Table 1
The list of third-party Python libraries used in the Green Paths routing software.
| PACKAGE | LINK | VERSION (TESTED) | DESCRIPTION AND USE |
|---|---|---|---|
| Flask | https://github.com/igraph/python-igraph | 1.1.2 | A simple web framework for publishing the routing functionality via APIs |
| GeoPandas | https://github.com/geopandas/geopandas | 0.8.3 | Data structures for spatial data processing and integration |
| Gunicorn | https://github.com/benoitc/gunicorn | 20.0.4 | A Python WSGI HTTP Server for UNIX, used for running the APIs of the routing application as a web service |
| igraph (python-igraph) | https://github.com/igraph/python-igraph | 0.8.3 | Graph data structure and built-in algorithms for solving least cost path problems |
| Shapely | https://github.com/Toblerity/Shapely | 1.7.1 | Geometry objects and overlay analysis |
Figure 1
The architecture, data processing workflow, and use cases of the Green Paths routing software.
Table 2
External data currently used in the Green Paths routing software for exposure-optimised routing.
| DATA | CONTENT | MEASURE | VALUE RANGE | FORMAT | SPATIAL EXTENT | SOURCE AND REFERENCES |
|---|---|---|---|---|---|---|
| Street network data | Street and path network | n/a | n/a | Standard compressed Protocolbuffer Binary Format (PBF) | Global | OpenStreetMap, www.openstreetmap.org, CC BY 2.0 |
| Traffic noise data | Day, evening, and night A-weighted equivalent continuous sound pressure level (Lden) from road and rail traffic. Modelled every five years according to the EU Environmental Noise Directive 2002/49/EC. | dB(A) | 40…75+ | Vector, shapefile | European urban areas | [30], accessible from ckan.ymparisto.fi/dataset/%7B0A7C0CF8-7BAA-49FF-835A-0B97DA89B9D4%7D, CC BY 4.0 |
| Real-time air quality data | Hourly composite air quality index covering NO2, SO2, O3, PM2.5, PM10, BC, and LDSA | Air Quality Index (AQI) 2.0 | 1…5 (good…very poor) | Raster, mesh size 13 × 13m, netCDF | Helsinki Metropolitan Region | FMI-ENFUSER 2.0 model, [29, 31], accessible from the Finnish Meteorological Institute (FMI) |
| Static air quality data | Annual average composite air quality index covering NO2, SO2, O3, PM2.5 and PM10 | Air Quality Index (AQI) 1.0 | 1…5 (good…very poor) | Raster, mesh size 13 × 13m, netCDF or TIFF | Helsinki Metropolitan Region | FMI-ENFUSER 1.0 model, [29], accessible from the Helsinki Region Environmental Services Authority (HSY) |
| Greenery data | Proportion of green vegetation visible at street level based on street view panoramas and regional land cover data | Green View Index (GVI) | 0…1 | Vector, shapefile | Helsinki Metropolitan Region | [32], CC BY 4.0; hri.fi/data/fi/dataset/paakaupunkiseudun-maanpeiteaineisto, CC BY 4.0 |
Figure 2
Flowchart of the start-up and the routing workflow of the main routing application (gp_server/gp_server_main.py).
Figure 3
Selected screenshots of the Green Paths routing tool user interface for finding and comparing quiet routes for walking.
Source: https://green-paths.web.app.