The GEDI Python API gedi.py is used to access the services provided by the gedi plugin for SlideRule. From Python, the module can be imported via:
from sliderule import gediFunctions¶
init¶
sliderule.gedi.init(url='slideruleearth.io', verbose=False, loglevel=50, organization='sliderule', desired_nodes=None, time_to_live=60)Initializes the Python client for use with SlideRule and should be called before other GEDI API calls.
This function is a wrapper for the sliderule.init(...) function </api_reference/sliderule.html#init>_.
Examples
>>> from sliderule import gedi
>>> gedi.init()gedi04a¶
sliderule.gedi.gedi04a(parm, resource)Performs GEDI L4A subsetting of elevation footprints
Parameters
parms (dict) parameters used to configure subsetting process
resource (str) GEDI HDF5 filename
asset (str) data source asset
Returns
GeoDataFrame
gridded footrpints
gedi04ap¶
sliderule.gedi.gedi04ap(parm, callbacks={}, resources=None, keep_id=False, as_numpy_array=False, height_key=None)Performs subsetting in parallel on GEDI data and returns elevation footprints. This function expects that the parm argument includes a polygon which is used to fetch all available resources from the CMR system automatically. If resources is specified then any polygon or resource filtering options supplied in parm are ignored.
Parameters
parms (dict) parameters used to configure subsetting process
asset (str) data source asset
callbacks (dictionary) a callback function that is called for each result record
resources (list) a list of granules to process (e.g. [“GEDI04_A_2019229131935_O03846_02_T03642_02_002_02_V002.h5”, ...])
keep_id (bool) whether to retain the “extent_id” column in the GeoDataFrame for future merges
as_numpy_array (bool) whether to provide all sampled values as numpy arrays even if there is only a single value
height_key (str) identifies the name of the column provided for the 3D CRS transformation
Returns
GeoDataFrame
geolocated footprints
Examples
>>> from sliderule import gedi
>>> gedi.init()
>>> region = [ {"lon":-105.82971551223244, "lat": 39.81983728534918},
... {"lon":-105.30742121965137, "lat": 39.81983728534918},
... {"lon":-105.30742121965137, "lat": 40.164048017973755},
... {"lon":-105.82971551223244, "lat": 40.164048017973755},
... {"lon":-105.82971551223244, "lat": 39.81983728534918} ]
>>> parms = { "poly": region }
>>> resources = ["GEDI04_A_2019229131935_O03846_02_T03642_02_002_02_V002.h5"]
>>> asset = "ornldaac-s3"
>>> rsps = gedi.gedi04ap(parms, asset=asset, resources=resources)gedi02a¶
sliderule.gedi.gedi02a(parm, resource)Performs GEDI L2A subsetting of elevation footprints
Parameters
parms (dict) parameters used to configure subsetting process
resource (str) GEDI HDF5 filename
asset (str) data source asset
Returns
GeoDataFrame
gridded footrpints
gedi02ap¶
sliderule.gedi.gedi02ap(parm, callbacks={}, resources=None, keep_id=False, as_numpy_array=False, height_key=None)Performs subsetting in parallel on GEDI data and returns geolocated footprints. This function expects that the parm argument includes a polygon which is used to fetch all available resources from the CMR system automatically. If resources is specified then any polygon or resource filtering options supplied in parm are ignored.
Parameters
parms (dict) parameters used to configure subsetting process
asset (str) data source asset
callbacks (dictionary) a callback function that is called for each result record
resources (list) a list of granules to process (e.g. [“GEDI04_A_2019229131935_O03846_02_T03642_02_002_02_V002.h5”, ...])
keep_id (bool) whether to retain the “extent_id” column in the GeoDataFrame for future merges
as_numpy_array (bool) whether to provide all sampled values as numpy arrays even if there is only a single value
height_key (str) identifies the name of the column provided for the 3D CRS transformation
Returns
GeoDataFrame
geolocated footprints
Examples
>>> from sliderule import gedi
>>> gedi.init()
>>> region = [ {"lon":-105.82971551223244, "lat": 39.81983728534918},
... {"lon":-105.30742121965137, "lat": 39.81983728534918},
... {"lon":-105.30742121965137, "lat": 40.164048017973755},
... {"lon":-105.82971551223244, "lat": 40.164048017973755},
... {"lon":-105.82971551223244, "lat": 39.81983728534918} ]
>>> parms = { "poly": region }
>>> resources = ["GEDI02_A_2019229131935_O03846_02_T03642_02_002_02_V002.h5"]
>>> asset = "gedi-local"
>>> rsps = gedi.gedi02ap(parms, asset=asset, resources=resources)gedi01b¶
sliderule.gedi.gedi01b(parm, resource)Performs GEDI L1B subsetting of elevation waveforms
Parameters
parms (dict) parameters used to configure subsetting process
resource (str) GEDI HDF5 filename
asset (str) data source asset
Returns
GeoDataFrame
gridded footrpints
gedi01bp¶
sliderule.gedi.gedi01bp(parm, callbacks={}, resources=None, keep_id=False, as_numpy_array=False, height_key=None)Performs subsetting in parallel on GEDI data and returns geolocated footprints. This function expects that the parm argument includes a polygon which is used to fetch all available resources from the CMR system automatically. If resources is specified then any polygon or resource filtering options supplied in parm are ignored.
Parameters
parms (dict) parameters used to configure subsetting process
asset (str) data source asset
callbacks (dictionary) a callback function that is called for each result record
resources (list) a list of granules to process (e.g. [“GEDI04_A_2019229131935_O03846_02_T03642_02_002_02_V002.h5”, ...])
keep_id (bool) whether to retain the “extent_id” column in the GeoDataFrame for future merges
as_numpy_array (bool) whether to provide all sampled values as numpy arrays even if there is only a single value
height_key (str) identifies the name of the column provided for the 3D CRS transformation
Returns
GeoDataFrame
geolocated footprints
Examples
>>> from sliderule import gedi
>>> gedi.init()
>>> region = [ {"lon":-105.82971551223244, "lat": 39.81983728534918},
... {"lon":-105.30742121965137, "lat": 39.81983728534918},
... {"lon":-105.30742121965137, "lat": 40.164048017973755},
... {"lon":-105.82971551223244, "lat": 40.164048017973755},
... {"lon":-105.82971551223244, "lat": 39.81983728534918} ]
>>> parms = { "poly": region }
>>> resources = ["GEDI01_B_2019229131935_O03846_02_T03642_02_002_02_V002.h5"]
>>> asset = "gedi-local"
>>> rsps = gedi.gedi01bp(parms, asset=asset, resources=resources)