예제 #1
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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')
예제 #2
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파일: image.py 프로젝트: sixy6e/eo-datasets
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
예제 #3
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     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),
예제 #4
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        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
        )
    ),
)
예제 #5
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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()}))
예제 #6
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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