Retrieving OpenStreetMap data

In this practical tutorial from AutoGIS university of Helsinki, i will try to retrieve with the 'Universite Cheikh Anta Diop de Dakar'

In [1]:

# Loading all the needed libraries, you might not use all of them, but just keep them in the case of any emmergency need
import osmnx as ox
import matplotlib.pyplot as plt
import geopandas
import pandas as pd
import collections
import networks as nt
import os
import numpy as np

In [2]:

# Geo-localisation of the address
place_name = 'Universite Cheikh Anta Diop de Dakar, Dakar, Senegal'
graph = ox.graph_from_place(place_name)

In [3]:

type(graph)

Out[3]:

networkx.classes.multidigraph.MultiDiGraph

In [4]:

fig, ax = ox.plot_graph(graph)
plt.tight_layout

Out[4]:

<function matplotlib.pyplot.tight_layout(*, pad=1.08, h_pad=None, w_pad=None, rect=None)>

In [5]:

area = ox.geocode_to_gdf(place_name)

In [6]:

area.plot()

Out[6]:

<AxesSubplot:>

In [7]:

area.head()

Out[7]:

	geometry	place_name	bbox_north	bbox_south	bbox_east	bbox_west
0	POLYGON ((-17.46941 14.68994, -17.46816 14.688...	Université Cheikh Anta Diop, Rue de Diourbel (...	14.693334	14.681233	-17.458759	-17.469406

In [8]:

area.columns.values

Out[8]:

array(['geometry', 'place_name', 'bbox_north', 'bbox_south', 'bbox_east',
       'bbox_west'], dtype=object)

In [9]:

area.info()

<class 'geopandas.geodataframe.GeoDataFrame'>
RangeIndex: 1 entries, 0 to 0
Data columns (total 6 columns):
 #   Column      Non-Null Count  Dtype   
---  ------      --------------  -----   
 0   geometry    1 non-null      geometry
 1   place_name  1 non-null      object  
 2   bbox_north  1 non-null      float64 
 3   bbox_south  1 non-null      float64 
 4   bbox_east   1 non-null      float64 
 5   bbox_west   1 non-null      float64 
dtypes: float64(4), geometry(1), object(1)
memory usage: 104.0+ bytes

In [10]:

buildings = ox.footprints_from_place(place_name)

d:\programm files\python\lib\site-packages\osmnx\footprints.py:129: UserWarning: The `footprints` module has been deprecated and will be removed in a future release. Instead, use the `geometries` module's `geometries_from_place` function, passing `tags={'building':True}`.
  warnings.warn(msg)

In [11]:

buildings.head()

d:\programm files\python\lib\site-packages\ipykernel\ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

Out[11]:

	unique_id	osmid	element_type	amenity	name	geometry	nodes	building	addr:city	alt_name	...	name:fr	addr:street	office	phone	website	shop	addr:postcode	religion	ways	type
0	way/27294227	27294227	way	library	Bibliothèque Universitaire Centrale	POLYGON ((-17.46261 14.68578, -17.46262 14.685...	[299625480, 2351175474, 299625481, 2351175471,...	yes	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	way/44213933	44213933	way	NaN	UCAD II	POLYGON ((-17.46758 14.68868, -17.46738 14.688...	[561541507, 561541508, 561541509, 561541512, 5...	yes	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	way/44213944	44213944	way	NaN	Faculté de Médecine	POLYGON ((-17.46615 14.68616, -17.46617 14.686...	[561541618, 561541621, 561541623, 561541624, 2...	yes	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	way/140465697	140465697	way	NaN	Institut Fondamental d'Afrique Noire	POLYGON ((-17.46786 14.68393, -17.46774 14.683...	[1538892006, 1538892004, 1538892008, 153889200...	university	Dakar	IFAN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	way/166709851	166709851	way	NaN	NaN	POLYGON ((-17.46285 14.68950, -17.46284 14.689...	[1781615389, 1781615361, 1781615363, 178161539...	yes	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

5 rows × 28 columns

In [12]:

buildings.columns

Out[12]:

Index(['unique_id', 'osmid', 'element_type', 'amenity', 'name', 'geometry',
       'nodes', 'building', 'addr:city', 'alt_name', 'building:levels',
       'wikidata', 'wikipedia', 'source', 'cuisine', 'operator', 'name_2',
       'short_name', 'name:fr', 'addr:street', 'office', 'phone', 'website',
       'shop', 'addr:postcode', 'religion', 'ways', 'type'],
      dtype='object')

In [13]:

type(buildings)

Out[13]:

geopandas.geodataframe.GeoDataFrame

The nodes and edges

In [14]:

nodes, edges = ox.graph_to_gdfs(graph)

In [15]:

nodes.head()

Out[15]:

	y	x	osmid	geometry
297236557	14.685538	-17.467039	297236557	POINT (-17.46704 14.68554)
297236559	14.685428	-17.467027	297236559	POINT (-17.46703 14.68543)
297236563	14.685435	-17.466705	297236563	POINT (-17.46671 14.68543)
299625358	14.685460	-17.465818	299625358	POINT (-17.46582 14.68546)
299625359	14.685454	-17.465696	299625359	POINT (-17.46570 14.68545)

In [16]:

nodes.columns

Out[16]:

Index(['y', 'x', 'osmid', 'geometry'], dtype='object')

In [17]:

nodes.plot()

Out[17]:

<AxesSubplot:>

In [18]:

edges.head()

Out[18]:

	osmid	oneway	highway	length	junction	geometry	lanes	service	name	u	v	key
0	27294217	True	unclassified	90.805	NaN	LINESTRING (-17.46704 14.68554, -17.46788 14.6...	NaN	NaN	NaN	297236557	6053931928	0
1	27090881	True	unclassified	12.521	roundabout	LINESTRING (-17.46704 14.68554, -17.46704 14.6...	NaN	NaN	NaN	297236557	297236559	0
2	27090881	True	unclassified	13.808	roundabout	LINESTRING (-17.46703 14.68543, -17.46699 14.6...	NaN	NaN	NaN	297236559	952097995	0
3	27294213	True	unclassified	74.654	NaN	LINESTRING (-17.46671 14.68543, -17.46601 14.6...	NaN	NaN	NaN	297236563	2351175472	0
4	27090881	True	unclassified	14.586	roundabout	LINESTRING (-17.46671 14.68543, -17.46669 14.6...	NaN	NaN	NaN	297236563	299625374	0

In [19]:

edges.columns

Out[19]:

Index(['osmid', 'oneway', 'highway', 'length', 'junction', 'geometry', 'lanes',
       'service', 'name', 'u', 'v', 'key'],
      dtype='object')

In [20]:

edges.plot()

Out[20]:

<AxesSubplot:>

In [22]:

fig, ax = plt.subplots(figsize=(20,8))
area.plot(ax=ax, facecolor='black')
edges.plot(ax=ax, linewidth = 1, edgecolor= '#8C8F8F')
buildings.plot(ax=ax, facecolor='khaki', alpha=0.7)
plt.tight_layout()