def test_Vector(testdata):
scene = Raster(testdata['tif'])
bbox1 = scene.bbox()
assert bbox1.getArea() == 23262400.0
assert bbox1.extent == {
'ymax': 4830114.70107,
'ymin': 4825774.70107,
'xmin': 620048.241204,
'xmax': 625408.241204
}
assert bbox1.nlayers == 1
assert bbox1.getProjection('epsg') == 32631
assert bbox1.proj4 == '+proj=utm +zone=31 +datum=WGS84 +units=m +no_defs'
assert isinstance(bbox1.getFeatureByIndex(0), ogr.Feature)
with pytest.raises(IndexError):
bbox1.getFeatureByIndex(1)
bbox1.reproject(4326)
assert bbox1.proj4 == '+proj=longlat +datum=WGS84 +no_defs'
assert isinstance(bbox1['fid=0'], Vector)
with pytest.raises(RuntimeError):
test = bbox1[0.1]
assert bbox1.fieldnames == ['area']
assert bbox1.getUniqueAttributes('area') == [23262400.0]
feat = bbox1.getFeatureByAttribute('area', 23262400.0)
assert isinstance(feat, ogr.Feature)
bbox2 = feature2vector(feat, ref=bbox1)
bbox2.close()
feat.Destroy()
with pytest.raises(KeyError):
select = bbox1.getFeatureByAttribute('foo', 'bar')
with pytest.raises(RuntimeError):
vec = Vector(driver='foobar')
bbox1.close()
def test_png(tmpdir, testdata):
outname = os.path.join(str(tmpdir), 'test')
with Raster(testdata['tif']) as ras:
png(src=ras, dst=outname, percent=100, scale=(2, 98), worldfile=True)
assert os.path.isfile(outname + '.png')
with pytest.raises(TypeError):
png(src=testdata['tif'],
dst=outname,
percent=100,
scale=(2, 98),
worldfile=True)
src = [testdata['tif'], testdata['tif2']]
with pytest.raises(ValueError):
with Raster(src) as ras:
png(src=ras,
dst=outname,
percent=100,
scale=(2, 98),
worldfile=True)
src.append(testdata['tif3'])
outname = os.path.join(str(tmpdir), 'test_rgb.png')
with Raster(src) as ras:
png(src=ras, dst=outname, percent=100, scale=(2, 98), worldfile=True)
def test_dissolve(tmpdir, travis, testdata):
scene = Raster(testdata['tif'])
bbox1 = scene.bbox()
# retrieve extent and shift its coordinates by one unit
ext = bbox1.extent
for key in ext.keys():
ext[key] += 1
# create new bbox shapefile with modified extent
bbox2_name = os.path.join(str(tmpdir), 'bbox2.shp')
bbox(ext, bbox1.srs, bbox2_name)
# assert intersection between the two bboxes and combine them into one
with Vector(bbox2_name) as bbox2:
assert intersect(bbox1, bbox2) is not None
bbox1.addvector(bbox2)
# write combined bbox into new shapefile
bbox3_name = os.path.join(str(tmpdir), 'bbox3.shp')
bbox1.write(bbox3_name)
bbox1.close()
if not travis and platform.system() != 'Windows':
# dissolve the geometries in bbox3 and write the result to new bbox4
# this test is currently disabled for Travis as the current sqlite3 version on Travis seems to not support
# loading gdal as extension; Travis CI setup: Ubuntu 14.04 (Trusty), sqlite3 version 3.8.2 (2018-06-04)
bbox4_name = os.path.join(str(tmpdir), 'bbox4.shp')
dissolve(bbox3_name, bbox4_name, field='area')
assert os.path.isfile(bbox4_name)
def test_Raster_filestack(testdata):
with pytest.raises(RuntimeError):
with Raster([testdata['tif']]) as ras:
print(ras)
with Raster([testdata['tif'], testdata['tif2']]) as ras:
assert ras.bands == 2
arr = ras.array()
mean = parallel_apply_along_axis(np.nanmean, axis=2, arr=arr, cores=4)
assert mean.shape == (217, 268)
def uzh_prepare(reference, outdir, source):
"""
create an UZH incident angle subset resampled to a reference image.
Parameters
----------
reference: str
the reference file with the target extent
outdir: str
the directory to write the new file to;
new files are named uzh_{epsg}_{index}.tif, e.g. uzh_4326_1.tif.
source: str
the original product to be subsetted
Returns
-------
numpy.ndarray
the content of the file written to `outdir`
"""
with Raster(reference) as ras:
xRes, yRes = ras.res
epsg = ras.epsg
ext = ras.extent
warp_opts = {'options': ['-q'], 'format': 'GTiff', 'multithread': True,
'dstNodata': -99, 'resampleAlg': 'bilinear'}
if not os.path.isdir(outdir):
os.makedirs(outdir)
# find existing files
uzh_subs = finder(outdir, ['uzh_[0-9]{4,5}_[0-9].tif'], regex=True)
# check if any of the existing files matches the extent of the reference
match = False
if len(uzh_subs) > 0:
for j, sub in enumerate(uzh_subs):
with Raster(sub) as ras:
if ras.extent == ext:
uzh_sub = sub
match = True
if not match:
with Raster(source) as ras:
if ras.epsg != epsg:
raise RuntimeError('CRS mismatch')
basename = 'uzh_{}_{}.tif'.format(epsg, len(uzh_subs))
uzh_sub = os.path.join(outdir, basename)
print('creating', uzh_sub)
warp_opts['dstSRS'] = 'EPSG:{}'.format(epsg)
warp_opts['xRes'] = xRes
warp_opts['yRes'] = yRes
warp_opts['outputBounds'] = (ext['xmin'], ext['ymin'],
ext['xmax'], ext['ymax'])
gdalwarp(src=source, dst=uzh_sub, options=warp_opts)
return uzh_sub
def clc_prepare(reference, outdir, source):
"""
create a CLC subset resampled to a reference image.
Parameters
----------
reference: str
the reference file with the target CRS and extent
outdir: str
the directory to write the new file to;
new files are named clc{index}.tif, e.g. clc1.tif.
source: str
the original product to be subsetted
Returns
-------
str
the name of the file written to `outdir`
"""
with Raster(reference) as ras:
xRes, yRes = ras.res
epsg = ras.epsg
ext = ras.extent
#########################################################################
warp_opts = {
'options': ['-q'],
'format': 'GTiff',
'multithread': True,
'dstNodata': -99,
'resampleAlg': 'mode'
}
if not os.path.isdir(outdir):
os.makedirs(outdir)
clc_subs = finder(outdir, ['clc[0-9].tif'], regex=True)
match = False
if len(clc_subs) > 0:
for j, sub in enumerate(clc_subs):
with Raster(sub) as ras:
if ras.extent == ext:
clc_sub = sub
match = True
if not match:
clc_sub = os.path.join(outdir, 'clc{}.tif'.format(len(clc_subs)))
print('creating', clc_sub)
warp_opts['dstSRS'] = 'EPSG:{}'.format(epsg)
warp_opts['xRes'] = xRes
warp_opts['yRes'] = yRes
warp_opts['outputBounds'] = (ext['xmin'], ext['ymin'], ext['xmax'],
ext['ymax'])
gdalwarp(src=source, dst=clc_sub, options=warp_opts)
return clc_sub
def test_Raster_extract(testdata):
with Raster(testdata['tif']) as ras:
assert ras.extract(px=624000, py=4830000,
radius=5) == -10.48837461270875
with pytest.raises(RuntimeError):
ras.extract(1, 4830000)
with pytest.raises(RuntimeError):
ras.extract(624000, 1)
# ensure corner extraction capability
assert ras.extract(px=ras.geo['xmin'],
py=ras.geo['ymax']) == -10.147890090942383
assert ras.extract(px=ras.geo['xmin'],
py=ras.geo['ymin']) == -14.640368461608887
assert ras.extract(px=ras.geo['xmax'],
py=ras.geo['ymax']) == -9.599242210388182
assert ras.extract(px=ras.geo['xmax'],
py=ras.geo['ymin']) == -9.406558990478516
# test nodata handling capability and correct indexing
mat = ras.matrix()
mat[0:10, 0:10] = ras.nodata
mat[207:217, 258:268] = ras.nodata
ras.assign(mat, band=0)
assert ras.extract(px=ras.geo['xmin'], py=ras.geo['ymax'],
radius=5) == ras.nodata
assert ras.extract(px=ras.geo['xmax'], py=ras.geo['ymin'],
radius=5) == ras.nodata
def dem_degree2meter(demfile):
"""
compute the spatial resolution in meters for a DEM with WGS84 degree coordinates.
Parameters
----------
demfile: str
the DEM file
Returns
-------
tuple
(posting_east, posting_north)
See Also
--------
spatialist.auxil.haversine
"""
with Raster(demfile) as ras:
res_lon, res_lat = ras.res
lat = (ras.geo['ymin'] + ras.geo['ymax']) / 2
lon = (ras.geo['xmin'] + ras.geo['xmax']) / 2
post_north = haversine(lat, lon, lat + res_lat, lon)
post_east = haversine(lat, lon, lat, lon + res_lon)
return post_east, post_north
def test_auxil(tmpdir, testdata):
dir = str(tmpdir)
with Raster(testdata['tif']) as ras:
bbox = os.path.join(dir, 'bbox.shp')
ras.bbox(bbox)
ogr2ogr(bbox, os.path.join(dir, 'bbox.gml'), {'format': 'GML'})
gdal_translate(ras.raster, os.path.join(dir, 'test'), {'format': 'ENVI'})
gdal_rasterize(bbox, os.path.join(dir, 'test2'), {'format': 'GTiff', 'xRes': 20, 'yRes': 20})
def clc_prep(clc, reference, outname):
"""
resample and crop the corine product to the resolution and extent of a reference image.
Parameters
----------
clc: str
the name of the CLC input file
reference: str
the name of the reference file
outname: str
the named of the output image
Returns
-------
"""
with Raster(reference).bbox() as box_ras:
with Raster(clc).bbox() as box_clc:
if intersect(box_ras, box_clc) is None:
print('no intersect')
return
if not os.path.isfile(outname):
with Raster(reference) as ras:
ref_crs = ras.projection
xres, yres = ras.res
with ras.bbox() as box:
ref_ext = box.extent
outputBounds = (ref_ext['xmin'], ref_ext['ymin'], ref_ext['xmax'],
ref_ext['ymax'])
gdalwarp_opt = {
'format': 'GTiff',
'outputBounds': outputBounds,
'multithread': True,
'xRes': xres,
'yRes': yres,
'dstSRS': ref_crs,
'resampleAlg': 'mode'
}
gdalwarp(src=clc, dst=outname, options=gdalwarp_opt)
else:
print('outfile already exists')
def __buildvrt(archives, vrtfile, pattern, vsi, extent, nodata=None, srs=None):
locals = [vsi + x for x in dissolve([finder(x, [pattern]) for x in archives])]
if nodata is None:
with Raster(locals[0]) as ras:
nodata = ras.nodata
opts = {'outputBounds': (extent['xmin'], extent['ymin'],
extent['xmax'], extent['ymax']),
'srcNodata': nodata}
if srs is not None:
opts['outputSRS'] = crsConvert(srs, 'wkt')
gdalbuildvrt(src=locals, dst=vrtfile,
options=opts)
def test_Raster_subset(testdata):
with Raster(testdata['tif']) as ras:
ext = ras.bbox().extent
xres, yres = ras.res
ext['xmin'] += xres
ext['xmax'] -= xres
ext['ymin'] += yres
ext['ymax'] -= yres
with bbox(ext, ras.proj4) as vec:
with ras[vec] as sub:
xres, yres = ras.res
assert sub.geo['xmin'] - ras.geo['xmin'] == xres
assert ras.geo['xmax'] - sub.geo['xmax'] == xres
assert sub.geo['ymin'] - ras.geo['ymin'] == xres
assert ras.geo['ymax'] - sub.geo['ymax'] == xres
def test_stack(tmpdir, testdata):
name = testdata['tif']
outname = os.path.join(str(tmpdir), 'test')
tr = (30, 30)
with pytest.raises(IOError):
stack(srcfiles=[], resampling='near', targetres=tr,
srcnodata=-99, dstnodata=-99, dstfile=outname)
with pytest.raises(IOError):
stack(srcfiles=[name, name], resampling='near', targetres=tr,
srcnodata=-99, dstnodata=-99, dstfile=outname, layernames=['a'])
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name], resampling='near', targetres=30,
srcnodata=-99, dstnodata=-99, dstfile=outname)
with pytest.raises(IOError):
stack(srcfiles=[name], resampling='near', targetres=tr, overwrite=True,
srcnodata=-99, dstnodata=-99, dstfile=outname)
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name], resampling='near', targetres=(30, 30, 30),
srcnodata=-99, dstnodata=-99, dstfile=outname)
with pytest.raises(IOError):
stack(srcfiles=[name, name], resampling='foobar', targetres=tr,
srcnodata=-99, dstnodata=-99, dstfile=outname)
with pytest.raises(OSError):
stack(srcfiles=[name, 'foobar'], resampling='near', targetres=tr,
srcnodata=-99, dstnodata=-99, dstfile=outname)
stack(srcfiles=[name, name], resampling='near', targetres=tr, overwrite=True,
srcnodata=-99, dstnodata=-99, dstfile=outname)
outdir = os.path.join(str(tmpdir), 'subdir')
stack(srcfiles=[name, name], resampling='near', targetres=tr, overwrite=True, layernames=['test1', 'test2'],
srcnodata=-99, dstnodata=-99, dstfile=outdir, separate=True, compress=True)
with Raster(outname) as ras:
assert ras.bands == 2
# Raster.rescale currently only supports one band
with pytest.raises(ValueError):
ras.rescale(lambda x: x * 10)
def test_rasterize(tmpdir, testdata):
outname = os.path.join(str(tmpdir), 'test.shp')
with Raster(testdata['tif']) as ras:
vec = ras.bbox()
# test length mismatch between burn_values and expressions
with pytest.raises(RuntimeError):
rasterize(vec, reference=ras, outname=outname, burn_values=[1], expressions=['foo', 'bar'])
# test a faulty expression
with pytest.raises(RuntimeError):
rasterize(vec, reference=ras, outname=outname, burn_values=[1], expressions=['foo'])
# test default parametrization
rasterize(vec, reference=ras, outname=outname)
assert os.path.isfile(outname)
# test appending to existing file with valid expression
rasterize(vec, reference=ras, outname=outname, append=True, burn_values=[1], expressions=['id=1'])
# test wrong input type for reference
with pytest.raises(RuntimeError):
rasterize(vec, reference='foobar', outname=outname)
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')
def test_stack(tmpdir, testdata):
name = testdata['tif']
outname = os.path.join(str(tmpdir), 'test')
tr = (30, 30)
# no input files provided
with pytest.raises(RuntimeError):
stack(srcfiles=[],
resampling='near',
targetres=tr,
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# two files, but only one layer name
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name],
resampling='near',
targetres=tr,
srcnodata=-99,
dstnodata=-99,
dstfile=outname,
layernames=['a'])
# targetres must be a two-entry tuple/list
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name],
resampling='near',
targetres=30,
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# only one file specified
with pytest.raises(RuntimeError):
stack(srcfiles=[name],
resampling='near',
targetres=tr,
overwrite=True,
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# targetres must contain two values
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name],
resampling='near',
targetres=(30, 30, 30),
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# unknown resampling method
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name],
resampling='foobar',
targetres=tr,
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# non-existing files
with pytest.raises(RuntimeError):
stack(srcfiles=['foo', 'bar'],
resampling='near',
targetres=tr,
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# create a multi-band stack
stack(srcfiles=[name, name],
resampling='near',
targetres=tr,
overwrite=True,
srcnodata=-99,
dstnodata=-99,
dstfile=outname,
layernames=['test1', 'test2'])
with Raster(outname) as ras:
assert ras.bands == 2
# Raster.rescale currently only supports one band
with pytest.raises(ValueError):
ras.rescale(lambda x: x * 10)
# outname exists and overwrite is False
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name],
resampling='near',
targetres=tr,
overwrite=False,
srcnodata=-99,
dstnodata=-99,
dstfile=outname,
layernames=['test1', 'test2'])
# pass shapefile
outname = os.path.join(str(tmpdir), 'test2')
with Raster(name).bbox() as box:
stack(srcfiles=[name, name],
resampling='near',
targetres=tr,
overwrite=True,
srcnodata=-99,
dstnodata=-99,
dstfile=outname,
shapefile=box,
layernames=['test1', 'test2'])
with Raster(outname) as ras:
assert ras.bands == 2
# pass shapefile and do mosaicing
outname = os.path.join(str(tmpdir), 'test3')
with Raster(name).bbox() as box:
stack(srcfiles=[[name, name]],
resampling='near',
targetres=tr,
overwrite=True,
srcnodata=-99,
dstnodata=-99,
dstfile=outname,
shapefile=box)
with Raster(outname + '.tif') as ras:
assert ras.bands == 1
assert ras.format == 'GTiff'
# projection mismatch
name2 = os.path.join(str(tmpdir), os.path.basename(name))
outname = os.path.join(str(tmpdir), 'test4')
gdalwarp(name, name2, options={'dstSRS': crsConvert(4326, 'wkt')})
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name2],
resampling='near',
targetres=tr,
overwrite=True,
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# no projection found
outname = os.path.join(str(tmpdir), 'test5')
gdal_translate(name, name2, {'options': ['-co', 'PROFILE=BASELINE']})
with Raster(name2) as ras:
print(ras.projection)
with pytest.raises(RuntimeError):
stack(srcfiles=[name2, name2],
resampling='near',
targetres=tr,
overwrite=True,
srcnodata=-99,
dstnodata=-99,
dstfile=outname)
# create separate GeoTiffs
outdir = os.path.join(str(tmpdir), 'subdir')
stack(srcfiles=[name, name],
resampling='near',
targetres=tr,
overwrite=True,
layernames=['test1', 'test2'],
srcnodata=-99,
dstnodata=-99,
dstfile=outdir,
separate=True,
compress=True)
# repeat with overwrite disabled (no error raised, just a print message)
stack(srcfiles=[name, name],
resampling='near',
targetres=tr,
overwrite=False,
layernames=['test1', 'test2'],
srcnodata=-99,
dstnodata=-99,
dstfile=outdir,
separate=True,
compress=True)
# repeat without layernames but sortfun
# bandnames not unique
outdir = os.path.join(str(tmpdir), 'subdir2')
with pytest.raises(RuntimeError):
stack(srcfiles=[name, name],
resampling='near',
targetres=tr,
overwrite=True,
sortfun=os.path.basename,
srcnodata=-99,
dstnodata=-99,
dstfile=outdir,
separate=True,
compress=True)
# repeat without layernames but sortfun
name2 = os.path.join(str(tmpdir),
os.path.basename(name).replace('VV', 'XX'))
shutil.copyfile(name, name2)
outdir = os.path.join(str(tmpdir), 'subdir2')
stack(srcfiles=[name, name2],
resampling='near',
targetres=tr,
overwrite=True,
sortfun=os.path.basename,
srcnodata=-99,
dstnodata=-99,
dstfile=outdir,
separate=True,
compress=True)
# shapefile filtering
outdir = os.path.join(str(tmpdir), 'subdir3')
files = [testdata['tif'], testdata['tif2'], testdata['tif3']]
with Raster(files[0]).bbox() as box:
stack(srcfiles=files,
resampling='near',
targetres=(30, 30),
overwrite=False,
layernames=['test1', 'test2', 'test3'],
srcnodata=-99,
dstnodata=-99,
dstfile=outdir,
separate=True,
compress=True,
shapefile=box)
# repeated run with different scene selection and only one scene after spatial filtering
stack(srcfiles=files[1:],
resampling='near',
targetres=(30, 30),
overwrite=True,
layernames=['test2', 'test3'],
srcnodata=-99,
dstnodata=-99,
dstfile=outdir,
separate=True,
compress=True,
shapefile=box)
def inc_stack(small, gamma, snap, outdir, prefix=''):
outnames_base = ['small', 'gamma', 'snap']
outnames = [
os.path.join(outdir, prefix + x) + '.tif' for x in outnames_base
]
if all([os.path.isfile(x) for x in outnames]):
return outnames
# set SMALL product nodata GeoTiff value
with Raster(small)[0:100, 0:100] as ras:
if ras.nodata is None:
print('setting nodata value for SMALL product')
mat = ras.matrix()
nodata = float(mat[0, 0])
ras2 = gdal.Open(small, GA_Update)
ras2.GetRasterBand(1).SetNoDataValue(nodata)
ras2 = None
tmpdir = os.path.join(outdir, 'tmp')
if not os.path.isdir(tmpdir):
os.makedirs(tmpdir)
small_edit = os.path.join(
tmpdir,
os.path.basename(small).replace('.tif', '_edit.tif'))
if not os.path.isfile(small_edit):
print('reducing resolution of SMALL product')
gdal_translate(small,
small_edit,
options={
'xRes': 90,
'yRes': 90,
'resampleAlg': 'average',
'format': 'GTiff'
})
# subtract 90 degrees from SMALL product
small_out = outnames[0]
if not os.path.isfile(small_out):
print('subtracting 90 degrees from SMALL product')
with Raster(small_edit) as ras:
mat = ras.matrix() - 90
ras.assign(mat, 0)
print('creating {}'.format(small_out))
ras.write(small_out, format='GTiff', nodata=-99)
# set GAMMA product nodata value
with Raster(gamma) as ras:
if ras.nodata != 0:
print('setting nodata value of GAMMA product')
ras2 = gdal.Open(gamma, GA_Update)
ras2.GetRasterBand(1).SetNoDataValue(0)
ras2 = None
# convert GAMMA product from radians to degrees
gamma_deg = os.path.join(
tmpdir,
os.path.basename(gamma).replace('.tif', '_deg.tif'))
if not os.path.isfile(gamma_deg):
print('converting GAMMA product from radians to degrees')
with Raster(gamma) as ras:
mat = np.rad2deg(ras.matrix())
ras.assign(mat, 0)
ras.write(gamma_deg, format='GTiff')
gamma = gamma_deg
# use extent of SMALL product as reference
ext = Raster(small_out).bbox().extent
# create new directory for the stacked files
if not os.path.isdir(outdir):
os.makedirs(outdir)
# warp the products to their common extent
warp_opts = {
'options': ['-q'],
'format': 'GTiff',
'multithread': True,
'outputBounds': (ext['xmin'], ext['ymin'], ext['xmax'], ext['ymax']),
'dstNodata': -99,
'xRes': 90,
'yRes': 90,
'resampleAlg': 'bilinear',
'dstSRS': 'EPSG:32632'
}
for i, item in enumerate([gamma, snap]):
outfile = outnames[i + 1]
if not os.path.isfile(outfile):
print('creating {}'.format(outfile))
gdalwarp(src=item, dst=outfile, options=warp_opts)
shutil.rmtree(tmpdir)
return outnames
def dem_create(src,
dst,
t_srs=None,
tr=None,
resampling_method='bilinear',
geoid_convert=False,
geoid='EGM96'):
"""
create a new DEM GeoTiff file and optionally convert heights from geoid to ellipsoid
Parameters
----------
src: str
the input dataset, e.g. a VRT from function :func:`dem_autoload`
dst: str
the output dataset
t_srs: None, 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 (None): use the crs of ``src``.
tr: None or tuple
the target resolution as (xres, yres)
resampling_method: str
the gdalwarp resampling method; See `here <https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r>`_
for options.
geoid_convert: bool
convert geoid heights?
geoid: str
the geoid model to be corrected, only used if ``geoid_convert == True``; current options:
* 'EGM96'
Returns
-------
"""
with Raster(src) as ras:
nodata = ras.nodata
epsg_in = ras.epsg
if t_srs is None:
epsg_out = epsg_in
else:
epsg_out = crsConvert(t_srs, 'epsg')
gdalwarp_args = {
'format': 'GTiff',
'multithread': True,
'srcNodata': nodata,
'dstNodata': nodata,
'srcSRS': 'EPSG:{}'.format(epsg_in),
'dstSRS': 'EPSG:{}'.format(epsg_out),
'resampleAlg': resampling_method
}
if tr is not None:
gdalwarp_args.update({'xRes': tr[0], 'yRes': tr[1]})
if geoid_convert:
if gdal.__version__ < '2.2':
raise RuntimeError('geoid conversion requires GDAL >= 2.2;'
'see documentation of gdalwarp')
if geoid == 'EGM96':
gdalwarp_args['srcSRS'] += '+5773'
else:
raise RuntimeError('geoid model not yet supported')
try:
message = 'creating mosaic'
crs = gdalwarp_args['dstSRS']
if crs != 'EPSG:4326':
message += ' and reprojecting to {}'.format(crs)
print(message)
gdalwarp(src, dst, gdalwarp_args)
except RuntimeError as e:
if os.path.isfile(dst):
os.remove(dst)
errstr = str(e)
if 'Cannot open egm96_15.gtx' in errstr:
addition = '\nplease refer to the following site for instructions ' \
'on how to use the file egm96_15.gtx (requires proj.4 >= 5.0.0):\n' \
'https://gis.stackexchange.com/questions/258532/' \
'noaa-vdatum-gdal-variable-paths-for-linux-ubuntu'
raise RuntimeError(errstr + addition)
else:
raise e
def test_Raster(tmpdir, testdata):
with pytest.raises(RuntimeError):
with Raster(1) as ras:
print(ras)
with Raster(testdata['tif']) as ras:
print(ras)
assert ras.bands == 1
assert ras.proj4.strip(
) == '+proj=utm +zone=31 +datum=WGS84 +units=m +no_defs'
assert ras.cols == 268
assert ras.rows == 217
assert ras.dim == (217, 268, 1)
assert ras.dtype == 'Float32'
assert ras.epsg == 32631
assert ras.format == 'GTiff'
assert ras.geo == {
'ymax': 4830114.70107,
'rotation_y': 0.0,
'rotation_x': 0.0,
'xmax': 625408.241204,
'xres': 20.0,
'xmin': 620048.241204,
'ymin': 4825774.70107,
'yres': -20.0
}
assert ras.geogcs == 'WGS 84'
assert ras.is_valid() is True
assert ras.proj4args == {
'units': 'm',
'no_defs': None,
'datum': 'WGS84',
'proj': 'utm',
'zone': '31'
}
assert ras.allstats() == [{
'min': -26.65471076965332,
'max': 1.4325850009918213,
'mean': -12.124929534450377,
'sdev': 4.738273594738293
}]
assert ras.bbox().getArea() == 23262400.0
assert len(ras.layers()) == 1
assert ras.projcs == 'WGS 84 / UTM zone 31N'
assert ras.res == (20.0, 20.0)
# test writing a subset with no original data in memory
outname = os.path.join(str(tmpdir), 'test_sub.tif')
with ras[0:200, 0:100] as sub:
sub.write(outname, format='GTiff')
with Raster(outname) as ras2:
assert ras2.cols == 100
assert ras2.rows == 200
ras.load()
mat = ras.matrix()
assert isinstance(mat, np.ndarray)
ras.assign(mat, band=0)
# ras.reduce()
ras.rescale(lambda x: 10 * x)
# test writing data with original data in memory
ras.write(os.path.join(str(tmpdir), 'test'),
format='GTiff',
compress_tif=True)
with pytest.raises(RuntimeError):
ras.write(os.path.join(str(tmpdir), 'test.tif'), format='GTiff')