Extract Graph Data from OpenStreetMap (OSM)

scraping data

geospatial

Introduction

When working with geographic networks, having access to raw road and pathway data is essential for tasks like route optimization, traffic analysis, and urban planning. OpenStreetMap (OSM) provides a wealth of such data. With this project, we are extracting structured graph data becomes a straightforward process. This project allows us to pull detailed network information, including nodes (intersections or points of interest) and edges (roads, paths, or trails), filtered by specific network types like drive, walk, or bike networks. This makes it an invaluable tool for researchers, data scientists, and urban planners looking to model and analyze real-world transportation systems efficiently.

The Code

By calling maps.get_geodata_area, we extract specific graph geographic data from the vast OpenStreetMap database. we can request difference network types to get nodes and edges for specific area.

nodes, edges = maps.get_geodata_area(places= ['5th district, Budapest'], 
                                    amenity_list= None, types= 'graph', network_type='drive')

This function requires the following parameters:

• places(list): specific locations
• amenity_list (list): amenity list that we want to extract.
• types(string): type of data request. ['polygon', 'graph']
• network_type (string): What type of street network to retrieve [“all”, “all_public”, “bike”, “drive”, “drive_service”, “walk”]

The result

Nodes

Edges