I am trying to use osmnx to find distances between a origin point (lat/lon) and nearest infrastructure, such as railways, water or parks.
1) I get the entire graph from an area with network_type='walk'
.
2) Get the needed infrastructure, e.g. railway for that same area.
3) Compose the two graphs into one.
4) Find the nearest node from origin point in the original graph.
5) Find the nearest node from the origin point in the infrastructure graph
6) Find the shortest route length between the two nodes.
If you run the example below, you will see that it is missing 20% of the data because it cannot find a route between the nodes. For infrastructure='way["leisure"~"park"]'
or infrastructure='way["natural"~"wood"]'
this is even worse, with 80-90% of nodes not being connected.
Minimal reproducible example:
import osmnx as ox
import networkx as nx
bbox = [55.5267243, 55.8467243, 12.4100724, 12.7300724]
g = ox.graph_from_bbox(bbox[0], bbox[1], bbox[2], bbox[3],
retain_all=True,
truncate_by_edge=True,
simplify=False,
network_type='walk')
points = [(55.6790884456018, 12.568493971506154),
(55.6790884456018, 12.568493971506154),
(55.6867418740291, 12.58232314016353),
(55.6867418740291, 12.58232314016353),
(55.6867418740291, 12.58232314016353),
(55.67119624894504, 12.587201455313153),
(55.677406927839506, 12.57651997656002),
(55.6856574907879, 12.590500429002823),
(55.6856574907879, 12.590500429002823),
(55.68465359365924, 12.585474365063224),
(55.68153666806675, 12.582594757267945),
(55.67796979175, 12.583111746311117),
(55.68767346629932, 12.610040871066179),
(55.6830855237578, 12.575431380892427),
(55.68746749645466, 12.589488615911913),
(55.67514254640597, 12.574308210656602),
(55.67812748568291, 12.568454119053886),
(55.67812748568291, 12.568454119053886),
(55.6701733527419, 12.58989203029166),
(55.677700136266616, 12.582800629527789)]
railway = ox.graph_from_bbox(bbox[0], bbox[1], bbox[2], bbox[3],
retain_all=True,
truncate_by_edge=True,
simplify=False,
network_type='walk',
infrastructure='way["railway"]')
g_rail = nx.compose(g, railway)
l_rail = []
for point in points:
nearest_node = ox.get_nearest_node(g, point)
rail_nn = ox.get_nearest_node(railway, point)
if nx.has_path(g_rail, nearest_node, rail_nn):
l_rail.append(nx.shortest_path_length(g_rail, nearest_node, rail_nn, weight='length'))
else:
l_rail.append(-1)
There are 2 things that caught my attention.
OSMNX documentation specifies ox.graph_from_bbox parameters be given in the order of north, south, east, west (https://osmnx.readthedocs.io/en/stable/osmnx.html). I mention this because when I tried to run your code, I was getting empty graphs.
The parameter 'retain_all = True' is the key as you may already know. When set to true, it retains all nodes in the graph, even if they are not connected to any of the other nodes in the graph. This happens primarily due to the incompleteness of OpenStreetMap which contains voluntarily contributed geographic information. I suggest you set 'retain_all = False' meaning your graph now contains only the connected nodes. In this way, you get a complete list without any -1.
I hope this helps.
g = ox.graph_from_bbox(bbox[1], bbox[0], bbox[3], bbox[2],
retain_all=False,
truncate_by_edge=True,
simplify=False,
network_type='walk')
railway = ox.graph_from_bbox(bbox[1], bbox[0], bbox[3], bbox[2],
retain_all=False,
truncate_by_edge=True,
simplify=False,
network_type='walk',
infrastructure='way["railway"]')
g_rail = nx.compose(g, railway)
l_rail = []
for point in points:
nearest_node = ox.get_nearest_node(g, point)
rail_nn = ox.get_nearest_node(railway, point)
if nx.has_path(g_rail, nearest_node, rail_nn):
l_rail.append(nx.shortest_path_length(g_rail, nearest_node, rail_nn, weight='length'))
else:
l_rail.append(-1)
print(l_rail)
Out[60]:
[7182.002999999995,
7182.002999999995,
5060.562000000002,
5060.562000000002,
5060.562000000002,
6380.099999999999,
7127.429999999996,
4707.014000000001,
4707.014000000001,
5324.400000000003,
6153.250000000002,
6821.213000000002,
8336.863999999998,
6471.305,
4509.258000000001,
5673.294999999996,
6964.213999999994,
6964.213999999994,
6213.673,
6860.350000000001]