def _populate_grid_spatial(md, mtl_):
product_md = _get(mtl_, 'PRODUCT_METADATA')
# We don't have a single set of dimensions. Depends on the band?
# md.grid_spatial.dimensions = []
if not md.grid_spatial:
md.grid_spatial = ptype.GridSpatialMetadata()
if not md.grid_spatial.projection:
md.grid_spatial.projection = ptype.ProjectionMetadata()
md.grid_spatial.projection.geo_ref_points = ptype.PointPolygon(
ul=ptype.Point(x=_get(product_md, 'corner_ul_projection_x_product'),
y=_get(product_md, 'corner_ul_projection_y_product')),
ur=ptype.Point(x=_get(product_md, 'corner_ur_projection_x_product'),
y=_get(product_md, 'corner_ur_projection_y_product')),
ll=ptype.Point(x=_get(product_md, 'corner_ll_projection_x_product'),
y=_get(product_md, 'corner_ll_projection_y_product')),
lr=ptype.Point(x=_get(product_md, 'corner_lr_projection_x_product'),
y=_get(product_md, 'corner_lr_projection_y_product')))
# centre_point=None,
projection_md = _get(mtl_, 'PROJECTION_PARAMETERS')
md.grid_spatial.projection.datum = _get(projection_md, 'datum')
md.grid_spatial.projection.ellipsoid = _get(projection_md, 'ellipsoid')
# Where does this come from? 'ul' etc.
# point_in_pixel=None,
md.grid_spatial.projection.map_projection = _get(projection_md,
'map_projection')
md.grid_spatial.projection.resampling_option = _get(
projection_md, 'resampling_option')
md.grid_spatial.projection.datum = _get(projection_md, 'datum')
md.grid_spatial.projection.ellipsoid = _get(projection_md, 'ellipsoid')
md.grid_spatial.projection.zone = _get(projection_md, 'utm_zone')
md.grid_spatial.projection.orientation = _get(projection_md, 'orientation')
def populate_from_image_metadata(md):
"""
Populate by extracting metadata from existing band files.
:type md: eodatasets.type.DatasetMetadata
:rtype: eodatasets.type.DatasetMetadata
"""
for band_id, band in md.image.bands.items():
i = gdal.Open(str(band.path))
if not i:
# TODO: log? throw?
continue
spacial_ref = osr.SpatialReference(i.GetProjectionRef())
# Extract actual image coords
# md.grid_spatial.projection.
band.shape = ptype.Point(i.RasterXSize, i.RasterYSize)
band.cell_size = ptype.Point(abs(i.GetGeoTransform()[1]),
abs(i.GetGeoTransform()[5]))
# TODO separately: create standardised WGS84 coords. for md.extent
# wkt_contents = spacial_ref.ExportToPrettyWkt()
# TODO: if srs IsGeographic()? Otherwise srs IsProjected()?
if not md.grid_spatial:
md.grid_spatial = ptype.GridSpatialMetadata()
if not md.grid_spatial.projection:
md.grid_spatial.projection = ptype.ProjectionMetadata()
md.grid_spatial.projection.geo_ref_points = _get_gdal_image_coords(i)
md.grid_spatial.projection.unit = spacial_ref.GetLinearUnitsName()
md.grid_spatial.projection.zone = spacial_ref.GetUTMZone()
# ?
md.grid_spatial.projection.datum = 'GDA94'
md.grid_spatial.projection.ellipsoid = 'GRS80'
# TODO: DATUM/Reference system etc.
if not md.extent:
md.extent = ptype.ExtentMetadata()
md.extent.coord = reproject_coords(
md.grid_spatial.projection.geo_ref_points, spacial_ref)
# Get positional info, projection etc.
# Is projection/etc same as previous?
# -- If all match, set on wider image.
i = None
return md
center_dt=datetime.datetime(2005, 1, 7, 2, 3, 36, 927051)
),
grid_spatial=ptype.GridSpatialMetadata(
projection=ptype.ProjectionMetadata(
geo_ref_points=ptype.PointPolygon(
ul=ptype.Point(
x=350012.500,
y=8028987.500
),
ur=ptype.Point(
x=587012.500,
y=8028987.500
),
ll=ptype.Point(
x=350012.500,
y=7817987.500
),
lr=ptype.Point(
x=587012.500,
y=7817987.500
)
),
datum='GDA94',
ellipsoid='GRS80',
map_projection='UTM',
orientation='NORTH_UP',
resampling_option='CUBIC_CONVOLUTION',
zone=-50
)
),
image=ptype.ImageMetadata(
satellite_ref_point_start=ptype.Point(x=114, y=73),
algorithm=ptype.AlgorithmMetadata(name='terrain', version='1.0'),
),
grid_spatial=ptype.GridSpatialMetadata(
projection=ptype.ProjectionMetadata(
geo_ref_points=ptype.PointPolygon(
ul=ptype.Point(
x=397012.5,
y=7235987.5
),
ur=ptype.Point(
x=625012.5,
y=7235987.5
),
ll=ptype.Point(
x=397012.5,
y=7013987.5
),
lr=ptype.Point(
x=625012.5,
y=7013987.5
)
),
datum='GDA94',
ellipsoid='GRS80',
map_projection='UTM',
orientation='NORTH_UP',
resampling_option='CUBIC_CONVOLUTION',
zone=-53
)
),
)
def _build_ls8_ortho():
_reset_runtime_id()
return ptype.DatasetMetadata(
id_=uuid.UUID('17b92c16-51d3-11e4-909d-005056bb6972'),
ga_label='LS8_OLITIRS_OTH_P51_GALPGS01-002_101_078_20141012',
product_type='GAORTHO01',
creation_dt=dateutil.parser.parse('2014-10-12 05:46:20'),
size_bytes=2386550 * 1024,
platform=ptype.PlatformMetadata(code='LANDSAT-8'),
instrument=ptype.InstrumentMetadata(name='OLI_TIRS',
type_="Multi-Spectral",
operation_mode='PUSH-BROOM'),
format_=ptype.FormatMetadata(name='GeoTiff', version=1),
extent=ptype.ExtentMetadata(
reference_system='WGS84',
coord=ptype.CoordPolygon(ul=ptype.Coord(lat=-24.97, lon=133.97969),
ur=ptype.Coord(lat=-24.96826,
lon=136.24838),
lr=ptype.Coord(lat=-26.96338,
lon=136.26962),
ll=ptype.Coord(lat=-26.96528,
lon=133.96233)),
from_dt=dateutil.parser.parse("2014-10-12T00:55:54"),
center_dt=dateutil.parser.parse("2014-10-12T00:56:06"),
to_dt=dateutil.parser.parse("2014-10-12T00:56:18"),
),
grid_spatial=ptype.GridSpatialMetadata(
dimensions=[
ptype.DimensionMetadata(name='sample',
resolution=25.0,
size=9161),
ptype.DimensionMetadata(name='line',
resolution=25.0,
size=9161)
],
projection=ptype.ProjectionMetadata(
centre_point=ptype.Point(511512.500000, 7127487.500000),
geo_ref_points=ptype.PointPolygon(
ul=ptype.Point(397012.5, 7237987.5),
ur=ptype.Point(626012.5, 7237987.5),
ll=ptype.Point(397012.5, 7016987.5),
lr=ptype.Point(626012.5, 7016987.5)),
datum='GDA94',
ellipsoid='GRS80',
point_in_pixel='UL',
map_projection='UTM',
resampling_option='CUBIC_CONVOLUTION',
zone=-53)),
browse={
'medium':
ptype.BrowseMetadata(path=Path(
'product/LS8_OLITIRS_OTH_P51_GALPGS01-032_101_078_20141012.jpg'
),
file_type='image/jpg',
cell_size=219.75,
red_band=7,
green_band=5,
blue_band=1),
'full':
ptype.BrowseMetadata(path=Path(
'LS8_OLITIRS_OTH_P51_GALPGS01-032_101_078_20141012_FR.jpg'),
file_type='image/jpg',
cell_size=25.0,
red_band=7,
green_band=5,
blue_band=1)
},
image=ptype.ImageMetadata(
satellite_ref_point_start=ptype.Point(101, 78),
cloud_cover_percentage=0,
cloud_cover_details=None,
sun_elevation=58.00268508,
sun_azimuth=59.41814014,
ground_control_points_model=420,
geometric_rmse_model=4.610,
geometric_rmse_model_x=3.527,
geometric_rmse_model_y=2.968,
# TODO: What are these two?
viewing_incidence_angle_long_track=0,
viewing_incidence_angle_x_track=0,
bands={
'coastal_aerosol':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B1.TIF'),
number=1,
type_='reflective',
cell_size=25.0,
),
'visible_blue':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B2.TIF'),
number=2,
type_='reflective',
cell_size=25.0,
),
'visible_green':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B3.TIF'),
number=3,
type_='reflective',
cell_size=25.0,
),
'visible_red':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B4.TIF'),
number=4,
type_='reflective',
cell_size=25.0,
),
'near_infrared':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B5.TIF'),
number=5,
type_='reflective',
cell_size=25.0,
),
'short_wave_infrared1':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B6.TIF'),
number=6,
type_='reflective',
cell_size=25.0,
),
'short_wave_infrared2':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B7.TIF'),
number=7,
type_='reflective',
cell_size=25.0,
),
'panchromatic':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B8.TIF'),
number=8,
type_='panchromatic',
cell_size=12.50,
shape=ptype.Point(17761, 18241),
),
'cirrus':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B9.TIF'),
number=9,
type_='atmosphere',
),
'thermal_infrared1':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B10.TIF'),
number=10,
type_='thermal',
cell_size=25.0,
shape=ptype.Point(8881, 9121),
),
'thermal_infrared2':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_B11.TIF'),
number=11,
type_='thermal',
cell_size=25.0,
shape=ptype.Point(8881, 9121),
),
'quality':
ptype.BandMetadata(
path=Path('product/LC81010782014285LGN00_BQA.TIF'),
number='QA',
type_='quality',
)
}),
lineage=ptype.LineageMetadata(
algorithm=ptype.AlgorithmMetadata(
name='Pinkmatter Landsat Processor',
version='3.3.3104',
parameters={
'resampling': 'CC',
'radiometric_correction': 'CPF',
'orientation': 'NUP',
'hemisphere': 'S',
}),
machine=ptype.MachineMetadata(
hostname='rhe-jm-prod08.prod.lan',
type_id='jobmanager',
uname=
'Linux rhe-jm-dev08.dev.lan 2.6.32-279.22.1.el6.x86_64 #1 SMP Sun Oct '
'12 '
'09:21:40 EST 2014 x86_64 x86_64 x86_64 GNU/Linux'),
ancillary={
'cpf':
ptype.AncillaryMetadata(
name='L8CPF20141001_20141231.01',
uri=
'/eoancillarydata/sensor-specific/LANDSAT8/CalibrationParameterFile'
'/L8CPF20141001_20141231.01'),
'bpf_tirs':
ptype.AncillaryMetadata(
name='LT8BPF20141012002432_20141012020301.01',
uri=
'/eoancillarydata/sensor-specific/LANDSAT8/BiasParameterFile/2014/10'
'/LT8BPF20141012002432_20141012020301.01'),
'bpf_oli':
ptype.AncillaryMetadata(
name='LO8BPF20141012002825_20141012011100.01',
uri=
'/eoancillarydata/sensor-specific/LANDSAT8/BiasParameterFile/2014/10'
'/LT8BPF20141012002432_20141012020301.01'),
'rlut':
ptype.AncillaryMetadata(name='L8RLUT20130211_20431231v09.h5')
},
source_datasets={'satellite_telemetry_data': _build_ls8_raw()}))
def _build_ls8_nbar():
_reset_runtime_id()
nbar = ptype.DatasetMetadata(
id_=uuid.UUID("249ae098-bd88-11e4-beaa-1040f381a756"),
size_bytes=622208 * 1024,
ga_label='LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012',
product_type='GANBAR01',
platform=ptype.PlatformMetadata(code='LANDSAT-8'),
instrument=ptype.InstrumentMetadata(name='OLI_TIRS',
type_="Multi-Spectral",
operation_mode='PUSH-BROOM'),
# acquisition=ptype.AcquisitionMetadata(),
format_=ptype.FormatMetadata(name='GeoTiff', version=1),
extent=ptype.ExtentMetadata(
reference_system='WGS84',
coord=ptype.CoordPolygon(ul=ptype.Coord(lat=-24.97, lon=133.97969),
ur=ptype.Coord(lat=-24.96826,
lon=136.24838),
lr=ptype.Coord(lat=-26.96338,
lon=136.26962),
ll=ptype.Coord(lat=-26.96528,
lon=133.96233)),
from_dt=dateutil.parser.parse("2014-10-12T00:55:54"),
to_dt=dateutil.parser.parse("2014-10-12T00:56:18"),
),
grid_spatial=ptype.GridSpatialMetadata(
dimensions=[
ptype.DimensionMetadata(name='sample',
resolution=25.0,
size=9161),
ptype.DimensionMetadata(name='line',
resolution=25.0,
size=9161)
],
projection=ptype.ProjectionMetadata(
centre_point=ptype.Point(511512.500000, 7127487.500000),
geo_ref_points=ptype.PointPolygon(
ul=ptype.Point(397012.5, 7237987.5),
ur=ptype.Point(626012.5, 7237987.5),
ll=ptype.Point(397012.5, 7016987.5),
lr=ptype.Point(626012.5, 7016987.5)),
datum='GDA94',
ellipsoid='GRS80',
point_in_pixel='UL',
map_projection='UTM',
resampling_option='CUBIC_CONVOLUTION',
zone=-53)),
browse={
'medium':
ptype.BrowseMetadata(path=Path(
'LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012.tif'),
file_type='image/jpg',
cell_size=219.75,
red_band=7,
green_band=5,
blue_band=2),
'full':
ptype.BrowseMetadata(path=Path(
'LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_FR.tif'),
file_type='image/jpg',
cell_size=25.0,
red_band=7,
green_band=5,
blue_band=2)
},
image=ptype.ImageMetadata(
satellite_ref_point_start=ptype.Point(101, 78),
cloud_cover_percentage=0.01,
cloud_cover_details=None,
# TODO: What are these two?
viewing_incidence_angle_long_track=0,
viewing_incidence_angle_x_track=0,
bands={
'1':
ptype.BandMetadata(path=Path(
'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B1.tif'
), ),
'2':
ptype.BandMetadata(path=Path(
'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B2.tif'
), ),
'3':
ptype.BandMetadata(path=Path(
'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B3.tif'
), ),
'4':
ptype.BandMetadata(path=Path(
'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B4.tif'
), ),
'5':
ptype.BandMetadata(path=Path(
'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B5.tif'
), ),
'6':
ptype.BandMetadata(path=Path(
'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B6.tif'
), ),
'7':
ptype.BandMetadata(path=Path(
'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B7.tif'
), )
}),
lineage=ptype.LineageMetadata(
algorithm=ptype.AlgorithmMetadata(name='GANBAR',
version='3.2.1',
parameters={}),
machine=ptype.MachineMetadata(),
source_datasets={'level1': _build_ls8_ortho()},
ancillary={}))
return nbar