Shapely geometries and spatial relationships

Lavorare con i dati geospaziali 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)
Lavorare con i dati geospaziali in Python

Scalar geometry values

brussels = cities.loc[170, 'geometry']
print(brussels)
POINT (4.33137074969045 50.83526293533032)
type(brussels)
shapely.geometry.point.Point
Lavorare con i dati geospaziali in Python

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
Lavorare con i dati geospaziali in Python

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)
Lavorare con i dati geospaziali in Python

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, ...)

Lavorare con i dati geospaziali in Python

Spatial relationships

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

Lavorare con i dati geospaziali in Python

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
Lavorare con i dati geospaziali in Python

Let's practice!

Lavorare con i dati geospaziali in Python

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