Population & Socioeconomic¶
| Class | Key params | Returns | Data source | Description |
|---|---|---|---|---|
WorldPop |
agesex_classes=[], version=1, year=2020 |
raster | GEE WorldPop/GP/100m/pop[_age_sex] (or sat-io community version) |
Gridded population counts, total or filtered by age-sex subgroup via WorldPopClass. |
API¶
city_metrix.layers.world_pop.WorldPopClass ¶
Bases: Enum
ADULT
class-attribute
instance-attribute
¶
ADULT = ['F_20', 'F_25', 'F_30', 'F_35', 'F_40', 'F_45', 'F_50', 'F_55', 'F_60', 'F_65', 'F_70', 'F_75', 'F_80', 'M_20', 'M_25', 'M_30', 'M_35', 'M_40', 'M_45', 'M_50', 'M_55', 'M_60', 'M_65', 'M_70', 'M_75', 'M_80']
ELDERLY
class-attribute
instance-attribute
¶
ELDERLY = ['F_60', 'F_65', 'F_70', 'F_75', 'F_80', 'M_60', 'M_65', 'M_70', 'M_75', 'M_80']
CHILDREN
class-attribute
instance-attribute
¶
CHILDREN = ['F_0', 'F_1', 'F_5', 'F_10', 'M_0', 'M_1', 'M_5', 'M_10']
FEMALE
class-attribute
instance-attribute
¶
FEMALE = ['F_0', 'F_1', 'F_5', 'F_10', 'F_15', 'F_20', 'F_25', 'F_30', 'F_35', 'F_40', 'F_45', 'F_50', 'F_55', 'F_60', 'F_65', 'F_70', 'F_75', 'F_80']
city_metrix.layers.world_pop.WorldPop ¶
WorldPop(agesex_classes: WorldPopClass = [], version=1, year=2020, **kwargs)
Bases: Layer
MINOR_NAMING_ATTS
class-attribute
instance-attribute
¶
MINOR_NAMING_ATTS = ['version']
Attributes: agesex_classes: Enum value from WorldPopClass OR list of age-sex classes to retrieve (see https://airtable.com/appDWCVIQlVnLLaW2/tblYpXsxxuaOk3PaZ/viwExxAgTQKZnRfWU/recFjH7WngjltFMGi?blocks=hide) year: year used for data retrieval
get_data ¶
get_data(bbox: GeoExtent, spatial_resolution: int = DEFAULT_SPATIAL_RESOLUTION, resampling_method=None)