FeatureCollection

class geodesic.stac.FeatureCollection(dataset=None, query=None, **obj)

Bases: geodesic.bases._APIObject

A collection of Features that is represented by a GeoJSON FeatureCollection in accordance with RFC7946 (https://datatracker.ietf.org/doc/html/rfc7946)

Parameters

• dataset (Dataset) – a geodesic.entanglement.Dataset associated with the FeatureCollection.

• query (dict) – a query, if any, used to initialize this from a request to Spacetime or Boson

• **obj – the underyling JSON data of the FeatureCollection to specify

features

(list) - this FeatureCollection’s Feature/Item objects

Descriptor: _FeatureListDescr

links

(dict) - links associated with this collection

Descriptor: _ListDescr

property type

the type is always FeatureCollection. This fills in for improperly constructed GeoJSON that doesn’t have the “type” field set.

property gdf: geopandas.geodataframe.GeoDataFrame

Return a geopandas.GeoDataFrame representation of this FeatureCollection

Returns

a Geopandas GeoDataFrame of this object

property df: pandas.core.frame.DataFrame

Return a Pandas DataFrame representation of this FeatureCollection

Returns

a Pandas DataFrame of this object

property sedf: pandas.core.frame.DataFrame

Return an ArcGIS API for Python representation of this feature collection as a spatially enabled Pandas DataFrame

Returns

a Pandas DataFrame of this object with a arcgis.features.GeoAccessor attached.

property ogr: gdal.Dataset

Return an GDAL Dataset with an OGR Layer for this feature collection

Returns

a gdal.Dataset for this object

rasterize(property_name=None, dtype=None, reference_dataset=None, shape=None, geo_transform=None, spatial_reference=None, return_dataset=True)

Rasterize this FeatureCollection given requirements on the input image

Parameters

• property_name (str) – the name of the property to rasterize

• dtype (np.dtype) – the numpy datatype you’d like for the output

• reference_dataset (gdal.Dataset) – a gdal.Dataset (image) that we would like to use as reference. Output will have the same shape, geo_transform, and spatial_reference

• shape (tuple) – a tuple of ints representing the output shape (if reference_dataset is None)

• geo_transform (tuple) – a tuple of affine transformation (if reference_dataset is None)

• spatial_reference (Union[str, int, osr.SpatialReference]) – the spatial reference of the output (if reference_dataset is None)

• return_dataset (bool) – return the gdal.Dataset instead of a numpy array.

static from_geojson_file(path)

loads a geojson file and returns a new FeatureCollection

Parameters

load (path - path to the file to) –

static from_shapefile(path)

loads a shapefile and returns a new FeatureCollection

This method uses pyshp

Parameters

load (path - path to the file root/prefix to) –

static from_file_geodatabase(path, layer, **kwargs)

loads a layer from a file geodatabase and returns a new FeatureCollection

Parameters

• geodatabase (path - path to the file) –

• load (layer - the name of the layer to) –

• fiona.open (**kwargs - additional keywords to pass to) –

static from_gpx(path, layer, **kwargs)

loads a GPX file and returns a new FeatureCollection

Parameters

• file (path - path to the GPX) –

• waypoints (layer - which layer to read. One of) – on the file

• routes – on the file

• tracks – on the file

• route_points – on the file

• track_points (or) – on the file

• depending – on the file

• fiona.open (**kwargs - additional keywords to pass to) –

static from_file(path, layer=None, **kwargs)

loads geospatial data using fiona and returns a new FeatureCollection

For more details about what can be read with fiona, see the following docs: https://fiona.readthedocs.io/en/latest/

Parameters

• file (path - path to the) –

• load (layer - the name of the layer to) –

• fiona.open (**kwargs - additional keywords to pass to) –