path.join(outdir, id.outname_base(basename_extensions))
extension = suffix if format == 'ENVI' else polarizations[0] + '_' + suffix
outname = basename + '_' + extension
write = workflow.find('.//node[@id="Write"]')
write.find('.//parameters/file').text = outname
write.find('.//parameters/formatName').text = format
############################################
############################################
# select DEM type
# print('-- configuring DEM')
if externalDEMFile is not None:
if os.path.isfile(externalDEMFile):
if externalDEMNoDataValue is None:
with Raster(externalDEMFile) as dem:
externalDEMNoDataValue = dem.nodata
if externalDEMNoDataValue is None:
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 and optionally execute it
# print('- writing 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')
parser.add_argument('-r', '--res', type=int, help='resolution', default=20)
return parser.parse_args(args)
# parse arguments
args = parseArguments(sys.argv[1:])
# check shape file exists
if (os.path.exists(args.aoi)):
if not os.path.isdir(args.path):
os.makedirs(args.path)
# reproject dem to projection / aoi as scene
with Vector(args.aoi) as site:
dem.dem_autocreate(geometry=site,
demType='SRTM 1Sec HGT',
outfile=args.path + '/base-4326',
t_srs=4326,
buffer=0.00)
sys.exit()
dem_id = args.dem.replace(' ', '-')
dem_base = 'dem_snap_{}'.format(dem_id)
dem_snap = os.path.join(args.path, dem_base + '.tif')
if not os.path.isfile(dem_snap):
# compile vrt of tiles covering aoi
import os
from spatialist import gdalwarp, Vector
#set directories
maindir = '/exports/csce/datastore/geos/groups/MSCGIS/s1937352/DEM_Uganda'
os.chdir(maindir)
#specify shapefile of region of interest
roi = '/exports/csce/datastore/geos/groups/MSCGIS/s1937352/DEM_Uganda/UgandaBigBox.shp'
epsg = 21036 #specify epsg
demType = 'SRTM 1Sec HGT' #specify dem type (Others: AW3D30, SRTM 3Sec)
dem_name = 'UgandaBig10'
dem_path = f'{maindir}/{dem_name}/.tif'
if not os.path.isfile(dem_path):
#create VRT with the specified DEM and Bounding Box
with Vector(roi) as bbox:
vrt = dem_autoload(geometries=[bbox],
demType=demType,
vrt=f'/{dem_name}.vrt',
buffer=0.1)
# create a tif from the VRT with a given resolution
dem_create(src=vrt,
dst=dem_path,
t_srs=epsg,
tr=(10, 10),
geoid_convert=True)
# convert tif to Gamma files (dem, dem_par)
gammastring = f'dem_import UgandaBig10.tif UgandaB.dem UgandaB.dem_par - - /opt/gamma/20190613/DIFF/scripts/egm96.dem /opt/gamma/20190613/DIFF/scripts/egm96.dem_par'
os.system(gammastring)