I want to generate dynamically a geoJSON with a variable number of polygons. Example for 2 polygons:
{
"type": "FeatureCollection",
"features": [
{"geometry": {
"type": "GeometryCollection",
"geometries": [
{
"type": "Polygon",
"coordinates":
[[11.0878902207, 45.1602390564],
[0.8251953125, 41.0986328125],
[7.63671875, 48.96484375],
[15.01953125, 48.1298828125]]
},
{
"type": "Polygon",
"coordinates":
[[11.0878902207, 45.1602390564],
[14.931640625, 40.9228515625],
[11.0878902207, 45.1602390564]]
}
]
},
"type": "Feature",
"properties": {}}
]
}
I have a function which gives me the list of coordinates for each polygon, so I can create a list of polygons, so I am able to build the geoJSON iterating it with a for loop.
The problem is that I don't see how to do it easily (I thought for example in returning the list as a string, but building the geoJSON as a string looks like a bad idea).
I have been suggested this very pythonic idea:
geo_json = [ {"type": "Feature",,
"geometry": {
"type": "Point",
"coordinates": [lon, lat] }}
for lon, lat in zip(ListOfLong,ListOfLat) ]
But since I am adding a variable number of Polygons instead of a list of points, this solutions does not seem suitable. Or at least I don't know how to adapt it.
I could build it as a string, but I'd like to do it in a smarter way. Any idea?
Once the library is loaded, the polyplot() function can be used to draw a map of the geospatial data frame. The polyplot() function is used to plot polygons, i.e any type of geographic area. Here we are, we've loaded a geoJson file, transformed it into a geopandas dataframe and drawn a map with geoplot from it!
GeoJSON is a format for encoding a variety of geographic data structures. GeoJSON supports the following geometry types: Point , LineString , Polygon , MultiPoint , MultiLineString , and MultiPolygon . Geometric objects with additional properties are Feature objects.
There is the python-geojson library (https://github.com/frewsxcv/python-geojson), which seems to make this task also much easier. Example from the library page:
>>> from geojson import Polygon
>>> Polygon([[(2.38, 57.322), (23.194, -20.28), (-120.43, 19.15), (2.38, 57.322)]])
{"coordinates": [[[2.3..., 57.32...], [23.19..., -20.2...], [-120.4..., 19.1...]]], "type": "Polygon"}
If you can get the libraries installed, django has some good tools for dealing with geometry objects, and these objects have a geojson
attribute, giving you access to the GeoJSON representation of the object:
https://docs.djangoproject.com/en/2.0/ref/contrib/gis/install/
>>> from django.contrib.gis.geos import Polygon, Point, MultiPoint, GeometryCollection
>>>
>>> poly = Polygon( ((0, 0), (0, 1), (1, 1), (0, 0)) )
>>> gc = GeometryCollection(Point(0, 0), MultiPoint(Point(0, 0), Point(1, 1)), poly)
>>> gc.geojson
u'{ "type": "GeometryCollection", "geometries": [ { "type": "Point", "coordinates": [ 0.0, 0.0 ] }, { "type": "MultiPoint", "coordinates": [ [ 0.0, 0.0 ], [ 1.0, 1.0 ] ] }, { "type": "Polygon", "coordinates": [ [ [ 0.0, 0.0 ], [ 0.0, 1.0 ], [ 1.0, 1.0 ], [ 0.0, 0.0 ] ] ] } ] }'
GeometryCollection can also accept a list of geometry objects:
>>> polys = []
>>> for i in range(5):
... poly = Polygon( ((0, 0), (0, 1), (1, 1), (0, 0)) )
... polys.append(poly)
...
>>> gc = GeometryCollection(polys)
Update 2019:
shapely with shapely-geojson is now available can may be more easily to introduce as it doesn't required django.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With