tobler.dasymetric.masked_area_interpolate

tobler.dasymetric.masked_area_interpolate(source_df, target_df, raster='nlcd_2011', codes=None, force_crs_match=True, extensive_variables=None, intensive_variables=None, allocate_total=True, tables=None)[source]

Interpolate data between two polygonal datasets using an auxiliary raster to mask out uninhabited land.

Parameters
source_dfgeopandas.GeoDataFrame

source data to be converted to another geometric representation.

target_dfgeopandas.GeoDataFrame

target geometries that will form the new representation of the input data

rasterstr

path to raster file that contains ancillary data. alternatively a user can pass ncld_2001 or nlcd_2011 to use built-in data from the National Land Cover Database

codeslist of ints

list of pixel values that should be considered part of the mask (the default is None). If no codes are passed, this defaults to [21, 22, 23, 24] which are the developed land use codes from the NLCD data

force_crs_matchbool

whether to force the input and target data to share the same CRS (the default is True).

extensive_variableslist

Columns of the input dataframe containing extensive variables to interpolate

intensive_variableslist

Columns of the input dataframe containing intensive variables to interpolate

allocate_totalbool

whether to allocate the total from the source geometries (the default is True).

tablestuple of two numpy.array (optional)

As generated from tobler.area_weighted.area_tables_raster (the default is None).

Returns
geopandas.GeoDataFrame

GeoDataFrame with geometries matching the target_df and extensive and intensive variables as the columns