sentinelhub.data_collections

Module defining data collections

class sentinelhub.data_collections.OrbitDirection[source]

Bases: object

Orbit directions

ASCENDING = 'ASCENDING'

DESCENDING = 'DESCENDING'

BOTH = 'BOTH'

class sentinelhub.data_collections.DataCollectionDefinition(api_id=None, catalog_id=None, wfs_id=None, service_url=None, collection_type=None, sensor_type=None, processing_level=None, swath_mode=None, polarization=None, resolution=None, orbit_direction=None, timeliness=None, bands=None, metabands=None, collection_id=None, is_timeless=False, has_cloud_coverage=False, dem_instance=None, _name=None)[source]

Bases: object

An immutable definition of a data collection

Check DataCollection.define for more info about attributes of this class

Parameters:

api_id (str | None) –
catalog_id (str | None) –
wfs_id (str | None) –
service_url (str | None) –
collection_type (str | None) –
sensor_type (str | None) –
processing_level (str | None) –
swath_mode (str | None) –
polarization (str | None) –
resolution (str | None) –
orbit_direction (str | None) –
timeliness (str | None) –
bands (Tuple[Band, ...] | None) –
metabands (Tuple[Band, ...] | None) –
collection_id (str | None) –
is_timeless (bool) –
has_cloud_coverage (bool) –
dem_instance (str | None) –
_name (str | None) –

api_id: str | None = None

catalog_id: str | None = None

wfs_id: str | None = None

service_url: str | None = None

collection_type: str | None = None

sensor_type: str | None = None

processing_level: str | None = None

swath_mode: str | None = None

polarization: str | None = None

resolution: str | None = None

orbit_direction: str | None = None

timeliness: str | None = None

bands: Tuple[Band, ...] | None = None

metabands: Tuple[Band, ...] | None = None

collection_id: str | None = None

is_timeless: bool = False

has_cloud_coverage: bool = False

dem_instance: str | None = None

derive(**params)[source]

Create a new data collection definition from current definition and parameters that override current parameters

Parameters:: params (Any) – Any of DataCollectionDefinition attributes
Returns:: A new data collection definition
Return type:: DataCollectionDefinition

class sentinelhub.data_collections.DataCollection(value, *args, **kwargs)[source]

Bases: Enum

An enum class for data collections

It contains a number of predefined data collections, which are the most commonly used with Sentinel Hub service. Additionally, it also allows defining new data collections by specifying data collection parameters relevant for the service. Check DataCollection.define and similar methods for more.

SENTINEL2_L1C = DataCollectionDefinition( api_id: sentinel-2-l1c catalog_id: sentinel-2-l1c wfs_id: DSS1 service_url: https://services.sentinel-hub.com collection_type: Sentinel-2 sensor_type: MSI processing_level: L1C bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B06', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B08', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B8A', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B09', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B10', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B11', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B12', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>))) metabands: (Band(name='sunAzimuthAngles', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='viewAzimuthMean', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='sunZenithAngles', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='viewZenithMean', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CLP', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='CLM', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

SENTINEL2_L2A = DataCollectionDefinition( api_id: sentinel-2-l2a catalog_id: sentinel-2-l2a wfs_id: DSS2 service_url: https://services.sentinel-hub.com collection_type: Sentinel-2 sensor_type: MSI processing_level: L2A bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B06', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B08', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B8A', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B09', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B11', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='B12', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>))) metabands: (Band(name='AOT', units=(<Unit.OPTICAL_DEPTH: 'OPTICAL_DEPTH'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='sunAzimuthAngles', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='viewAzimuthMean', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='sunZenithAngles', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='viewZenithMean', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SNW', units=(<Unit.PERCENT: 'PERCENT'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='CLD', units=(<Unit.PERCENT: 'PERCENT'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='SCL', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='CLP', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='CLM', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

SENTINEL1 = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD orbit_direction: BOTH metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_IW = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: IW polarization: DV resolution: HIGH orbit_direction: BOTH bands: (Band(name='VV', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)), Band(name='VH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_IW_ASC = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: IW polarization: DV resolution: HIGH orbit_direction: ASCENDING bands: (Band(name='VV', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)), Band(name='VH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_IW_DES = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: IW polarization: DV resolution: HIGH orbit_direction: DESCENDING bands: (Band(name='VV', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)), Band(name='VH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_EW = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: EW polarization: DH resolution: MEDIUM orbit_direction: BOTH bands: (Band(name='HH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)), Band(name='HV', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_EW_ASC = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: EW polarization: DH resolution: MEDIUM orbit_direction: ASCENDING bands: (Band(name='HH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)), Band(name='HV', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_EW_DES = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: EW polarization: DH resolution: MEDIUM orbit_direction: DESCENDING bands: (Band(name='HH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)), Band(name='HV', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_EW_SH = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: EW polarization: SH resolution: MEDIUM orbit_direction: BOTH bands: (Band(name='HH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)),) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_EW_SH_ASC = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: EW polarization: SH resolution: MEDIUM orbit_direction: ASCENDING bands: (Band(name='HH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)),) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL1_EW_SH_DES = DataCollectionDefinition( api_id: sentinel-1-grd catalog_id: sentinel-1-grd wfs_id: DSS3 service_url: https://services.sentinel-hub.com collection_type: Sentinel-1 sensor_type: C-SAR processing_level: GRD swath_mode: EW polarization: SH resolution: MEDIUM orbit_direction: DESCENDING bands: (Band(name='HH', units=(<Unit.LINEAR_POWER: 'LINEAR_POWER'>,), output_types=(<class 'numpy.float32'>,)),) metabands: (Band(name='localIncidenceAngle', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='scatteringArea', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='shadowMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

DEM = DataCollectionDefinition( api_id: dem service_url: https://services.sentinel-hub.com collection_type: DEM bands: (Band(name='DEM', units=(<Unit.METERS: 'METERS'>,), output_types=(<class 'numpy.float32'>,)),) metabands: (Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)),) is_timeless: True has_cloud_coverage: False )

DEM_MAPZEN = DataCollectionDefinition( api_id: dem service_url: https://services.sentinel-hub.com collection_type: DEM bands: (Band(name='DEM', units=(<Unit.METERS: 'METERS'>,), output_types=(<class 'numpy.float32'>,)),) metabands: (Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)),) is_timeless: True has_cloud_coverage: False dem_instance: MAPZEN )

DEM_COPERNICUS_30 = DataCollectionDefinition( api_id: dem service_url: https://services.sentinel-hub.com collection_type: DEM bands: (Band(name='DEM', units=(<Unit.METERS: 'METERS'>,), output_types=(<class 'numpy.float32'>,)),) metabands: (Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)),) is_timeless: True has_cloud_coverage: False dem_instance: COPERNICUS_30 )

DEM_COPERNICUS_90 = DataCollectionDefinition( api_id: dem service_url: https://services.sentinel-hub.com collection_type: DEM bands: (Band(name='DEM', units=(<Unit.METERS: 'METERS'>,), output_types=(<class 'numpy.float32'>,)),) metabands: (Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)),) is_timeless: True has_cloud_coverage: False dem_instance: COPERNICUS_90 )

MODIS = DataCollectionDefinition( api_id: modis catalog_id: modis wfs_id: DSS5 service_url: https://services-uswest2.sentinel-hub.com collection_type: MODIS bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)),) is_timeless: False has_cloud_coverage: False )

LANDSAT_MSS_L1 = DataCollectionDefinition( api_id: landsat-mss-l1 catalog_id: landsat-mss-l1 wfs_id: DSS14 service_url: https://services-uswest2.sentinel-hub.com collection_type: Landsat 1-5 MSS sensor_type: MSS processing_level: L1 bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='BQA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='QA_RADSAT', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

LANDSAT_TM_L1 = DataCollectionDefinition( api_id: landsat-tm-l1 catalog_id: landsat-tm-l1 wfs_id: DSS15 service_url: https://services-uswest2.sentinel-hub.com collection_type: Landsat 4-5 TM sensor_type: TM processing_level: L1 bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='BQA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='QA_RADSAT', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='VAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='VZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

LANDSAT_TM_L2 = DataCollectionDefinition( api_id: landsat-tm-l2 catalog_id: landsat-tm-l2 wfs_id: DSS16 service_url: https://services-uswest2.sentinel-hub.com collection_type: Landsat 4-5 TM sensor_type: TM processing_level: L2 bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06', units=(<Unit.SURFACE_TEMPERATURE: 'SURFACE_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='BQA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='QA_RADSAT', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='ST_TRAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_URAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_DRAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_ATRAN', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_EMIS', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_EMSD', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_CDIST', units=(<Unit.KILOMETERS: 'KILOMETERS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SR_ATMOS_OPACITY', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SR_CLOUD_QA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_QA', units=(<Unit.KELVIN: 'KELVIN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

LANDSAT_ETM_L1 = DataCollectionDefinition( api_id: landsat-etm-l1 catalog_id: landsat-etm-l1 wfs_id: DSS17 service_url: https://services-uswest2.sentinel-hub.com collection_type: Landsat 7 ETM+ sensor_type: ETM+ processing_level: L1 bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06_VCID_1', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06_VCID_2', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B08', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='BQA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='QA_RADSAT', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='VAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='VZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

LANDSAT_ETM_L2 = DataCollectionDefinition( api_id: landsat-etm-l2 catalog_id: landsat-etm-l2 wfs_id: DSS18 service_url: https://services-uswest2.sentinel-hub.com collection_type: Landsat 7 ETM+ sensor_type: ETM+ processing_level: L2 bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06', units=(<Unit.SURFACE_TEMPERATURE: 'SURFACE_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='BQA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='QA_RADSAT', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='ST_TRAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_URAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_DRAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_ATRAN', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_EMIS', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_EMSD', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_CDIST', units=(<Unit.KILOMETERS: 'KILOMETERS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SR_ATMOS_OPACITY', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SR_CLOUD_QA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_QA', units=(<Unit.KELVIN: 'KELVIN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

LANDSAT_OT_L1 = DataCollectionDefinition( api_id: landsat-ot-l1 catalog_id: landsat-ot-l1 wfs_id: DSS12 service_url: https://services-uswest2.sentinel-hub.com collection_type: Landsat 8 OLI and TIRS sensor_type: OLI-TIRS processing_level: L1 bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B08', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B09', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B10', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B11', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='BQA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='QA_RADSAT', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='VAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='VZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

LANDSAT_OT_L2 = DataCollectionDefinition( api_id: landsat-ot-l2 catalog_id: landsat-ot-l2 wfs_id: DSS13 service_url: https://services-uswest2.sentinel-hub.com collection_type: Landsat 8 OLI and TIRS sensor_type: OLI-TIRS processing_level: L2 bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B10', units=(<Unit.SURFACE_TEMPERATURE: 'SURFACE_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='BQA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='QA_RADSAT', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='SR_QA_AEROSOL', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint8'>,)), Band(name='ST_QA', units=(<Unit.KELVIN: 'KELVIN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_TRAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_URAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_DRAD', units=(<Unit.RADIANCE: 'RADIANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_ATRAN', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_EMIS', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_EMSD', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,)), Band(name='ST_CDIST', units=(<Unit.KILOMETERS: 'KILOMETERS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

SENTINEL5P = DataCollectionDefinition( api_id: sentinel-5p-l2 catalog_id: sentinel-5p-l2 wfs_id: DSS7 service_url: https://creodias.sentinel-hub.com collection_type: Sentinel-5P sensor_type: TROPOMI processing_level: L2 bands: (Band(name='CO', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='HCHO', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='NO2', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='O3', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SO2', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CH4', units=(<Unit.PPB: 'PPB'>,), output_types=(<class 'numpy.float32'>,)), Band(name='AER_AI_340_380', units=(<Unit.INDEX: 'INDEX'>,), output_types=(<class 'numpy.float32'>,)), Band(name='AER_AI_354_388', units=(<Unit.INDEX: 'INDEX'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CLOUD_BASE_PRESSURE', units=(<Unit.PASCALS: 'PASCALS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CLOUD_TOP_PRESSURE', units=(<Unit.PASCALS: 'PASCALS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CLOUD_BASE_HEIGHT', units=(<Unit.METERS: 'METERS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CLOUD_TOP_HEIGHT', units=(<Unit.METERS: 'METERS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CLOUD_OPTICAL_THICKNESS', units=(<Unit.OPTICAL_DEPTH: 'OPTICAL_DEPTH'>,), output_types=(<class 'numpy.float32'>,)), Band(name='CLOUD_FRACTION', units=(<Unit.FRACTION: 'FRACTION'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)),) is_timeless: False has_cloud_coverage: False )

SENTINEL3_OLCI = DataCollectionDefinition( api_id: sentinel-3-olci catalog_id: sentinel-3-olci wfs_id: DSS8 service_url: https://creodias.sentinel-hub.com collection_type: Sentinel-3 sensor_type: OLCI processing_level: L1B bands: (Band(name='B01', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B02', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B03', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B04', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B05', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B06', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B07', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B08', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B09', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B10', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B11', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B12', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B13', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B14', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B15', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B16', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B17', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B18', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B19', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B20', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='B21', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='VAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='VZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SAA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SZA', units=(<Unit.DEGREES: 'DEGREES'>,), output_types=(<class 'numpy.float32'>,)), Band(name='HUMIDITY', units=(<Unit.PERCENT: 'PERCENT'>,), output_types=(<class 'numpy.float32'>,)), Band(name='SEA_LEVEL_PRESSURE', units=(<Unit.HECTOPASCALS: 'HECTOPASCALS'>,), output_types=(<class 'numpy.float32'>,)), Band(name='TOTAL_COLUMN_OZONE', units=(<Unit.KG_M2: 'KG_M2'>,), output_types=(<class 'numpy.float32'>,)), Band(name='TOTAL_COLUMN_WATER_VAPOUR', units=(<Unit.KG_M2: 'KG_M2'>,), output_types=(<class 'numpy.float32'>,)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: False )

SENTINEL3_SLSTR = DataCollectionDefinition( api_id: sentinel-3-slstr catalog_id: sentinel-3-slstr wfs_id: DSS9 service_url: https://creodias.sentinel-hub.com collection_type: Sentinel-3 sensor_type: SLSTR processing_level: L1B bands: (Band(name='S1', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S2', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S3', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S4', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S5', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S6', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S7', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S8', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='S9', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='F1', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,)), Band(name='F2', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>,), output_types=(<class 'numpy.float32'>,))) metabands: (Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,)),) is_timeless: False has_cloud_coverage: True )

HARMONIZED_LANDSAT_SENTINEL = DataCollectionDefinition( api_id: hls catalog_id: hls service_url: https://services-uswest2.sentinel-hub.com collection_type: Harmonized Landsat Sentinel bands: (Band(name='CoastalAerosol', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='Blue', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='Green', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='Red', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='RedEdge1', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='RedEdge2', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='RedEdge3', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='NIR_Broad', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='NIR_Narrow', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='SWIR1', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='SWIR2', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='WaterVapor', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='Cirrus', units=(<Unit.REFLECTANCE: 'REFLECTANCE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='ThermalInfrared1', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='ThermalInfrared2', units=(<Unit.BRIGHTNESS_TEMPERATURE: 'BRIGHTNESS_TEMPERATURE'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>))) metabands: (Band(name='QA', units=(<Unit.DN: 'DN'>,), output_types=(<class 'numpy.uint16'>,)), Band(name='VAA', units=(<Unit.DEGREES: 'DEGREES'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='VZA', units=(<Unit.DEGREES: 'DEGREES'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='SAA', units=(<Unit.DEGREES: 'DEGREES'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='SZA', units=(<Unit.DEGREES: 'DEGREES'>, <Unit.DN: 'DN'>), output_types=(<class 'numpy.float32'>, <class 'numpy.uint16'>)), Band(name='dataMask', units=(<Unit.DN: 'DN'>,), output_types=(<class 'bool'>,))) is_timeless: False has_cloud_coverage: True )

classmethod define(name, *, api_id=None, catalog_id=None, wfs_id=None, service_url=None, collection_type=None, sensor_type=None, processing_level=None, swath_mode=None, polarization=None, resolution=None, orbit_direction=None, timeliness=None, bands=None, metabands=None, collection_id=None, is_timeless=False, has_cloud_coverage=False, dem_instance=None)[source]

Define a new data collection

Note that all parameters, except name are optional. If a data collection definition won’t be used for a certain use case (e.g. Process API, WFS, etc.), parameters for that use case don’t have to be defined

Parameters:

name (str) – A name of a new data collection
api_id (str | None) – An ID to be used for Sentinel Hub Process API
catalog_id (str | None) – An ID to be used for Sentinel Hub Catalog API
wfs_id (str | None) – An ID to be used for Sentinel Hub WFS service
service_url (str | None) – A base URL of Sentinel Hub service deployment from where to download data. If it is not specified, a sh_base_url from a config will be used by default
collection_type (str | None) – A collection type
sensor_type (str | None) – A type of a satellite’s sensor
processing_level (str | None) – A level of processing applied on satellite data
swath_mode (str | None) – A swath mode of SAR sensors
polarization (str | None) – A type of polarization
resolution (str | None) – A type of (Sentinel-1) resolution
orbit_direction (str | None) – A direction of satellite’s orbit by which to filter satellite’s data
timeliness (str | None) – A timeliness of data
bands (Tuple[Band, ...] | None) – Information about data collection bands
metabands (Tuple[Band, ...] | None) – Information about data collection metabands
collection_id (str | None) – An ID of a BYOC or BATCH collection
is_timeless (bool) – True if a data collection can be filtered by time dimension and False otherwise
has_cloud_coverage (bool) – True if data collection can be filtered by cloud coverage percentage and False otherwise
dem_instance (str | None) – one of the options listed in DEM documentation

Returns:

A new data collection

Return type:

DataCollection

define_from(name, **params)[source]

Define a new data collection from an existing one

Parameters:

name (str) – A name of a new data collection
params (Any) – Any parameter to override current data collection parameters

Returns:

A new data collection

Return type:

DataCollection

classmethod define_byoc(collection_id, **params)[source]

Defines a BYOC data collection

Parameters:

collection_id (str) – An ID of a data collection
params (Any) – Any parameter to override default BYOC data collection parameters

Returns:

A new data collection

Return type:

DataCollection

classmethod define_batch(collection_id, **params)[source]

Defines a BATCH data collection

Parameters:

collection_id (str) – An ID of a data collection
params (Any) – Any parameter to override default BATCH data collection parameters

Returns:

A new data collection

Return type:

DataCollection

property api_id: str

Provides a Sentinel Hub Process API identifier or raises an error if it is not defined

Returns:: An identifier
Raises:: ValueError

property catalog_id: str

Provides a Sentinel Hub Catalog API identifier or raises an error if it is not defined

Returns:: An identifier
Raises:: ValueError

property wfs_id: str

Provides a Sentinel Hub WFS identifier or raises an error if it is not defined

Returns:: An identifier
Raises:: ValueError

property bands: Tuple[Band, ...]

Provides band information available for the data collection

Returns:: A tuple of band info
Raises:: ValueError

property metabands: Tuple[Band, ...]

Provides metaband information available for the data collection

Returns:: A tuple of metaband info
Raises:: ValueError

property is_sentinel1: bool

Checks if data collection is a Sentinel-1 collection type

Example: DataCollection.SENTINEL1_IW.is_sentinel1

Returns:: True if collection is Sentinel-1 collection type and False otherwise

property is_byoc: bool

Checks if data collection is a BYOC collection type

Returns:: True if collection is a BYOC collection type and False otherwise

property is_batch: bool

Checks if data collection is a batch collection type

Returns:: True if collection is a batch collection type and False otherwise

contains_orbit_direction(orbit_direction)[source]

Checks if a data collection contains given orbit direction

Parameters:: orbit_direction (str) – An orbit direction
Returns:: True if data collection contains the orbit direction
Return type:: bool

classmethod get_available_collections()[source]

Returns which data collections are available for configured Sentinel Hub OGC URL

Returns:: List of available data collections
Return type:: List[DataCollection]