Shapely geometries and spatial relationships

Working with Geospatial Data in Python

Dani Arribas-Bel

Geographic Data Science Lab (University of Liverpool)

Scalar geometry values

cities = geopandas.read_file("ne_110m_populated_places.shp")
cities.head()

           name                                      geometry
0  Vatican City   POINT (12.45338654497177 41.90328217996012)
1    San Marino     POINT (12.44177015780014 43.936095834768)
2         Vaduz   POINT (9.516669472907267 47.13372377429357)
3       Lobamba  POINT (31.19999710971274 -26.46666746135247)
4    Luxembourg   POINT (6.130002806227083 49.61166037912108)

brussels = cities.loc[170, 'geometry']
print(brussels)

POINT (4.33137074969045 50.83526293533032)

Scalar geometry values

brussels = cities.loc[170, 'geometry']
print(brussels)

POINT (4.33137074969045 50.83526293533032)

type(brussels)

shapely.geometry.point.Point

The Shapely python package

type(brussels)

shapely.geometry.point.Point

Shapely

Python Package for the manipulation and analysis of geometric objects
Provides the Point, LineString and Polygon objects
GeoSeries (GeoDataFrame 'geometry' column) consists of shapely objects

Geometry objects

Accessing from a GeoDataFrame:

brussels = cities.loc[170, 'geometry']
paris = cities.loc[235, 'geometry']
belgium = countries.loc[countries['name'] == 'Belgium', 'geometry'].squeeze()
france = countries.loc[countries['name'] == 'France', 'geometry'].squeeze()
uk = countries.loc[countries['name'] == 'United Kingdom', 'geometry'].squeeze()

Creating manually:

from shapely.geometry import Point
p = Point(1, 2)
print(p)

POINT (1 2)

Spatial methods

The area of a geometry:

belgium.area

3.8299974609075753

The distance between 2 geometries:

brussels.distance(paris)

2.8049127723186214

And many more! (e.g. centroid, simplify, ...)

Spatial relationships

geopandas.GeoSeries([belgium, france, uk, paris,  brussels, line]).plot()

Spatial relationships

belgium.contains(brussels)

True

france.contains(brussels)

False

brussels.within(belgium)

True

belgium.touches(france)

True

line.intersects(france)

True

line.intersects(uk)

False

Let's practice!

Working with Geospatial Data in Python