Tutorials
These tutorials give you the required tools and knowledge for completing the project. For most tasks there are many options available.
Jupyter Setup
Basic Knowledge (Data Exploration and Spatial Analysis)
- Introduction to data analysis with Python
- Introduction to geographic data in Python
- Introduction to spatial data analysis with GeoPandas
- Using online geographic data sources
- Understanding Coordinate Reference Systems (CRS)
- Geographic Data Visualization
Network Analysis and Routing
- Retrieving data from OSM
- Simple routing on OSM (osmnx)
- Routing with OSRM
- Valhalla - especially strong for bicycle/micromobility trips
- routingpy - a Python client service for many different routing webservices (including Valhalla, Graphhopper, OTP etc)
Data aggregation
- The most straight-forward way of aggregating trajectory data is using edge counts. If you have used OSM in previous tasks, then most routing results also output the edge list that make up this trajectory. You can then count the edges to get the traffic counts on all edges.
- Data aggregation with MovingPandas
- Data aggregation using H3 spatial indexing
Emissions modelling
- Emissions modelling with CO2 absorption from green areas
- Vehicle emissions from sustainably-mobility-api
- PyEmission - Python Library for Vehicular Emission Estimation