def test_get_geolocation_grids(self):
d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
lon, lat = d.get_geolocation_grids()
self.assertEqual(type(lon), np.ndarray)
self.assertEqual(type(lat), np.ndarray)
self.assertEqual(lat.shape, (500, 500))
def test_get_geolocation_grids(self):
d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
lon, lat = d.get_geolocation_grids()
self.assertEqual(type(lon), np.ndarray)
self.assertEqual(type(lat), np.ndarray)
self.assertEqual(lat.shape, (500, 500))
def test_get_geolocation_grids_from_geolocationArray(self):
lat, lon = np.mgrid[25:35:0.02, 70:72:0.004]
d = Domain(lon=lon, lat=lat)
lon, lat = d.get_geolocation_grids()
self.assertEqual(type(lon), np.ndarray)
self.assertEqual(type(lat), np.ndarray)
self.assertEqual(lat.shape, (500, 500))
def test_get_geolocation_grids_from_GDAL_transformer(
self, mock_transform_points):
d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
lon, lat = d.get_geolocation_grids()
self.assertEqual(type(lon), np.ndarray)
self.assertEqual(type(lat), np.ndarray)
self.assertEqual(lat.shape, (500, 500))
def test_get_geolocation_grids_from_geolocationArray(self):
lat, lon = np.mgrid[25:35:0.02, 70:72:0.004]
d = Domain(lon=lon, lat=lat)
lon, lat = d.get_geolocation_grids()
self.assertEqual(type(lon), np.ndarray)
self.assertEqual(type(lat), np.ndarray)
self.assertEqual(lat.shape, (500, 500))
def test_get_geolocation_grids_from_GDAL_transformer(self, mock_transform_points):
mock_transform_points.return_value=(
np.meshgrid(range(0,500),range(0,500))[0].flatten()*(35-25)/500.+25,
np.meshgrid(range(0,500),range(0,500))[1].flatten()*(70-72)/500.+72)
d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
lon, lat = d.get_geolocation_grids()
self.assertEqual(type(lon), np.ndarray)
self.assertEqual(type(lat), np.ndarray)
self.assertEqual(lat.shape, (500, 500))
def test_get_geolocation_grids_from_GDAL_transformer(self, mock_transform_points):
mock_transform_points.return_value=(
np.meshgrid(range(0,500),range(0,500))[0].flatten()*(35-25)/500.+25,
np.meshgrid(range(0,500),range(0,500))[1].flatten()*(70-72)/500.+72)
d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
lon, lat = d.get_geolocation_grids()
self.assertEqual(type(lon), np.ndarray)
self.assertEqual(type(lat), np.ndarray)
self.assertEqual(lat.shape, (500, 500))
def __init__(self, fileName, gdalDataset, gdalMetadata, **kwargs):
''' Create Radarsat2 VRT '''
fPathName, fExt = os.path.splitext(fileName)
if zipfile.is_zipfile(fileName):
# Open zip file using VSI
fPath, fName = os.path.split(fPathName)
fileName = '/vsizip/%s/%s' % (fileName, fName)
if not 'RS' in fName[0:2]:
raise WrongMapperError('Provided data is not Radarsat-2')
gdalDataset = gdal.Open(fileName)
gdalMetadata = gdalDataset.GetMetadata()
#if it is not RADARSAT-2, return
if (not gdalMetadata
or not 'SATELLITE_IDENTIFIER' in gdalMetadata.keys()):
raise WrongMapperError
elif gdalMetadata['SATELLITE_IDENTIFIER'] != 'RADARSAT-2':
raise WrongMapperError
# read product.xml
productXmlName = os.path.join(fileName, 'product.xml')
productXml = self.read_xml(productXmlName)
# Get additional metadata from product.xml
rs2_0 = Node.create(productXml)
rs2_1 = rs2_0.node('sourceAttributes')
rs2_2 = rs2_1.node('radarParameters')
if rs2_2['antennaPointing'].lower() == 'right':
antennaPointing = 90
else:
antennaPointing = -90
rs2_3 = rs2_1.node('orbitAndAttitude').node('orbitInformation')
passDirection = rs2_3['passDirection']
# create empty VRT dataset with geolocation only
VRT.__init__(self, gdalDataset)
#define dictionary of metadata and band specific parameters
pol = []
metaDict = []
# Get the subdataset with calibrated sigma0 only
for dataset in gdalDataset.GetSubDatasets():
if dataset[1] == 'Sigma Nought calibrated':
s0dataset = gdal.Open(dataset[0])
s0datasetName = dataset[0][:]
band = s0dataset.GetRasterBand(1)
s0datasetPol = band.GetMetadata()['POLARIMETRIC_INTERP']
for i in range(1, s0dataset.RasterCount + 1):
iBand = s0dataset.GetRasterBand(i)
polString = iBand.GetMetadata()['POLARIMETRIC_INTERP']
suffix = polString
# The nansat data will be complex
# if the SAR data is of type 10
dtype = iBand.DataType
if dtype == 10:
# add intensity band
metaDict.append({
'src': {
'SourceFilename': ('RADARSAT_2_CALIB:SIGMA0:' +
fileName + '/product.xml'),
'SourceBand':
i,
'DataType':
dtype
},
'dst': {
'wkv':
'surface_backwards_scattering_coefficient_of_radar_wave',
'PixelFunctionType': 'intensity',
'SourceTransferType':
gdal.GetDataTypeName(dtype),
'suffix': suffix,
'polarization': polString,
'dataType': 6
}
})
# modify suffix for adding the compled band below
suffix = polString + '_complex'
pol.append(polString)
metaDict.append({
'src': {
'SourceFilename': ('RADARSAT_2_CALIB:SIGMA0:' +
fileName + '/product.xml'),
'SourceBand':
i,
'DataType':
dtype
},
'dst': {
'wkv':
'surface_backwards_scattering_coefficient_of_radar_wave',
'suffix': suffix,
'polarization': polString
}
})
if dataset[1] == 'Beta Nought calibrated':
b0dataset = gdal.Open(dataset[0])
b0datasetName = dataset[0][:]
for j in range(1, b0dataset.RasterCount + 1):
jBand = b0dataset.GetRasterBand(j)
polString = jBand.GetMetadata()['POLARIMETRIC_INTERP']
if polString == s0datasetPol:
b0datasetBand = j
###############################
# Add SAR look direction
###############################
d = Domain(ds=gdalDataset)
lon, lat = d.get_geolocation_grids(100)
'''
(GDAL?) Radarsat-2 data is stored with maximum latitude at first
element of each column and minimum longitude at first element of each
row (e.g. np.shape(lat)=(59,55) -> latitude maxima are at lat[0,:],
and longitude minima are at lon[:,0])
In addition, there is an interpolation error for direct estimate along
azimuth. We therefore estimate the heading along range and add 90
degrees to get the "satellite" heading.
'''
if str(passDirection).upper() == 'DESCENDING':
sat_heading = initial_bearing(lon[:, :-1], lat[:, :-1], lon[:, 1:],
lat[:, 1:]) + 90
elif str(passDirection).upper() == 'ASCENDING':
sat_heading = initial_bearing(lon[:, 1:], lat[:, 1:], lon[:, :-1],
lat[:, :-1]) + 90
else:
print 'Can not decode pass direction: ' + str(passDirection)
# Calculate SAR look direction
SAR_look_direction = sat_heading + antennaPointing
# Interpolate to regain lost row
SAR_look_direction = np.mod(SAR_look_direction, 360)
SAR_look_direction = scipy.ndimage.interpolation.zoom(
SAR_look_direction, (1, 11. / 10.))
# Decompose, to avoid interpolation errors around 0 <-> 360
SAR_look_direction_u = np.sin(np.deg2rad(SAR_look_direction))
SAR_look_direction_v = np.cos(np.deg2rad(SAR_look_direction))
look_u_VRT = VRT(array=SAR_look_direction_u, lat=lat, lon=lon)
look_v_VRT = VRT(array=SAR_look_direction_v, lat=lat, lon=lon)
# Note: If incidence angle and look direction are stored in
# same VRT, access time is about twice as large
lookVRT = VRT(lat=lat, lon=lon)
lookVRT._create_band([{
'SourceFilename': look_u_VRT.fileName,
'SourceBand': 1
}, {
'SourceFilename': look_v_VRT.fileName,
'SourceBand': 1
}], {'PixelFunctionType': 'UVToDirectionTo'})
# Blow up to full size
lookVRT = lookVRT.get_resized_vrt(gdalDataset.RasterXSize,
gdalDataset.RasterYSize)
# Store VRTs so that they are accessible later
self.bandVRTs['look_u_VRT'] = look_u_VRT
self.bandVRTs['look_v_VRT'] = look_v_VRT
self.bandVRTs['lookVRT'] = lookVRT
# Add band to full sized VRT
lookFileName = self.bandVRTs['lookVRT'].fileName
metaDict.append({
'src': {
'SourceFilename': lookFileName,
'SourceBand': 1
},
'dst': {
'wkv': 'sensor_azimuth_angle',
'name': 'SAR_look_direction'
}
})
###############################
# Create bands
###############################
self._create_bands(metaDict)
###################################################
# Add derived band (incidence angle) calculated
# using pixel function "BetaSigmaToIncidence":
###################################################
src = [{
'SourceFilename': b0datasetName,
'SourceBand': b0datasetBand,
'DataType': dtype
}, {
'SourceFilename': s0datasetName,
'SourceBand': 1,
'DataType': dtype
}]
dst = {
'wkv': 'angle_of_incidence',
'PixelFunctionType': 'BetaSigmaToIncidence',
'SourceTransferType': gdal.GetDataTypeName(dtype),
'_FillValue': -10000, # NB: this is also hard-coded in
# pixelfunctions.c
'dataType': 6,
'name': 'incidence_angle'
}
self._create_band(src, dst)
self.dataset.FlushCache()
###################################################################
# Add sigma0_VV - pixel function of sigma0_HH and beta0_HH
# incidence angle is calculated within pixel function
# It is assummed that HH is the first band in sigma0 and
# beta0 sub datasets
###################################################################
if 'VV' not in pol and 'HH' in pol:
s0datasetNameHH = pol.index('HH') + 1
src = [{
'SourceFilename': s0datasetName,
'SourceBand': s0datasetNameHH,
'DataType': 6
}, {
'SourceFilename': b0datasetName,
'SourceBand': b0datasetBand,
'DataType': 6
}]
dst = {
'wkv':
'surface_backwards_scattering_coefficient_of_radar_wave',
'PixelFunctionType': 'Sigma0HHBetaToSigma0VV',
'polarization': 'VV',
'suffix': 'VV'
}
self._create_band(src, dst)
self.dataset.FlushCache()
############################################
# Add SAR metadata
############################################
if antennaPointing == 90:
self.dataset.SetMetadataItem('ANTENNA_POINTING', 'RIGHT')
if antennaPointing == -90:
self.dataset.SetMetadataItem('ANTENNA_POINTING', 'LEFT')
self.dataset.SetMetadataItem('ORBIT_DIRECTION',
str(passDirection).upper())
# Set time
validTime = gdalDataset.GetMetadata()['ACQUISITION_START_TIME']
self.logger.info('Valid time: %s', str(validTime))
self._set_time(parse(validTime))
# set SADCAT specific metadata
self.dataset.SetMetadataItem(
'start_date', (parse(gdalMetadata['FIRST_LINE_TIME']).isoformat()))
self.dataset.SetMetadataItem(
'stop_date', (parse(gdalMetadata['LAST_LINE_TIME']).isoformat()))
self.dataset.SetMetadataItem('sensor', 'SAR')
self.dataset.SetMetadataItem('satellite', 'Radarsat2')
self.dataset.SetMetadataItem('mapper', 'radarsat2')
def __init__(self, fileName, gdalDataset, gdalMetadata, **kwargs):
''' Create Radarsat2 VRT '''
fPathName, fExt = os.path.splitext(fileName)
if zipfile.is_zipfile(fileName):
# Open zip file using VSI
fPath, fName = os.path.split(fPathName)
fileName = '/vsizip/%s/%s' % (fileName, fName)
if not 'RS' in fName[0:2]:
raise WrongMapperError('Provided data is not Radarsat-2')
gdalDataset = gdal.Open(fileName)
gdalMetadata = gdalDataset.GetMetadata()
#if it is not RADARSAT-2, return
if (not gdalMetadata or
not 'SATELLITE_IDENTIFIER' in gdalMetadata.keys()):
raise WrongMapperError
elif gdalMetadata['SATELLITE_IDENTIFIER'] != 'RADARSAT-2':
raise WrongMapperError
# read product.xml
productXmlName = os.path.join(fileName, 'product.xml')
productXml = self.read_xml(productXmlName)
# Get additional metadata from product.xml
rs2_0 = Node.create(productXml)
rs2_1 = rs2_0.node('sourceAttributes')
rs2_2 = rs2_1.node('radarParameters')
if rs2_2['antennaPointing'].lower() == 'right':
antennaPointing = 90
else:
antennaPointing = -90
rs2_3 = rs2_1.node('orbitAndAttitude').node('orbitInformation')
passDirection = rs2_3['passDirection']
# create empty VRT dataset with geolocation only
VRT.__init__(self, gdalDataset)
#define dictionary of metadata and band specific parameters
pol = []
metaDict = []
# Get the subdataset with calibrated sigma0 only
for dataset in gdalDataset.GetSubDatasets():
if dataset[1] == 'Sigma Nought calibrated':
s0dataset = gdal.Open(dataset[0])
s0datasetName = dataset[0][:]
band = s0dataset.GetRasterBand(1)
s0datasetPol = band.GetMetadata()['POLARIMETRIC_INTERP']
for i in range(1, s0dataset.RasterCount+1):
iBand = s0dataset.GetRasterBand(i)
polString = iBand.GetMetadata()['POLARIMETRIC_INTERP']
suffix = polString
# The nansat data will be complex
# if the SAR data is of type 10
dtype = iBand.DataType
if dtype == 10:
# add intensity band
metaDict.append(
{'src': {'SourceFilename':
('RADARSAT_2_CALIB:SIGMA0:'
+ fileName + '/product.xml'),
'SourceBand': i,
'DataType': dtype},
'dst': {'wkv': 'surface_backwards_scattering_coefficient_of_radar_wave',
'PixelFunctionType': 'intensity',
'SourceTransferType': gdal.GetDataTypeName(dtype),
'suffix': suffix,
'polarization': polString,
'dataType': 6}})
# modify suffix for adding the compled band below
suffix = polString+'_complex'
pol.append(polString)
metaDict.append(
{'src': {'SourceFilename': ('RADARSAT_2_CALIB:SIGMA0:'
+ fileName
+ '/product.xml'),
'SourceBand': i,
'DataType': dtype},
'dst': {'wkv': 'surface_backwards_scattering_coefficient_of_radar_wave',
'suffix': suffix,
'polarization': polString}})
if dataset[1] == 'Beta Nought calibrated':
b0dataset = gdal.Open(dataset[0])
b0datasetName = dataset[0][:]
for j in range(1, b0dataset.RasterCount+1):
jBand = b0dataset.GetRasterBand(j)
polString = jBand.GetMetadata()['POLARIMETRIC_INTERP']
if polString == s0datasetPol:
b0datasetBand = j
###############################
# Add SAR look direction
###############################
d = Domain(ds=gdalDataset)
lon, lat = d.get_geolocation_grids(100)
'''
(GDAL?) Radarsat-2 data is stored with maximum latitude at first
element of each column and minimum longitude at first element of each
row (e.g. np.shape(lat)=(59,55) -> latitude maxima are at lat[0,:],
and longitude minima are at lon[:,0])
In addition, there is an interpolation error for direct estimate along
azimuth. We therefore estimate the heading along range and add 90
degrees to get the "satellite" heading.
'''
if str(passDirection).upper() == 'DESCENDING':
sat_heading = initial_bearing(lon[:, :-1], lat[:, :-1],
lon[:, 1:], lat[:, 1:]) + 90
elif str(passDirection).upper() == 'ASCENDING':
sat_heading = initial_bearing(lon[:, 1:], lat[:, 1:],
lon[:, :-1], lat[:, :-1]) + 90
else:
print 'Can not decode pass direction: ' + str(passDirection)
# Calculate SAR look direction
look_direction = sat_heading + antennaPointing
# Interpolate to regain lost row
look_direction = np.mod(look_direction, 360)
look_direction = scipy.ndimage.interpolation.zoom(
look_direction, (1, 11./10.))
# Decompose, to avoid interpolation errors around 0 <-> 360
look_direction_u = np.sin(np.deg2rad(look_direction))
look_direction_v = np.cos(np.deg2rad(look_direction))
look_u_VRT = VRT(array=look_direction_u, lat=lat, lon=lon)
look_v_VRT = VRT(array=look_direction_v, lat=lat, lon=lon)
# Note: If incidence angle and look direction are stored in
# same VRT, access time is about twice as large
lookVRT = VRT(lat=lat, lon=lon)
lookVRT._create_band(
[{'SourceFilename': look_u_VRT.fileName, 'SourceBand': 1},
{'SourceFilename': look_v_VRT.fileName, 'SourceBand': 1}],
{'PixelFunctionType': 'UVToDirectionTo'})
# Blow up to full size
lookVRT = lookVRT.get_resized_vrt(gdalDataset.RasterXSize,
gdalDataset.RasterYSize)
# Store VRTs so that they are accessible later
self.bandVRTs['look_u_VRT'] = look_u_VRT
self.bandVRTs['look_v_VRT'] = look_v_VRT
self.bandVRTs['lookVRT'] = lookVRT
# Add band to full sized VRT
lookFileName = self.bandVRTs['lookVRT'].fileName
metaDict.append({'src': {'SourceFilename': lookFileName,
'SourceBand': 1},
'dst': {'wkv': 'sensor_azimuth_angle',
'name': 'look_direction'}})
###############################
# Create bands
###############################
self._create_bands(metaDict)
###################################################
# Add derived band (incidence angle) calculated
# using pixel function "BetaSigmaToIncidence":
###################################################
src = [{'SourceFilename': b0datasetName,
'SourceBand': b0datasetBand,
'DataType': dtype},
{'SourceFilename': s0datasetName,
'SourceBand': 1,
'DataType': dtype}]
dst = {'wkv': 'angle_of_incidence',
'PixelFunctionType': 'BetaSigmaToIncidence',
'SourceTransferType': gdal.GetDataTypeName(dtype),
'_FillValue': -10000, # NB: this is also hard-coded in
# pixelfunctions.c
'dataType': 6,
'name': 'incidence_angle'}
self._create_band(src, dst)
self.dataset.FlushCache()
###################################################################
# Add sigma0_VV - pixel function of sigma0_HH and beta0_HH
# incidence angle is calculated within pixel function
# It is assummed that HH is the first band in sigma0 and
# beta0 sub datasets
###################################################################
if 'VV' not in pol and 'HH' in pol:
s0datasetNameHH = pol.index('HH')+1
src = [{'SourceFilename': s0datasetName,
'SourceBand': s0datasetNameHH,
'DataType': 6},
{'SourceFilename': b0datasetName,
'SourceBand': b0datasetBand,
'DataType': 6}]
dst = {'wkv': 'surface_backwards_scattering_coefficient_of_radar_wave',
'PixelFunctionType': 'Sigma0HHBetaToSigma0VV',
'polarization': 'VV',
'suffix': 'VV'}
self._create_band(src, dst)
self.dataset.FlushCache()
############################################
# Add SAR metadata
############################################
if antennaPointing == 90:
self.dataset.SetMetadataItem('ANTENNA_POINTING', 'RIGHT')
if antennaPointing == -90:
self.dataset.SetMetadataItem('ANTENNA_POINTING', 'LEFT')
self.dataset.SetMetadataItem('ORBIT_DIRECTION',
str(passDirection).upper())
# set valid time
self.dataset.SetMetadataItem('time_coverage_start',
(parse(gdalMetadata['FIRST_LINE_TIME']).
isoformat()))
self.dataset.SetMetadataItem('time_coverage_end',
(parse(gdalMetadata['LAST_LINE_TIME']).
isoformat()))
# Get dictionary describing the instrument and platform according to
# the GCMD keywords
mm = pti.get_gcmd_instrument('sar')
ee = pti.get_gcmd_platform('radarsat-2')
# TODO: Validate that the found instrument and platform are indeed what we
# want....
self.dataset.SetMetadataItem('instrument', json.dumps(mm))
self.dataset.SetMetadataItem('platform', json.dumps(ee))
self._add_swath_mask_band()
